- Email: [email protected]
Visualizing cerebral veins in fetal brain using susceptibility-weighted MRI
Clinical Radiology 69 (2014) e392ee397
Contents lists available at ScienceDirect
Clinical Radiology journal homepage: www.clinicalradiologyonline.net
Visualizing cerebral veins in fetal brain using susceptibility-weighted MRI Y. Dai a, S. Dong b, M. Zhu b, *, D. Wu c, Y. Zhong b a
Philips Healthcare, People’s Republic of China Shanghai Children’s Medical Center Affiliated to Shanghai Jiaotong University School of Medicine, People’s Republic of China c Shanghai Key Laboratory of Magnetic Resonance, Department of Physics, East China Normal University, People’s Republic of China b
article in formation Article history: Received 3 May 2014 Received in revised form 9 June 2014 Accepted 10 June 2014
AIM: To explore the feasibility of two-dimensional (2D) susceptibility-weighted imaging (SWI) in the visualization of cerebral veins in the foetal brain. MATERIALS AND METHODS: Forty-two pregnant healthy women (gestational age: 19e37 weeks, mean: 28.5 7.1 weeks) underwent SWI examination using a 1.5 T MRI system. Two neurologists independently analysed all magnetic resonance imaging (MRI) studies. The relationship between the veins detected and the gestational age was investigated. The prominence of veins was assessed using a categorical score. RESULTS: In total, 167 veins were detected by SWI in 29 subjects with a symmetric hemisphere distribution (p > 0.05). An additional vein was detected by SWI biweekly from 24 weeks of gestation. Most veins of Galen and internal cerebral veins on SWI images were prominent, whereas others were faint or moderate. CONCLUSION: SWI appears to be a feasible method of detecting cerebral veins in the foetal brain. Ó 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Introduction Studying the cerebral venous system in foetuses and neonates is important because the various diseases related to hypoxiceischaemic injury are of growing importance.1,2 For instance, perinatal stroke is a common cerebrovascular disorder affecting one in every 4000 births, which accounts for 30% of children with hemiplegic cerebral palsy (CP).3,4 Perinatal ischaemic stroke has been defined as a
* Guarantor and correspondent: M. Zhu, Shanghai Children’s Medical Center Affiliated to Shanghai Jiaotong University School of Medicine, 1678 Dongfang Road, Pudong, Shanghai, People’s Republic of China. Tel.: þ86 (21) 38626161. E-mail address: [email protected] (M. Zhu).
group of heterogeneous conditions in which there is a focal disruption of cerebral blood flow secondary to arterial or cerebral venous thrombosis or embolization, between the 20th weeks of foetal life through the 28th post-natal day, and confirmed by neuroimaging or neuropathological studies.5 In addition, foetal brain damage associated with cerebral vein engorgement or thrombosis, and with periventricular haemorrhage or haemorrhagic infarction is one of the main causes of foetal brain stroke.6 With few acute clinical signs and frequent retrospective recognition, the diagnosis of perinatal stroke is primarily radiographic. Better depiction in the acute or sub-acute phase of cerebral venous anomalies could improve the understanding of pathophysiology and the natural course of venous-based stroke. Magnetic resonance imaging (MRI) is the method of choice in studying perinatal stroke because of its superior
http://dx.doi.org/10.1016/j.crad.2014.06.010 0009-9260/Ó 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Y. Dai et al. / Clinical Radiology 69 (2014) e392ee397
soft-tissue contrast. So far, T1-, T2-weighted turbo spin echo (TSE) sequences, and T2*-weighted echo planar imaging (EPI) sequence have been used to demonstrate diseases related to foetal veins in a few studies.1,2 Susceptibility-weighted imaging (SWI) is well known as a three-dimensional (3D) gradient-echo sequence (GRE) based technique. With phase information as an additional source of contrast, SWI is able to visualize the susceptibility changes induced by different substances, such as blood products (haemosiderin and ferritin), deoxygenated blood, iron, and calcium, and small vein depiction in various physiological and pathological conditions.7e10 The applications of 3D SWI are readily extended to a two-dimensional (2D) GRE based approach for studies in the abdomen, including the detection of siderotic nodules in cirrhosis, liver fibrosis staging, and haemorrhage in hepatocellular carcinoma and renal cancer.11e14 In the present study, a novel MRI method, 2D SWI, was used to assess foetal cerebral veins in healthy volunteers.
e393
sampling; 310 Hz/pixel bandwidth; 15 s acquisition time); and (c) SWI: 2D GRE (20 flip angle; 407 ms TR/40 ms TE; 350 262 mm2 FOV: eight sections; sense ¼ 2; 0.8 0.8 5.0 mm3 spatial resolution; 170 Hz/pixel bandwidth; 1 min 2 s acquisition time, free breathing). The participant was positioned supine, with the feet placed first into the magnet to minimize claustrophobia. No maternal sedation or foetal paralysis was used. Scout imaging was initially performed in three orthogonal directions to accurately locate the foetus. After the localization, T2weighted single-shot TSE was used to provide clear anatomical images of the foetal brain in the sagittal direction. Based on the TSE images, the SWI was performed along the anterior commissureeposterior commissure (AC-PC) direction to obtain transverse foetal brain images (Fig 1). The SWI reconstruction was implemented based on both magnitude and phase images of the GRE sequence following the method used in the previous study.11
Image analysis
Materials and methods Volunteers A total of 42 pregnant healthy volunteers (age 24e35 years, mean 26.5 6.1 years) with a gestational age of 19e37 weeks were consecutively enrolled in the study at Shanghai Children’s Medical Center from January 2013 to September 2013. A medical history was collected for each participant, especially regarding risk factors for the foetus. The criteria for participant enrolment were as follows: (1) all participants were in a stable clinical condition with no known contraindications to MRI; (2) no participant had diagnosed or self-reported malignancy, cardiovascular disease, pulmonary disease, metabolic disease, renal disease, hepatic disease, parathyroid gland diseases, rheumatoid arthritis, malabsorption syndrome, blood diseases, as well as coexisting diabetes; and (3) none of the participants were using therapies that affect foetal development (such as glucocorticoids, immunosuppressive medications). Institutional review board approval was obtained prior to the MRI examinations, and written informed consent was obtained for all participants.
Two paediatric neurologists with 10 and 12 years in neurology imaging evaluation independently reviewed all 42 sets of SWI images using software SPIN (Signal Process in NMR, MR Institute of Research, Wayne State University, MI, USA). First, an intersection line (15e20 pixels long) was drawn vertically across each vein displayed on all SWI images (Fig 2a). With the intersection line in place, the veins were identified and counted. In addition, the prominence of vein (POV) on SWI images was evaluated using the signal intensity (SI) profile of the intersection line. The POV was defined as the signal difference between the vein and surrounding tissue parenchyma, namely the signal difference (DS) from bottom (vein) to flat top (surrounding tissue parenchyma) of the SI profile (Fig 2b). The POV was quantitatively categorized into faint (score 1: DS 80); moderate (score 2: 80 < DS 100); and prominent (score 3: DS > 100). Finally, the distribution of the veins detected by SWI was dichotomized into to the left and right hemisphere brain. An average value of the number of veins in each subject and average POV score were used for analysis when a disagreement existed between the two neurologists.
MRI Statistical analysis All MRI examinations were carried out using a 1.5 T whole-body MRI system (Achieva TX, Philips Healthcare, Best, The Netherlands) with a commercialized 16-channel torso coil. The imaging sequences included (a) scout imaging: GRE (18 flip angle; 7 ms repetition time (TR)/2.5 ms echo time (TE); 440 440 mm2 field of view (FOV); 13 sections; sensitivity encoding (Sense) ¼ 2; 1.7 2.3 9 mm3 spatial resolution; 280 Hz/pixel bandwidth; 21 s acquisition time); (b) sagittal foetal brain imaging: T2-weighted single shot turbo spin-echo (TSE; 160 flip angle; 3000 ms TR/260 ms TE; 340 340 mm2 FOV; five sections; sense ¼ 2; 0.9 1.3 3.0 mm3 spatial resolution; length of echo train ¼ 128; 62.5% partial Fourier k-space
The correlation between the number of veins detected at SWI and the gestational age of the foetuses was determined using linear regression and Pearson’s correlation analysis. Student’s t-test was used to evaluate the distribution of veins for all foetuses. Interobserver reliability for the categorical items was analysed by Cohen’s kappa method. A priori classifications of k value were as follows: k ¼ 0 indicated no agreement, 0 < k 0.2 indicated slight agreement, 0.2 < k 0.4 indicated fair agreement, 0.4 < k 0.6 indicated moderate agreement, 0.6 < k 0.8 indicated substantial agreement, and k > 0.8 indicated near perfect agreement. All statistics were performed with software
e394
Y. Dai et al. / Clinical Radiology 69 (2014) e392ee397
Figure 1 A pregnant woman at 36 weeks of gestation. (a) T2-weighted single-shot TSE sequence imaging in the sagittal direction (0.9 1.3 3.0 mm3 spatial resolution; 160 flip angle; 3000 ms TR/260 ms TE). The numbered white dotted lines indicate the sections positioned along the ACePC direction for SWI. (b) Corresponding SWI image (0.8 0.8 5.0 mm3 spatial resolution; 20 flip angle; 407 ms TR/ 40 ms TE).
SPSS (Statistical Product and Service Solutions, version 16.0, Chicago, IL, USA) using a 0.05 level of significance.
Results Of the 42 volunteers, 13 were excluded owing to either artefacts from maternal respiration that considerably impaired image quality or no veins detected at SWI. In nine of the 13 volunteers, the foetal brains were all positioned towards the ventral part of the abdomen of varying degrees, which increased the sensitivity of images to the breathing artefacts. In the other four volunteers, no veins were detected on the SWI images at a gestational age of 19, 20, 21, and 24 weeks, respectively. In the remaining 29 volunteers, with a gestational age of 24e37 weeks, the positions of foetal brains were all towards the cervix, making it similar to pelvic imaging and less affected by respiration artefacts. In total, 167 veins were detected in 29 foetal brains with a range of two to 10 for each subject (mean 5.6 2.4). The
types of detected veins included vein of Galen (n ¼ 29), internal cerebral vein (n ¼ 29), septal vein (n ¼ 44), medial atrial vein (n ¼ 29), striate vein (n ¼ 13), choroidal vein (n ¼ 10), and superficial Sylvian vein (n ¼ 13; Fig 3). Symmetric distribution revealed that 56 veins were located in the left hemisphere whereas 53 veins were located in the right hemisphere (p > 0.5). The vein of Galen and internal cerebral vein were not included for distribution analysis due to their centred position. A linear relationship was found between the number of visible veins (N) and gestational age (G) as follows: N ¼ 10:9 þ 0:53G
(1)
where G ranged from 24e37 weeks with r ¼ 0.82, p < 0.001. From equation (1), one can deduce that an additional vein will be “seen” by SWI every 2 weeks from the 24th week of gestation, as shown in Fig 4. According to POV categorization, 46 veins including vein of Galen (n ¼ 23) and internal cerebral vein (n ¼ 23) were
Figure 2 A pregnant woman at 34 weeks of gestation. (a) Every intersection line with a width of 15e20 pixels (red line) is drawn across each vein on SWI image. (b) The corresponding SI profile of the intersection line in (a). The horizontal axis indicates the pixels of the intersection line and the vertical axis indicates signal intensity. DS is the signal difference between the vein (bottom) and surrounding tissue parenchyma (flat top). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.).
Y. Dai et al. / Clinical Radiology 69 (2014) e392ee397
e395
Table 1 Prominence of vein (POV) categorization.
Vein of Galen Internal cerebral vein Medial atrial vein Septal vein Striate vein Choroidal vein Superficial Sylvian vein
Faint
Moderate
Prominent
0 0 4 10 5 7 13
6 6 25 34 8 3 0
23 23 0 0 0 0 0
The veins detected at SWI were categorized into three POV scores, which were defined by the signal difference between the veins and surrounding tissue parenchyma.
Figure 3 A pregnant woman at 35 weeks of gestation. All veins detected on one of SWI images are highlighted (white arrows).
termed prominent; 86 veins including vein of Galen (n ¼ 6), internal cerebral vein (n ¼ 6), medial atrial vein (n ¼ 25), septal vein (n ¼ 34), striate vein (n ¼ 8), and choroidal vein (n ¼ 3) were termed moderate; and 35 veins including medial atrial vein (n ¼ 4), septal vein (n ¼ 10) striate vein (n ¼ 5), choroidal vein (n ¼ 7), and superficial Sylvian vein (n ¼ 13) were termed faint (Table 1). POV scores from the two neurologists were in near perfect agreement (k ¼ 0.91).
Discussion In the present study, the veins of 29 foetal brains were visualized using SWI. The cerebral veins detected were vein
Figure 4 A plot of the number of veins detected by SWI per foetus in order of gestational age from 24e37 weeks. The horizontal axis indicates the weeks of gestation and the vertical axis indicates the number of veins. Each dot represents one subject and a triangle represents two coincided subjects. The number of veins as a function of gestational age is described by the straight line computed by linear regression algorithm as N ¼ 10.9 þ 0.53 G, where N stands for the number of veins and G stands for the weeks of gestation.
of Galen, internal cerebral vein, medial atrial vein, choroidal vein, septal vein, striate vein, and superficial Sylvian vein, with a symmetric distribution. The veins were initially detected at 24 weeks of gestation; starting from that time, it was proven statistically that an additional vein would be detected biweekly until 37 weeks of gestation. This finding indirectly confirmed the results found in previous studies of foetal vasculature development.15,16 POV results for all veins were analysed. It is noteworthy that a small number of veins were detected in the present study, and 10 veins were detected in foetuses at 36 weeks of gestation. However, few studies have demonstrated the presence of normal veins in the foetal brain using conventional T1-, T2-weighted TSE sequences, or T2*-weighted EPI sequences. Abnormal cases regarding venous engorgement, thrombosis, or haemorrhage are the exception.1,2 The advantages of SWI over conventional sequences in the detection of veins are twofold. First, SWI, as a T2*-weighted GRE sequence, successfully adopts the phase information into final image contrast, which vastly improves its sensitivity to tissue susceptibilities, making it, to date, the most sensitive MRI technique for detecting veins, blood products, and haemorrhage.17 In contrast, TSE sequences are insensitive to veins owing to its 180 radiofrequency refocusing pulses, which eliminate the local field changes caused by tissue susceptibilities. Second, a higher signal-to-noise (SNR) and less distortion of SWI compared to EPI sequences make it a better choice for detecting cerebral veins. Compared to the performance of SWI in adults or neonatal brain studies,18,19 the existing deep medullary veins (DMVs) or small veins in the periventricular white matter were seldom revealed by SWI for all foetuses in the present study. Also, from the POV results, only veins of Galen and internal cerebral veins were consistently prominent, most of the other veins had only a moderate and faint display. These characteristics of vein visualization could probably be explained by the blood oxygenation level dependent (BOLD) effect, the development of veins in the foetal brain and sequence protocol settings. Foetal blood is different from adult blood. It contains predominant foetal haemoglobin, which has a considerably higher oxygen affinity compared with adult haemoglobin. The relative ratios of foetal haemoglobin and adult haemoglobin in red blood cells change as a function of gestational age.20,21 The predominant foetal haemoglobin keeps foetal
e396
Y. Dai et al. / Clinical Radiology 69 (2014) e392ee397
venous blood at a higher oxygen level relative to that of an adult, resulting in higher SWI signals in the veins and poorer contrast to the surrounding tissue parenchyma. This BOLD effect on venous SWI signal has been confirmed in a neonate study. The sulcal and intramedullary veins are usually faintly visible in neonates when examined in “natural sleep”; in intubated ventilated neonates the higher oxygenation typically increases the signal intensity of the veins, frequently making them almost invisible at SWI.19 During the process of vasculature development in the foetal brain, the density and diameter of vessels, both arteries and veins, increase rapidly from about 26 weeks of gestation and peak at 35 weeks, although there exists developmental discrepancy among different cerebral regions.15,16 Moreover, in the developing foetal brain a majority of veins are found to have a diameter less than 1 mm.22 Fast imaging is indispensable, and 2D SWI, instead of 3D SWI, was used in the present study to minimize motion artefacts via the high temporal resolution. The spatial resolution of 0.8 0.8 5.0 mm3 was used to tradeoff between the temporal resolution and the SNR. According to the SWI theory, SWI could detect veins smaller than the in-plane resolution, called the blooming effect.23 However, a section thickness of 5 mm will aggravate partial volume effects in the direction of the section, thus reducing the efficiency of vein detection. Therefore, the smaller number of tiny premature veins in developing foetal brain and the partial volume effect might be responsible for the first detection of veins at 24 weeks of gestation. It is also important to note that the angle between the static magnetic field and veins has an impact on phase changes, and thus affects the contrast of veins on SWI.17 In light of the high sensitivity of SWI to cerebral veins, blood products, and haemorrhage, SWI and its quantitative analysis open avenues for future research in studying hypoxiceischaemic injury in the foetus. Initially, periventricular venous infarction (PVI), as part of perinatal stroke, occurs well before birth and is characterized by germinal matrix haemorrhage leading to an impairment of blood drainage from the periventricular white matter that becomes infarcted.24 As SWI has nearly three to six-times higher sensitivity to microhaemorrhage than T2*-weighted GRE sequences,25 early and accurate detection of haemorrhage in PVI during pregnancy is expected. It was also reported that the T2*-weighted GRE sequence had a higher sensitivity to venous thrombosis than T1- or T2-weighted TSE sequences at the acute stage due to the susceptibility effects of thrombus,26 and, further, SWI was shown to have the highest sensitivity to thrombosed cortical veins compared to T1-weighted TSE sequences, fluid attenuated inversion recovery (FLAIR) sequences, or diffusion-weighted imaging (DWI), even in the absence of visible occlusion.27 Therefore, SWI could be of clinical value for foetal stroke imaging in the presence of venous engorgement, thrombosis, and haemorrhage. In addition, as the SWI signal is highly dependent on the amount of deoxyhaemoglobin, the quantitative POV for vein contrast can be used as an indicator of the deoxyhaemoglobin level in the cerebral venous system and provide insight into oxygen extraction in foetal
neurological diseases such as hypoxiceischaemic injury.28 Future applications of quantitative susceptibility mapping to obtain information on oxygen saturation may be possible but will require higher resolution than provided in the present study.29 To avoid motion artifacts in the future a faster breath-hold study which could be repeated multiple times would likely improve the number of cases providing high quality data.30 Several limitations of the present study should be recognized. The sample size is small (n ¼ 29), although it is enough to achieve statistically significant results. Besides the investigation of vein development in the foetal brain with participants of different gestational ages, no individual cases with venous-related diseases were enrolled in the study. For the safety reasons, comparison studies using SWI on 1.5 and on 3 T systems have not been performed, which may lead to different results. In conclusion, the results of the present study demonstrate that 2D SWI can visualize the veins in foetal brain from 24 weeks of gestation. The characteristics of vein visualization are tightly associated with the developmental of the foetal brain and the mechanics of 2D SWI. This finding indicates that 2D SWI would provide a useful tool adjunct to conventional imaging methods, and could become a useful imaging technique for diagnosing foetal neurological diseases in the future.
References 1. Arrigoni F, Prazzini C, Righini A, et al. Deep medullary vein involvement in neonates with brain damage: an MR imaging study. AJNR Am J Neuroradiol 2011;32:2030e6. 2. Done C, Righini A, Parazzini C, et al. Prenatal MR imaging detection of deep medullary vein involvement in fetal brain damage. AJNR Am J Neuroradiol 2011;32:E146e9. 3. Nelson KB. Perinatal ischemic stroke. Stroke 2007;38(Suppl.):742e5. 4. Kirton A, deVeber G. Advances in perinatal ischemic stroke. Pediatr Neurol 2009;40:205e14. 5. Govaert P, Ramenghi L, Taal R, et al. Diagnosis of perinatal stroke I: definitions, differential diagnosis and registration. Acta Paediatr 2009;98:1556e7. 6. Bousser M-G. Cerebral venous thrombosis: diagnosis and management. J Neurol 2000;247:252e8. 7. Haacke EM, Xu Y, Cheng YC, et al. Susceptibility weighted imaging. Magn Reson Med 2004;52:612e8. 8. Rauscher A, Sedlacik J, Barth M, et al. Noninvasive assessment of vascular architecture and function during modulated blood oxygenation using susceptibility weighted magnetic resonance imaging. Magn Reson Med 2005;54:87e95. 9. Kao HW, Tsai FY, Hasso AN. Predicting stroke evolution: comparison of susceptibility-weighted MR imaging with MR perfusion. Eur Radiol 2012;22:1397e403. 10. Sehgal V, Delproposto Z, Haddar D, et al. Susceptibility-weighted imaging to visualize blood products and improve tumor contrast in the study of brain masses. J Magn Reson Imaging 2006;24:41e51. 11. Dai Y, Zeng M, Li R, et al. Improving detection of siderotic nodules in cirrhotic liver with multi-breath-hold susceptibility-weighted imaging technique. J Magn Reson Imaging 2011;34:318e25. 12. Balassy C, Feier D, Peck-Radosavljevic M, et al. Susceptibility-weighted MR imaging in grading liver fibrosis d a feasibility study. Radiology 2014;270:149e58. 13. Li RK, Zeng MS, Rao SX, et al. Using a new 2D susceptibility-weighted imaging to visualize intratumoral hemorrhage and predict histological grade of hepatocellular carcinoma at 3T MRI: a preliminary study. J Magn Reson Imaging 2012;36:900e6.
Y. Dai et al. / Clinical Radiology 69 (2014) e392ee397 14. Xing W, He X, Kassir MA, et al. Evaluating hemorrhage in renal cell carcinoma using susceptibility weighted imaging. PLoS One 2013;8:e57691. 15. Mito T, Konomi H, Houdou S, et al. Immunohistochemical. Study of the vasculature in the developing brain. Pediatr Neurol 1991;7:19e22. 16. Miyawaki T, Matsui K, Takashima S. Developmental characteristics of vessel density in the human fetal and infant brains. Early Hum Dev 1998;53:65e72. 17. Haacke EM, Mittal S, Wu Z, et al. Susceptibility-weighted imaging: technical aspects and clinical applications, part 1. AJNR Am J Neuroradiol 2009;30:19e30. 18. Mittal S, Wu Z, Neelavalli J, et al. Susceptibility-weighted imaging: technical aspects and clinical applications, part 2. AJNR Am J Neuroradiol 2009;30:232e52. 19. Meoded A, Poretti A, Northington FJ, et al. Susceptibility weighted imaging of the neonatal brain. Clin Radiol 2012;67:793e801. 20. Zijlstra WG, Buursma A, Meeuwsen-van der Roest WP. Absorption spectra of human fetal and adult oxyhemoglobin, de-oxyhemoglobin, carboxyhemoglobin, and methemoglobin. Clin Chem 1991;37:1633e8. 21. Bard H, Makowski EL, Meschia G, et al. The relative rates of synthesis of hemoglobins A and F in immature red cells of newborn infants. Pediatrics 1970;45:766e72. 22. Maehara F, Okudera T, Ohta T, et al. Radiological anatomy of the vein of . Nihon Igaku Hoshasen Gakkai Zasshi 1997;57:305e13. Labbe
e397
23. Cheng YC, Haacke EM. Predicting BOLD signal changes as a function of blood volume fraction and resolution. NMR Biomed 2001;14:468e77. 24. Kirton A, Shroff M, Pontigon AM, et al. Risk factors and presentations of periventricular venous infarction vs. arterial presumed perinatal ischemic stroke. Arch Neurol 2010;67:842e8. 25. Haacke EM, DelProposto ZS, Chaturvedi S, et al. Imaging cerebral amyloid angiopathy with susceptibility-weighted imaging. AJNR AM J Neuroradiol 2007;28:316e7. 26. Leach JL, Strub WM, Gaskill-Shipley MR. Cerebral venous thrombus signal intensity and susceptibility effects on gradient recalled-echo MR imaging. AJNR Am J Neuroradiol 2007;28:940e5. 27. Idabaih A, Boukobza M, Crassard I, et al. MRI of clot in cerebral venous thrombosis: high diagnostic value of susceptibility-weighted images. Stroke 2006;37:991e5. 28. Kitamura G, Kido D, Wycliffe N, et al. Hypoxiceischemic injury: utility of susceptibility-weighted imaging. Pediatri Neuro 2011;45:220e4. 29. Haacke EM, Tang J, Neelavalli J, et al. Susceptibility mapping as a means to visualize veins and quantify oxygen saturation. J Magn Reson Imaging 2010;32:663e76. 30. Neelavalli J, Mody S, Yeo L, et al. MR venography of the fetal brain using susceptibility weighted imaging. J Magn Reson Imaging 2013 Nov 25. http://dx.doi.org/10.1002/jmri.24476. [Epub ahead of print].
Contents lists available at ScienceDirect
Clinical Radiology journal homepage: www.clinicalradiologyonline.net
Visualizing cerebral veins in fetal brain using susceptibility-weighted MRI Y. Dai a, S. Dong b, M. Zhu b, *, D. Wu c, Y. Zhong b a
Philips Healthcare, People’s Republic of China Shanghai Children’s Medical Center Affiliated to Shanghai Jiaotong University School of Medicine, People’s Republic of China c Shanghai Key Laboratory of Magnetic Resonance, Department of Physics, East China Normal University, People’s Republic of China b
article in formation Article history: Received 3 May 2014 Received in revised form 9 June 2014 Accepted 10 June 2014
AIM: To explore the feasibility of two-dimensional (2D) susceptibility-weighted imaging (SWI) in the visualization of cerebral veins in the foetal brain. MATERIALS AND METHODS: Forty-two pregnant healthy women (gestational age: 19e37 weeks, mean: 28.5 7.1 weeks) underwent SWI examination using a 1.5 T MRI system. Two neurologists independently analysed all magnetic resonance imaging (MRI) studies. The relationship between the veins detected and the gestational age was investigated. The prominence of veins was assessed using a categorical score. RESULTS: In total, 167 veins were detected by SWI in 29 subjects with a symmetric hemisphere distribution (p > 0.05). An additional vein was detected by SWI biweekly from 24 weeks of gestation. Most veins of Galen and internal cerebral veins on SWI images were prominent, whereas others were faint or moderate. CONCLUSION: SWI appears to be a feasible method of detecting cerebral veins in the foetal brain. Ó 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Introduction Studying the cerebral venous system in foetuses and neonates is important because the various diseases related to hypoxiceischaemic injury are of growing importance.1,2 For instance, perinatal stroke is a common cerebrovascular disorder affecting one in every 4000 births, which accounts for 30% of children with hemiplegic cerebral palsy (CP).3,4 Perinatal ischaemic stroke has been defined as a
* Guarantor and correspondent: M. Zhu, Shanghai Children’s Medical Center Affiliated to Shanghai Jiaotong University School of Medicine, 1678 Dongfang Road, Pudong, Shanghai, People’s Republic of China. Tel.: þ86 (21) 38626161. E-mail address: [email protected] (M. Zhu).
group of heterogeneous conditions in which there is a focal disruption of cerebral blood flow secondary to arterial or cerebral venous thrombosis or embolization, between the 20th weeks of foetal life through the 28th post-natal day, and confirmed by neuroimaging or neuropathological studies.5 In addition, foetal brain damage associated with cerebral vein engorgement or thrombosis, and with periventricular haemorrhage or haemorrhagic infarction is one of the main causes of foetal brain stroke.6 With few acute clinical signs and frequent retrospective recognition, the diagnosis of perinatal stroke is primarily radiographic. Better depiction in the acute or sub-acute phase of cerebral venous anomalies could improve the understanding of pathophysiology and the natural course of venous-based stroke. Magnetic resonance imaging (MRI) is the method of choice in studying perinatal stroke because of its superior
http://dx.doi.org/10.1016/j.crad.2014.06.010 0009-9260/Ó 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Y. Dai et al. / Clinical Radiology 69 (2014) e392ee397
soft-tissue contrast. So far, T1-, T2-weighted turbo spin echo (TSE) sequences, and T2*-weighted echo planar imaging (EPI) sequence have been used to demonstrate diseases related to foetal veins in a few studies.1,2 Susceptibility-weighted imaging (SWI) is well known as a three-dimensional (3D) gradient-echo sequence (GRE) based technique. With phase information as an additional source of contrast, SWI is able to visualize the susceptibility changes induced by different substances, such as blood products (haemosiderin and ferritin), deoxygenated blood, iron, and calcium, and small vein depiction in various physiological and pathological conditions.7e10 The applications of 3D SWI are readily extended to a two-dimensional (2D) GRE based approach for studies in the abdomen, including the detection of siderotic nodules in cirrhosis, liver fibrosis staging, and haemorrhage in hepatocellular carcinoma and renal cancer.11e14 In the present study, a novel MRI method, 2D SWI, was used to assess foetal cerebral veins in healthy volunteers.
e393
sampling; 310 Hz/pixel bandwidth; 15 s acquisition time); and (c) SWI: 2D GRE (20 flip angle; 407 ms TR/40 ms TE; 350 262 mm2 FOV: eight sections; sense ¼ 2; 0.8 0.8 5.0 mm3 spatial resolution; 170 Hz/pixel bandwidth; 1 min 2 s acquisition time, free breathing). The participant was positioned supine, with the feet placed first into the magnet to minimize claustrophobia. No maternal sedation or foetal paralysis was used. Scout imaging was initially performed in three orthogonal directions to accurately locate the foetus. After the localization, T2weighted single-shot TSE was used to provide clear anatomical images of the foetal brain in the sagittal direction. Based on the TSE images, the SWI was performed along the anterior commissureeposterior commissure (AC-PC) direction to obtain transverse foetal brain images (Fig 1). The SWI reconstruction was implemented based on both magnitude and phase images of the GRE sequence following the method used in the previous study.11
Image analysis
Materials and methods Volunteers A total of 42 pregnant healthy volunteers (age 24e35 years, mean 26.5 6.1 years) with a gestational age of 19e37 weeks were consecutively enrolled in the study at Shanghai Children’s Medical Center from January 2013 to September 2013. A medical history was collected for each participant, especially regarding risk factors for the foetus. The criteria for participant enrolment were as follows: (1) all participants were in a stable clinical condition with no known contraindications to MRI; (2) no participant had diagnosed or self-reported malignancy, cardiovascular disease, pulmonary disease, metabolic disease, renal disease, hepatic disease, parathyroid gland diseases, rheumatoid arthritis, malabsorption syndrome, blood diseases, as well as coexisting diabetes; and (3) none of the participants were using therapies that affect foetal development (such as glucocorticoids, immunosuppressive medications). Institutional review board approval was obtained prior to the MRI examinations, and written informed consent was obtained for all participants.
Two paediatric neurologists with 10 and 12 years in neurology imaging evaluation independently reviewed all 42 sets of SWI images using software SPIN (Signal Process in NMR, MR Institute of Research, Wayne State University, MI, USA). First, an intersection line (15e20 pixels long) was drawn vertically across each vein displayed on all SWI images (Fig 2a). With the intersection line in place, the veins were identified and counted. In addition, the prominence of vein (POV) on SWI images was evaluated using the signal intensity (SI) profile of the intersection line. The POV was defined as the signal difference between the vein and surrounding tissue parenchyma, namely the signal difference (DS) from bottom (vein) to flat top (surrounding tissue parenchyma) of the SI profile (Fig 2b). The POV was quantitatively categorized into faint (score 1: DS 80); moderate (score 2: 80 < DS 100); and prominent (score 3: DS > 100). Finally, the distribution of the veins detected by SWI was dichotomized into to the left and right hemisphere brain. An average value of the number of veins in each subject and average POV score were used for analysis when a disagreement existed between the two neurologists.
MRI Statistical analysis All MRI examinations were carried out using a 1.5 T whole-body MRI system (Achieva TX, Philips Healthcare, Best, The Netherlands) with a commercialized 16-channel torso coil. The imaging sequences included (a) scout imaging: GRE (18 flip angle; 7 ms repetition time (TR)/2.5 ms echo time (TE); 440 440 mm2 field of view (FOV); 13 sections; sensitivity encoding (Sense) ¼ 2; 1.7 2.3 9 mm3 spatial resolution; 280 Hz/pixel bandwidth; 21 s acquisition time); (b) sagittal foetal brain imaging: T2-weighted single shot turbo spin-echo (TSE; 160 flip angle; 3000 ms TR/260 ms TE; 340 340 mm2 FOV; five sections; sense ¼ 2; 0.9 1.3 3.0 mm3 spatial resolution; length of echo train ¼ 128; 62.5% partial Fourier k-space
The correlation between the number of veins detected at SWI and the gestational age of the foetuses was determined using linear regression and Pearson’s correlation analysis. Student’s t-test was used to evaluate the distribution of veins for all foetuses. Interobserver reliability for the categorical items was analysed by Cohen’s kappa method. A priori classifications of k value were as follows: k ¼ 0 indicated no agreement, 0 < k 0.2 indicated slight agreement, 0.2 < k 0.4 indicated fair agreement, 0.4 < k 0.6 indicated moderate agreement, 0.6 < k 0.8 indicated substantial agreement, and k > 0.8 indicated near perfect agreement. All statistics were performed with software
e394
Y. Dai et al. / Clinical Radiology 69 (2014) e392ee397
Figure 1 A pregnant woman at 36 weeks of gestation. (a) T2-weighted single-shot TSE sequence imaging in the sagittal direction (0.9 1.3 3.0 mm3 spatial resolution; 160 flip angle; 3000 ms TR/260 ms TE). The numbered white dotted lines indicate the sections positioned along the ACePC direction for SWI. (b) Corresponding SWI image (0.8 0.8 5.0 mm3 spatial resolution; 20 flip angle; 407 ms TR/ 40 ms TE).
SPSS (Statistical Product and Service Solutions, version 16.0, Chicago, IL, USA) using a 0.05 level of significance.
Results Of the 42 volunteers, 13 were excluded owing to either artefacts from maternal respiration that considerably impaired image quality or no veins detected at SWI. In nine of the 13 volunteers, the foetal brains were all positioned towards the ventral part of the abdomen of varying degrees, which increased the sensitivity of images to the breathing artefacts. In the other four volunteers, no veins were detected on the SWI images at a gestational age of 19, 20, 21, and 24 weeks, respectively. In the remaining 29 volunteers, with a gestational age of 24e37 weeks, the positions of foetal brains were all towards the cervix, making it similar to pelvic imaging and less affected by respiration artefacts. In total, 167 veins were detected in 29 foetal brains with a range of two to 10 for each subject (mean 5.6 2.4). The
types of detected veins included vein of Galen (n ¼ 29), internal cerebral vein (n ¼ 29), septal vein (n ¼ 44), medial atrial vein (n ¼ 29), striate vein (n ¼ 13), choroidal vein (n ¼ 10), and superficial Sylvian vein (n ¼ 13; Fig 3). Symmetric distribution revealed that 56 veins were located in the left hemisphere whereas 53 veins were located in the right hemisphere (p > 0.5). The vein of Galen and internal cerebral vein were not included for distribution analysis due to their centred position. A linear relationship was found between the number of visible veins (N) and gestational age (G) as follows: N ¼ 10:9 þ 0:53G
(1)
where G ranged from 24e37 weeks with r ¼ 0.82, p < 0.001. From equation (1), one can deduce that an additional vein will be “seen” by SWI every 2 weeks from the 24th week of gestation, as shown in Fig 4. According to POV categorization, 46 veins including vein of Galen (n ¼ 23) and internal cerebral vein (n ¼ 23) were
Figure 2 A pregnant woman at 34 weeks of gestation. (a) Every intersection line with a width of 15e20 pixels (red line) is drawn across each vein on SWI image. (b) The corresponding SI profile of the intersection line in (a). The horizontal axis indicates the pixels of the intersection line and the vertical axis indicates signal intensity. DS is the signal difference between the vein (bottom) and surrounding tissue parenchyma (flat top). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.).
Y. Dai et al. / Clinical Radiology 69 (2014) e392ee397
e395
Table 1 Prominence of vein (POV) categorization.
Vein of Galen Internal cerebral vein Medial atrial vein Septal vein Striate vein Choroidal vein Superficial Sylvian vein
Faint
Moderate
Prominent
0 0 4 10 5 7 13
6 6 25 34 8 3 0
23 23 0 0 0 0 0
The veins detected at SWI were categorized into three POV scores, which were defined by the signal difference between the veins and surrounding tissue parenchyma.
Figure 3 A pregnant woman at 35 weeks of gestation. All veins detected on one of SWI images are highlighted (white arrows).
termed prominent; 86 veins including vein of Galen (n ¼ 6), internal cerebral vein (n ¼ 6), medial atrial vein (n ¼ 25), septal vein (n ¼ 34), striate vein (n ¼ 8), and choroidal vein (n ¼ 3) were termed moderate; and 35 veins including medial atrial vein (n ¼ 4), septal vein (n ¼ 10) striate vein (n ¼ 5), choroidal vein (n ¼ 7), and superficial Sylvian vein (n ¼ 13) were termed faint (Table 1). POV scores from the two neurologists were in near perfect agreement (k ¼ 0.91).
Discussion In the present study, the veins of 29 foetal brains were visualized using SWI. The cerebral veins detected were vein
Figure 4 A plot of the number of veins detected by SWI per foetus in order of gestational age from 24e37 weeks. The horizontal axis indicates the weeks of gestation and the vertical axis indicates the number of veins. Each dot represents one subject and a triangle represents two coincided subjects. The number of veins as a function of gestational age is described by the straight line computed by linear regression algorithm as N ¼ 10.9 þ 0.53 G, where N stands for the number of veins and G stands for the weeks of gestation.
of Galen, internal cerebral vein, medial atrial vein, choroidal vein, septal vein, striate vein, and superficial Sylvian vein, with a symmetric distribution. The veins were initially detected at 24 weeks of gestation; starting from that time, it was proven statistically that an additional vein would be detected biweekly until 37 weeks of gestation. This finding indirectly confirmed the results found in previous studies of foetal vasculature development.15,16 POV results for all veins were analysed. It is noteworthy that a small number of veins were detected in the present study, and 10 veins were detected in foetuses at 36 weeks of gestation. However, few studies have demonstrated the presence of normal veins in the foetal brain using conventional T1-, T2-weighted TSE sequences, or T2*-weighted EPI sequences. Abnormal cases regarding venous engorgement, thrombosis, or haemorrhage are the exception.1,2 The advantages of SWI over conventional sequences in the detection of veins are twofold. First, SWI, as a T2*-weighted GRE sequence, successfully adopts the phase information into final image contrast, which vastly improves its sensitivity to tissue susceptibilities, making it, to date, the most sensitive MRI technique for detecting veins, blood products, and haemorrhage.17 In contrast, TSE sequences are insensitive to veins owing to its 180 radiofrequency refocusing pulses, which eliminate the local field changes caused by tissue susceptibilities. Second, a higher signal-to-noise (SNR) and less distortion of SWI compared to EPI sequences make it a better choice for detecting cerebral veins. Compared to the performance of SWI in adults or neonatal brain studies,18,19 the existing deep medullary veins (DMVs) or small veins in the periventricular white matter were seldom revealed by SWI for all foetuses in the present study. Also, from the POV results, only veins of Galen and internal cerebral veins were consistently prominent, most of the other veins had only a moderate and faint display. These characteristics of vein visualization could probably be explained by the blood oxygenation level dependent (BOLD) effect, the development of veins in the foetal brain and sequence protocol settings. Foetal blood is different from adult blood. It contains predominant foetal haemoglobin, which has a considerably higher oxygen affinity compared with adult haemoglobin. The relative ratios of foetal haemoglobin and adult haemoglobin in red blood cells change as a function of gestational age.20,21 The predominant foetal haemoglobin keeps foetal
e396
Y. Dai et al. / Clinical Radiology 69 (2014) e392ee397
venous blood at a higher oxygen level relative to that of an adult, resulting in higher SWI signals in the veins and poorer contrast to the surrounding tissue parenchyma. This BOLD effect on venous SWI signal has been confirmed in a neonate study. The sulcal and intramedullary veins are usually faintly visible in neonates when examined in “natural sleep”; in intubated ventilated neonates the higher oxygenation typically increases the signal intensity of the veins, frequently making them almost invisible at SWI.19 During the process of vasculature development in the foetal brain, the density and diameter of vessels, both arteries and veins, increase rapidly from about 26 weeks of gestation and peak at 35 weeks, although there exists developmental discrepancy among different cerebral regions.15,16 Moreover, in the developing foetal brain a majority of veins are found to have a diameter less than 1 mm.22 Fast imaging is indispensable, and 2D SWI, instead of 3D SWI, was used in the present study to minimize motion artefacts via the high temporal resolution. The spatial resolution of 0.8 0.8 5.0 mm3 was used to tradeoff between the temporal resolution and the SNR. According to the SWI theory, SWI could detect veins smaller than the in-plane resolution, called the blooming effect.23 However, a section thickness of 5 mm will aggravate partial volume effects in the direction of the section, thus reducing the efficiency of vein detection. Therefore, the smaller number of tiny premature veins in developing foetal brain and the partial volume effect might be responsible for the first detection of veins at 24 weeks of gestation. It is also important to note that the angle between the static magnetic field and veins has an impact on phase changes, and thus affects the contrast of veins on SWI.17 In light of the high sensitivity of SWI to cerebral veins, blood products, and haemorrhage, SWI and its quantitative analysis open avenues for future research in studying hypoxiceischaemic injury in the foetus. Initially, periventricular venous infarction (PVI), as part of perinatal stroke, occurs well before birth and is characterized by germinal matrix haemorrhage leading to an impairment of blood drainage from the periventricular white matter that becomes infarcted.24 As SWI has nearly three to six-times higher sensitivity to microhaemorrhage than T2*-weighted GRE sequences,25 early and accurate detection of haemorrhage in PVI during pregnancy is expected. It was also reported that the T2*-weighted GRE sequence had a higher sensitivity to venous thrombosis than T1- or T2-weighted TSE sequences at the acute stage due to the susceptibility effects of thrombus,26 and, further, SWI was shown to have the highest sensitivity to thrombosed cortical veins compared to T1-weighted TSE sequences, fluid attenuated inversion recovery (FLAIR) sequences, or diffusion-weighted imaging (DWI), even in the absence of visible occlusion.27 Therefore, SWI could be of clinical value for foetal stroke imaging in the presence of venous engorgement, thrombosis, and haemorrhage. In addition, as the SWI signal is highly dependent on the amount of deoxyhaemoglobin, the quantitative POV for vein contrast can be used as an indicator of the deoxyhaemoglobin level in the cerebral venous system and provide insight into oxygen extraction in foetal
neurological diseases such as hypoxiceischaemic injury.28 Future applications of quantitative susceptibility mapping to obtain information on oxygen saturation may be possible but will require higher resolution than provided in the present study.29 To avoid motion artifacts in the future a faster breath-hold study which could be repeated multiple times would likely improve the number of cases providing high quality data.30 Several limitations of the present study should be recognized. The sample size is small (n ¼ 29), although it is enough to achieve statistically significant results. Besides the investigation of vein development in the foetal brain with participants of different gestational ages, no individual cases with venous-related diseases were enrolled in the study. For the safety reasons, comparison studies using SWI on 1.5 and on 3 T systems have not been performed, which may lead to different results. In conclusion, the results of the present study demonstrate that 2D SWI can visualize the veins in foetal brain from 24 weeks of gestation. The characteristics of vein visualization are tightly associated with the developmental of the foetal brain and the mechanics of 2D SWI. This finding indicates that 2D SWI would provide a useful tool adjunct to conventional imaging methods, and could become a useful imaging technique for diagnosing foetal neurological diseases in the future.
References 1. Arrigoni F, Prazzini C, Righini A, et al. Deep medullary vein involvement in neonates with brain damage: an MR imaging study. AJNR Am J Neuroradiol 2011;32:2030e6. 2. Done C, Righini A, Parazzini C, et al. Prenatal MR imaging detection of deep medullary vein involvement in fetal brain damage. AJNR Am J Neuroradiol 2011;32:E146e9. 3. Nelson KB. Perinatal ischemic stroke. Stroke 2007;38(Suppl.):742e5. 4. Kirton A, deVeber G. Advances in perinatal ischemic stroke. Pediatr Neurol 2009;40:205e14. 5. Govaert P, Ramenghi L, Taal R, et al. Diagnosis of perinatal stroke I: definitions, differential diagnosis and registration. Acta Paediatr 2009;98:1556e7. 6. Bousser M-G. Cerebral venous thrombosis: diagnosis and management. J Neurol 2000;247:252e8. 7. Haacke EM, Xu Y, Cheng YC, et al. Susceptibility weighted imaging. Magn Reson Med 2004;52:612e8. 8. Rauscher A, Sedlacik J, Barth M, et al. Noninvasive assessment of vascular architecture and function during modulated blood oxygenation using susceptibility weighted magnetic resonance imaging. Magn Reson Med 2005;54:87e95. 9. Kao HW, Tsai FY, Hasso AN. Predicting stroke evolution: comparison of susceptibility-weighted MR imaging with MR perfusion. Eur Radiol 2012;22:1397e403. 10. Sehgal V, Delproposto Z, Haddar D, et al. Susceptibility-weighted imaging to visualize blood products and improve tumor contrast in the study of brain masses. J Magn Reson Imaging 2006;24:41e51. 11. Dai Y, Zeng M, Li R, et al. Improving detection of siderotic nodules in cirrhotic liver with multi-breath-hold susceptibility-weighted imaging technique. J Magn Reson Imaging 2011;34:318e25. 12. Balassy C, Feier D, Peck-Radosavljevic M, et al. Susceptibility-weighted MR imaging in grading liver fibrosis d a feasibility study. Radiology 2014;270:149e58. 13. Li RK, Zeng MS, Rao SX, et al. Using a new 2D susceptibility-weighted imaging to visualize intratumoral hemorrhage and predict histological grade of hepatocellular carcinoma at 3T MRI: a preliminary study. J Magn Reson Imaging 2012;36:900e6.
Y. Dai et al. / Clinical Radiology 69 (2014) e392ee397 14. Xing W, He X, Kassir MA, et al. Evaluating hemorrhage in renal cell carcinoma using susceptibility weighted imaging. PLoS One 2013;8:e57691. 15. Mito T, Konomi H, Houdou S, et al. Immunohistochemical. Study of the vasculature in the developing brain. Pediatr Neurol 1991;7:19e22. 16. Miyawaki T, Matsui K, Takashima S. Developmental characteristics of vessel density in the human fetal and infant brains. Early Hum Dev 1998;53:65e72. 17. Haacke EM, Mittal S, Wu Z, et al. Susceptibility-weighted imaging: technical aspects and clinical applications, part 1. AJNR Am J Neuroradiol 2009;30:19e30. 18. Mittal S, Wu Z, Neelavalli J, et al. Susceptibility-weighted imaging: technical aspects and clinical applications, part 2. AJNR Am J Neuroradiol 2009;30:232e52. 19. Meoded A, Poretti A, Northington FJ, et al. Susceptibility weighted imaging of the neonatal brain. Clin Radiol 2012;67:793e801. 20. Zijlstra WG, Buursma A, Meeuwsen-van der Roest WP. Absorption spectra of human fetal and adult oxyhemoglobin, de-oxyhemoglobin, carboxyhemoglobin, and methemoglobin. Clin Chem 1991;37:1633e8. 21. Bard H, Makowski EL, Meschia G, et al. The relative rates of synthesis of hemoglobins A and F in immature red cells of newborn infants. Pediatrics 1970;45:766e72. 22. Maehara F, Okudera T, Ohta T, et al. Radiological anatomy of the vein of . Nihon Igaku Hoshasen Gakkai Zasshi 1997;57:305e13. Labbe
e397
23. Cheng YC, Haacke EM. Predicting BOLD signal changes as a function of blood volume fraction and resolution. NMR Biomed 2001;14:468e77. 24. Kirton A, Shroff M, Pontigon AM, et al. Risk factors and presentations of periventricular venous infarction vs. arterial presumed perinatal ischemic stroke. Arch Neurol 2010;67:842e8. 25. Haacke EM, DelProposto ZS, Chaturvedi S, et al. Imaging cerebral amyloid angiopathy with susceptibility-weighted imaging. AJNR AM J Neuroradiol 2007;28:316e7. 26. Leach JL, Strub WM, Gaskill-Shipley MR. Cerebral venous thrombus signal intensity and susceptibility effects on gradient recalled-echo MR imaging. AJNR Am J Neuroradiol 2007;28:940e5. 27. Idabaih A, Boukobza M, Crassard I, et al. MRI of clot in cerebral venous thrombosis: high diagnostic value of susceptibility-weighted images. Stroke 2006;37:991e5. 28. Kitamura G, Kido D, Wycliffe N, et al. Hypoxiceischemic injury: utility of susceptibility-weighted imaging. Pediatri Neuro 2011;45:220e4. 29. Haacke EM, Tang J, Neelavalli J, et al. Susceptibility mapping as a means to visualize veins and quantify oxygen saturation. J Magn Reson Imaging 2010;32:663e76. 30. Neelavalli J, Mody S, Yeo L, et al. MR venography of the fetal brain using susceptibility weighted imaging. J Magn Reson Imaging 2013 Nov 25. http://dx.doi.org/10.1002/jmri.24476. [Epub ahead of print].