Neonatal Neuroimaging

63 

Neonatal Neuroimaging JEFFREY J. NEIL AND TERRIE E. INDER

KEY POINTS • Cranial ultrasonography is useful for evaluating ventricular size and hemorrhage in preterm neonates during their neonatal intensive care unit (NICU) stay. • Magnetic resonance imaging (MRI) is the most sensitive imaging modality for many of the forms of injury found in both term and preterm neonates, including watershed injury, basal ganglia injury, white matter injury, and stroke. • Computed tomography (CT) should only be used when MRI is not available. • The MRI findings following brain injury are dynamic, with diffusion imaging being most sensitive 2–4 days after injury, and T1-weighted and T2-weighted imaging being most sensitive thereafter. • Neuroimaging studies of both term and preterm neonates have prognostic value.

CONTROVERSY BOX Is Brain Magnetic Resonance Imaging Near Term Equivalent Age Helpful in Extremely Preterm Babies? Pros: An MRI study obtained near the time of hospital discharge (term equivalent age) has better predictive value for subsequent neurodevelopmental outcome than any other clinical or imaging metric, particularly when systematic MRI scoring systems are employed. The use of MRI to help identify those infants at high risk for neurodevelopmental impairment may allow targeting of therapy services to those infants who would benefit most from them, and early initiation of appropriate therapy services may improve outcomes. MRI at term may also be used as a quality neurologic outcome metric for brain injury that is difficult to detect on ultrasound, such as white matter and cerebellar injury, and brain growth measures, thereby allowing the neonatal unit to track the true incidences of injury and impaired brain growth in their patient population. Cons: There are no studies proving that obtaining an MRI at the time of hospital discharge in very preterm infants leads to improved neurodevelopmental outcomes. Furthermore, the imprecise relationship between MRI findings and outcome may cause uncertainty in prognosis, leading to increased anxiety for parents. Additional comments: Discussing long-term prognosis for very preterm infants with their parents prior to discharge from the NICU should be standard practice. This discussion should be informed by clinical markers such as gestational age, clinical history, and neurologic examination as well as MRI (when appropriate). We suggest that term MRI studies be obtained on those infants at highest risk for adverse outcome based on gestational age and/or clinical course. In this context, it is important that clinicians be trained in the relationship between gestational age, clinical course, MRI, and outcome. Concerns regarding parental anxiety are based on anecdotal evidence but highlight the importance of the nature of this communication to empower and enable families rather than cause concern.

922

I

n this chapter, we focus primarily on the three main techniques for assessing brain structure and injury in infants— cranial ultrasonography (CUS), computed tomography (CT), and magnetic resonance imaging (MRI). We review the fundamentals of the methods and describe their application to the preterm and term-born populations. We also review methods that are under development and may prove clinically useful in the future.

Imaging Modalities Cranial Ultrasonography CUS is based on the reflection of ultrasound from tissue. Since ultrasound does not penetrate bone well, CUS is limited to infants with open fontanels (though ultrasound can sometimes be obtained through the squamous portion of the temporal bone). CUS studies are mainly done through the anterior fontanel, often with inclusion of images of the posterior fossa taken through the mastoid foramen (Fig. 63.1). Since image quality falls off with distance from the ultrasound probe, images of the posterior fossa obtained through the mastoid foramen have richer detail than those obtained through the anterior fontanel. Image quality also worsens somewhat as the fontanels gradually close, and obtaining CUS images of the brain is no longer feasible once the fontanel closes completely at the approximate age of 6 months. Tissue interfaces, such as that between cerebrospinal fluid (CSF) and brain parenchyma, give a strong echo return. Consequently, CUS excels at providing an outline of the ventricular system. Hemorrhage is also readily visible and appears bright because of the strong echo from the loosely packed red blood cells. This combination of properties makes CUS very useful for evaluating posthemorrhagic hydrocephalus as well as cystic changes in the periventricular white matter in preterm neonates (vide infra). In comparison, the echo return from brain parenchyma is considerably smaller, with parenchyma appearing relatively dark compared with hemorrhage or the ventricular outline. Furthermore, there is little contrast between injured and uninjured tissue. As a result, areas of nonhemorrhagic brain injury, such as stroke, are difficult to detect with CUS, though areas of nonhemorrhagic injury may sometimes appear brighter than surrounding tissue. It is important that clinicians caring for preterm neonates personally review the images from every CUS study on their patients, just as neonatologists look at every chest X-ray and neurologists every MRI study. One potential hurdle to learning to evaluate CUS studies is its unique imaging planes. A standard CUS image set obtained through the anterior fontanel typically starts with

CHAPTER 63  Neonatal Neuroimaging



IHF

F

A

E

B CC

D A

C

B

SF

LV

CSP CB

C

D

I CP H

G

E

F CC CP

IV CB

G

H

J

TH III SF

I

IV CB

J

• Fig. 63.1  Head Ultrasound Studies and Their Corresponding Imaging Planes. The imaging planes

(yellow) are shown on a midline sagittal magnetic resonance image upon which an outline of a lateral ventricle is drawn in red. (A–I) The ultrasound images were taken through the anterior fontanel. (J) The image was taken through the mastoid foramen. CB, Cerebellum; CC, corpus callosum; CP, choroid plexus; CSP, cavum septum pellucidum; III, third ventricle; IV, fourth ventricle; IHF, interhemispheric fissure; LV, lateral ventricles; SF, Sylvian fissure; TH, temporal horn of the lateral ventricle.

923

924

PART XI I  Neurologic System

slices that are very close to coronal in the anterior part of the brain, with the images becoming progressively more oblique, and closer to axial, for images from the posterior parts of the brain (see Fig. 63.1A–F). Images are then obtained with the ultrasound probe oriented to obtain a sagittal midline image (see Fig. 63.1G), as well as parasagittal images of the hemispheres and lateral ventricles (see Fig. 63.1H–I). Images obtained through the mastoid window are also oblique and may extend superiorly/anteriorly to include the third ventricle in very preterm neonates, for whom the mastoid window is still wide open (see Fig. 63.1J). Another effect of the necessity of imaging around rather than through bone is that the cerebral convexities cannot be seen using CUS. In addition to structural information, ultrasound also has the capacity to provide measurements related to blood flow. This ability results because the frequency of the ultrasound signal used for imaging undergoes a Doppler shift when reflected by moving structures such as the cells in flowing blood. Thus Doppler ultrasonography has proven useful for evaluating the patency of both arteries and veins. This Doppler shift is readily converted to units of velocity (m/s), but deriving a blood flow value (mL/min per g of tissue) from a velocity value is not straightforward, as factors such as the diameter of the vessel, laminar blood flow, and the angle of the ultrasound beam relative to the blood vessel must be taken into account. In practice, the Doppler measurements are usually expressed as the resistive index, which is a unitless number calculated as the difference between systolic and diastolic flow velocities divided by the systolic flow velocity. Notably, resistive index is not affected by changes in the angle of the probe relative to the blood vessel. A related index is the pulsatility index, which is calculated in the same fashion as the resistive index except that the denominator is the mean flow velocity rather than systolic flow velocity. These measurements are typically taken from the anterior cerebral artery as it wraps around the genu of the corpus callosum and/or the middle cerebral artery as it turns in a superior– inferior direction. These vessel segments are chosen because the beam from the ultrasound probe, positioned at the anterior fontanel, is parallel to the arteries at these points, providing more consistent measurements. A comparison of CUS with other imaging modalities is provided in Table 63.1.

Computed Tomography CT scanning has been used to study infants since its invention in the 1970s and was the imaging modality used 40 years ago to TABLE 63.1 

develop the Papile classification of intracranial hemorrhage for preterm neonates (Papile et al., 1978). It is similar to CUS in that it excels at showing hemorrhage and the ventricular outline. In addition, like CUS, it does not provide particularly good tissue contrast for nonhemorrhagic injury. However, unlike CUS, it provides a clear view of the cerebral convexities. It provides a reasonable view of the posterior fossa, but image quality in this area is often degraded by the effects of surrounding bone. CT scanning is falling out of favor as an imaging modality for infants because of concerns regarding its use of ionizing radiation. In the rapidly developing brain, irradiation may cause injury that affects subsequent IQ (Ron et al., 1982; Hall et al., 2004). Furthermore, there is concern about an increased incidence of subsequent head and neck cancers (Karlsson et al., 1998; Brenner et al., 2003; Boice, 2015; Krille et al., 2015).

Magnetic Resonance Imaging In comparison with CUS, MRI has the disadvantage that infants must be moved from the intensive care unit to the radiology department for study, though this may change as MR scanning systems that are suitable for housing within the neonatal intensive care unit (NICU) are developed. Furthermore, the infant is relatively inaccessible while in the MRI scanner in the event of a medical emergency. The major advantage of MRI relative to CUS and CT is that it provides unmatched structural detail, high sensitivity to parenchymal injury, and high sensitivity to brain malformations (Raybaud et al., 1996; Cowan et al., 2005; de Vries and Volpe, 2013). From a practical standpoint, imaging infants requires adaptations of the scanning process. For example, optimum signalto-noise ratio, and hence better image quality, is achieved when the radiofrequency coil used for imaging is size-matched to the infant head, although it remains common practice to use a head coil designed for adult imaging for imaging infants. In addition, image contrast is different for newborns as compared with older children (see below) so that pulse sequence timing parameters must be optimized for the infant brain to obtain images with optimum contrast-to-noise ratio. Finally, infants are considerably less cooperative in holding still during the scanning process than older patients. As a result, it is standard practice in some centers to sedate infants to minimize movement. However, a variety of approaches have been developed to mitigate subject motion (Glover and Pauly, 1992; Pipe, 1999; Mathur et al., 2008; Tamhane and Arfanakis, 2009; Olesen et al., 2010; Gholipour et al., 2011; Tisdall et al., 2012; Ooi et al., 2013; Gumus et al., 2015). Thus sedation

Comparison of Imaging Modalities

Modality

Advantages

Disadvantages

Cranial ultrasound (CUS)

• • • •

• • • •

Computed tomography (CT)

• Readily available in most medical centers • Relatively inexpensive • Shows hemorrhage and the ventricular outline well

• Uses ionizing radiation • Poor tissue contrast for nonhemorrhagic injury • Requires the infant to be transported to the scanner

Magnetic resonance imaging (MRI)

• • • •

• • • •

Bedside test Inexpensive Excellent for evaluating ventricular size and hemorrhage Provides an indication of vessel patency (Doppler)

Offers a rich variety of contrast types (structural and functional) Provides unparalleled image detail Shows parenchymal injury well Shows malformations and heterotopias well

Unable to image cerebral convexities Challenging for nonradiologist to interpret Poor tissue contrast for nonhemorrhagic injury Misses subtle brain malformations such as heterotopias

Expensive Requires the infant to be transported to the scanner. It can be challenging to monitor infants while in the scanner. Scan times are longer than for CT or CUS.

CHAPTER 63  Neonatal Neuroimaging



925

for scanning should no longer be standard practice, though may still be necessary in some cases.

the clinical use of MRI for detection of hemorrhage is provided near the end of this chapter.

T1-Weighted and T2-Weighted Imaging MRI differs from CUS and CT in that it offers a wide variety of contrast types. Most MRI is based on the detection of signal from the hydrogen nuclei of water (1H2O), which are present at a concentration of approximately 110 mol/L in tissue. For “conventional” (T1-weighted and T2-weighted) imaging, image contrast is based on the T1 or T2 relaxation time constants of water 1H. These time constants vary with the local chemical environment. For example, 1H in CSF water has a relatively large T2 time constant, and hence CSF appears bright on T2-weighted images compared with other tissues. White matter contrast on MRI studies changes dramatically between birth and 1 year of life. Unmyelinated white matter appears dark on T1-weighted images and bright on T2-weighted images. With myelination, the T1 and T2 time constants change such that myelinated white matter has the opposite signal properties—bright on T1-weighted images and dark on T2-weighted images. This change in contrast can be employed to detect myelination (Ganzetti et al., 2014), which takes place at different rates in different brain areas. For example, primary motor cortex and visual cortex develop earlier than most other brain areas, and this corresponds to the relatively early myelination of their associated white matter tracts. In a term-born neonate, the myelinated corticospinal tract and optic radiations appear bright on T1-weighted images against a background of darker-appearing, unmyelinated white matter (Fig. 63.2). Since the majority of white matter in newborns is unmyelinated, and the signal characteristics of gray matter do not change appreciably during development, gray–white contrast is inverted in neonates compared with older infants and children. As myelination proceeds, white matter signal intensity gradually changes (Almli et al., 2007). Between the ages of 6 and 9 months, white and gray matter signal intensities are similar on both T1-weighted and T2-weighted images, making it difficult to obtain good gray–white image contrast (see Fig. 63.2). Thus while MRI may still be useful in patients at this age, it is not particularly sensitive for detecting subtle cortical malformations and heterotopias. By the age of 1 year, gray–white contrast is fully inverted and is similar to that of older children and adults. One final consideration for T1-weighted and T2-weighted imaging is the detection of hemorrhage. While both CT and CUS also detect hemorrhage, MRI can provide both an indication of the age of the injury (Table 63.2) and the presence of associated nonhemorrhagic parenchymal injury. MR angiography can also sometimes be used to identify associated vascular occlusion. A detailed description of

Diffusion Imaging The contrast in diffusion images is based on water motion, with water displacements on the order of 2–10 µm being measured. The method was originally used for measuring diffusion in liquids and was subsequently adapted to MRI in the mid-1980s (LeBihan et al., 1986). When the method is applied to tissue, the parameter describing water displacements is referred to as the apparent diffusion coefficient (ADC, with units of mm2/s) in recognition of the fact that water motion in tissue is influenced by a variety of factors in addition to Brownian motion, such as active transport and barriers to water movement. Diffusion imaging quickly became a mainstay of clinical imaging when it was discovered that it provides an early marker of stroke (Moseley et al., 1990). It is now known that diffusion images are sensitive to brain injury because water ADC values decrease within minutes following a variety of injuries in addition to stroke, including seizure (Zhong et al., 1993, 1995; Righini et al., 1994; Prichard et al., 1995), spreading depression (Latour et al., 1994; Busch et al., 1995; Rother et al., 1996; Takano et al., 1996), excitotoxic injury (Benveniste et al., 1992; Verheul et al., 1993), and trauma (Ford et al., 1994). The ADC changes following injury are dynamic, both on a time scale of hours and a time scale of days. In rodent studies (Li et al., 2000), water ADC values in an area of stroke fall within minutes of occlusion of the middle cerebral artery. If the occlusion is maintained for 90 minutes or more, the ADC values remain low for 3–4 days and then gradually rise to greater than normal values by 5–6 days (Fig. 63.3A). This process is known as pseudonormalization because ADC values pass through normal 4–6 days after injury. Notably, the time course of ADC changes is different for briefer injury. If blood flow is restored after 30 minutes of occlusion, ADC values return to normal within minutes of restoring blood flow (see Fig. 63.3A). This is followed by a secondary ADC decline within the first 24 hours and a subsequent increase with pseudonormalization at 4–6 days. It has been suggested that this short-term return of ADC values to normal followed by a secondary decline may be related to secondary energy failure, but this has not been proven. However, this more complex time course following briefer injury may explain the presence of “diffusion negative” injury. In adults with stroke, diffusion MRI within the first day shows nearly all strokes, failing to show the injury in only approximately 6% of cases (Oppenheim et al., 2000). The failures may be due to a small fraction of stroke patients in whom blood flow spontaneously returns shortly after injury. In term-born infants, the incidence of diffusion negative injury is higher, perhaps on the order of 30% (McKinstry et al., 2002b). This is probably related to the different mechanism of injury in this population. One can imagine a neonate in utero who undergoes a period of hypoxic–ischemic injury (e.g., caused by placental abruption). This period of injury may be relatively brief if the neonate is rescued by being delivered and resuscitated. In this case, ADC values in injured tissue may transiently return to normal before undergoing a secondary decline followed by pseudonormalization. For neonates with somewhat longer injury, there is no short-term return of ADC values to normal. ADC values are low at delivery and stay low until pseudonormalization takes place. The time course of ADC changes in term-born neonates with injury is shown in Fig. 63.3B. Note also that ADC values tend to fall lower and for longer in neonates treated with therapeutic hypothermia (Bednarek et al., 2012). Overall, diffusion imaging is most sensitive to injury

TABLE 63.2 

Magnetic Resonance Imaging Signal Changes After Parenchymal Hemorrhage SIGNAL INTENSITY

Age of Hemorrhage

T1-Weighted

T2-Weighted

1–3 days

Isointense

Low

3–10 days

High

Low

10–21 days

High

High

3–6 weeks

High

High

6 weeks to 10 months

Isointense

Low

926

PART XI I  Neurologic System

T1-weighted

T2-weighted

Newborn

8 months

14 months

• Fig. 63.2  Sagittal (Left Column) and Axial (Right Column) Images From Subjects at Varying Ages.

The images in the first row are from a newborn. Note that myelination of the corticospinal tract is visible at this age as an increase in signal intensity on the T1-weighted image (white arrow). The images in the second row are from an 8-month-old child. Note the relatively poor gray–white contrast at this age as the signal intensity of white matter changes with myelination changes. Myelination of the optic radiations is visible on the T2-weighted image as reduced signal intensity (black arrows). The images in the bottom row are from a 14-month-old child. Note that gray–white contrast is now fully reversed as a result of myelination.

CHAPTER 63  Neonatal Neuroimaging



ADC ratio 1.0

Time Brief occlusion Sustained occlusion

A

ADC ratio 1.0

0.6 Normothermic Hypothermic 0

B

2

4

6 8 Time (days)

10

12

• Fig. 63.3  Time

Course of Apparent Diffusion Coefficient Change Following Brain Injury. (A) The time course of apparent diffusion coefficient (ADC) change following brain injury. Blue represents 30-minute occlusion. Green represents 90-minute occlusion. The data are a composite from animal studies. (B) The time course of ADC change following brain injury in term-born human neonates. Red represents normothermic neonates. Blue shows neonates treated with therapeutic hypothermia. ADC ratios rather than absolute ADC values are used in the ordinate of both graphs because ADC values vary regionally in neonates and the areas of injury vary neonate to neonate. The ratio represents injured tissue over normal tissue, so values less than 1 indicate a reduction in ADC values. The dotted green line represents data from neonates treated with therapeutic hypothermia who had mild to moderate injury based on follow up MRI studies. The dashed green line represents data from those neonates with severe injury. ([A] Adapted from Kinstry RC, Miller JH, Snyder AZ, et al. A prospective, longitudinal diffusion tensor imaging study of brain injury in newborns. Neurology. 2002;59:824–833. [B] Adapted from Bednarek N, Mathur A, Inder T, Wilkinson J, Neil J, Shimony J. Impact of therapeutic hypothermia on MRI diffusion changes in neonatal encephalopathy. Neurology. 2012;78:1420–1427.)

2–4 days following injury but may show injury during the first day if the injury is severe. T1-weighted and T2-weighted imaging, on the other hand, usually show injury after 4–5 days. This timing should be taken into account when ordering/interpreting MRI studies to evaluate injury in neonates. Another interesting aspect of diffusion is diffusion anisotropy. In white matter, water ADC values are greater parallel to axons than perpendicular to them. This is because water moving parallel to axons can move freely within myelin layers without crossing lipid membranes. Water moving perpendicular to axons must pass through myelin layers or go around them, which reduces their displacements.

927

This spatial variation in water ADC values is referred to as anisotropy, and diffusion for which ADC is the same in all directions is called isotropic. When diffusion images are obtained, diffusion is measured several times, along different axes, for each individual image slice. For each element, or voxel, in the image, these measurements can be combined to provide a spatial representation of water displacements. This representation can be expressed mathematically as a tensor, and hence the name “diffusion tensor imaging.” While these tensors can be displayed as ellipsoids (Neil, 2008), ellipsoid representations are cumbersome to use in clinical practice. As a result, summary parameters from these ellipsoids are shown (Fig. 63.4). Measurement of diffusion anisotropy is applied most often to the evaluation of white matter. During development, anisotropy values increase dramatically with the addition of myelin (Huppi et al., 1998a; Neil et al., 1998), though unmyelinated white matter has a degree of diffusion anisotropy by virtue of the parallel arrangement of tubular axons. In many research studies, high anisotropy is associated with healthy white matter, and lower values are associated with injury or other abnormalities. Diffusion anisotropy measures can also be applied to gray matter. While cortical gray matter in adults has very low anisotropy values, this is not the case early in development, especially prior to term equivalent age. The developing cortical plate has a radial organization to its microstructure caused by the presence of radial glia and the apical dendrites of pyramidal cells (McKinstry et al., 2002a; Kroenke et al., 2005). This microstructure leads to high anisotropy values for the cortical plate for preterm infants in whom water ADC values are greater parallel to radial glia and apical dendrites than perpendicular to them. As the cortical plate matures, this radial organization is disrupted by the addition of basal dendrites to pyramidal cells, involution of radial glia, and myelination of intracortical white matter. As a result, anisotropy values fall steadily, reaching low values by term equivalent age and remaining low thereafter. Note that the pattern of anisotropy change over time is opposite for white and gray matter. Anisotropy values for the developing cortical plate are high and decrease as the cortex matures; anisotropy values for white matter initially are low and increase as white matter myelinates. The well-known regional variation in the rate of cortical development is also reflected in regional variation in the rate of change of cortical water anisotropy values (Kroenke et al., 2009). While diffusion anisotropy is not commonly used in clinical practice, it can be helpful for white matter tractography (Basser et al., 2000). In this usage, the orientation of greatest water ADC values is determined for each white matter voxel. Since this is parallel to the direction of the axons in that voxel, this orientation can be used to follow fibers from voxel to voxel, thereby following a particular white matter tract (see Fig. 63.4D). This is starting to be used clinically for neurosurgical patients for whom identification of white matter tracts can help determine the optimum surgical approach (Potgieser et al., 2014).

Angiography MR angiography is an important imaging modality for the evaluation of newborns. While a variety of approaches have been used to delineate vessels, contrast is usually based on macroscopic water motion. For example, it is possible to reduce the signal from static, extravascular water within an imaging slice so that the strongest remaining signal arises from intravascular water that flows into the slice during image acquisition. This can then be used to generate an angiogram. As noted below, angiography is particularly useful for assessing vascular occlusion in perinatal arterial stroke (Lequin et al., 2009) and for detecting sinovenous thrombosis (Berfelo et al., 2010).

928

PART XI I  Neurologic System

A

B

C

D • Fig. 63.4  Diffusion Magnetic Resonance Imaging Data From Preterm (A–C) and Term (D) Neonates. (A) A diffusion map in which image intensity corresponds to water diffusion coefficient. (B) An anisotropy map in which image intensity corresponds to the degree of anisotropy. The arrow indicates an area of the developing cortical plate that has high anisotropy. The arrowhead indicates the genu of the corpus callosum. (C) A color map showing the preferred direction of water displacements: red = medial–lateral, green = anterior–posterior, and blue = superior–inferior. Note the medial–lateral crossing fibers of the corpus callosum (arrowhead) and superior–inferior corticospinal fibers of the posterior limb of the internal capsule (arrow). (D) Diffusion tractography of the corticospinal tracts (purple) in a term neonate.

Susceptibility-Weighted Imaging Another form of contrast available in MR images is based on differences in local magnetic susceptibility and is sometimes known as T2*-weighted imaging. Susceptibility effects are caused by the juxtaposition of regions of different magnetic properties or susceptibilities. In the head, such areas are found at air–tissue

interfaces such as the sinuses, where they can cause unwanted image distortions, and near hemorrhages, where the reduced iron in deoxyhemoglobin produces strong susceptibility effects. Susceptibility-weighted images are extremely sensitive to hemorrhage, which appears dark (Fig. 63.5). Because magnetic field distortions caused by susceptibility effects extend beyond the susceptibility

CHAPTER 63  Neonatal Neuroimaging



929

• Fig. 63.5  Axial, Susceptibility-Weighted Images From a Former Preterm Neonate. Note the areas of signal dropout caused by periventricular hemorrhage (arrows). Choline

NAA Creatine

Lactate

ppm

ppm 4

3

2

1

4

3

2

1

• Fig. 63.6  1H Magnetic Resonance Spectra Obtained From a Human Brain at 3.0 Tesla. The spectrum

on the left shows a relatively large lactate doublet in an asphyxiated term neonate. The spectrum on the right, obtained 9 days later, shows resolution of the lactate doublet and a reduction in the NAA resonance (arrow) relative to the choline and creatine resonances caused by neuronal loss. NAA, N-acetyl-containing compounds; ppm, parts per million.

boundary, small hemorrhages appear as relatively large areas of low signal on susceptibility-weighted images, making them very conspicuous and also making them appear larger than they actually are.

Magnetic Resonance Spectroscopy As noted above, the concentration of water 1H in brain is on the order of 110 mol/L, which provides abundant signal for the imaging modalities described above. MR spectroscopy involves the detection of 1H in brain metabolites, such as lactate, which are present in concentrations on the order of 10−2 mol/L. This factor of 104

difference in concentration makes MR spectroscopy more challenging than conventional imaging. For example, it is not feasible to obtain a high-resolution image of brain lactate concentration. Instead, an MR spectrum is obtained from a single region of interest (single voxel spectroscopy), or a grid of spectra is obtained from a thick slice of brain (often known as chemical shift imaging). For typical 1H spectroscopy in clinical use, the resonance peaks visible are choline, creatine, N-acetyl-containing compounds (NAA), and lactate (Fig. 63.6). The reasons that these resonances are more conspicuous than others are related to their chemistry and the fact that these metabolites are present in relatively higher concentrations.

930

PART XI I  Neurologic System

Choline serves as a component of membranes and is also a constituent of the neurotransmitter acetylcholine. Creatine, when phosphorylated, stores energy in the form of phosphate bonds. (Phosphocreatine levels reflect the cellular energy state, but their detection requires phosphorous 31 (31P) spectroscopy, as creatine and phosphocreatine are indistinguishable using 1H spectroscopy.) The precise role of NAA in brain metabolism is unclear, but it is widely believed that NAA is found primarily in neurons and not glia, and a reduction in NAA level is often taken to reflect a reduction in the number of neurons present in a given region. Lactate is an intermediary of energy metabolism, and its levels may be increased under a variety of circumstances, including lack of oxygen and anaerobic glycolysis. Lactate levels may also be increased by the presence of inflammatory cells, which often utilize anaerobic glycolysis. Note that the 1H signal from the methyl group of lactate is a doublet (a pair of peaks) because of its chemistry. In theory, it is possible to quantify metabolite levels (in mM) by comparing resonance amplitudes of metabolites with the water resonance amplitude in the same brain region. This quantitation is rarely employed in clinical practice, and resonance amplitudes are more often expressed as ratios. For example, the NAA/choline or NAA/creatine ratio may provide an estimate of the fraction of cells in a given area that are neurons. Finally, nuclei in addition to 1H are detectable by MR spectroscopy. They include 31P, sodium (23Na), an isotope of carbon (13C), and even the other two isotopes of hydrogen (2H or nonradioactive deuterium and 3H or radioactive tritium). While detection of these other nuclei is of significant scientific/research interest, particularly detection of hyperpolarized 13 C for noninvasive assessment of metabolism, non-1H spectroscopy has not yet found its way into clinical use.

Preterm Neonates In recent decades, survival rates for very preterm neonates (born at less than 30 weeks’ gestation) have improved dramatically due to advances in perinatal and neonatal care. In contrast to this improvement in mortality, long-term neurodevelopmental outcomes have not improved and remain problematic, with significant associated costs to individuals, families, and society (Anderson and Doyle, 2008; Hintz et al., 2011). In recent years, significant investigation has been undertaken to correlate perinatal, medical, and physical examination findings with long-term neurodevelopmental outcomes in an attempt to identify the neonates at greatest risk. High-grade brain injury (grade III or IV intraventricular hemorrhage [IVH], posthemorrhagic hydrocephalus, large cerebellar hemorrhage, and/or cystic periventricular leukomalacia [c-PVL]) is among the major risk factors for adverse neurodevelopmental outcome. This section will explore the neuroimaging characteristics of these forms of brain injury on CUS and MRI alongside a brief description of their neuropathologic characteristics.

Intraventricular Hemorrhage Germinal matrix-IVH is the most common variety of neonatal intracranial hemorrhage and is characteristic of the preterm neonate. IVH has traditionally been graded as grade I–IV, as first reported by Papile and colleagues (Papile et al., 1978). This system is based on the presence and amount of blood in the germinal matrix and the lateral ventricles (Fig. 63.7). Grade I represents hemorrhage confined to the subependymal germinal matrix, grade II is hemorrhage within the lateral ventricles without ventricular dilatation, grade III is hemorrhage with ventricular dilatation and/or

hemorrhage occupying more than 50% of the ventricle, and grade IV requires parenchymal hemorrhage, typically abutting the superolateral aspect of the body and atrium of the lateral ventricle. Although grade IV IVH is now referred to as periventricular hemorrhagic infarction rather than IVH per se, most reports continue to classify the cranial ultrasound findings according to this earlier established classification system. The incidence of IVH in preterm neonates remains high. Incidences derived from neonates studied in the late 1980s through the 2000s have documented that the incidence of IVH has remained unchanged at a level of approximately 25%. This is clearly documented in recent data summarizing the risk of IVH between 1993 and 2012 (Stoll et al., 2015). These data suggest that there may be a small decline in the risk of IVH for neonates with gestational ages of 26–28 weeks, with no change in the most immature neonates born at 22–25 weeks’ gestation (Fig. 63.8). It has long been known that there is a higher risk for all forms of IVH in the most immature preterm neonates, with neonates less than 750 g having a risk of any IVH that is approximately threefold higher than for a preterm neonate over 1250 g (42% vs 14%) and a 10-fold higher risk of grade III–IV IVH (20% vs 2.1%) (Wilson-Costello et al., 2005). The other perinatal risk factors for IVH are summarized in Fig. 63.9. CUS is the cornerstone of diagnosis for IVH in the preterm neonate and provides accurate and useful information for grading. At times, it may be difficult to distinguish a germinal matrix only (grade I) from a small intraventricular (grade II) IVH. Under these circumstances, a view of the lateral ventricles through the posterior fossa may be of assistance because blood tends to settle in the occipital horns of the lateral ventricles (neonates are usually lying face up during the CUS study), which are well seen with this view. MRI can also show the presence of IVH with similar accuracy, particularly in the acute phase, although it is not practical for serial examinations of preterm neonates. However, if MRI is first performed at term equivalent age, a small grade I hemorrhage may no longer be visible as a hemorrhage on conventional T1-weighted and T2-weighted images but may still be inferred from the presence of a germinal matrix cyst at the site of the original hemorrhage and/or an area of low signal intensity on susceptibilityweighted images reflecting remnants of blood products in the area. Information on the typical timing of IVH can inform the decision of when to undertake CUS in the preterm neonate early in the hospital course. In a cumulative series of 105 neonates with IVH studied by CUS from the first hours of life, approximately 50% had onset of hemorrhage on the first postnatal day, an additional 25% on the second day, and an additional 15% on the third day (Volpe, 2001). In a single study of 1105 neonates weighing 2000 g or less at birth, approximately 40% of the 265 who developed IVH did so within the first 5 hours of life (Paneth et al., 1993). The likelihood of onset of hemorrhage on the first postnatal day varied inversely with birth weight; in one series, 62% of hemorrhages in neonates between 500 g and 700 g birth weight occurred in the first 18 hours (Perlman and Volpe, 1986). In general, if screening were to be confined to a single postnatal day in the first days of life, a scan on the fourth postnatal day would be expected to detect approximately 90% of all hemorrhages. However, progression of the lesions occurs in approximately 20%–40% of the affected infants, with maximal extent of the lesion attained usually within 3–5 days of the initial diagnosis (Volpe, 2001). Thus a second scan after approximately 5 days is necessary to identify the maximal extent of hemorrhage.

CHAPTER 63  Neonatal Neuroimaging



COR

LOGIQ E9

SAG LT

LOGIQ E9

A COR

LOGIQ E9

SAG RIGHT

LOGIQ E9

B COR

LOGIQ E9

SAG RT

LOGIQ E9

C COR

LOGIO E9

SAG RT

LOGIO E9

D • Fig. 63.7  Grading of the Severity of Germinal Matrix–Intraventricular Hemorrhage on Coronal and

Parasagittal Cranial Ultrasonography. (A) Grade I: germinal matrix hemorrhage. (B) Grade II: intraventricular hemorrhage (IVH) (filling < 50% of the ventricular volume). (C) Grade III: IVH with ventricular dilatation. (D) Grade V: large IVH with associated parenchymal echogenicity (hemorrhagic infarct). COR, Coronal; SAG RT, right parasagitta. (Courtesy of Walsh B, Inder T, Volpe JJ. IVH. In: Polin R, Abman SH, Rowitch D, Benitz WE [eds], Fetal and Neonatal Physiology, 5th ed. Elsevier, 2016, chapter 134, pp. 1333—1349.)

931

PART XI I  Neurologic System

GA 22 wk

GA 23 wk

GA 24 wk

GA 26 wk

GA 27 wk

GA 28 wk

1995 2000 2005 2010

1995 2000 2005 2010

GA 25 wk

100 80 60 40 Severe ICH, %

932

20 0 100 80 60 40 20 0 1995 2000 2005 2010

1995 2000 2005 2010

Birth year

• Fig. 63.8  Severe Intracranial Hemorrhage by Birth Year and Gestation for Neonates Born at 22–28

Weeks’ Gestation 1993–2012. Circles show the percentage of neonates born each year who were evaluated by cranial ultrasonography and diagnosed with grade III–IV intraventricular hemorrhage, a smoothed curve shows the trend, and shading indicates the 95% confidence interval for the curve. The year–gestational age interaction was significant (P = .03). Relative risks for the change per year were adjusted for study center, maternal race/ethnicity, neonate gestational age, small for gestational age, and sex. GA, Gestational age. (Data from Stoll BJ, Hansen NI, Bell EF, et al.; Eunice Kennedy Shriver National Institute of Child and Human Development Neonatal Research Network. Trends in care practices, morbidity, and mortality of extremely preterm neonates, 1993–2012. JAMA. 2015;314:1039–1051.)

Cerebral immaturity - Vascular immaturity - Pressure passive system

Metabolic/electrolytes - Hypoglycemia - Hypernatremia - Metabolic acidosis

Delivery history - Need for resuscitation - Low Apgar scores

Cardiac - Hypotension (dopamine) - Low cardiac output - Low blood volume (immediate cord clamping) - PDA (prophylatic indomethacin)

INTRAVENTRICULAR HEMORRHAGE

Respiratory - Hypercarbia/hypocarbia - Hypoxia - Increased central venous pressure - PPV and pneumothorax

Inflammatory - Chorioamnionitis - Sepsis

Hematologic - Anemia - Thrombocytopenia - Coagulation disorders

• Fig. 63.9  Risk Factors for Intraventricular Hemorrhage. PDA, Patent ductus arteriosus; PPV, positive pressure ventilation.

CHAPTER 63  Neonatal Neuroimaging



Approximately 30%–50% of neonates with a grade III–IV IVH develop posthemorrhagic ventricular dilatation (PHVD), and 20%–40% of neonates will consequently need a permanent ventriculoperitoneal shunt (Adams-Chapman et al., 2008; de Vries et al., 2013b). Thus preterm neonates with blood in the lateral ventricles (grade II–IV IVH) should be followed with serial CUS studies to monitor ventricular size. While qualitative evaluation of ventricular size can be useful, it is more informative to evaluate ventricular size in a quantitative fashion using established normative

A

933

values (Davies et al., 2000). Several quantitative measurements have been developed, including ventricular index, ventricular height, anterior horn width, and thalamo–occipital distance. No one measurement has proven to be superior to the others (Fig. 63.10) (Brouwer et al., 2010). However, the occipital horn area is the first and the frontal horn the last area to enlarge after IVH (Allan et al., 1982). Thus measurement of the thalamo–occipital dimension of the lateral ventricle (Brouwer et al., 2010) via the posterior fontanel is potentially the earliest indicator of ventriculomegaly.

B

C • Fig. 63.10  T2-Weighted Coronal Magnetic Resonance Images From Three Preterm Neonates With a Periventricular Hemorrhagic Infarction. (A) A large periventricular hemorrhagic infarction (PVHI) is communicating with the lateral ventricle. (B) A smaller PVHI appears to be separate. (C) A small frontal PVHI without associated intraventricular hemorrhage. (Adapted from de Vries LS, Benders MJ, Groenendaal F. Progress in neonatal neurology with a focus on neuroimaging in the preterm infant. Neuropediatrics. 2015;46:234–241.)

934

PART XI I  Neurologic System

At present, there are no standard recommendations for the frequency of CUS studies in this situation. Our practice has been to obtain CUS studies twice per week until ventricular size is stable for 1 week and then every 1–2 weeks thereafter. In addition to helping identify infants in need of CSF drainage procedures, CUS is also useful for evaluating the effect of CSF drainage using preintervention and postintervention imaging and guiding the frequency and volume of CSF drainage necessary to reduce ventricular size. For example, when using lumbar puncture to treat ventriculomegaly infants with PHVD, the volume of CSF to drain varies greatly between infants (10 mL/kg is typical), with some infants requiring removal of large volumes of CSF to improve ventricular size (Hunt et al., 2003). In this case, CUS studies before and after the procedure give an indication of its effectiveness. It is worth noting that the ventricular size at which to intervene with a CSF drainage procedure, as well as the drainage procedure to be used, remains an area of active research (Mazzola et al., 2014). Furthermore, the role of aggressive CSF drainage in improving outcomes remains unproven, although there are studies suggesting that more aggressive drainage may be helpful. For example, there are retrospective data suggesting that earlier intervention may be associated with a reduced need for a ventriculoperitoneal shunt and improved neurodevelopmental outcomes (de Vries et al., 2002; Brouwer et al., 2008). In addition, greater ventriculomegaly was associated with worse neurodevelopmental outcome in a study of 173 preterm neonates with grade III–IV IVH (Fig. 63.11) (Srinivasakumar et al., 2013). Overall, more data are needed to settle this issue. A multicenter randomized trial of early versus late ventricular intervention (ELVIS, number ISRCTN43171322, or ClinicalTrials.gov NCT00875758) has completed recruitment, and the results should shed further light on this question. From a practical standpoint, it is important to make a clear clinical distinction between ventriculomegaly resulting from periventricular cerebral atrophy and ventriculomegaly resulting from hydrocephalus with attendant impairment of CSF dynamics for the formulation of appropriate management decisions. In general, the development of ventriculomegaly resulting from atrophy occurs slowly, over several weeks, and is not associated with the development of increased intracranial pressure (perhaps with a bulging fontanel) or rapid head growth and evolves to a state of stable ventricular size. In hydrocephalus, ventricular size may be unstable, decreasing if the condition is transient or increasing if the condition is progressive. The typical evolution of PHVD in a very preterm neonate (24 weeks’ gestation) with grade IV IVH is shown in Fig. 63.12. Note the steady progression in ventricular dilatation, which is relieved by subgaleal shunt. The MRI at term equivalent demonstrates the asymmetry from left intraparenchymal volume loss and ex vacuo expansion. The use of MRI to detect IVH early in the hospital course of a very preterm neonate is impractical for a variety of reasons, and there is no consensus regarding its use in this role. Nevertheless, MRI may be helpful for evaluating infants with PHVD by showing parenchymal details of periventricular hemorrhagic infarction that are useful for prediction of later neurodevelopmental outcome. Grade IV IVH can range from a small focal hemorrhage to an extensive hemorrhage involving most of both cerebral hemispheres (Jary et al., 2012). MRI can be used to more accurately determine the extent of a grade IV hemorrhagic lesion, which is a strong determinant of outcome (de Vries et al., 2015). With or without MRI, it is important for the clinician to appreciate the extent of a grade IV IVH (Fig. 63.13), ideally by reviewing the images, to accurately counsel the baby’s family.

White Matter Injury Extensive cystic white matter injury (Fig. 63.14), or c-PVL, is now a relatively uncommon problem in very and extremely preterm neonates, with subtle white matter injury now recognized more commonly, particularly on MRI, in this population (Hamrick et al., 2004; Kidokoro et al., 2014). CUS is relatively limited for showing these more subtle white matter lesions (Inder et al., 2003), but nonhemorrhagic injury can sometimes be detected. It has been suggested that any abnormality in the cerebral white matter of echo density at least as echogenic as the choroid plexus and persisting for at least 7 days is significant. Furthermore, the presence of white matter inhomogeneity or a “patchy” appearance on CUS should also alert the clinician to potential white matter abnormalities (Fig. 63.15) (van Wezel-Meijler et al., 2011). These lesions can be hemorrhagic or ischemic in origin, and a combination of diffusionweighted and susceptibility-weighted MRI can help distinguish between the two (Niwa et al., 2011). They also can be detected by MRI both early and at term equivalent age, tending to be more abundant on the early MRI. Thus early MRI shows the full extent of the white matter lesions, while MRI at term equivalent age identifies the remaining lesions and shows early glial scarring and associated white matter volume loss (Fig. 63.16). Another, more confluent MRI white matter signal abnormality, known as diffuse excessive high signal intensity, has also been described. It is seen on T2-weighted images at term equivalent age (Counsell et al., 2003) and is a common finding (Dyet et al., 2006). While these white matter signal intensity changes are associated with increased ADC values on diffusion imaging, the qualitative identification of signal changes on T2-weighted images is rather subjective, and recent studies have failed to identify a relationship between these signal changes and outcome at either 18 or 30 months of age (Kidokoro et al., 2011; Skiold et al., 2012). As noted above, extensive c-PVL, which is readily visible with both CUS and MRI, has declined over the last decades and now has an incidence of less than 1% in some cohort studies (van Haastert et al., 2011). There is also more localized variant c-PVL. This variant is also relatively uncommon but is more difficult to detect, requiring repeated cranial ultrasound examinations for at least 4–6 weeks for its identification. The cysts are typically located in the frontoparietal white matter adjacent to the lateral border of the lateral ventricles and extend to the occipital white matter in more severe cases. They are usually only visible for a few weeks and may have fully resolved by term equivalent, but their appearance is predictive of subsequent cerebral palsy (CP) (de Vries et al., 2004). Their “resolution” is probably due to coalescence of the cysts with the adjacent lateral ventricle. As a result, their manifestation on MRI at term equivalent may be subtle, consisting of mild to moderate ventricular dilatation and an irregularly contoured ventricular wall. Detection of these transient cystic changes by CUS can be challenging. The American Academy of Neurology recommended in 2002 that all preterm neonates (<30 weeks’ gestation) undergo one CUS at 7–14 days for identification of large hemorrhages and a second CUS at 36–40 weeks to identify cystic lesions or ventriculomegaly for prediction of long-term outcome (Ment et al., 2002). However, transient periventricular cystic change may be missed using this protocol. Furthermore, in a study of 1473 extremely low birth weight infants (<1000 g) with only two CUS studies done at mean ages of 6 and 47 days, 29% of those with normal CUS studies had CP or a Bayley Mental Developmental Index less than 70 at 18–22 months of age (Laptook et al., 2005). Thus the finding of two normal CUS studies does

LOGIQ E9

LOGIQ E9

A

B LOGIQ E9

LOGIQ E9

1+

C

+

D LOGIQ E9

100

E

mm

F • Fig. 63.11  Grade IV Intraventricular Hemorrhage With Complicating Periventricular Hemorrhagic Infarction in a Preterm Neonate Born

at 24 Weeks’ Gestation. (A) Cranial ultrasonography (CUS) on day 2 of life shows a large left-sided intraventricular hemorrhage (IVH) with intraparenchymal echodensity consistent with a periventricular hemorrhagic infarction (PVHI). (B) CUS on day 12 of life shows a significant increase in ventricular size. (C) Coronal and (D) sagittal CUS studies on day 20 of life show significant ventricular dilatation with a thalamo– occiptal diameter of 33 mm (measured between the yellow crosses on the thalamus, labeled 1, and the occipital horn of the lateral ventricle) one day before a subgaleal shunt was inserted. (E) Sagittal CUS on day 40 of life showing a left porencephalic cyst resulting from the PVHI. Note that ventricular size is reduced following insertion of the subgaleal shunt. (F) Magnetic resonance imaging at day 84 of life (36 weeks’ postmenstrual age) demonstrating asymmetric ventriculomegaly caused by ex vacuo loss of volume in the left hemisphere. There is also left thalamic injury with hemosiderin present. There is an imaging artifact caused by magnetic susceptibility effects over the right hemisphere surface from the subgaleal shunt. Note that the gyral development remains immature for 36 weeks’ postmenstrual age.

936

PART XI I  Neurologic System

Ventricular index (mm)

15

LOGIQ E9

14 13 12 11 10 9 Levene (1981) Liao et al., (1986)

8 7

VI

24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

AHW

A

Postmenstrual age (weeks)

SAG LT

Anterior horn width (mm)

4

LOGIQ E9

3 2 1 Perry et al., (1985) Liao et al., (1986) Davies et al., (2000) Sondhi et al., (2008)

0 –1

24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

TOD

Thalamo–occipital distance (mm)

B

Postmenstrual age (weeks) 25 20 15 10 Reeder et al., (1983) Davies et al., (2000) Sondhi et al., (2008)

5 0

24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

C

Postmenstrual age (weeks)

• Fig. 63.12  Overview of the reference curves for the (A) ventricular index, (B) anterior horn width, and

(C) thalamo–occipital distance according to Davies et al., (2000). Regression lines with 95% confidence intervals are from (Levene, 1981) and (Liao et al., 1986). Also adapted from (Brouwer et al., 2012). AHW, Anterior horn width; TOD, thalamo–occipital distance; VI, ventricular distance. (Data from Brouwer AJ, Brouwer MJ, Groenendaal F, Benders MJ, Whitelaw A, de Vries LS. European perspective on the diagnosis and treatment of posthaemorrhagic ventricular dilatation. Arch Dis Child Fetal Neonatal Ed. 2012;97:F50– 55; Davies MW, Swaminathan M, Chuang SL, Betheras FR. Reference ranges for the linear dimensions of the intracranial ventricles in preterm neonates. Arch Dis Child Fetal Neonatal Ed. 2000;82:F218–223; Levene MI. Measurement of the growth of the lateral ventricles in preterm infants with real-time ultrasound. Arch Dis Child. 1981;56:900–904; Liao MF, Chaou WT, Tsao LY, Nishida H, Sakanoue M. Ultrasound measurement of the ventricular size in newborn infants. Brain Dev. 1986;8:262–268.)

not have a strong positive predictive value for normal neurodevelopmental outcome. Some centers obtain more frequent CUS studies of very preterm neonates in order to better delineate the nature and progression of intracranial lesions with the hopes of improving prognostic ability (Table 63.3) (Wezel-Meijler and de Vries, 2014). While the relative lack of sensitivity of CUS for injury leading to

neurodevelopmental impairment may be due, to some degree, to missing transient abnormalities, its inability to detect more subtle forms of brain injury, such as diffuse PVL at any time, undoubtedly also contributes. The prevalence of the various types of white matter abnormalities for preterm and term control neonates at term equivalent age is shown in Table 63.4.

CHAPTER 63  Neonatal Neuroimaging



BSID-III score

Cognitive

120

P = .006, r2 = 0.18

P = .003, r2 = 0.21

100 80 60

A

B P = .005, r2 = 0.19

100

Motor

P = .04, r2 = 0.10

937

C P = .007, r2 = 0.18

P = .002, r2 = 0.23

80 60 40

D

E Anterior horn width (mm)

F

Thalamo–occipital dist. (mm)

Ventricular index (mm)

• Fig. 63.13  Bayley Scales of Infant Development Scores for Motor and Cognition at 18–24 Months

in 173 Preterm Neonates With Grade III–IV Intraventricular Hemorrhage. BSID-III, Bayley Scales of Infant Development. (Adapted from Srinivasakumar P, Limbrick D, Munro R, et al. Posthemorrhagic ventricular dilatation—impact on early neurodevelopmental outcome. Am J Perinatol. 2013;30:207–214.)

Sag left

A

B • Fig. 63.14  Cystic periventricular leukomalacia visible on (A) cranial ultrasound at 28 days of age and

(B) magnetic resonance imaging at term equivalent age. Note also the more widespread loss of white matter volume, immature gyral folding, and loss of thalamic volume on the magnetic resonance imaging study.

Cerebellar Hemorrhage Cerebellar hemorrhage (CBH) is increasingly recognized in the very preterm neonate. This is probably the result of two key factors—the improved survival of extremely preterm neonates (24–28 weeks’ gestation) who are at greatest risk for CBH and more routine use of the mastoid window in CUS evaluations (see Fig. 63.1) (Limperopoulos et al., 2005; Steggerda et al., 2009; Ecury-Goossen et al., 2010). The cerebellum undergoes rapid and complex development during the preterm period. From 24–40 weeks’ gestation, the cerebellar volume, as assessed with three-dimensional volumetric ultrasound, increases fivefold, and the surface area of the cerebellar

cortex increases more than 30-fold (Volpe, 2009b). Based on CUS, the reported incidence of CBH ranges from 2%–9% depending on the gestational age of the population studied. When MRI is performed as well, the incidence is much higher, ranging from 15%–20% (Limperopoulos et al., 2005; Steggerda et al., 2013). This may be because CUS is only sensitive to hemorrhages that are more than 4–5 mm in size. Smaller, punctate CBHs are far more common but can only be diagnosed with MRI, particularly susceptibility-weighted images (Parodi et al., 2015; Plaisier et al., 2015). Of note, larger CBHs tend to be associated with supratentorial lesions such as IVH and evolve to atrophy of the affected cerebellar hemisphere on MRI at term equivalent age.

938

PART XI I  Neurologic System

LOGIQ E9

• Fig. 63.15  White matter echo density in a 28-week preterm neonate comparing cranial ultrasound on day 5 of life (left) with linear hemorrhagic lesions in the periventricular white matter (red arrow) and thalamus (white arrow) on term equivalent magnetic resonance imaging.

A

B

C

• Fig. 63.16  White matter lesions (arrows) for (A) focal small punctate lesions, (B) multiple focal punctate lesions, and (C) linear hyperintensity in the periventricular white matter.

Predicting Outcome With Imaging at Term Equivalent Age Clinicians and researchers continue to possess limited ability to definitively predict and meaningfully improve neurodevelopmental outcomes. While both CUS and MRI have value in this regard, neither is perfect (Table 63.5) (de Vries et al., 2013a). As noted above, CUS is strongly predictive of subsequent cerebral palsy, in the right hands (de Vries et al., 2004), but normal CUS studies are not good predictors of normal neurodevelopmental outcome. MRI is significantly more sensitive to subtle injuries to white matter and cerebellum. Below, we briefly outline the literature on MRI at term equivalent age and outcome for preterm neonates.

Structural Magnetic Resonance Imaging There is an increasing amount of literature available on the association of white matter abnormalities with structural MRI and neurodevelopmental outcome. White matter abnormalities have been associated not only with motor difficulties (Spittle et al., 2011) but also with impairments in executive functioning (Edgin et al., 2008; Woodward et al., 2011), verbal and visuospatial working memory (Clark and Woodward, 2010), language skills (FosterCohen et al., 2010; Reidy et al., 2013), and learning and attention (Murray et al., 2014; Omizzolo et al., 2014). Cortical gray matter abnormalities can also be detected with structural MRI, but gray matter tissue signal abnormalities in preterm neonates are less

CHAPTER 63  Neonatal Neuroimaging



common than white matter signal abnormalities, and gray matter injury is more typically manifest as alterations of cortical folding and enlarged extracerebral spaces. In a study of 167 very preterm neonates, gray matter abnormalities were found in half of the neonates and consisted of abnormal/immature cortical folding patterns and/or enlarged subarachnoid space (Woodward et al., 2006). These abnormalities were associated with an increased risk of severe cognitive delay, psychomotor delay, and CP at age 2 but to a lesser extent than white matter abnormalities (Woodward et al., 2006). In contrast, a study of 76 preterm neonates in which TABLE 63.3 

Recommendations for Cranial Ultrasonography by Gestational Age at Birth GESTATIONAL AGE AT BIRTH (WEEKS)

Postnatal age at which cranial ultrasonography should be performed

TABLE 63.4 

23–26

27–29

30–32

33–35

days 1,2, and 3

day 1

day 1

day 1

1 week

1 week

1 week

1 week

2 weeks

2 weeks

weekly to 31 weeks

weekly to 31 weeks

3 weeks

3 weeks

alternating weeks to 36 weeks

at 36 weeks

term

term

term

term

939

a similar scoring system for gray matter abnormality was used found no association between gray matter abnormality and outcome at age 9 years (Iwata et al., 2012). It is worth noting that alterations of cortical folding and enlarged extracerebral spaces involve both gray and white matter. Cortical folding probably represents an interaction between cortical gray matter and underlying white matter, whereas enlarged extracerebral spaces may reflect an overall reduction in cerebral volume involving multiple brain tissue types. The literature on cerebellar abnormalities detected by structural MRI and outcome in preterm neonates is relatively sparse, but cerebellar injury is associated with adverse neurodevelopmental outcome. Neonates with isolated cerebellar lesions have a range of neurodevelopmental deficits, including severe motor disabilities, abnormalities of expressive and receptive language, and cognitive deficits (Limperopoulos et al., 2007). They additionally experience a higher incidence of autism and behavioral dysfunction (BrossardRacine et al., 2015). Isolated cerebellar injury has also been associated with impairment of regional volumetric growth in the contralateral cerebrum, with corresponding deficits of language, motor, and social-behavioral function (Bolduc et al., 2011; Limperopoulos et al., 2014). While structural MRI is often helpful for predicting neurodevelopmental outcome of preterm neonates, a relatively high proportion of neonates without any evidence of brain injury (IVH, PVL, or CBH) have abnormal outcomes. For example, in one study the mean mental developmental index of preterm neonates with normal structural MRI was 87, with a 6% incidence of cerebral palsy (Kidokoro et al., 2014). In a metaanalysis of the prognostic accuracy of abnormalities on term MRI for predicting long-term outcome in preterm neonates (Van’t Hooft et al., 2015), the sensitivity and specificity for predicting CP were 77% and 79%, respectively. The corresponding values for predicting cognitive impairment were 66% and 61%. It is important to note that the analysis was done

Nature and Prevalence of White Matter Abnormalities in the Very Preterm Neonatea

Variables

Score 0

Score 1

Score 2

Score 3

Score 4 Extensive bilateral 1/0

CEREBRAL WHITE MATTER Cystic lesions

Nil 94/100

Focal unilateral 2/0

Focal bilateral 1/0

Extensive unilateral 2/0

Focal signal abnormality

Nil 80/90

Focal punctate 13/10

Extensive punctate 5/0

Linear 2/0

Myelination delay

PLIC and corona radiata 67/100

Only PLIC 27/0

Minimal – no PLIC 6/0

Thinning of the corpus callosum

Nil 41/82

Partial (genu/body <1.3 mm or splenium <2.0 mm) 55/18

Global (genu/body <1.3 mm and splenium <2.0 mm) 4/0

Both sides VD <7.5 mm

One side 7.5 mm < VD < 10 mm

Both sides VD > 10 mm

27/77

20/18

Both sides 7.5 mm < VD < 10 mm or one side VD > 10 mm 43/5

cBPD ≥77 mm 22/86

77 mm > cBPW ≥ 72 mm 31/9

72 mm > cBPW ≥ 67 mm 41/5

67 mm >cBPW 6/0

Dilated lateral ventricles

Volume reduction

a Data are shown as percent preterm/percent term control. cBPD, Corrected biparietal diameter; cBPW, corrected biparietal width; PLIC, posterior limb of internal capsule; VD, ventricular diameter.

10/0

940 PART XI I  Neurologic System

TABLE 63.5 

Comparison of Cranial Ultrasonography and Magnetic Resonance Imaging Used for the Prediction of Motor Outcome at 18–30 Months Number

Age at Follow-Up (months)

Sensitivity

Specificity

PPV

NPV

Valkama et al., (55) (severe IVH/PVL/FI)

CUS MRI

51 50

18

0.67 0.82

0.85 0.97

0.57 0.90

0.89 0.95

Woodward et al., (57) (severe IVH/PVL, moderate– severe WMI)

CUS MRI

167

24

0.18 0.65

0.95 0.85

0.23 0.31

0.91 0.95

de Vries et al., (44) (CUS only) (severe IVH/c-PVL/FI)

CUS

1460

24

0.76

0.95

0.48

0.99

de Vries et al., (25) (sequential CUS/MRI-TEA)

CUS MRI

1691 77

24

0.57 0.92

0.98 0.55

0.44 0.73

0.99 0.90

de Vries et al., (25) (combined serial CUS, MRI-TEA) (severe IVH/c-PVL/FI)

CUS MRI

77

24

0.79

0.94

0.96

0.69

Mirmiran et al., (56) (moderate–severe WMI; focal par. injury)

CUS MRI

61

30

0.43 0.86

0.82 0.89

0.33 0.60

0.87 0.97

Munck et al., (60)a

CUS MRI

180

24

0.54 0.85

0.95 0.78

0.47 0.23

0.96 0.98

Leijser et al., (7)b

CUS MRI

32

24

0.75 1.00

0.86 0.86

0.43 0.43

0.96 1.00

Skiold et al., (40) (MRI only) (moderate–severe WMI)

MRI

107

30

0.60

0.96

0.50

0.98

a

Major abnormalities: IVH grades III-IV, hemorrhage of the brain parenchyma, white matter cysts, abnormal T1 or T2 signals in cortex, basal ganglia, thalamus, cerebellum or internal capsule, abnormality of the corpus callosum, an extracerebral space width of 6 mm or more, and ventriculitis. b Severe CUS: multicystic PVL and/or focal echodensities within the white matter; severely abnormal MRI: extensive SI changes with hemorrhagic or (pre)cystic lesions in the periventricular white matter, with periventricular and/or subcortical extension. cPVL, Cystic periventricular leukomalacia; CUS, cranial ultrasonography; FI, focal infarction; IVH, intraventricular hemorrhage; MRI, magnetic resonance imaging; NPV, negative predictive value; PPV, positive predictive value; PVL, periventricular leukomalacia; SI, signal intensity; TEA, term equivalent age; WMI, white matter injury.

on a small number of studies, with only two or three studies included in each category of outcome, underscoring the serious need for more research in this area. Nevertheless, the relative lack of sensitivity of structural MRI for identifying brain injury in the preterm neonate has led to a search for more sensitive approaches, including volumetric studies, diffusion imaging analysis, and functional connectivity MRI, in hopes of finding more sensitive and accurate predictors of outcome. As above, the finding of enlarged extracerebral spaces on term equivalent MRI may reflect a small brain caused by volume loss and/or poor growth as a consequence of injury and undernutrition during the period from preterm birth to term age. For research studies, brain volume can be quantified with more specificity: i.e., after segmenting brain into tissue classes such as cortical gray matter, white matter, deep nuclear gray matter, brainstem, and cerebellum. Widespread alterations in cerebral volumes have been described for preterm neonates imaged at term age (Huppi et al., 1998b), and a number of studies have related volume changes with neurodevelopmental outcome. At short-term follow-up (< 2 years), neurodevelopmental disability was associated with reduced cortical and deep nuclear gray matter volumes, increased CSF volume (Inder et al., 2005; Young et al., 2015), reduced white matter volume (Peterson et al., 2003), reduced hippocampal volume (Beauchamp et al., 2008; Thompson et al., 2008), reduced total cerebral tissue volume (Woodward et al., 2005), and reduced cerebellar volume (Van Kooij et al., 2012a). At 5 years, a relationship was found between reduced cerebellar volume and poorer executive function and motor skills (Lind et al., 2010). Finally, smaller infant

hippocampal volumes were associated with lower verbal memory scores at 7 years of age (Thompson et al., 2013). Volumetric analysis of infant brain MR images requires specialized computer software and, often, user intervention to ensure that segmentations are done correctly, which hampers the use of these measures in routine clinical practice. Simpler, one-dimensional measures from structural MR images are highly correlated with volumes and could potentially be useful in a clinical setting (Nguyen The Tich et al., 2009). For example, biparietal diameter, which correlates with overall brain volume, was predictive of cognitive and motor outcomes in 2-yearold subjects after adjustment for perinatal variables and social risk (Tich et al., 2011).

Diffusion Magnetic Resonance Imaging Diffusion MRI is unique in that it provides aspects of both structural and functional information. The rapid reduction in brain water ADC associated with acute brain injury reflects an alteration in brain “function” in the sense that this reduction takes place within minutes of injury, a much shorter time frame than that of the structural changes that are subsequently detectable by histology. For the discussion here, we focus more on the microstructural information available through diffusion imaging. This information is most commonly applied to white matter and is encoded as diffusion anisotropy. Traditionally, higher anisotropy is taken to reflect “healthier” or more “ordered” white matter. During early brain development, overall water diffusion coefficients decrease steadily, most likely as a reflection of the reduction



in brain water content that accompanies maturation. Diffusion anisotropy values in white matter, on the other hand, increase during development in association with myelination (Huppi et al., 1998a; Neil et al., 1998). As noted above, the most common white matter injury in preterm neonates is characterized by diffuse white matter changes. This diffuse injury is defined histologically (Volpe, 2009a), but diffusion imaging provides supporting evidence for its presence in the form of globally reduced white matter diffusion anisotropy values in preterm neonates (Huppi et al., 2001). Abnormalities of diffusion have been correlated with neurodevelopmental outcome as well. For infants evaluated at less than 2 years old, high diffusion coefficient values for white matter (Kaukola et al., 2010) and cerebellum (Brouwer et al., 2014) were associated with worse motor outcomes. Low white matter anisotropy values, particularly in the posterior limb of the internal capsule and corpus callosum, were also associated with poor motor outcomes (Arzoumanian et al., 2003; Drobyshevsky et al., 2007; Rose et al., 2009; van Kooij et al., 2012b; Chau et al., 2013; De Bruine et al., 2013). In longitudinal studies of preterm children at ages 4 through 7 years, high ADC values in the right orbitofrontal area have been associated with social–emotional problems (Rogers et al., 2012), and high ADC values in regions of the occipital pole and cerebellum were associated with impairment of motor and executive function (Thompson et al., 2014). In addition, low anisotropy values in the posterior limb of the internal capsule were associated with poor motor outcome at age 4 years (Rose et al., 2007). In the studies outlined above, low white matter anisotropy was associated with impaired outcome, but this relationship is not universal. In a study of preterm children evaluated at age 2 years, lower anisotropy in the right inferior temporal lobe, but higher anisotropy in the left inferior temporal lobe, was associated with lower motor scores. In another study, lower anisotropy in the left cingulum bundle was associated with better social–emotional competence (Rogers et al., 2016). These results are consistent with diffusion studies on older subjects with autism and other developmental impairments (Cheon et al., 2011). The microstructural alterations underlying these opposing results are not fully understood. It has been hypothesized that reduced axonal branching or fewer fiber tracts crossing the tract of interest may lead to higher anisotropy in injured white matter areas.

Term Neonates Neonatal Encephalopathy Among the clinical indications for neuroimaging studies from term neonates, the presence of neonatal encephalopathy is the most common. Neonatal encephalopathy has been defined as “a clinically defined syndrome of disturbed neurologic function in the earliest days of life in the term infant, manifested by difficulty with initiating and maintaining respiration, depression of tone and reflexes, subnormal level of consciousness, and often by seizures” (Nelson and Leviton, 1991). It affects 2–6 per 1000 live births, has a 15%–20% mortality rate, and 25% of survivors are left with severe disability. It is important to bear in mind that not all neonatal encephalopathy is caused by intrapartum ischemia (Kurinczuk et al., 2010). It has been estimated that on the order of 40% is due to other causes such as infection, stroke, metabolic disorder, and genetic disorders (Shah et al., 2006). The common patterns of brain injury in the encephalopathic term neonate include diffuse global injury, deep nuclear gray matter injury, brainstem injury, watershed injury, periventricular white matter injury, and focal

CHAPTER 63  Neonatal Neuroimaging

941

infarction. Of these, deep nuclear gray matter injury (25%–75% of cases) and watershed injury (15%–45% of cases) are most common (Barkovich et al., 1998; Task Force on Neonatal Encephalopathy, 2014). Deep nuclear gray matter injury involves the deep gray nuclei and perirolandic cortex, extending further into the cortex when severe. The watershed pattern involves injury at the watershed areas between the anterior and middle cerebral arteries anteriorly and the middle and posterior cerebral arteries posteriorly. Watershed injury may be unilateral or bilateral and affect the anterior watershed, the posterior watershed, or both. It primarily involves white matter but can extend into the cortical gray matter in severe cases. An example of each category of injury is shown in Fig. 63.17. From a clinical standpoint, the two forms of injury tend to be associated with different clinical scenarios. The watershed pattern of injury often follows normal labor with minimal resuscitation, relatively good Apgar scores, and an umbilical cord pH of greater than 7.00. During the postnatal period, the watershed pattern of injury is typically associated with proximal limb weakness, truncal hypotonia, and a relatively high incidence of seizures. Later in life, this injury pattern is associated with predominantly cognitive impairments with fewer functional motor deficits (Miller et al., 2005). The deep nuclear gray matter pattern of injury, on the other hand, often follows a sentinel event (e.g., cord prolapse, placental abruption, or uterine rupture) with low Apgar scores and an umbilical cord pH of less than 7.00. These neonates are more profoundly encephalopathic and may have evidence of multiorgan injury involving the heart, kidneys, and liver. During the postnatal period they are often hypotonic and feed poorly. Subsequent neurologic impairment tends to be more severe in these patients and depends on the extent of injury, as has been outlined by Martinez-Biarge et al. (2010). Furthermore, signal abnormality in the posterior limb of the internal capsule on MR imaging has a strong association with subsequent motor deficit in these neonates (Martinez-Biarge et al., 2011). It is important to bear in mind that while the patterns described here are usually associated with hypoxic–ischemic injury, there are mimics of these patterns associated with other causes such as meningitis (Hernandez et al., 2011) and metabolic disorders (Johnston and Hoon, 2000). Thus the presence of either of these patterns on MRI may be consistent with a hypoxic–ischemic insult but does not prove that one occurred. Thus the clinician should be wary. In addition to the findings derived from conventional and diffusion imaging, spectroscopy can also provide information regarding prognosis. A rise in lactate and fall in NAA are the most significant changes observed, with lactate being detected within 24 hours following injury and NAA beginning to decrease after 48 hours (Barkovich et al., 1999). Elevated lactate levels are seen for months after injury and thus do not always indicate acute injury, although the persistence of lactate signal signifies a worse prognosis (Miller et al., 2002). In a metaanalysis of 32 studies grouping 806 newborns with neonatal encephalopathy, the lactate/ NAA ratio in the deep gray matter had strong prognostic accuracy for disability, with a pooled sensitivity of 82% and a specificity of 92% (Thayyil et al., 2010). Although this measure was useful for predicting death or profound disability, more detailed anatomic imaging may assist in refining prognostic information. A study of term neonates who underwent conventional diffusion MRI and spectroscopy measurements in the basal ganglia at a median of day 4 of life showed that the addition of quantitative measures ADC, lactate/NAA, or both improved the predictive power for conventional imaging for adverse neurodevelopmental outcome (for lactate/NAA, area under the curve [AUC] = .85 and P = .006;

942

PART XI I  Neurologic System

A

B • Fig. 63.17  Common Patterns of Cerebral Injury. These are diffusion images obtained 2–4 days after injury in which areas of injury appear bright (arrow). (A) A watershed injury, predominantly in the anterior and posterior watershed areas of the left hemisphere. (B) A basal ganglia thalamic injury (arrow).

TABLE 63.6 

Neuroimaging in 1421 Infants From the Vermont Oxford Neonatal Encephalopathy Registry Ultrasonography

Computed Tomography

Magnetic Resonance Imaging

729 (51%) 42% of total

477 (34%) 28% of total

1074 (75%) 63% of total

Mean (SD) of age (days) at first examination

3.1 (4.4)

3.2 (3.5)

7.3 (8.7)

Abnormal

232 (32%)

271 (57%)

717 (67%)

Hemorrhage   IVH/SE   Extraaxial   Parenchymal

56 (8%) 24 (3%) 37 (5%)

59 (12%) 165 (35%) 57 (12%)

79 (7%) 212 (20%) 105 (10%)

Deep nuclear gray matter injury

70 (10%)

50 (10%)

309 (29%)

White matter injury

16 (2%)

15 (3%)

271 (25%)

Number of infants

IVH, Intraventricular hemorrhage; SD, standard deviation; SE, subependymal hemorrhage.

for ADC values from the basal ganglia, AUC = .93 and P < .001) (Alderliesten et al., 2011). Different imaging modalities—CUS, CT, and MRI—provide different information for patients with neonatal encephalopathy. Table 63.6 shows data from the Vermont Oxford Neonatal Encephalopathy Registry on the clinical application of these modalities (Task Force on Neonatal Encephalopathy, 2014). Note that all three modalities remain in fairly wide use. Note also that the mean time to obtaining the imaging study varies by modality, with CUS and CT being performed at a mean age of 3 days as compared with 7 days for MRI. This probably reflects the more demanding logistics of moving a neonate to the MRI suite for study. However, MRI outperforms both CUS and CT for detection of abnormalities, detecting injury in 67% of cases as opposed to

32% and 57%, respectively. Importantly, the additional injuries detected by MRI are clinically relevant. While CUS and CT show sensitivity mainly for intraventricular and extraaxial hemorrhage, MRI is much more sensitive to injury to deep nuclear gray matter and white matter (e.g., watershed injury). For neonates with neonatal encephalopathy, the American College of Obstetrics and Gynecology (with the endorsement of the American Academy of Pediatrics) suggests that information regarding the likely timing of injury is best obtained with early imaging (during the first 24–96 hours of life) with follow-up imaging to define the full nature of the abnormalities, optimally at 10 days of life (but with an acceptable window between 7 and 21 days of life) (American College of Obstetrics and Gynecology, 2014). This recommendation is supported by the finding that the extent of injury may change in up

CHAPTER 63  Neonatal Neuroimaging



to 20% of neonates on images obtained between days 3–4 and those obtained later (>7 days), particularly in neonates with hypoglycemia and moderate–severe lesions in the deep nuclear gray matter (Chakkarapani et al., 2016). However, from a practical standpoint, often only a single MRI study can be obtained. In that circumstance, we recommend that the single study be obtained later than 1 week after the initial insult and as late as feasible. Finally, it may be useful to obtain an MRI study earlier than days 3–4 in some instances, for example, to confirm the absence of injury in neonates for whom early rewarming is being considered (often in association with a normal examination and electroencephalography). Another instance is to confirm the severity of injury in profoundly encephalopathic neonates for whom redirection of care is under consideration. In this case, diffusion MRI will very likely show the injury from its onset, and MR spectroscopy (lactate/NAA ratio) will be informative.

Sinovenous Thrombosis Neuroimaging is necessary for detecting sinovenous thrombosis as well as following patient response to therapy. Sinovenous thrombosis is less common than neonatal encephalopathy and has an incidence of 2–12 per 100,000. Infants usually present with seizures and/or encephalopathy. Risk factors for sinovenous thrombosis include hypoxic–ischemic encephalopathy, complicated delivery, complicated pregnancy, dehydration, prematurity, congenital heart disease, sepsis, and prothrombotic abnormalities (Moharir et al., 2011). From an imaging standpoint, sinovenous thrombosis is often initially detected by CUS or MRI as IVH with or without associated thalamic hemorrhage (Fig. 63.18). The presence of a clot in a sinus may sometimes be visible as an area of high signal intensity (bright) on T1-weighted imaging. When these findings are present, MR venography is very helpful for delineating the thrombosis, and involvement of multiple sinuses and veins is relatively common. Identifying the extent of thrombosis is important because it is a treatable condition, and it is common to use anticoagulant therapy (cautiously, in the presence of significant hemorrhagic injury). MR venography provides a means of evaluating the response to anticoagulant therapy, and follow-up imaging is typically obtained some weeks following the initiation of therapy.

Stroke Perinatal stroke has been defined as focal ischemic brain injury secondary to vascular occlusion (Kirton and deVeber, 2009). It has an incidence of approximately 1 per 5000 live births, making it much more common than sinovenous thrombosis. As described in detail above, the appearance of stroke evolves over time. It is initially most readily detected by diffusion MR and is subsequently visible on T1-weighted and T2-weighted images (Fig. 63.19). In the case of nonhemorrhagic stroke, MRI is considerably more sensitive than CUS or CT, making MRI the preferred imaging modality. Because focal neurologic signs are relatively rare in newborns with stroke, it is not uncommon for perinatal strokes to go undiagnosed until later in the first year or so of life when neurologic deficits (typically hemiparesis) become obvious. In a study of 248 neonates with arterial ischemic stroke, part of the International Pediatric Stroke Study (Kirton et al., 2011), 72% presented with seizures and 63% with nonfocal neurologic signs. Once stroke is detected, consideration should be given to MR angiography to more fully define the anatomy of the injury. In the International Pediatric Stroke Study (Kirton et al., 2011),

943

infarcts preferentially involved the anterior circulation and the left hemisphere and were multifocal in 30% of neonates. The causes of neonatal stroke are often obscure, with cardiac and prothrombotic abnormalities identified in less than 20% of the newborns. Research on neurologic outcome following stroke is relatively sparse (Lehman and Rivkin, 2014), although clinical experience suggests that neonates have a much greater capacity for recovery than adults with similar injuries. For example, in neonates with middle cerebral artery occlusion, hemiparesis is only present in 26% of children by age 2 years, although this number increases to 50%–70% when there is corticospinal tract involvement on MRI (Husson et al., 2010).

Vein of Galen Malformation Vein of Galen malformation is the most common arteriovenous malformation of the newborn, and the majority are identified during the neonatal period. The malformation is associated with dilatation of the vein of Galen and straight sinus extending to the torcula (Fig. 63.20). Newborns often present with hydrocephalus caused by compression of the cerebral aqueduct or high-output cardiac failure. Seizures are also not uncommon. Prognosis depends upon the size of the malformation, age at diagnosis, and successful neurosurgical outcome.

Infection The imaging appearance of infection is remarkably diverse, varying not only with the infectious agent but also having different appearances with the same infectious agent (Table 63.7). For example, the brain injury associated with bacterial meningitis includes watershed injury, arterial occlusion with stroke, capillary thrombosis with smaller areas of injury, and sinovenous thrombosis, all of which have a characteristic appearance on MRI. As noted above, bacterial meningitis may very closely mimic hypoxic–ischemic injury (Hernandez et al., 2011). The characteristic abnormalities associated with congenital cytomegalovirus infection are shown in Fig. 63.21. The marked predilection for parechovirus (which is postnatally acquired) for white matter is evident in Fig. 63.22.

Other Intracranial Hemorrhages Aside from the IVHs described in detail above for preterm neonates, the other major, clinically important types of neonatal intracranial hemorrhage are: (1) epidural hemorrhage, (2) subdural hemorrhage, including posterior fossa subdural hemorrhages, (3) primary subarachnoid hemorrhage, and (4) other forms of intraparenchymal hemorrhages (other than cerebellar). The approximate incidence, anatomic site of blood, relative frequency in preterm versus term born neonates, and the usual clinical gravity of these hemorrhages, including CBH and IVH, are noted in Table 63.8. The incidence of intracranial hemorrhage has been challenging to define, as most studies have focused on symptomatic newborns, and some hemorrhages are asymptomatic. In one small study of symptomatic newborns, the estimated incidence was 4.9 per 10,000 live births (Hanigan et al., 1995). The largest epidemiologic data relate to the Californian Perinatal Database, which includes maternal and neonatal hospital discharge records on 600,000 infants (2500–4000 g) born to nulliparous women. In this study, the incidence of symptomatic intracranial hemorrhage associated with spontaneous delivery was 1 per 1900 births, vacuum extraction delivery was 1 per 860 births, and forceps delivery was 1 per 664

944 PART XI I  Neurologic System

A

B

C

D • Fig. 63.18  Images From a Term Newborn With Sinus Thrombosis. (A) A coronal cranial ultrasonog-

raphy (CUS) image with a bright-appearing thalamic hemorrhage (arrow). (B) A parasagittal view of the left lateral ventricle. Note the thalamic hemorrhage (arrow) and blood in the occipital horn of the ventricle (arrowhead). (C) The coronal T1-weighted magnetic resonance (MR) image corresponding to the CUS image in A. The thalamic hemorrhage appears bright (arrow). (D) An axial T2-weighted MR image in which hemorrhage appears dark. Note the thalamic hemorrhage (arrow) and blood in the lateral ventricles (arrowheads).

births (Towner et al., 1999). In contrast, more recent studies utilizing MRI in asymptomatic newborns in the first month of life have revealed a much higher frequency of intracranial hemorrhage. A large prospective study found an 8% prevalence of subdural hemorrhage in this population (Whitby et al., 2004; Rooks et al., 2008). A second study of 88 asymptomatic neonates born via vaginal delivery who underwent MRI between the ages of 1 and 5 weeks demonstrated 17 term neonates with intracranial hemorrhage for a study prevalence of 26% (Looney et al., 2007). Such findings suggest that asymptomatic intracranial hemorrhage in term newborns is more frequent than previously thought. With these limitations regarding the incidence of intracranial hemorrhage in mind, Table 63.8 provides a summary of the

location, incidence, and usual clinical outcomes of the main types of hemorrhage. Note that subdural hemorrhage is more frequent in the term neonate than in the preterm neonate and is frequently asymptomatic but can be clinically serious if large. Primary subarachnoid hemorrhage is more frequent in the preterm neonate than in the term neonate and is fairly common but is almost always clinically benign. Cerebellar hemorrhage is more frequent in the preterm neonate than in the term neonate and can have developmental consequences as outlined above. As also outlined above, IVH, almost exclusively a lesion of the preterm neonate, affects developmental outcome. IVH recently has been more commonly recognized in the term-born infant, particularly in relation to sinovenous thrombosis and/or hypoxic–ischemic

CHAPTER 63  Neonatal Neuroimaging



945

T2

Diffusion

Two days

*

*

Three weeks

• Fig. 63.19  Images from a term newborn who presented with episodes of rhythmic jerking of the right

upper and lower extremities with rightward eye deviation at approximately 24 hours of age. Note the area of stroke on the diffusion image at age 2 days (top left), which appears bright (representing a low apparent diffusion coefficient value). Note also that the injury is visible on the T2-weighted image (top right), in this case as loss of the cortical ribbon (arrow). The asterisk on each image denotes an area of magnetic susceptibility artifact. The lower row images were obtained at age 3 weeks. Note that the injury is no longer detectable on diffusion imaging (bottom left) but is now an area of encephalomalacia on the T2weighted image (bottom right; arrow).

cerebral injury. Other forms of intraparenchymal hemorrhage, more frequent in the term neonate than in the preterm neonate, are uncommon. The three primary brain imaging modalities—CUS, CT, and MRI—have different sensitivities for detecting hemorrhage. As noted above, CUS is the method of choice for evaluating IVH

in preterm neonates because of its suitability for serial imaging of critically ill neonates. However, CUS is not the modality of choice for all forms of hemorrhage. In a study analyzing 4171 term-born infants, imaging was performed for 2006 patients with CUS, 933 patients with CT, and 2690 patients with MRI. Although cranial ultrasound identified IVH well, it lacked the

946

PART XI I  Neurologic System

A

B

C • Fig. 63.20  Images From a Term Newborn With Vein of Galen Malformation. (A, B) Note the large flow void on the T2-weighted images. (C) The corresponding angiogram. (Images courtesy of Dr. Bob McKinstry.) sensitivity of MRI and CT for identifying other types of hemorrhage and intracranial injury and was particularly limited for the detection of extraaxial hemorrhage (subdural, subarachnoid, and extradural) (Pfister et al., 2012; Barnette et al., 2014). CT was recommended in the 2002 American Academy of Neurology practice parameters for neonates with birth trauma and a low hematocrit or coagulopathy (Ment et al., 2002) on the basis of data from two small studies reporting on CT diagnoses of intracranial hemorrhages leading to interventions (Odita and Hebi, 1996; Perrin et al., 1997). Although the authors were unable to determine the impact of the imaging findings on the neonates who needed surgical intervention, only 9 of 933 neonates with CT examinations underwent any central nervous system surgery. Given the risks of radiation exposure associated with CT imaging, we suggest using MRI, when available, to detect extraaxial hemorrhage. The use of MRI has the added benefit of better sensitivity for detecting parenchymal injury than CT. Development of more rapid MRI sequences to allow for shorter studies to detect cerebral hemorrhage should enhance physician comfort with this as a first-line technique.

Subdural Hemorrhage MRI is more effective than CT in the delineation of posterior fossa subdural hemorrhage (Barkovich, 2005). Detection of subdural hematoma by ultrasound scanning, although reported, generally is difficult. Moreover, even when these hematomas are detected, the extent and distribution of supratentorial lesions are usually demonstrated far better by MRI or CT and infratentorial lesions are detected better by MRI. In addition, the vast majority of subdural hematomas are infratentorial, where ultrasound has even greater challenges in accurate diagnosis (Fig. 63.23).

Subarachnoid Hemorrhage The diagnosis of primary subarachnoid hemorrhage is usually made by MRI or CT and, on rare occasions, by ultrasound (Barnette et al., 2014). On CT, distinction between the normal, slightly increased attenuation in the regions of the falx and major venous sinuses and the increased attenuation caused by subarachnoid hemorrhage may be difficult. Sometimes, the possibility of primary

CHAPTER 63  Neonatal Neuroimaging



TABLE 63.7 

Magnetic Resonance Imaging Findings for Neonatal Infections

Infection

Imaging Findings

Infection

Imaging Findings

Bacterial meningitis

Basal ganglia injury Watershed injury Sinovenous thrombosis Infarct (may be multifocal) Abscess Extraaxial empyema Ventriculomegaly

Varicella (congenital)

Diffuse cerebral necrosis Cerebellar hypoplasia Cortical malformations, including pachygyria

Herpes simplex (congenital)

Microcephaly with severe volume loss

Herpes simplex (peripartum/ postnatal)

Early

Cytomegalovirus (congenital)

Calcifications (periventricular and cortical) Cortical malformations (lissencephaly, polymicrogyria, heterotopias) Ventriculomegaly Cerebellar hypoplasia Periventricular leukomalacia Porencephaly

Toxoplasmosis (congenital)

Diffuse cerebral necrosis Porencephaly Hydranencephaly Diffuse cerebral calcifications Periventricular necrosis Hydrocephalus

Rubella (congenital)

TABLE 63.8 

947

Periventricular and basal ganglia calcification Ventriculomegaly Multifocal white matter lesions Leukoencephalopathy Subcortical cysts Cortical malformations are uncommon.

Multifocal injury Signal abnormality may be limited to the temporal lobes, cerebellum, or brainstem (may be hemorrhagic) Basal ganglia injury Watershed injury

Late Multicystic encephalomalacia White and gray matter volume loss Calcification Zika (congenital)

Cortical malformations (lissencephaly, heterotopias, polymicrogyria) Parenchymal calcifications Ventriculomegaly Dysgenesis of the corpus callosum Cerebellar hypoplasia Brainstem hypoplasia

Parechovirus (neonatal)

Diffuse white matter injury with cortical sparing

Intracranial Hemorrhage

Hemorrhage

Incidence %

Site of Blood

Full Term or Preterm

Usual Clinical Outcome

Extradural (Epidural)

Very rare

Between skull and outside of dura

FT > PT

Variable

Subdural

5–25

Between dura and arachnoid

FT > PT

Benign

Subarachnoid

1–2 FT 10 PT

Between arachnoid and pia

PT > FT

Benign

Cerebellar

0.1 FT 5 PT

Cerebellar hemispheres and/or vermis

PT > FT

Serious

Intraventricular

0.2 FT 15 PT

Within ventricles or Including periventricular hemorrhagic infarction

PT > FT

Serious

Parenchymal

0.1 FT 2–4 PT

Cerebral parenchyma

FT > PT

Variable

FT, Full term; PT, preterm.

subarachnoid hemorrhage is raised initially by the findings of an elevated number of red blood cells and an elevated protein content in the CSF, usually obtained for another purpose (e.g., to rule out meningitis). Exclusion of the relatively common (e.g., extension from subdural, cerebellar, or IVH) and uncommon (e.g., tumor, vascular lesions) causes of blood in the subarachnoid space is best done by MRI.

Ultrasonography is insensitive in detecting subarachnoid hemorrhage because of the normal increase in echogenicity around the periphery of the brain (Shackelford and Volpe, 1985). A large subarachnoid hemorrhage occasionally distends the Sylvian fissure and thus becomes detectable, but care must be taken not to confuse a Sylvian fissure distended with blood from the wide fissure seen consistently in preterm neonates and resulting from the normal

948

PART XI I  Neurologic System

A

B

C • Fig. 63.21 A

16-day-old neonate born after 31 weeks’ gestation with congenital cytomegalovirus infection identified in utero. (A) An axial T1-weighted magnetic resonance imaging (MRI) scan shows an increased signal in the periventricular regions (short arrows), consistent with calcification, and diffuse polymicrogyria (long arrow). (B) Note the striking cerebellar hypoplasia (arrows). (C) At 6 months of age, the axial T2-weighted MRI scan shows diffuse frontal polymicrogyria (long arrows), abnormal high signal intensity in cerebral white matter (short black arrows), and marked paucity of parieto–occipital cerebral white matter (double white arrows). (Courtesy of Dr. Omar Khwaja.)

separation of the frontal operculum and superior temporal region until late in gestation (Chamnanvanakij and Perlman, 1999).

Methods Not Yet in Clinical Use Quantitative Interpretation of Magnetic Resonance Imaging Studies MRI studies are almost universally subjected to qualitative interpretation in the clinical setting. However, a number of quantitative

scoring systems have been devised (see Table 63.4), though there is no universally accepted, or gold standard, scoring system. Most scoring systems rely upon features of conventional T1-weighted and T2-weighted images, with a tendency for some scoring systems to focus mainly on loss of brain volume, while others focus primarily on signal abnormality. Since brain injury during the neonatal period may lead to both poor brain growth (small volume) and injury to remaining tissue (signal abnormality on MRI studies), it is useful to take both into account in a scoring system. To complicate matters further, some scoring systems focus on relatively confined

CHAPTER 63  Neonatal Neuroimaging



A

949

B

C • Fig. 63.22  Parechovirus Infection in a Neonate. T2-weighted (A) and diffusion (B) magnetic resonance images obtained 6 days after the onset of human parechovirus infection in a neonate. (C) A T1-weighted image obtained at 3 months. Note the multiple punctate white matter lesions (A, arrows) and diffusion abnormality (B, areas of low apparent diffusion coefficient appear bright) in the periventricular white matter and involving the optic radiation and the internal capsule. Note also the areas of high signal intensity in the periventricular white matter present at 3 months of age, suggesting gliosis (C). (Adapted from VerboonMaciolek MA, Groenendaal F, Hahn CD, et al. Human parechovirus causes encephalitis with white matter injury in neonates. Ann Neurol. 2008;64:266–273.) areas of the brain, such as white matter, without evaluation of cortical gray matter, deep nuclear gray matter, and/or the posterior fossa. The broadest scoring system would take both loss of volume and signal abnormality into account for the entire brain and cerebellum (Kidokoro et al., 2013).

Cortical Cartography In addition to the scoring systems noted above, cortical cartography provides a means by which to quantify MRI studies. Cortical

cartography involves analysis of the cortical surface. With this approach, a surface is generated from conventional images and a number of summary parameters are measured to capture features of the cerebral topography. One of the more common of these is cortical surface area, which increases dramatically during the immediate postnatal period in preterm neonates. A second parameter is the gyrification index, a ratio of surface areas: the numerator is the cortical surface area, and the denominator is the cerebral hull area, which can be imagined as the surface area of cling wrap if it were wrapped around the brain (Van Essen, 2005). For a completely

950

PART XI I  Neurologic System

smooth, or lissencephalic, brain, the gyrification index would be 1. As the number and depth of cortical folds increase the gyrification index increases. As would be expected, the gyrification index increases during normal brain development (Shimony et al., 2016). As for cortical surface area, the gyrification index is affected by preterm birth and is lower for preterm neonates at term equivalent age compared with control neonates in a region-specific fashion (Engelhardt et al., 2015). Gyrification index values have also been related to neurodevelopmental outcome (Dubois et al., 2008a). A third index derived from cortical cartography is sulcal depth, which is the distance between the cerebral hull and the bottom of each sulcus (Van Essen, 2005). As with the other parameters, sulcal depth increases with brain development (Dubois et al., 2008b; Zubiaurre-Elorza et al., 2009; Shimony et al., 2016), and abnormalities of sulcal depth have been described for preterm neonates (Engelhardt et al., 2015).

Functional Magnetic Resonance Imaging

• Fig. 63.23  Tentorial

Near-Infrared Spectroscopy

Subdural Hemorrhage With Blood Layering Along Both Leaves of the Tentorium and Posterior Falx. (Adapted from Castillo M, Fordham LA. MR of neurologically symptomatic newborns after vacuum extraction delivery. AJNR Am J Neuroradiol. 1995;16:816–818.)

26 wks

30 wks

34 wks

As described above for susceptibility-weighted imaging, the signal in an MRI study can be made sensitive to the presence of reduced iron in deoxyhemoglobin. In regions of hemorrhage, the effects are striking. However, more subtle effects can also be detected in the case of changes to intravascular deoxyhemoglobin concentration. For example, when neuronal firing rates increase in an area of brain because of activation by a task, local blood flow increases while local oxygen utilization changes very little. As a result, local deoxyhemoglobin levels fall, and this reduction is detectable as a small (on the order of a few percent) increase in the signal intensity on susceptibility-weighted images. This contrast forms the basis of functional MRI, in which susceptibility-weighted images are obtained before, during, and after a subject performs a task. The MR signal in these studies is referred to as blood oxygenation level dependent, or BOLD, signal. Areas of neural activation can be detected as areas of increased BOLD signal intensity during performance of the task. One might be forgiven for thinking that this particular approach is not very useful for studying neonates, who are not particularly adept at performing tasks on demand, but there is a variant of this method that can be used to identify neural networks in the resting, or even sleeping, subject. While the precise neurophysiologic basis of this method is not yet completely understood, it is probably related to spontaneous, gradual changes in local neuronal firing rates. These changes take place over tens of seconds or minutes and are associated with matching changes in local BOLD signal. If two brain regions are connected, these gradual changes in firing rate, and hence changes in BOLD signal intensity, take place synchronously. As a result, one can identify brain regions that are connected by searching for areas that have synchronous spontaneous fluctuations in BOLD signal. Conversely, areas that have an inhibitory connection show anticorrelated fluctuations in BOLD signal. This method can be used in preterm neonates to monitor the emergence of neural networks (Fig. 63.24). While functional connectivity MRI is not in routine clinical use and requires specialized data acquisition and software, studies have shown widespread alterations in neural networks in preterm neonates at term equivalent age despite normal conventional images (Smyser et al., 2016).

Near-infrared spectroscopy (NIRS) is analogous to the pulse oximetry that is commonly used in clinical practice to monitor

38 wks

• Fig. 63.24  Resting State Functional Magnetic Resonance Imaging Data From Neonates at Various

Postmenstrual Ages. A seed point was placed in the motor cortex (bright yellow dot). The connections between motor cortex, contralateral motor cortex (arrow) and supplementary motor cortex (arrowhead) emerge at approximately 38 weeks’ gestation. (Adapted from Smyser CD, Inder TE, Shimony JS, et al. Longitudinal analysis of neural network development in preterm infants. Cereb Cortex. 2010;20:2852– 2862.)

Term control



arterial oxygen saturation. Both pulse oximetry and NIRS use similar wavelengths of light. For pulse oximetry, the signal is processed to isolate the signal from arterial blood to measure arterial oxygen saturation. Localization is not particularly crucial in this case and is achieved by passing the light through a digit using a pair of optodes. Commercially available NIRS devices work very similarly to pulse oximetry. Since the signal is not usually processed to evaluate arterial blood, NIRS typically provides a relative measure of mixed venous tissue oxygenation. For research applications such as functional activation, localization to various brain regions may be achieved using optode arrays (Gregg et al., 2010; Liao et al., 2010). The parameters available from NIRS include oxyhemoglobin and deoxyhemoglobin levels, cerebral oxygen saturation, and the fraction of tissue oxygen extraction (this last parameter is calculated

CHAPTER 63  Neonatal Neuroimaging

951

in conjunction with arterial oxygen saturation levels obtained with pulse oximetry). While NIRS is not widely used in clinical practice, it has been used to study a variety of conditions, including infants with apnea and bradycardia (Petrova and Mehta, 2006), different modes of ventilation (Schwaberger et al., 2015; Guerin et al., 2016), IVH (Vesoulis et al., 2016), and extracorporeal membrane oxygenation (Liem et al., 1995). In a study of asphyxiated neonates, higher cerebral oxygen saturation and lower fractional cerebral tissue oxygen extraction after 24 hours were associated with poor neurodevelopmental outcome, suggesting secondary energy failure in these neonates (Toet et al., 2006). Complete references used in this text can be found online at www .expertconsult.com



References Adams-Chapman I, Hansen NI, Stoll BJ, Higgins R, NICHD Research Network. Neurodevelopmental outcome of extremely low birth weight infants with posthemorrhagic hydrocephalus requiring shunt insertion. Pediatrics. 2008;121:e1167-e1177. Alderliesten T, de Vries LS, Benders MJ, Koopman C, Groenendaal F. MR imaging and outcome of term neonates with perinatal asphyxia: value of diffusion-weighted MR imaging and (1)H MR spectroscopy. Radiology. 2011;261:235-242. Allan WC, Holt PJ, Sawyer LR, Tito AM, Meade SK. Ventricular dilation after neonatal periventricular-intraventricular hemorrhage. Natural history and therapeutic implications. Am J Dis Child. 1982;136:589-593. Almli CR, Rivkin MJ, McKinstry PR, Brain Development Cooperative Group. The NIH MRI study of normal brain development (Objective-2): newborns, infants, toddlers, and preschoolers. Neuroimage. 2007;35:308-325. American College of Obstetrics and Gynecology. Executive summary: Neonatal encephalopathy and neurologic outcome, second edition. Report of the American College of Obstetricians and Gynecologists’ Task Force on Neonatal Encephalopathy. Obstet Gynecol. 2014;123:896-901. Anderson PJ, Doyle LW. Cognitive and educational deficits in children born extremely preterm. Semin Perinatol. 2008;32:51-58. Arzoumanian Y, Mirmiran M, Barnes PD, et al. Diffusion tensor brain imaging findings at term-equivalent age may predict neurologic abnormalities in low birth weight preterm infants. AJNR Am J Neuroradiol. 2003;24:1646-1653. Barkovich AJ. Pediatric Neuroimaging. Philadelphia, PA: Lippincott Williams & Wilkins; 2005. Barkovich AJ, Baranski K, Vigneron D, et al. Proton MR spectroscopy for the evaluation of brain injury in asphyxiated, term neonates. AJNR Am J Neuroradiol. 1999;20:1399-1405. Barkovich AJ, Hajnal BL, Vigneron D, et al. Prediction of neuromotor outcome in perinatal asphyxia: evaluation of MR scoring systems. AJNR Am J Neuroradiol. 1998;19:143-149. Barnette AR, Horbar JD, Soll RF, et al. Neuroimaging in the evaluation of neonatal encephalopathy. Pediatrics. 2014;133:e1508-e1517. Basser PJ, Pajevic S, Pierpaoli C, Duda J, Aldroubi A. In vivo fiber tractography using DT-MRI data. Magn Reson Med. 2000;44:625-632. Beauchamp MH, Thompson DK, Howard K, et al. Preterm infant hippocampal volumes correlate with later working memory deficits. Brain. 2008;131:2986-2994. Bednarek N, Mathur A, Inder T, Wilkinson J, Neil J, Shimony J. Impact of therapeutic hypothermia on MRI diffusion changes in neonatal encephalopathy. Neurology. 2012;78:1420-1427. Benveniste H, Hedlund LW, Johnson GA. Mechanism of detection of acute cerebral ischemia in rats by diffusion-weighted magnetic resonance spectroscopy. Stroke. 1992;23:746-754. Berfelo FJ, Kersbergen KJ, van Ommen CH, et al. Neonatal cerebral sinovenous thrombosis from symptom to outcome. Stroke. 2010;41:1382-1388. Boice JD Jr. Radiation epidemiology and recent paediatric computed tomography studies. Ann ICRP. 2015;44:236-248. Bolduc ME, Du Plessis AJ, Evans A, et al. Cerebellar malformations alter regional cerebral developmen. Dev Med Child Neurol. 2011;53:1128-1134. Brenner DJ, Doll R, Goodhead DT, et al. Cancer risks attributable to low doses of ionizing radiation: assessing what we really know. Proc Natl Acad Sci USA. 2003;100:13761-13766. Brossard-Racine M, Du Plessus AJ, Limperopoulos C. Developmental cerebellar cognitive affective syndrome in ex-preterm survivors following cerebellar injury. Cerebellum. 2015;14:151-164. Brouwer AJ, Brouwer MJ, Groenendaal F, Benders MJ, Whitelaw A, De Vries LS. European perspective on the diagnosis and treatment of posthaemorrhagic ventricular dilatation. Arch Dis Child Fetal Neonatal Ed. 2012;97:F50-F55. Brouwer MJ, De Vries LS, Pistorius L, Rademaker KJ, Groenendaal F, Benders MJ. Ultrasound measurements of the lateral ventricles in

CHAPTER 63  Neonatal Neuroimaging

951.e1

neonates: why, how and when? A systematic review. Acta Paediatr. 2010;99:1298-1306. Brouwer A, Groenendaal F, Van Haastert IL, Rademaker K, Hanlo P, De Vries L. Neurodevelopmental outcome of preterm infants with severe intraventricular hemorrhage and therapy for post-hemorrhagic ventricular dilatation. J Pediatr. 2008;152:648-654. Brouwer MJ, Van Kooij BJ, Van Haastert IC, et al. Sequential cranial ultrasound and cerebellar diffusion weighted imaging contribute to the early prognosis of neurodevelopmental outcome in preterm infants. PLoS ONE. 2014;9:e109556. Busch E, Hoehn-Berlage M, Eis M, Gyngell ML, Hossman KA. Simultaneous recording of EEG, DC potential and diffusion-weighted NMR imaging during potassium induced cortical spreading depression in rats. NMR Biomed. 1995;8:59-64. Castillo M, Fordham LA. MR of neurologically symptomatic newborns after vacuum extraction delivery. AJNR Am J Neuroradiol. 1995;16:816818. Chakkarapani E, Poskitt KJ, Miller SP, et al. Reliability of early magnetic resonance imaging (MRI) and necessity of repeating MRI in noncooled and cooled infants with neonatal encephalopathy. J Child Neurol. 2016;31:553-559. Chamnanvanakij S, Perlman JM. Extensive late-onset primary subarachnoid hemorrhage in a preterm infant. Pediatr Neurol. 1999;21:735-738. Chau V, Synnes A, Grunau RE, Poskitt KJ, Brant R, Miller SP. Abnormal brain maturation in preterm neonates associated with adverse developmental outcomes. Neurology. 2013;81:2082-2089. Cheon KA, Kim YS, Oh SH, et al. Involvement of the anterior thalamic radiation in boys with high functioning autism spectrum disorders: a Diffusion Tensor Imaging study. Brain Res. 2011;1417:77-86. Clark CA, Woodward LJ. Neonatal cerebral abnormalities and later verbal and visuospatial working memory abilities of children born very preterm. Dev Neuropsychol. 2010;35:622-642. Counsell SJ, Allsop JM, Harrison MC, et al. Diffusion-weighted imaging of the brain in preterm infants with focal and diffuse white matter abnormality. Pediatrics. 2003;112:1-7. Cowan F, Mercuri E, Groenendaal F, et al. Does cranial ultrasound imaging identify arterial cerebral infarction in term neonates? Arch Dis Child Fetal Neonatal Ed. 2005;90:F252-F256. Davies MW, Swaminathan M, Chuang SL, Betheras FR. Reference ranges for the linear dimensions of the intracranial ventricles in preterm neonates. Arch Dis Child Fetal Neonatal Ed. 2000;82:F218-F223. De Bruine FT, Van Wezel-Meijler G, Leijser LM, et al. Tractography of white-matter tracts in very preterm infants: a 2-year follow-up study. Dev Med Child Neurol. 2013;55:427-433. de Vries LS, Benders MJ, Groenendaal F. Imaging the premature brain: ultrasound or MRI? Neuroradiology. 2013a;55(suppl 2):13-22. de Vries LS, Benders MJ, Groenendaal F. Progress in neonatal neurology with a focus on neuroimaging in the preterm infant. Neuropediatrics. 2015;46:234-241. de Vries LS, Brouwer AJ, Groenendaal F. Posthaemorrhagic ventricular dilatation: when should we intervene? Arch Dis Child Fetal Neonatal Ed. 2013b;98:F284-F285. de Vries LS, Liem KD, van Dijk K, Dutch Working Group of Neonatal Neurology, et al. Early versus late treatment of posthaemorrhagic ventricular dilatation: results of a retrospective study from five neonatal intensive care units in The Netherlands. Acta Paediatr. 2002;91:212-217. de Vries LS, van Haastert IL, Rademaker KJ, Koopman C, Groenendaal F. Ultrasound abnormalities preceding cerebral palsy in high-risk preterm infants. J Pediatr. 2004;144:815-820. de Vries LS, Volpe J. Value of sequential MRI in preterm infants. Neurology. 2013;81:2062-2063. Drobyshevsky A, Bregman J, Storey P, et al. Serial diffusion tensor imaging detects white matter changes that correlate with motor outcome in premature infants. Dev Neurosci. 2007;29:289-301. Dubois J, Benders M, Borradori-Tolsa C, et al. Primary cortical folding in the human newborn: an early marker of later functional development. Brain. 2008a;131:2028-2041.

951.e2

PART XI I  Neurologic System

Dubois J, Benders M, Cachia A, et al. Mapping the early cortical folding process in the preterm newborn brain. Cereb Cortex. 2008b;18:1444-1454. Dyet LE, Kennea N, Counsell SJ, et al. Natural history of brain lesions in extremely preterm infants studied with serial magnetic resonance imaging from birth and neurodevelopmental assessment. Pediatrics. 2006;118:536-548. Ecury-Goossen GM, Dudink J, Lequin M, Feijen-Roon M, Horsch S, Govaert P. The clinical presentation of preterm cerebellar haemorrhage. Eur J Pediatr. 2010;169:1249-1253. Edgin JO, Inder TE, Anderson PJ, Hood KM, Clark CA, Woodward LJ. Executive functioning in preschool children born very preterm: relationship with early white matter pathology. J Int Neuropsychol Soc. 2008;14:90-101. Engelhardt E, Inder TE, Alexopoulos D, et al. Regional impairments of cortical folding in premature infants. Ann Neurol. 2015;77:154-162. Ford JC, Hackney DB, Alsop DC, et al. MRI characterization of diffusion coefficients in a rat spinal cord injury model. Magn Reson Med. 1994;31:488-494. Foster-Cohen SH, Friesen MD, Champion PR, Woodward LJ. High prevalence/low severity language delay in preschool children born very preterm. J Dev Behav Pediatr. 2010;31:658-667. Ganzetti M, Wenderoth N, Mantini D. Whole brain myelin mapping using T1- and T2-weighted MR imaging data. Front Hum Neurosci. 2014;8:671. Gholipour A, Polak M, Van Der Kouwe A, Nevo E, Warfield SK. Motionrobust MRI through real-time motion tracking and retrospective super-resolution volume reconstruction. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:5722-5725. Glover GH, Pauly JM. Projection reconstruction techniques for reduction of motion effects in MRI. Magn Reson Med. 1992;28:275-289. Gregg NM, White BR, Zeff BW, Berger AJ, Culver JP. Brain specificity of diffuse optical imaging: improvements from superficial signal regression and tomography. Front Neuroenergetics. 2010;2:pii: 14. Guerin C, Bailey SM, Mally PV, Rojas M, Bhutada A, Rastogi S. Randomized control trial comparing physiologic effects in preterm infants during treatment with nasal continuous positive airway pressure (NCPAP) generated by Bubble NCPAP and Ventilator NCPAP: a pilot study. J Perinat Med. 2016;44:655-661. Gumus K, Keating B, White N, et al. Comparison of optical and MR-based tracking. Magn Reson Med. 2015;74:894-902. Hall P, Adami HO, Trichopoulos D, et al. Effect of low doses of ionising radiation in infancy on cognitive function in adulthood: Swedish population based cohort study. BMJ. 2004;328:19. Hamrick SE, Miller SP, Leonard C, et al. Trends in severe brain injury and neurodevelopmental outcome in premature newborn infants: the role of cystic periventricular leukomalacia. J Pediatr. 2004;145:593599. Hanigan WC, Powell FC, Miller TC, Wright RM. Symptomatic intracranial hemorrhage in full-term infants. Childs Nerv Syst. 1995;11:698-707. Hernandez MI, Sandoval CC, Tapia JL, et al. Stroke patterns in neonatal group B streptococcal meningitis. Pediatr Neurol. 2011;44:282-288. Hintz SR, Kendrick DE, Wilson-Costello DE, NICHD Neonatal Research Network, et al. Early-childhood neurodevelopmental outcomes are not improving for infants born at <25 weeks’ gestational age. Pediatrics. 2011;127:62-70. Hunt RW, Warfield SK, Wang H, Kean M, Volpe JJ, Inder TE. Assessment of the impact of the removal of cerebrospinal fluid on cerebral tissue volumes by advanced volumetric 3D-MRI in posthaemorrhagic hydrocephalus in a premature infant. J Neurol Neurosurg Psychiatry. 2003;74:658-660. Huppi PS, Maier SE, Peled S. Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging. Pediatr Res. 1998a;44:584-590. Huppi PS, Murphy B, Maier SE, et al. Microstructural brain development after perinatal cerebral white matter injury assessed by diffusion tensor magnetic resonance imaging. Pediatrics. 2001;107:455-460.

Huppi PS, Warfield S, Kikinis R, et al. Quantitative magnetic resonance imaging of brain development in premature and mature newborns. Ann Neurol. 1998b;43:224-235. Husson B, Hertz-Pannier L, Renaud C, AVCnn Group, et al. Motor outcomes after neonatal arterial ischemic stroke related to early MRI data in a prospective study. Pediatrics. 2010;126:912-918. Inder T, Anderson N, Spencer C, Wells S, Volpe J. White matter injury in the premature infant: a comparison between serial cranial ultrasound and MRI at term. AJNR Am J Neuroradiol. 2003;24:804-809. Inder TE, Warfield SK, Wang H, Huppi PS, Volpe JJ. Abnormal cerebral structure is present at term in premature infants. Pediatrics. 2005;115:286-294. Iwata S, Nakamura T, Hizume E, et al. Qualitative brain MRI at term and cognitive outcomes at 9 years after very preterm birth. Pediatrics. 2012;129:e1138-e1147. Jary S, Kmita G, Wroblewska J, Whitelaw A. Quantitative cranial ultrasound prediction of severity of disability in premature infants with posthaemorrhagic ventricular dilatation. Arch Dis Child. 2012;97:955-959. Johnston MV, Hoon AH JR. Possible mechanisms in infants for selective basal ganglia damage from asphyxia, kernicterus, or mitochondrial encephalopathies. J Child Neurol. 2000;15:588-591. Karlsson P, Holmberg E, Lundell M, Mattsson A, Holm LE, Wallgren A. Intracranial tumors after exposure to ionizing radiation during infancy: a pooled analysis of two Swedish cohorts of 28,008 infants with skin hemangioma. Radiat Res. 1998;150:357-364. Kaukola T, Perhomaa M, Vainionpaa L, et al. Apparent diffusion coefficient on magnetic resonance imaging in pons and in corona radiata and relation with the neurophysiologic measurement and the outcome in very preterm infants. Neonatology. 2010;97:15-21. Kidokoro H, Anderson PJ, Doyle LW, Neil JJ, Inder TE. High signal intensity on T2-weighted MR imaging at term-equivalent age in preterm infants does not predict 2-year neurodevelopmental outcomes. AJNR Am J Neuroradiol. 2011;32:2005-2010. Kidokoro H, Anderson PJ, Doyle LW, Woodward LJ, Neil JJ, Inder TE. Brain injury and altered brain growth in preterm infants: predictors and prognosis. Pediatrics. 2014;134:e444-e453. Kidokoro H, Neil J, Inder T. A new MRI assessment tool to define brain abnormalities in very preterm infants at term. AJNR Am J Neuroradiol. 2013;34:2208-2214. Kirton A, Armstrong-Wells J, Chang T, International Pediatric Stroke Study Investigators, et al. Symptomatic neonatal arterial ischemic stroke: the International Pediatric Stroke Study. Pediatrics. 2011;128:e1402-e1410. Kirton A, deVeber G. Advances in perinatal ischemic stroke. Pediatr Neurol. 2009;40:205-214. Krille L, Dreger S, Schindel R, et al. Risk of cancer incidence before the age of 15 years after exposure to ionising radiation from computed tomography: results from a German cohort study. Radiat Environ Biophys. 2015;54:1-12. Kroenke CD, Bretthorst GL, Inder TE, Neil JJ. Diffusion MR imaging characteristics of the developing primate brain. Neuroimage. 2005;25:1205-1213. Kroenke CD, Taber EN, Leigland LA, Knutsen AK, Bayly PV. Regional patterns of cerebral cortical differentiation determined by diffusion tensor MRI. Cereb Cortex. 2009;19:2916-2929. Kurinczuk JJ, White-Koning M, Badawi N. Epidemiology of neonatal encephalopathy and hypoxic-ischaemic encephalopathy. Early Hum Dev. 2010;86:329-338. Laptook AR, O’shea TM, Shankaran S, Bhaskar B, Network NN. Adverse neurodevelopmental outcomes among extremely low birth weight infants with a normal head ultrasound: prevalence and antecedents. Pediatrics. 2005;115:673-680. Latour LL, Hasegawa Y, Formato JE, Fisher M, Sotak CH. Spreading waves of decreased diffusion coefficient after cortical stimulation in the rat brain. Magn Reson Med. 1994;32:189-198. Lebihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of intravoxel incoherent motions: Application to diffusion and perfusion in neurologic disorders. Radiology. 1986;161:401-407.



Lehman LL, Rivkin MJ. Perinatal arterial ischemic stroke: presentation, risk factors, evaluation, and outcome. Pediatr Neurol. 2014;51:760-768. Lequin MH, Dudink J, Tong KA, Obenaus A. Magnetic resonance imaging in neonatal stroke. Semin Fetal Neonatal Med. 2009;14:299-310. Levene MI. Measurement of the growth of the lateral ventricles in preterm infants with real-time ultrasound. Arch Dis Child. 1981;56:900-904. Li F, Silva MD, Liu KF, et al. Secondary decline in apparent diffusion coefficient and neurological outcomes after a short period of focal brain ischemia in rats. Ann Neurol. 2000;48:236-244. Liao MF, Chaou WT, Tsao LY, Nishida H, Sakanoue M. Ultrasound measurement of the ventricular size in newborn infants. Brain Dev. 1986;8:262-268. Liao SM, Gregg NM, White BR, et al. Neonatal hemodynamic response to visual cortex activity: high-density near-infrared spectroscopy study. J Biomed Opt. 2010;15:026010. Liem KD, Hopman JC, Oeseburg B, De Haan AF, Festen C, Kollee LA. Cerebral oxygenation and hemodynamics during induction of extracorporeal membrane oxygenation as investigated by near infrared spectrophotometry. Pediatrics. 1995;95:555-561. Limperopoulos C, Bassan H, Gauvreau K, et al. Does cerebellar injury in premature infants contribute to the high prevalence of long-term cognitive, learning, and behavioral disability in survivors? Pediatrics. 2007;120:584-593. Limperopoulos C, Benson CB, Bassan H, et al. Cerebellar hemorrhage in the preterm infant: ultrasonographic findings and risk factors. Pediatrics. 2005;116:717-724. Limperopoulos C, Chilingaryan G, Sullivan N, Guizard N, Robertson RL, Du Plessis AJ. Injury to the premature cerebellum: outcome is related to remote cortical development. Cereb Cortex. 2014;24:728-736. Lind A, Haataja L, Rautava L, GROUP, P. S., et al. Relations between brain volumes, neuropsychological assessment and parental questionnaire in prematurely born children. Eur Child Adolesc Psychiatry. 2010;19:407-417. Looney CB, Smith JK, Merck LH, et al. Intracranial hemorrhage in asymptomatic neonates: prevalence on MR images and relationship to obstetric and neonatal risk factors. Radiology. 2007;242:535-541. Martinez-Biarge M, Diez-Sebastian J, Kapellou O, et al. Predicting motor outcome and death in term hypoxic-ischemic encephalopathy. Neurology. 2011;76:2055-2061. Martinez-Biarge M, Diez-Sebastian J, Rutherford MA, Cowan FM. Outcomes after central grey matter injury in term perinatal hypoxicischaemic encephalopathy. Early Hum Dev. 2010;86:675-682. Mathur AM, Neil JJ, Mckinstry RC, Inder TE. Transport, monitoring, and successful brain MR imaging in unsedated neonates. Pediatr Radiol. 2008;38:260-264. Mazzola CA, Choudhri AF, Auguste KI, et al. Pediatric hydrocephalus systematic review and evidence-based guidelines task force. Pediatric hydrocephalus: systematic literature review and evidence-based guidelines. Part 2: management of posthemorrhagic hydrocephalus in premature infants. J Neurosurg Pediatr. 2014;14(suppl 1):8-23. Mckinstry RC, Mathur A, Miller JP, et al. Radial Organization of Developing Human Cerebral Cortex Revealed by Non-invasive Water Diffusion Anisotropy MRI. Cereb Cortex. 2002a;12:1237-1243. McKinstry RC, Miller JH, Snyder AZ, et al. A prospective, longitudinal diffusion tensor imaging study of brain injury in newborns. Neurology. 2002b;59:824-833. Ment LR, Bada HS, Barnes P, et al. Practice parameter: neuroimaging of the neonate: report of the quality standards subcommittee of the American academy of neurology and the practice committee of the child neurology society. Neurology. 2002;58:1726-1738. Miller SP, Newton N, Ferriero DM, et al. Predictors of 30-month outcome after perinatal depression: role of proton MRS and socioeconomic factors. Pediatr Res. 2002;52:71-77. Miller SP, Ramaswamy V, Michelson D, et al. Patterns of brain injury in term neonatal encephalopathy. J Pediatr. 2005;146:453-460. Moharir MD, Shroff M, Pontigon AM, et al. A prospective outcome study of neonatal cerebral sinovenous thrombosis. J Child Neurol. 2011;26:1137-1144.

CHAPTER 63  Neonatal Neuroimaging

951.e3

Moseley ME, Cohen Y, Mintorovitch J, et al. Early detection of regional cerebral ischemia in cats: comparison of diffusion- and T2-weighted MRI and spectroscopy. Magn Reson Med. 1990;14:330-346. Murray AL, Scratch SE, Thompson DK, et al. Neonatal brain pathology predicts adverse attention and processing speed outcomes in very preterm and/or very low birth weight children. Neuropsychology. 2014;28:552-562. Neil JJ. Diffusion imaging concepts for clinicians. J Magn Reson Imaging. 2008;27:1-7. Neil JJ, Shiran SI, Mckinstry RC, et al. Normal brain in human newborns: Apparent diffusion coefficient and diffusion anisotropy measured using diffusion tensor imaging. Radiology. 1998;209:57-66. Nelson KB, Leviton A. How much of neonatal encephalopathy is due to birth asphyxia? Am J Dis Child. 1991;145:1325-1331. Nguyen The Tich S, Anderson PJ, Shimony JS, Hunt RW, Doyle LW, Inder TE. A novel quantitative simple brain metric using MR imaging for preterm infants. AJNR Am J Neuroradiol. 2009;30:125-131. Niwa T, De Vries LS, Benders MJ, Takahara T, Nikkels PG, Groenendaal F. Punctate white matter lesions in infants: new insights using susceptibility-weighted imaging. Neuroradiology. 2011;53:669-679. Odita JC, Hebi S. CT and MRI characteristics of intracranial hemorrhage complicating breech and vacuum delivery. Pediatr Radiol. 1996;26:782-785. Olesen OV, Paulsen RR, Hojgaar L, Roed B, Larsen R. Motion tracking in narrow spaces: a structured light approach. Med Image Comput Comput Assist Interv. 2010;13:253-260. Omizzolo C, Scratch SE, Stargatt R, et al. Neonatal brain abnormalities and memory and learning outcomes at 7 years in children born very preterm. Memory. 2014;22:605-615. Ooi MB, Aksoy M, Maclaren J, Watkins RD, Bammer R. Prospective motion correction using inductively coupled wireless RF coils. Magn Reson Med. 2013;70:639-647. Oppenheim C, Stanescu R, Dormont D, et al. False-negative diffusionweighted MR findings in acute ischemic stroke. AJNR Am J Neuroradiol. 2000;21:1434-1440. Paneth N, Pinto-Martin J, Gardiner J, et al. Incidence and timing of germinal matrix/intraventricular hemorrhage in low birth weight infants. Am J Epidemiol. 1993;137:1167-1176. Papile LA, Burstein J, Burstein R, Koffler H. Incidence and evolution of subependymal and intraventricular hemorrhage: a study of infants with birth weights less than 1,500 gm. J Pediatr. 1978;92:529-534. Parodi A, Rossi A, Severino M, et al. Accuracy of ultrasound in assessing cerebellar haemorrhages in very low birth weight babies. Arch Dis Child Fetal Neonatal Ed. 2015;100:F289-F292. Perlman JM, Volpe JJ. Intraventricular hemorrhage in extremely small premature infants. Am J Dis Child. 1986;140:1122-1124. Perrin RG, Rutka JT, Drake JM, et al. Management and outcomes of posterior fossa subdural hematomas in neonates. Neurosurgery. 1997;40:1190-1199, discussion 1199-1200. Peterson BS, Anderson AW, Ehrenkranz R, et al. Regional brain volumes and their later neurodevelopmental correlates in term and preterm infants. Pediatrics. 2003;111:939-948. Petrova A, Mehta R. Near-infrared spectroscopy in the detection of regional tissue oxygenation during hypoxic events in preterm infants undergoing critical care. Pediatr Crit Care Med. 2006;7:449-454. Pfister RH, Bingham P, Edwards EM, et al. The Vermont Oxford Neonatal Encephalopathy Registry: rationale, methods, and initial results. BMC Pediatr. 2012;12:84. Pipe JG. Motion correction with PROPELLER MRI: application to head motion and free-breathing cardiac imaging. Magn Reson Med. 1999;42:963-969. Plaisier A, Raets MM, Ecury-Goossen GM, et al. Serial cranial ultrasonography or early MRI for detecting preterm brain injury? Arch Dis Child Fetal Neonatal Ed. 2015;100:F293-F300. Potgieser AR, Wagemakers M, Van Hulzen AL, De Jong BM, Hoving EW, Groen RJ. The role of diffusion tensor imaging in brain tumor surgery: a review of the literature. Clin Neurol Neurosurg. 2014;124:51-58.

951.e4

PART XI I  Neurologic System

Prichard JW, Zhong J, Petroff OAC, Gore JC. Diffusion-weighted NMR imaging changes caused by electrical activation of the brain. NMR Biomed. 1995;8:359-364. Raybaud C, Girard N, Canto-Moreira N, Poncet M. High-definition magnetic resonance imaging identification of cortical dysplasias: micropolygyria versus lissencephaly. In: Guerrini RFA, Canapicchi R, Roger J, Zifkin BG, Pfanner P, eds. Dysplasias of Cerebral Cortex and Epilepsy. Philadelphia, PA: Lippincott-Raven; 1996. Reidy N, Morgan A, Thompson DK, Inder TE, Doyle LW, Anderson PJ. Impaired language abilities and white matter abnormalities in children born very preterm and/or very low birth weight. J Pediatr. 2013;162:719-724. Righini A, Pierpaolo C, Alger JR, Chiro GD. Brain parenchyma apparent diffusion coefficient alterations associated with experimental complex partial status epilepticus. Magn Reson Imaging. 1994;12:865-871. Rogers CE, Anderson PJ, Thompson DK, et al. Regional cerebral development at term relates to school-age social-emotional development in very preterm children. J Am Acad Child Adolesc Psychiatry. 2012;51: 181-191. Rogers CE, Smyser T, Smyser CD, Shimony J, Inder TE, Neil JJ. Regional white matter development in very preterm infants: perinatal predictors and early developmental outcomes. Pediatr Res. 2016;79:87-95. Ron E, Modan B, Floro S, Harkedar I, Gurewitz R. Mental function following scalp irradiation during childhood. Am J Epidemiol. 1982;116:149-160. Rooks VJ, Eaton JP, Ruess L, Petermann GW, Keck-Wherley J, Pedersen RC. Prevalence and evolution of intracranial hemorrhage in asymptomatic term infants. AJNR Am J Neuroradiol. 2008;29:1082-1089. Rose J, Butler EE, Lamont LE, Barnes PD, Atlas SW, Stevenson DK. Neonatal brain structure on MRI and diffusion tensor imaging, sex, and neurodevelopment in very-low-birth weight preterm children. Dev Med Child Neurol. 2009;51:526-555. Rose J, Mirmiran M, Butler EE, et al. Neonatal microstructural development of the internal capsule on diffusion tensor imaging correlates with severity of gait and motor deficits. Dev Med Child Neurol. 2007;49:745-750. Rother J, Decrespigny AJ, D’arceuil H, Moseley ME. MR detection of cortical spreading depression immediately after focal ischemia in the rat. J Cereb Blood Flow Metab. 1996;16:214-220. Schwaberger B, Pichler G, Avian A, Binder-Heschl C, Baik N, Urlesberger B. Do Sustained Lung Inflations during Neonatal Resuscitation Affect Cerebral Blood Volume in Preterm Infants? A Randomized Controlled Pilot Study. PLoS ONE. 2015;10:e0138964. Shackelford GD, Volpe JJ. Cranial ultrasonography in the evaluation of neonatal intracranial hemorrhage and its complications. J Perinat Med. 1985;13:293-304. Shah DK, Lavery S, Doyle LW, Wong C, Mcdougall P, Inder TE. Use of 2-channel bedside electroencephalogram monitoring in term-born encephalopathic infants related to cerebral injury defined by magnetic resonance imaging. Pediatrics. 2006;118:47-55. Shimony JS, Smyser CD, Wideman G, et al. Comparison of cortical folding measures for evaluation of developing human brain. Neuroimage. 2016;125:780-790. Skiold B, Vollmer B, Bohm B, et al. Neonatal magnetic resonance imaging and outcome at age 30 months in extremely preterm infants. J Pediatr. 2012;160:559-566 e1. Smyser CD, Inder TE, Shimony JS, et al. Longitudinal analysis of neural network development in preterm infants. Cereb Cortex. 2010;20:2852-2862. Smyser CD, Snyder AZ, Shimony JS, Mitra A, Inder TE, Neil JJ. Restingstate network complexity and magnitude are reduced in prematurely born infants. Cereb Cortex. 2016;26:322-333. Spittle AJ, Cheong J, Doyle LW, et al. Neonatal white matter abnormality predicts childhood motor impairment in very preterm children. Dev Med Child Neurol. 2011;53:1000-1006. Srinivasakumar P, Limbrick D, Munro R, et al. Posthemorrhagic ventricular dilatation-impact on early neurodevelopmental outcome. Am J Perinatol. 2013;30:207-214.

Steggerda SJ, De Bruine FT, Van Den Berg-Huysmans AA, et al. Small cerebellar hemorrhage in preterm infants: perinatal and postnatal factors and outcome. Cerebellum. 2013;12:794-801. Steggerda SJ, Leijser LM, Wiggers-De Bruine FT, Van Der Grond J, Walther FJ, Van Wezel-Meijler G. Cerebellar injury in preterm infants: incidence and findings on US and MR images. Radiology. 2009;252:190-199. Stoll BJ, Hansen HI, Bell EF, Eunice Kennedy Shriver National Institute of Child and Human Development Neonatal Research Network, et al. Trends in care practices, morbidity, and mortality of extremely preterm neonates, 1993–2012. JAMA. 2015;314:1039-1051. Takano K, Latour LL, Formato JE, et al. The role of spreading depression in focal ischemia evaluated by diffusion mapping. Ann Neurol. 1996;39:308-318. Tamhane AA, Arfanakis K. Motion correction in periodically-rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) and turboprop MRI. Magn Reson Med. 2009;62:174-182. Task Force on Neonatal Encephalopathy. Role of neuroimaging. In: Neonatal Encephalopathy and Neurologic Outcome. 2nd ed. Washington, DC: The American College of Obstetrics and Gynecology; 2014. Thayyil S, Chandrasekaran M, Taylor A, et al. Cerebral magnetic resonance biomarkers in neonatal encephalopathy: a meta-analysis. Pediatrics. 2010;125:e382-e395. Thompson DK, Adamson C, Roberts G, et al. Hippocampal shape variations at term equivalent age in very preterm infants compared with term controls: perinatal predictors and functional significance at age 7. Neuroimage. 2013;70:278-287. Thompson DK, Lee KJ, Egan GF, et al. Regional white matter microstructure in very preterm infants: predictors and 7 year outcomes. Cortex. 2014;52:60-74. Thompson DK, Wood SJ, Doyle LW, et al. Neonate hippocampal volumes: prematurity, perinatal predictors, and 2-year outcome. Ann Neurol. 2008;63:642-651. Tich SN, Anderson PJ, Hunt RW, Lee KJ, Doyle LW, Inder TE. Neurodevelopmental and perinatal correlates of simple brain metrics in very preterm infants. Arch Pediatr Adolesc Med. 2011;165:216-222. Tisdall MD, Hess AT, Reuter M, Meintjes EM, Fischl B, Van Der Kouwe AJ. Volumetric navigators for prospective motion correction and selective reacquisition in neuroanatomical MRI. Magn Reson Med. 2012;68:389-399. Toet MC, Lemmers PM, Van Schelven LJ, Van Bel F. Cerebral oxygenation and electrical activity after birth asphyxia: their relation to outcome. Pediatrics. 2006;117:333-339. Towner D, Castro MA, Eby-Wilkens E, Gilbert WM. Effect of mode of delivery in nulliparous women on neonatal intracranial injury. N Engl J Med. 1999;341:1709-1714. Van Essen DC. A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex. Neuroimage. 2005;28:635-662. Van Haastert IC, Groenendaal F, Uiterwaal CS, et al. Decreasing incidence and severity of cerebral palsy in prematurely born children. J Pediatr. 2011;159:86-91 e1. Van Kooij BJ, Benders MJ, Anbeek P, Van Haastert IC, De Vries LS, Groenendaal F. Cerebellar volume and proton magnetic resonance spectroscopy at term, and neurodevelopment at 2 years of age in preterm infants. Dev Med Child Neurol. 2012a;54:260-266. Van Kooij BJ, De Vries LS, Ball G, et al. Neonatal tract-based spatial statistics findings and outcome in preterm infants. AJNR Am J Neuroradiol. 2012b;33:188-194. Van Wezel-Meijler G, De Bruine FT, Steggerda SJ, et al. Ultrasound detection of white matter injury in very preterm neonates: practical implications. Dev Med Child Neurol. 2011;53(suppl 4):29-34. Van’t Hooft J, Van Der Lee JH, Opmeer BC, et al. Predicting developmental outcomes in premature infants by term equivalent MRI: systematic review and meta-analysis. Syst Rev. 2015;4:71. Verboon-Maciolek MA, Groenendaal F, Hahn CD, et al. Human parechovirus causes encephalitis with white matter injury in neonates. Ann Neurol. 2008;64:266-273. Verheul HB, Balazs R, Van Der Sprenkel JWB, Tulleken CAF, Nicolay K, Van Lookeren Campagne M. Temporal evolution of NMDA-induced



excitotoxicity in the neonatal rat brain measured with 1H nuclear magnetic resonance imaging. Brain Res. 1993;618:203-212. Vesoulis ZA, Liao SM, Trivedi SB, Ters NE, Mathur AM. A novel method for assessing cerebral autoregulation in preterm infants using transfer function analysis. Pediatr Res. 2016;79:453-459. Volpe J. Neurology of the Newborn. Philadelphia, PA.: WB Saunders; 2001. Volpe JJ. Brain injury in premature infants: a complex amalgam of destructive and developmental disturbances. Lancet Neurol. 2009a;8:110-124. Volpe JJ. Cerebellum of the premature infant: rapidly developing, vulnerable, clinically important. J Child Neurol. 2009b;24:1085-1104. Wezel-Meijler G, De Vries LS. Cranial ultrasound – optimizing utility in the NICU. Curr Pediatr Rev. 2014;10:16-27. Whitby EH, Griffiths PD, Rutter S, et al. Frequency and natural history of subdural haemorrhages in babies and relation to obstetric factors. Lancet. 2004;363:846-851. Wilson-Costello D, Friedman H, Minich N, Fanaroff AA, Hack M. Improved survival rates with increased neurodevelopmental disability for extremely low birth weight infants in the 1990s. Pediatrics. 2005;115:997-1003. Woodward LJ, Anderson PJ, Austin NC, Howard K, Inder TE. Neonatal MRI to predict neurodevelopmental outcomes in preterm infants. N Engl J Med. 2006;355:685-694.

CHAPTER 63  Neonatal Neuroimaging

951.e5

Woodward LJ, Clark CA, Pritchard VE, Anderson PJ, Inder TE. Neonatal white matter abnormalities predict global executive function impairment in children born very preterm. Dev Neuropsychol. 2011;36:22-41. Woodward LJ, Edgin JO, Thompson D, Inder TE. Object working memory deficits predicted by early brain injury and development in the preterm infant. Brain. 2005;128:2578-2587. Young JM, Powell TL, Morgan BR, et al. Deep grey matter growth predicts neurodevelopmental outcomes in very preterm children. Neuroimage. 2015;111:360-368. Zhong J, Petroff OAC, Prichard JW, Gore JC. Changes in water diffusion and relaxation properties of rat cerebrum during status epilepticus. Magn Reson Med. 1993;30:241-246. Zhong J, Petroff OAC, Prichard JW, Gore JC. Barbiturate-reversible reduction of water diffusion coefficient in flurothyl-induced status epilepticus in rats. Magn Reson Med. 1995;33:253-256. Zubiaurre-Elorza L, Soria-Pastor S, Junque C, et al. Magnetic resonance imaging study of cerebral sulci in low-risk preterm children. Int J Dev Neurosci. 2009;27:559-565.