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Cerebral Perfusion Imaging using Contrast-enhanced MRI
Clinical Radiology (2003) 58: 505–513 doi:10.1016/S0009-9260(03)00130-2, available online at www.sciencedirect.com
Review Cerebral Perfusion Imaging using Contrast-enhanced MRI P. KE ST ON * , A . D . M U R R A Y * , A . J A C K S O N † *Academic Department of Radiology, Foresterhill, Aberdeen, and †Imaging Science, Department of Medicine, University of Manchester, Manchester, UK Received: 21 November 2002 Accepted: 18 December 2002 New developments in fast magnetic resonance imaging (MRI) have enabled imaging of cerebral haemodynamics. This article describes the theory behind perfusion imaging and provides an overview of the most commonly used MRI technique. Limitations of this technique are described, and the potential clinical applications are discussed, with particular attention to the role of perfusion imaging in the context of stroke and brain tumour. Keston, P. et al. (2003). Clinical Radiology 58 505– 513 q 2003 The Royal College of Radiologists. Published by Elsevier Science Ltd. All rights reserved. Key words: magnetic resonance imaging, haemodynamics, contrast media, brain.
INTRODUCTION
Perfusion is defined as the volume of blood flowing through a given volume of tissue per unit time. When calculating this figure for a whole organ the situation is conceptually simple, requiring measurement of the flow rate in the feeding vessels and of the volume of the organ. In the case of the brain, the normal value is around 50 ml/100 g/min. In practice, these measurements are difficult to make, and physiologists have developed a number of methods to estimate whole brain blood flow (CBF), blood volume (CBV) and transit time (MTT). Two approaches have been described. The first uses a marker that will penetrate freely into brain tissue (i.e. nitrous oxide) and estimates CBF by measuring the extraction of the marker from the circulation. The second technique, used in intensive care monitoring systems to measure changes in CBF, uses a bolus injection of a marker (usually a dye) that stays within the bloodstream. CBF measurements are derived from changes in bolus width and height that occur during passage through the brain. Measurement of cerebral perfusion by imaging uses similar basic principles and has the advantage of demonstrating regional Guarantor and correspondent: Dr P. Keston, Academic Department of Radiology, Lillian Sutton Building, Foresterhill, Aberdeen AB25, Scotland, UK. Tel: þ44-1224-559718; Fax: þ 44-1224-552157; E-mail: [email protected] 0009-9260/03/$30.00/0
changes in perfusion and other blood flow parameters. Several imaging techniques are capable of producing perfusion data. Both isotope techniques, such as hexamethyl propylene amine oxime single photon emission computed tomography (HMPAO SPECT) and [18O]–H2O positron emission tomography (PET) and xenonbased perfusion computed tomography (CT) use markers that pass freely from the blood into the brain. They derive regional CBF measurements from images of the distribution of the marker within the brain. Each of these techniques has inherent advantages and disadvantages that are beyond the scope of this article. Bolus techniques are used in both iodinated contrast perfusion CT and with magnetic resonance imaging (MRI). There are two commonly used methods for measuring CBF using MRI. Arterial spin labelling magnetically labels the water in the arterial blood entering the brain, to provide an endogenous tracer of flow. Although the possibility of measuring perfusion without the need for an exogenous tracer is attractive, this technique is not yet sufficiently robust for routine clinical use [1,2]. Dynamic susceptibility contrastenhanced MRI (DSC-MRI), first described in 1991 by Rosen et al. [3], uses rapid measurements of MRI signal change after the injection of a bolus of a paramagnetic MRI contrast agent [4]. This is the most commonly employed MRI perfusion technique and has been studied extensively in clinical settings. Perfusion is a fundamental characteristic of brain tissue. Numerous pathological processes alter the normal pattern of
q 2003 The Royal College of Radiologists. Published by Elsevier Science Ltd. All rights reserved.
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blood flow. The ability to measure this flow pattern is of undoubted clinical value. The evidence for the role of MRI perfusion imaging in a clinical setting is reviewed. DSC-MRI
DSC-MRI is simple to perform in a clinical environment and is now the MRI perfusion technique most commonly used in clinical studies [5 –8]. High concentrations of gadolinium contrast agents produce significant T2 and T2* relaxation and thus signal drop on T2-weighted spin-echo (SE) and T2*weighted gradient echo (GE) sequences (Fig. 1). The signal loss is roughly proportional to the log of the contrast concentration. A bolus of contrast, injected intravenously, produces maximal signal drop in the brain during its first pass through the intracranial circulation. Unlike T1 signal enhancement, which has a short radius of action, T2 susceptibility effects extends to a few millimetres around the contrast agent, making this method particularly sensitive to the presence of contrast in areas of low vascular density such as capillary beds. Rapid imaging of the brain is repeated at short intervals before, during and after the first pass of the contrast bolus to enable estimation of contrast concentration within each voxel and plot this against the scan time.
Collecting DSC-MRI Data MRI of bolus passage is a relatively straightforward process. The imaging technique must collect a time course series of T2*weighted images of the area of interest with sufficient temporal resolution to allow accurate analysis and without significant sliceto-slice movement. The typical imaging strategy is to collect data using a fast imaging technique such as single or multi-shot echo planar imaging (EPI) to produce a temporal resolution of approximately 2 s. During this 2 s acquisition window it is usually possible to acquire in the region of five to 15 slices at a resolution of 128 £ 128, dependent on the scanner specifications. The imaging sequence can be GE, which will maximize T2* weighting, or alternatively SE, which will minimize the signal contribution from large vessels. Many authors prefer the latter approach as it produces signal changes that predominantly reflect the passage of contrast through the capillary bed and it is relatively free from the artefacts that are a feature of GE imaging (Fig. 2). A series of at least five pre-contrast image sets is collected before the passage of the bolus to measure the signal intensity baseline.
Fig. 2 – A sample GE, EPI section in the posterior fossa. Distortion of anatomy is seen due to susceptibility artefact from the skull base and orbits. This is due to close approximation of tissues with large inherent differences in magnetic susceptibility: air, in the mastoid air cells and paranasal sinuses; cortical bone and brain parenchyma. Early filling with the contrast bolus is seen in the right middle cerebral artery. It is necessary to compromise between the use of spin echo (SE) and GE EPI. The sensitivity of GE to susceptibility effect is useful to increase accuracy of perfusion measurement while the distortion present in the posterior fossa may detract from the value of these images. SE imaging is more useful in imaging posterior fossa or peripheral lesions due to lesser anatomical distortion.
Gadolinium contrast agents are almost uniformly employed, although perfusion imaging has been performed with other agents [9,10]. A standard contrast dose (0.1 mmol/kg) is adequate in most cases although a double dose will improve signal:noise ratio. Increased contrast dose is more critical if SE sequences are used. The use of an automated pressure injector is recommended. It should be programmed to deliver the contrast over approximately 4 s, followed by a saline flush of at least 25 ml, delivered at the same rate. A manual injection technique can produce acceptable and reproducible results.
Analysis of DSC-MRI Data Basic Theory One of the main aims of DSC-MRI is the production of quantified images of blood flow. In theory this is a straightforward process. In practice a number of problems exist, which
Fig. 1 – Series of source images obtained at intervals during the perfusion imaging sequence. The initial GE, EPI image (1) shows normal appearances before arrival of the bolus. The bolus arrives at image (2) and the concentration increases to a peak at image (3) where marked loss of signal is seen within the cortical vessels and brain parenchyma. The signal loss declines rapidly (4). The final image (5) shows appearances similar to those pre-contrast. The relatively low spatial and contrast resolution of the source images is apparent.
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have considerably restricted the clinical use of the technique. The first step in analysis is the calculation of contrast concentration versus time curves from the signal intensity data (Fig. 3). The area under the contrast concentration curve provides an estimate of CBV within the voxel and the width of the contrast bolus is used as an estimate of the MTT of blood through the voxel. The regional CBF can then be calculated using the central volume theorem: CBF ¼ CBV=MTT In addition to these flow-related parameters it is possible to produce maps of bolus arrival time ðT0 Þ and time to peak contrast concentration (TTP). These parameters are simple to produce, are clinically relevant, and are unique to bolus tracking techniques. Unfortunately, this approach to the measurement of CBF is subject to significant errors, arising from a number of sources. These errors have led to modifications of the analysis method, in an attempt to produce a more accurate, quantitative estimate of blood flow.
Problems in the Analysis of DSC-MRI Data Contrast recirculation. Analysis of the contrast bolus passage assumes that the bolus passes through the voxel and that the concentration of contrast then returns to zero. In fact, the contrast recirculates through the body and a second, recirculation peak is seen after the first pass peak. As the contrast recirculates, the bolus disperses and widens so that the second peak is lower and broader than the first and, by the time of the third recirculation, the contrast has mixed evenly throughout the blood volume, causing a small, constant baseline elevation in the contrast concentration. Measurement
Fig. 3 – A graph of the signal strength (arbitrary MR units) within a region of interest in the frontal lobe, plotted against image number. In this example the images are at 2 s intervals and the graph therefore covers a time period of 80 s—the acquisition time for the perfusion sequence.
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of CBV is therefore subject to errors, due to the presence of both first pass and recirculating contrast in the vessels during the later part of the bolus passage. In addition, identification of the end of the bolus passage is complicated by the second recirculation peak. One solution to this problem is the use of a g-variate curve-fitting technique to produce a mathematical description of the contrast concentration changes from the early part of the bolus passage. The use of curve fitting smoothes the data, effectively reducing noise, and eliminates the contamination of the first pass bolus due to contrast agent recirculation [4,11–13]. Contrast Leakage. The analysis of contrast bolus studies also assumes that the signal change observed results entirely from contrast within the blood vessels. In the normal brain the blood–brain barrier prevents passage of contrast from the vascular compartment. However, leakage of contrast into the interstitial space does occur in pathological processes, e.g. tumours. The leaked contrast will also cause signal changes, principally by relaxivity mechanisms. Susceptibility based imaging methods offer the opportunity to separate these relaxivity and susceptibility based effects and to produce images in which the effect of contrast leakage is eliminated or minimized. The use of techniques with reduced T1 sensitivity such as low flip angle GE sequences is common [14 – 16]. This technique effectively removes relaxivity effects, although this may not work well in rapidly enhancing tumours. A significant problem with this method is the loss of signal:noise ratio produced by the reduction in flip angle. This can be partially compensated by increased contrast dose. Another approach to reducing T1 sensitivity is to use a dual echo technique in which the T1-weighted first echo is used to correct the predominantly T2-weighted second echo [17]. This method is a simple and effective way to remove relaxivity effects but places considerable demands on sampling time and inevitably restricts the number of slices that can be obtained. Pre-enhancement with a small amount of contrast can mitigate some of the T1-shortening effect and thus reduce error caused by contrast leakage. The change in signal intensity resulting from T1 shortening is bi-exponential such that there is a plateau phase during which signal intensity remains relatively constant despite increasing contrast concentrations. Much of the T1 shortening effect is produced by the pre-enhancement and the effects of leakage during the main contrast injection are decreased. The problem with this approach is that the efficiency of the technique is dependent on the interstitial contrast concentration at the time of the bolus passage. As tumours show differing contrast diffusion rates [18,19] this concentration cannot be accurately predicted, although it can be measured. Each of these methods has specific advantages and disadvantages. The choice of technique must be made by considering the requirements of the individual study. Dual echo methods will reliably eliminate relaxivity effects but suffer from poor signal:noise ratio and limited sampling volume. Low flip angle methods provide reliable elimination of relaxivity effects so long as TR times are adequate. These methods are fast but also suffer from poor signal:noise ratios in normal tissue. Pre-enhancement techniques enable the use of sequences
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that are sensitive to relaxivity changes and consequently provide good signal:noise ratio. However, pre-enhancement causes residual bolus effects, which alter the dynamics of signal change during subsequent bolus passage in normal tissue. Bolus Calibration and Dispersion. The use of the central volume theorem to calculate values for CBF assumes that the technique can produce quantitative measurements of CBV and MTT. In fact the use of the area under the curve to estimate CBV results in relative measures that enable comparison of CBV between tissues rather than producing an absolute measurement. This relative measure, commonly called relative CBV (rCBV) can be calibrated in a number of ways by use of standard tissue values such as grey or white matter or by measurement of CBV in major vessels. Each of these has associated problems, and the use of large vessels to provide estimates of 100% CBV is particularly problematic as the relationship between signals in large and small vessels is heavily dependent on the image acquisition technique. Indeed many workers deliberately use SE techniques in order to selectively suppress signal contributions from contrast in large vessels. The quantification of CBF also requires accurate estimation of MTT, which is extracted from the width of the contrast bolus in each voxel [2,7,20]. The width of the contrast bolus is affected by a combination of three factors. These are: the width of the bolus entering the voxel (the arterial input function or AIF); changes in bolus width (due to regional alterations in flow) and physical bolus broadening due to dispersive effects unrelated to flow. In practice the width of the bolus is strongly affected by individual variations in injection technique, contrast dose and cardiovascular function so that direct comparison of derived CBF measurements between individuals requires assumptions that these sources of variation have been minimized or removed [21,22]. One approach to this problem is to deconvolve data from each voxel with an input response function that removes such variability to produce an estimate of the contrast concentration time course in each voxel that approximates the changes that would be seen if the input were a bolus of infinitely short duration. This has been used as the basis of quantitative techniques for the absolute measurement of CBF [2,21,23,24]. The use of a deconvolution approach assumes that the input function to each voxel can be measured accurately, which is not possible. These techniques therefore measure a surrogate AIF from one of the major arteries in the basal cisterns, most commonly the middle cerebral artery. The use of a surrogate measure requires an assumption that no additional broadening of the contrast bolus occurs between the AIF measurement point and the voxel [2,25]. In fact it is clear that these effects do occur, even in normal subjects [26,27]. Recent simulation studies have suggested that this error introduces significant underestimation of CBF and overestimation of MTT. Additional broadening of the bolus by over 2.5 s overestimates MTT by 200% and underestimates CBF by 50% and this underestimation increases further as bolus broadening increases [20].
Interpretation of DSC-MRI Data Many commercially available software systems analyse
DSC-MRI data in a simplistic manner, without the facility for deconvolution of the arterial input function. In these circumstances typical parametric mapping parameters will be rCBV, rCBF and rMTT (Fig. 4). In fact the doubt surrounding the exact relationship between these measurements and their physiological counterparts has led most manufacturers to use more descriptive labels such as: integrated area under the curve (rCBV), bolus width (rMTT) and area under the curve:bolus width ratio (rCBF). This should warn the clinician that the interpretation and physiological meaning of these parameters can be difficult to understand. Maps of rCBV appear to represent regional variations in CBV accurately and are of particular use in the study of tumours. Estimations of T0 and TTP also accurately represent local variations in contrast arrival time. These parameters are affected by any delay in flow along the vascular pathway proximal to the voxel. This makes them exquisitely sensitive to changes in flow rate that occur in the presence of vascular stenosis and occlusive lesions. It must be appreciated that large changes in T0 and TTP can be seen without associated changes in CBF. In patients with unilateral carotid stenosis compensatory vasodilatation will maintain CBF but will be associated with slowing of flow and increases in T0 and TTP. Similarly it is important to realize that it is easy to misinterpret these parameters because they are relative and not absolute values. For example, in unilateral carotid stenosis, an ipsilateral increase in TTP will easily be appreciated since the contralateral side remains normal. In a patient with severe multi-vessel disease, with associated reductions in CBF, both sides of the brain will develop
Fig. 4 – Normal parametric maps demonstrating the relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF) and relative mean transit time (rMTT). The signal–time graph for a representative region of interest is also shown. The rCBV and rCBF maps show similar distribution of perfusion, which is generally greater in the cerebral cortex than the white matter. The homogenous appearance of the rMTT map is often useful in clinical applications as abnormality is often more apparent. However, this higher sensitivity to perfusion abnormality can lead to overestimation of the size of a lesion.
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vasodilatation and slowing of contrast flow. In these circumstances both hemispheres will have slow flow and prolonged TTP but this will result in relatively symmetric images, from which these abnormalities are difficult or impossible to detect. Appreciation of the flow abnormalities in this situation requires absolute quantified measurements of blood flow such as may be obtained after deconvolution with an arterial input function, however, the intrinsic potential problems with this technique and consequent potential inaccuracies in quantitative measurements must also be considered [20,28,29]. This is most important where the identification of an appropriate arterial input function is complicated by pathology as in occlusive vascular disease.
CLINICAL APPLICATIONS
Stroke The most apparent and best-described application of DSCMRI is in the field of stroke imaging [30–34]. Thromboembolic occlusion of the cerebral circulation is by far the commonest cause of stroke and accounts for 80% of cases (Fig. 5). Whilst CT and morphological MRI provide accurate diagnosis of established infarction, both techniques are limited in the acute setting (, 6 h post-ictus). With the recent understanding of the benefits of thrombolytic treatment in cerebral infarction [35], there is a need for fast and accurate diagnosis. DSC-MRI has been shown to accurately demonstrate the underlying vascular occlusion immediately post-ictus [36]. Typical findings are of decreased rCBV and rCBF in the infarcted area with a corresponding, though normally larger, area of increased rMTT. T0 and TTP are similarly prolonged in an area larger than the final infarct. It is more sensitive than diffusion imaging in making the diagnosis of infarct at less than 4 h following the ictus [37]. At present in the UK, there is poor access to out of hours MRI. There are also inherent difficulties in bringing stroke patients to hospital rapidly and then imaging these acutely ill patients [38]. These factors are likely to prevent the general application of diffusion and DSC-MRI to diagnose stroke. Early estimation of the size of an infarct and demonstration of ischaemic, but non-infarcted, tissue is valuable in planning treatment. A combination of perfusion and diffusion weighted imaging may achieve this goal. A mismatch between the size of a perfusion defect and the often smaller diffusion abnormality is said to correspond to the presence of an ischaemic penumbra of poorly perfused yet viable tissue. Although this concept is enticing and apparently logical, the size of mismatch varies considerably and is dependent on the perfusion parameter employed and the method used to derive it. To date no standardized technique has been agreed, so information about sensitivity and specificity of these findings is poor. rMTT maps generally overestimate the lesion size. rCBV and rCBF show a closer relationship [39,40]. Less contrived parameters of relative peak height and TTP have recently been found to be useful predictors of final infarct size and require less time to produce [41]. There has also been some interest in the concept of decreased flow heterogeneity [42] in ischaemic tissues. It is
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possible to highlight areas where the rCBF shows less variation between voxels and this is thought to correspond to low overall perfusion. Reperfusion of infarcted tissue may be spontaneous or due to thrombolysis. In either case this feature is eloquently demonstrated with DSC-MRI [43 – 47]. The detection of spontaneous reperfusion may avoid potentially harmful thrombolysis. Altered perfusion parameters have been noted in the presence of leukoaraiosis [48,49], in keeping with its presumed ischaemic origin.
Tumours The imaging of perfusion in neoplastic brain lesions has been studied extensively [50,51]. Brain tumours require a blood supply to grow and this in turn requires angiogenesis. The new blood vessels formed are generally less organized than the normal vessels and hence have altered perfusion characteristics [50,52,53] with increased blood flow and volume. Recent work has studied the role of another perfusion parameter—the relative recirculation (rR) [54,55]. This parameter is thought to relate to the amount of disorganized flow and recirculation due to vascular tortuosity and local reductions in perfusion pressure in the tumour circulation. Perfusion imaging is of value in establishing a diagnosis of tumour by aiding differentiation from other mass lesions (e.g. abscess/tumefactive demyelination) and from metastases [56–58]. Initial experience suggests a role in discrimination between toxoplasmosis and lymphoma in acquired immunodeficiency syndrome (AIDS) patients [59]. Tumour grade can be established with some accuracy by semi-quantitative perfusion imaging [60–62]. Combination of the perfusion image results with those of diffusion imaging and MR spectroscopy improve tumour grading further [63]. Biopsy is more accurate when the most active region of the tumour is sampled, this can be determined by DSC-MRI. Treatment monitoring may also be more sensitive. Measurements of permeability have been described for use in this situation [62, 64–67]. Decreased perfusion and permeability are indicators of response to treatment. Recurrent tumour can be better distinguished from radiotherapy change with DSC-MRI than with standard imaging techniques [68]. Increased blood flow and volume are seen with recurrent tumour while areas of post-radiotherapy change show little alteration or decreased perfusion.
Dementia SPECT studies of blood flow characteristics in vascular dementia and Alzheimer’s disease have been replicated with DSC-MRI [69,70] and the results show good correlation. The use of MRI may be limited by the higher costs and poorer availability compared with SPECT. In the research setting the avoidance of ionizing radiation is advantageous.
Pharmacology Perfusion mapping is of value in the sphere of pharmacology. Alteration of cerebral blood flow and volume has been
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Fig. 5 – (a) Standard T2-weighted image demonstrating an established right middle cerebral artery (MCA) territory infarct. Parametric images of rCBV (b) and rCBF (c) confirm the expected finding of decreased perfusion in the region of this infarct. The rMTT map (d) shows global increase in the transit time throughout the right hemisphere, overestimating the lesion size. It is possible to detect perfusion abnormality immediately after occlusion of the vessel, before infarct can be established with diffusion or morphological imaging.
found after the administration of general anaesthetics. Specific perfusion abnormalities have also been seen after long-term use of MDMA (“Ecstasy”) and cocaine [71 –74]. More clinically relevant applications are in monitoring the effect of novel thrombolytic agents in ischaemic stroke [46] and potentially in demonstrating which patients with Alzheimer’s disease respond to anticholinesterase therapy.
Epilepsy Perfusion MRI may demonstrate decreased perfusion of the medial temporal lobe structures as additional confirmation of abnormality prior to epilepsy surgery [75]. This abnormality
has been demonstrated with arterial spin-labelled perfusion MRI.
Others Other conditions causing abnormality of large cerebral vessels have been demonstrated using DSC-MRI (Fig. 6). Typical changes have been described in patients with carotid stenosis as described above [76]. Similar changes have been described in the presence of giant intracranial aneurysm [77]. Arterial vasospasm in relation to subarachnoid haemorrhage [78,79] and its treatment causes local perfusion deficits in the affected vascular territories and similar, more localized abnormality may be seen in
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external carotid to middle cerebral artery anastomosis in Moyamoya has been demonstrated. CONCLUSIONS
Perfusion MRI is a maturing imaging method that is a clinically useful adjunct to routine brain imaging. Whilst it is not yet possible to quantify regional blood flow, the bolus tracking technique enables assessment of perfusion characteristics not available with isotope methods or xenon CT. DSCMRI has been shown to be clinically useful, particularly in the initial investigation of stroke and in tumour imaging. As more experience is gained, and with improving technical capabilities, it is likely that it will be used more widely as an adjunct to morphological imaging. The faster acquisition time and better spatial resolution of susceptibility contrast studies make this technique optimal for current clinical use.
REFERENCES
Fig. 6 – A large arteriovenous malformation (AVM) is seen in the right posterior parietal region with conventional T2-weighted imaging (a). The corresponding rCBV perfusion map (b) highlights the markedly increased blood volume within this lesion. The black area in the centre of the lesion is due to threshold levels set for the image and does not represent an area of zero flow. Similar appearances were seen with the rCBF map. A role for perfusion imaging in the follow up of AVM to ensure obliteration of abnormal flow following treatment has been suggested.
migraine attacks [80,81]. In Moyamoya [82 – 84], there are gross, patchy areas of altered blood flow, volume and transit time. Although in the above situations DSC-MRI is not of diagnostic importance, it is conceivable that the functional information would be of value in the planning of treatment. For example, DSC-MRI during the test occlusion of a carotid vessel has been shown to be of value in ensuring adequate postocclusion blood flow [85] and improved perfusion after
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accurately identifies tissue destined to infarct. Stroke, 2001;32: 1581– 1587. Grandin CB, Duprez TP, Smith AM, et al. Which MR-derived perfusion parameters are the best predictors of infarct growth in hyperacute stroke? Comparative study between relative and quantitative measurements. Radiology, 2002;223:361–370. Ostergaard L, Sorensen AG, Chesler DA, et al. Combined diffusionweighted and perfusion-weighted flow heterogeneity magnetic resonance imaging in acute stroke. Stroke, 2000;31:1097 –1103. Uno M, Harada M, Yoneda K, et al. Can diffusion- and perfusionweighted magnetic resonance imaging evaluate the efficacy of acute thrombolysis in patients with internal carotid artery or middle cerebral artery occlusion? Neurosurgery, 2002;50:28–34. Parsons MW, Barber PA, Chalk J, et al. Diffusion- and perfusionweighted MRI response to thrombolysis in stroke. Ann Neurol, 2002;51: 28–37. Kidwell CS, Saver JL, Mattiello J, et al. Diffusion–perfusion MRI characterization of post-recanalization hyperperfusion in humans. Neurology, 2001;57:2015–2021. Marks MP, Tong DC, Beaulieu C, et al. Evaluation of early reperfusion and i.v. TPA therapy using diffusion- and perfusion-weighted MRI. Neurology, 1999;52:1792–1798. Schellinger PD, Jansen O, Fiebach JB, et al. Monitoring intravenous recombinant tissue plasminogen activator thrombolysis for acute ischemic stroke with diffusion and perfusion MRI. Stroke, 2000;31: 1318– 1328. Marstrand JR, Garde E, Rostrup E, et al. Cerebral perfusion and cerebrovascular reactivity are reduced in white matter hyperintensities. Stroke, 2002;33:972–976. O’Sullivan M, Lythgoe DJ, Pereira AC, et al. Patterns of cerebral blood flow reduction in patients with ischemic leukoaraiosis. Neurology, 2002;59:321–326. Cha S, Knopp EA, Johnson G, et al. Intracranial mass lesions: dynamic contrast-enhanced susceptibility-weighted echo-planar perfusion MR imaging. Radiology, 2002;223:11–29. Knopp MV, Essig M, Hawighorst H, et al. Functional neuroimaging in the assessment of CNS neoplasms. Eur Radiol, 1997;7(Suppl. 5): 209– 215. Sugahara T, Korogi Y, Kochi M, et al. Perfusion-sensitive MR imaging of gliomas: comparison between gradient-echo and spin-echo echoplanar imaging techniques. AJNR Am J Neuroradiol, 2001;22: 1306– 1315. Uematsu H, Maeda M, Sadato N, et al. Blood volume of gliomas determined by double-echo dynamic perfusion-weighted MR imaging: a preliminary study. AJNR Am J Neuroradiol, 2001;22:1915 –1919. Jackson A, Kassner A, Zhu XP, Li KL. Reproducibility of T2* blood volume and vascular tortuosity maps in cerebral gliomas. J Magn Reson Imaging, 2001;14:510–516. Jackson A, Kassner A, Annesley-Williams D, et al. Abnormalities in the recirculation phase of contrast agent bolus passage in cerebral gliomas: comparison with relative blood volume and tumor grade. AJNR Am J Neuroradiol, 2002;23:7–14. Chan JH, Tsui EY, Chau LF, et al. Discrimination of an infected brain tumor from a cerebral abscess by combined MR perfusion and diffusion imaging. Comput Med Imaging Graphics, 2002;26:19–23. Law M, Cha S, Knopp EA, et al. High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MR imaging. Radiology, 2002;222:715 –721. Cha S, Pierce S, Knopp EA, et al. Dynamic contrast-enhanced T2*weighted MR imaging of tumefactive demyelinating lesions. AJNR Am J Neuroradiol, 2001;22:1109 –1116. Ernst TM, Chang L, Witt MD, et al. Cerebral toxoplasmosis and lymphoma in AIDS: perfusion MR imaging experience in 13 patients. Radiology, 1998;208:663–669. Lee SJ, Kim JH, Kim YM, et al. Perfusion MR imaging in gliomas: comparison with histologic tumor grade. Korean J Radiol, 2001;2:1 –7. Ludemann L, Grieger W, Wurm R, et al. Comparison of dynamic contrast-enhanced MRI with WHO tumor grading for gliomas. Eur Radiol, 2001;11:1231–1241. Provenzale JM, Wang GR, Brenner T, et al. Comparison of permeability in high-grade and low-grade brain tumors using dynamic susceptibility contrast MR imaging. AJR Am J Roentgenol, 2002;178: 711 –716.
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63 Yang D, Korogi Y, Sugahara T, et al. Cerebral gliomas: prospective comparison of Multivoxel 2D chemical-shift imaging proton MR spectroscopy, echoplanar perfusion and diffusion-weighted MRI. Neuroradiology, 2002;44:656–666. 64 Gossmann A, Helbich TH, Kuriyama N, et al. Dynamic contrastenhanced magnetic resonance imaging as a surrogate marker of tumor response to anti-angiogenic therapy in a xenograft model of glioblastoma multiforme. J Magn Reson Imaging, 2002;15:233–240. 65 Roberts HC, Roberts TP, Brasch RC, Dillon WP. Quantitative measurement of microvascular permeability in human brain tumors achieved using dynamic contrast-enhanced MR imaging: correlation with histologic grade. AJNR Am J Neuroradiol, 2000;21:891– 899. 66 Uematsu H, Maeda M, Sadato N, et al. Vascular permeability: quantitative measurement with double-echo dynamic MR imaging— theory and clinical application. Radiology, 2000;214:912–917. 67 Zhu XP, Li KL, Kamaly-Asl ID, et al. Quantification of endothelial permeability, leakage space, and blood volume in brain tumors using combined T1 and T2* contrast-enhanced dynamic MR imaging. J Magn Reson Imaging, 2000;11:575–585. 68 Wenz F, Rempp K, Hess T, et al. Effect of radiation on blood volume in low-grade astrocytomas and normal brain tissue: quantification with dynamic susceptibility contrast MR imaging. AJR Am J Roentgenol, 1996;166:187 –193. 69 Bozzao A, Floris R, Baviera ME, et al. Diffusion and perfusion MR imaging in cases of Alzheimer’s disease: correlations with cortical atrophy and lesion load. AJNR Am J Neuroradiol, 2001;22:1030– 1036. 70 Harris GJ, Lewis RF, Satlin A, et al. Dynamic susceptibility contrast MR imaging of regional cerebral blood volume in Alzheimer’s disease: a promising alternative to nuclear medicine. AJNR Am J Neuroradiol, 1998;19:1727 –1732. 71 Li KL, Suojanen JN. Cocaine-induced changes in time course of regional cerebral blood volume and transit time as determined by dynamic MR imaging. J Magn Reson Imaging, 1995;5:715–718. 72 Lorenz IH, Kolbitsch C, Hormann C, et al. Influence of equianaesthetic concentrations of nitrous oxide and isoflurane on regional cerebral blood flow, regional cerebral blood volume, and regional mean transit time in human volunteers. BJA: Br J Anaesth, 2001;87:691–698. 73 Reneman L, Habraken JB, Majoie CB, et al. MDMA (“Ecstasy”) and its association with cerebrovascular accidents: preliminary findings. AJNR Am J Neuroradiol, 2000;21:1001– 1007.
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74 Reneman L, Majoie CB, Habraken JB, den Heeten GJ. Effects of ecstasy (MDMA) on the brain in abstinent users: initial observations with diffusion and perfusion MR imaging. Radiology, 2001;220: 611– 617. 75 Wolf RL, Alsop DC, Levy-Reis I, et al. Detection of mesial temporal lobe hypoperfusion in patients with temporal lobe epilepsy by use of arterial spin labeled perfusion MR imaging. AJNR Am J Neuroradiol, 2001;22:1334–1341. 76 Doerfler A, Eckstein HH, Eichbaum M, et al. Perfusion-weighted magnetic resonance imaging in patients with carotid artery disease before and after carotid endarterectomy. J Vasc Surg, 2001;34: 587– 593. 77 Caramia F, Santoro A, Pantano P, et al. Cerebral hemodynamics on MR perfusion images before and after bypass surgery in patients with giant intracranial aneurysms. AJNR Am J Neuroradiol, 2001;22:1704 –1710. 78 Griffiths PD, Wilkinson ID, Mitchell P, et al. Multimodality MR imaging depiction of hemodynamic changes and cerebral ischemia in subarachnoid hemorrhage. AJNR Am J Neuroradiol, 2001;22: 1690– 1697. 79 Rordorf G, Koroshetz WJ, Copen WA, et al. Diffusion- and perfusionweighted imaging in vasospasm after subarachnoid hemorrhage. Stroke, 1999;30:599–605. 80 Cutrer FM, Sorensen AG, Weisskoff RM, et al. Perfusion-weighted imaging defects during spontaneous migrainous aura. Ann Neurol, 1998;43:25–31. 81 Cutrer FM, O’Donnell A, Sanchez del Rio. Functional neuroimaging: enhanced understanding of migraine pathophysiology. Neurology, 2000;55(Suppl. 2):S45. 82 Calamante F, Ganesan V, Kirkham FJ, et al. MR perfusion imaging in Moyamoya syndrome: potential implications for clinical evaluation of occlusive cerebrovascular disease. Stroke, 2001;32:2810–2816. 83 Tsuchiya K, Inaoka S, Mizutani Y, Hachiya J. Echo-planar perfusion MR of Moyamoya disease. AJNR Am J Neuroradiol, 1998;19:211–216. 84 Yamada I, Himeno Y, Nagaoka T, et al. Moyamoya disease: evaluation with diffusion-weighted and perfusion echo-planar MR imaging. Radiology, 1999;212:340–347. 85 Michel E, Liu H, Remley KB, et al. Perfusion MR neuroimaging in patients undergoing balloon test occlusion of the internal carotid artery. AJNR Am J Neuroradiol, 2001;22:1590– 1596.
Review Cerebral Perfusion Imaging using Contrast-enhanced MRI P. KE ST ON * , A . D . M U R R A Y * , A . J A C K S O N † *Academic Department of Radiology, Foresterhill, Aberdeen, and †Imaging Science, Department of Medicine, University of Manchester, Manchester, UK Received: 21 November 2002 Accepted: 18 December 2002 New developments in fast magnetic resonance imaging (MRI) have enabled imaging of cerebral haemodynamics. This article describes the theory behind perfusion imaging and provides an overview of the most commonly used MRI technique. Limitations of this technique are described, and the potential clinical applications are discussed, with particular attention to the role of perfusion imaging in the context of stroke and brain tumour. Keston, P. et al. (2003). Clinical Radiology 58 505– 513 q 2003 The Royal College of Radiologists. Published by Elsevier Science Ltd. All rights reserved. Key words: magnetic resonance imaging, haemodynamics, contrast media, brain.
INTRODUCTION
Perfusion is defined as the volume of blood flowing through a given volume of tissue per unit time. When calculating this figure for a whole organ the situation is conceptually simple, requiring measurement of the flow rate in the feeding vessels and of the volume of the organ. In the case of the brain, the normal value is around 50 ml/100 g/min. In practice, these measurements are difficult to make, and physiologists have developed a number of methods to estimate whole brain blood flow (CBF), blood volume (CBV) and transit time (MTT). Two approaches have been described. The first uses a marker that will penetrate freely into brain tissue (i.e. nitrous oxide) and estimates CBF by measuring the extraction of the marker from the circulation. The second technique, used in intensive care monitoring systems to measure changes in CBF, uses a bolus injection of a marker (usually a dye) that stays within the bloodstream. CBF measurements are derived from changes in bolus width and height that occur during passage through the brain. Measurement of cerebral perfusion by imaging uses similar basic principles and has the advantage of demonstrating regional Guarantor and correspondent: Dr P. Keston, Academic Department of Radiology, Lillian Sutton Building, Foresterhill, Aberdeen AB25, Scotland, UK. Tel: þ44-1224-559718; Fax: þ 44-1224-552157; E-mail: [email protected] 0009-9260/03/$30.00/0
changes in perfusion and other blood flow parameters. Several imaging techniques are capable of producing perfusion data. Both isotope techniques, such as hexamethyl propylene amine oxime single photon emission computed tomography (HMPAO SPECT) and [18O]–H2O positron emission tomography (PET) and xenonbased perfusion computed tomography (CT) use markers that pass freely from the blood into the brain. They derive regional CBF measurements from images of the distribution of the marker within the brain. Each of these techniques has inherent advantages and disadvantages that are beyond the scope of this article. Bolus techniques are used in both iodinated contrast perfusion CT and with magnetic resonance imaging (MRI). There are two commonly used methods for measuring CBF using MRI. Arterial spin labelling magnetically labels the water in the arterial blood entering the brain, to provide an endogenous tracer of flow. Although the possibility of measuring perfusion without the need for an exogenous tracer is attractive, this technique is not yet sufficiently robust for routine clinical use [1,2]. Dynamic susceptibility contrastenhanced MRI (DSC-MRI), first described in 1991 by Rosen et al. [3], uses rapid measurements of MRI signal change after the injection of a bolus of a paramagnetic MRI contrast agent [4]. This is the most commonly employed MRI perfusion technique and has been studied extensively in clinical settings. Perfusion is a fundamental characteristic of brain tissue. Numerous pathological processes alter the normal pattern of
q 2003 The Royal College of Radiologists. Published by Elsevier Science Ltd. All rights reserved.
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blood flow. The ability to measure this flow pattern is of undoubted clinical value. The evidence for the role of MRI perfusion imaging in a clinical setting is reviewed. DSC-MRI
DSC-MRI is simple to perform in a clinical environment and is now the MRI perfusion technique most commonly used in clinical studies [5 –8]. High concentrations of gadolinium contrast agents produce significant T2 and T2* relaxation and thus signal drop on T2-weighted spin-echo (SE) and T2*weighted gradient echo (GE) sequences (Fig. 1). The signal loss is roughly proportional to the log of the contrast concentration. A bolus of contrast, injected intravenously, produces maximal signal drop in the brain during its first pass through the intracranial circulation. Unlike T1 signal enhancement, which has a short radius of action, T2 susceptibility effects extends to a few millimetres around the contrast agent, making this method particularly sensitive to the presence of contrast in areas of low vascular density such as capillary beds. Rapid imaging of the brain is repeated at short intervals before, during and after the first pass of the contrast bolus to enable estimation of contrast concentration within each voxel and plot this against the scan time.
Collecting DSC-MRI Data MRI of bolus passage is a relatively straightforward process. The imaging technique must collect a time course series of T2*weighted images of the area of interest with sufficient temporal resolution to allow accurate analysis and without significant sliceto-slice movement. The typical imaging strategy is to collect data using a fast imaging technique such as single or multi-shot echo planar imaging (EPI) to produce a temporal resolution of approximately 2 s. During this 2 s acquisition window it is usually possible to acquire in the region of five to 15 slices at a resolution of 128 £ 128, dependent on the scanner specifications. The imaging sequence can be GE, which will maximize T2* weighting, or alternatively SE, which will minimize the signal contribution from large vessels. Many authors prefer the latter approach as it produces signal changes that predominantly reflect the passage of contrast through the capillary bed and it is relatively free from the artefacts that are a feature of GE imaging (Fig. 2). A series of at least five pre-contrast image sets is collected before the passage of the bolus to measure the signal intensity baseline.
Fig. 2 – A sample GE, EPI section in the posterior fossa. Distortion of anatomy is seen due to susceptibility artefact from the skull base and orbits. This is due to close approximation of tissues with large inherent differences in magnetic susceptibility: air, in the mastoid air cells and paranasal sinuses; cortical bone and brain parenchyma. Early filling with the contrast bolus is seen in the right middle cerebral artery. It is necessary to compromise between the use of spin echo (SE) and GE EPI. The sensitivity of GE to susceptibility effect is useful to increase accuracy of perfusion measurement while the distortion present in the posterior fossa may detract from the value of these images. SE imaging is more useful in imaging posterior fossa or peripheral lesions due to lesser anatomical distortion.
Gadolinium contrast agents are almost uniformly employed, although perfusion imaging has been performed with other agents [9,10]. A standard contrast dose (0.1 mmol/kg) is adequate in most cases although a double dose will improve signal:noise ratio. Increased contrast dose is more critical if SE sequences are used. The use of an automated pressure injector is recommended. It should be programmed to deliver the contrast over approximately 4 s, followed by a saline flush of at least 25 ml, delivered at the same rate. A manual injection technique can produce acceptable and reproducible results.
Analysis of DSC-MRI Data Basic Theory One of the main aims of DSC-MRI is the production of quantified images of blood flow. In theory this is a straightforward process. In practice a number of problems exist, which
Fig. 1 – Series of source images obtained at intervals during the perfusion imaging sequence. The initial GE, EPI image (1) shows normal appearances before arrival of the bolus. The bolus arrives at image (2) and the concentration increases to a peak at image (3) where marked loss of signal is seen within the cortical vessels and brain parenchyma. The signal loss declines rapidly (4). The final image (5) shows appearances similar to those pre-contrast. The relatively low spatial and contrast resolution of the source images is apparent.
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have considerably restricted the clinical use of the technique. The first step in analysis is the calculation of contrast concentration versus time curves from the signal intensity data (Fig. 3). The area under the contrast concentration curve provides an estimate of CBV within the voxel and the width of the contrast bolus is used as an estimate of the MTT of blood through the voxel. The regional CBF can then be calculated using the central volume theorem: CBF ¼ CBV=MTT In addition to these flow-related parameters it is possible to produce maps of bolus arrival time ðT0 Þ and time to peak contrast concentration (TTP). These parameters are simple to produce, are clinically relevant, and are unique to bolus tracking techniques. Unfortunately, this approach to the measurement of CBF is subject to significant errors, arising from a number of sources. These errors have led to modifications of the analysis method, in an attempt to produce a more accurate, quantitative estimate of blood flow.
Problems in the Analysis of DSC-MRI Data Contrast recirculation. Analysis of the contrast bolus passage assumes that the bolus passes through the voxel and that the concentration of contrast then returns to zero. In fact, the contrast recirculates through the body and a second, recirculation peak is seen after the first pass peak. As the contrast recirculates, the bolus disperses and widens so that the second peak is lower and broader than the first and, by the time of the third recirculation, the contrast has mixed evenly throughout the blood volume, causing a small, constant baseline elevation in the contrast concentration. Measurement
Fig. 3 – A graph of the signal strength (arbitrary MR units) within a region of interest in the frontal lobe, plotted against image number. In this example the images are at 2 s intervals and the graph therefore covers a time period of 80 s—the acquisition time for the perfusion sequence.
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of CBV is therefore subject to errors, due to the presence of both first pass and recirculating contrast in the vessels during the later part of the bolus passage. In addition, identification of the end of the bolus passage is complicated by the second recirculation peak. One solution to this problem is the use of a g-variate curve-fitting technique to produce a mathematical description of the contrast concentration changes from the early part of the bolus passage. The use of curve fitting smoothes the data, effectively reducing noise, and eliminates the contamination of the first pass bolus due to contrast agent recirculation [4,11–13]. Contrast Leakage. The analysis of contrast bolus studies also assumes that the signal change observed results entirely from contrast within the blood vessels. In the normal brain the blood–brain barrier prevents passage of contrast from the vascular compartment. However, leakage of contrast into the interstitial space does occur in pathological processes, e.g. tumours. The leaked contrast will also cause signal changes, principally by relaxivity mechanisms. Susceptibility based imaging methods offer the opportunity to separate these relaxivity and susceptibility based effects and to produce images in which the effect of contrast leakage is eliminated or minimized. The use of techniques with reduced T1 sensitivity such as low flip angle GE sequences is common [14 – 16]. This technique effectively removes relaxivity effects, although this may not work well in rapidly enhancing tumours. A significant problem with this method is the loss of signal:noise ratio produced by the reduction in flip angle. This can be partially compensated by increased contrast dose. Another approach to reducing T1 sensitivity is to use a dual echo technique in which the T1-weighted first echo is used to correct the predominantly T2-weighted second echo [17]. This method is a simple and effective way to remove relaxivity effects but places considerable demands on sampling time and inevitably restricts the number of slices that can be obtained. Pre-enhancement with a small amount of contrast can mitigate some of the T1-shortening effect and thus reduce error caused by contrast leakage. The change in signal intensity resulting from T1 shortening is bi-exponential such that there is a plateau phase during which signal intensity remains relatively constant despite increasing contrast concentrations. Much of the T1 shortening effect is produced by the pre-enhancement and the effects of leakage during the main contrast injection are decreased. The problem with this approach is that the efficiency of the technique is dependent on the interstitial contrast concentration at the time of the bolus passage. As tumours show differing contrast diffusion rates [18,19] this concentration cannot be accurately predicted, although it can be measured. Each of these methods has specific advantages and disadvantages. The choice of technique must be made by considering the requirements of the individual study. Dual echo methods will reliably eliminate relaxivity effects but suffer from poor signal:noise ratio and limited sampling volume. Low flip angle methods provide reliable elimination of relaxivity effects so long as TR times are adequate. These methods are fast but also suffer from poor signal:noise ratios in normal tissue. Pre-enhancement techniques enable the use of sequences
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that are sensitive to relaxivity changes and consequently provide good signal:noise ratio. However, pre-enhancement causes residual bolus effects, which alter the dynamics of signal change during subsequent bolus passage in normal tissue. Bolus Calibration and Dispersion. The use of the central volume theorem to calculate values for CBF assumes that the technique can produce quantitative measurements of CBV and MTT. In fact the use of the area under the curve to estimate CBV results in relative measures that enable comparison of CBV between tissues rather than producing an absolute measurement. This relative measure, commonly called relative CBV (rCBV) can be calibrated in a number of ways by use of standard tissue values such as grey or white matter or by measurement of CBV in major vessels. Each of these has associated problems, and the use of large vessels to provide estimates of 100% CBV is particularly problematic as the relationship between signals in large and small vessels is heavily dependent on the image acquisition technique. Indeed many workers deliberately use SE techniques in order to selectively suppress signal contributions from contrast in large vessels. The quantification of CBF also requires accurate estimation of MTT, which is extracted from the width of the contrast bolus in each voxel [2,7,20]. The width of the contrast bolus is affected by a combination of three factors. These are: the width of the bolus entering the voxel (the arterial input function or AIF); changes in bolus width (due to regional alterations in flow) and physical bolus broadening due to dispersive effects unrelated to flow. In practice the width of the bolus is strongly affected by individual variations in injection technique, contrast dose and cardiovascular function so that direct comparison of derived CBF measurements between individuals requires assumptions that these sources of variation have been minimized or removed [21,22]. One approach to this problem is to deconvolve data from each voxel with an input response function that removes such variability to produce an estimate of the contrast concentration time course in each voxel that approximates the changes that would be seen if the input were a bolus of infinitely short duration. This has been used as the basis of quantitative techniques for the absolute measurement of CBF [2,21,23,24]. The use of a deconvolution approach assumes that the input function to each voxel can be measured accurately, which is not possible. These techniques therefore measure a surrogate AIF from one of the major arteries in the basal cisterns, most commonly the middle cerebral artery. The use of a surrogate measure requires an assumption that no additional broadening of the contrast bolus occurs between the AIF measurement point and the voxel [2,25]. In fact it is clear that these effects do occur, even in normal subjects [26,27]. Recent simulation studies have suggested that this error introduces significant underestimation of CBF and overestimation of MTT. Additional broadening of the bolus by over 2.5 s overestimates MTT by 200% and underestimates CBF by 50% and this underestimation increases further as bolus broadening increases [20].
Interpretation of DSC-MRI Data Many commercially available software systems analyse
DSC-MRI data in a simplistic manner, without the facility for deconvolution of the arterial input function. In these circumstances typical parametric mapping parameters will be rCBV, rCBF and rMTT (Fig. 4). In fact the doubt surrounding the exact relationship between these measurements and their physiological counterparts has led most manufacturers to use more descriptive labels such as: integrated area under the curve (rCBV), bolus width (rMTT) and area under the curve:bolus width ratio (rCBF). This should warn the clinician that the interpretation and physiological meaning of these parameters can be difficult to understand. Maps of rCBV appear to represent regional variations in CBV accurately and are of particular use in the study of tumours. Estimations of T0 and TTP also accurately represent local variations in contrast arrival time. These parameters are affected by any delay in flow along the vascular pathway proximal to the voxel. This makes them exquisitely sensitive to changes in flow rate that occur in the presence of vascular stenosis and occlusive lesions. It must be appreciated that large changes in T0 and TTP can be seen without associated changes in CBF. In patients with unilateral carotid stenosis compensatory vasodilatation will maintain CBF but will be associated with slowing of flow and increases in T0 and TTP. Similarly it is important to realize that it is easy to misinterpret these parameters because they are relative and not absolute values. For example, in unilateral carotid stenosis, an ipsilateral increase in TTP will easily be appreciated since the contralateral side remains normal. In a patient with severe multi-vessel disease, with associated reductions in CBF, both sides of the brain will develop
Fig. 4 – Normal parametric maps demonstrating the relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF) and relative mean transit time (rMTT). The signal–time graph for a representative region of interest is also shown. The rCBV and rCBF maps show similar distribution of perfusion, which is generally greater in the cerebral cortex than the white matter. The homogenous appearance of the rMTT map is often useful in clinical applications as abnormality is often more apparent. However, this higher sensitivity to perfusion abnormality can lead to overestimation of the size of a lesion.
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vasodilatation and slowing of contrast flow. In these circumstances both hemispheres will have slow flow and prolonged TTP but this will result in relatively symmetric images, from which these abnormalities are difficult or impossible to detect. Appreciation of the flow abnormalities in this situation requires absolute quantified measurements of blood flow such as may be obtained after deconvolution with an arterial input function, however, the intrinsic potential problems with this technique and consequent potential inaccuracies in quantitative measurements must also be considered [20,28,29]. This is most important where the identification of an appropriate arterial input function is complicated by pathology as in occlusive vascular disease.
CLINICAL APPLICATIONS
Stroke The most apparent and best-described application of DSCMRI is in the field of stroke imaging [30–34]. Thromboembolic occlusion of the cerebral circulation is by far the commonest cause of stroke and accounts for 80% of cases (Fig. 5). Whilst CT and morphological MRI provide accurate diagnosis of established infarction, both techniques are limited in the acute setting (, 6 h post-ictus). With the recent understanding of the benefits of thrombolytic treatment in cerebral infarction [35], there is a need for fast and accurate diagnosis. DSC-MRI has been shown to accurately demonstrate the underlying vascular occlusion immediately post-ictus [36]. Typical findings are of decreased rCBV and rCBF in the infarcted area with a corresponding, though normally larger, area of increased rMTT. T0 and TTP are similarly prolonged in an area larger than the final infarct. It is more sensitive than diffusion imaging in making the diagnosis of infarct at less than 4 h following the ictus [37]. At present in the UK, there is poor access to out of hours MRI. There are also inherent difficulties in bringing stroke patients to hospital rapidly and then imaging these acutely ill patients [38]. These factors are likely to prevent the general application of diffusion and DSC-MRI to diagnose stroke. Early estimation of the size of an infarct and demonstration of ischaemic, but non-infarcted, tissue is valuable in planning treatment. A combination of perfusion and diffusion weighted imaging may achieve this goal. A mismatch between the size of a perfusion defect and the often smaller diffusion abnormality is said to correspond to the presence of an ischaemic penumbra of poorly perfused yet viable tissue. Although this concept is enticing and apparently logical, the size of mismatch varies considerably and is dependent on the perfusion parameter employed and the method used to derive it. To date no standardized technique has been agreed, so information about sensitivity and specificity of these findings is poor. rMTT maps generally overestimate the lesion size. rCBV and rCBF show a closer relationship [39,40]. Less contrived parameters of relative peak height and TTP have recently been found to be useful predictors of final infarct size and require less time to produce [41]. There has also been some interest in the concept of decreased flow heterogeneity [42] in ischaemic tissues. It is
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possible to highlight areas where the rCBF shows less variation between voxels and this is thought to correspond to low overall perfusion. Reperfusion of infarcted tissue may be spontaneous or due to thrombolysis. In either case this feature is eloquently demonstrated with DSC-MRI [43 – 47]. The detection of spontaneous reperfusion may avoid potentially harmful thrombolysis. Altered perfusion parameters have been noted in the presence of leukoaraiosis [48,49], in keeping with its presumed ischaemic origin.
Tumours The imaging of perfusion in neoplastic brain lesions has been studied extensively [50,51]. Brain tumours require a blood supply to grow and this in turn requires angiogenesis. The new blood vessels formed are generally less organized than the normal vessels and hence have altered perfusion characteristics [50,52,53] with increased blood flow and volume. Recent work has studied the role of another perfusion parameter—the relative recirculation (rR) [54,55]. This parameter is thought to relate to the amount of disorganized flow and recirculation due to vascular tortuosity and local reductions in perfusion pressure in the tumour circulation. Perfusion imaging is of value in establishing a diagnosis of tumour by aiding differentiation from other mass lesions (e.g. abscess/tumefactive demyelination) and from metastases [56–58]. Initial experience suggests a role in discrimination between toxoplasmosis and lymphoma in acquired immunodeficiency syndrome (AIDS) patients [59]. Tumour grade can be established with some accuracy by semi-quantitative perfusion imaging [60–62]. Combination of the perfusion image results with those of diffusion imaging and MR spectroscopy improve tumour grading further [63]. Biopsy is more accurate when the most active region of the tumour is sampled, this can be determined by DSC-MRI. Treatment monitoring may also be more sensitive. Measurements of permeability have been described for use in this situation [62, 64–67]. Decreased perfusion and permeability are indicators of response to treatment. Recurrent tumour can be better distinguished from radiotherapy change with DSC-MRI than with standard imaging techniques [68]. Increased blood flow and volume are seen with recurrent tumour while areas of post-radiotherapy change show little alteration or decreased perfusion.
Dementia SPECT studies of blood flow characteristics in vascular dementia and Alzheimer’s disease have been replicated with DSC-MRI [69,70] and the results show good correlation. The use of MRI may be limited by the higher costs and poorer availability compared with SPECT. In the research setting the avoidance of ionizing radiation is advantageous.
Pharmacology Perfusion mapping is of value in the sphere of pharmacology. Alteration of cerebral blood flow and volume has been
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Fig. 5 – (a) Standard T2-weighted image demonstrating an established right middle cerebral artery (MCA) territory infarct. Parametric images of rCBV (b) and rCBF (c) confirm the expected finding of decreased perfusion in the region of this infarct. The rMTT map (d) shows global increase in the transit time throughout the right hemisphere, overestimating the lesion size. It is possible to detect perfusion abnormality immediately after occlusion of the vessel, before infarct can be established with diffusion or morphological imaging.
found after the administration of general anaesthetics. Specific perfusion abnormalities have also been seen after long-term use of MDMA (“Ecstasy”) and cocaine [71 –74]. More clinically relevant applications are in monitoring the effect of novel thrombolytic agents in ischaemic stroke [46] and potentially in demonstrating which patients with Alzheimer’s disease respond to anticholinesterase therapy.
Epilepsy Perfusion MRI may demonstrate decreased perfusion of the medial temporal lobe structures as additional confirmation of abnormality prior to epilepsy surgery [75]. This abnormality
has been demonstrated with arterial spin-labelled perfusion MRI.
Others Other conditions causing abnormality of large cerebral vessels have been demonstrated using DSC-MRI (Fig. 6). Typical changes have been described in patients with carotid stenosis as described above [76]. Similar changes have been described in the presence of giant intracranial aneurysm [77]. Arterial vasospasm in relation to subarachnoid haemorrhage [78,79] and its treatment causes local perfusion deficits in the affected vascular territories and similar, more localized abnormality may be seen in
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external carotid to middle cerebral artery anastomosis in Moyamoya has been demonstrated. CONCLUSIONS
Perfusion MRI is a maturing imaging method that is a clinically useful adjunct to routine brain imaging. Whilst it is not yet possible to quantify regional blood flow, the bolus tracking technique enables assessment of perfusion characteristics not available with isotope methods or xenon CT. DSCMRI has been shown to be clinically useful, particularly in the initial investigation of stroke and in tumour imaging. As more experience is gained, and with improving technical capabilities, it is likely that it will be used more widely as an adjunct to morphological imaging. The faster acquisition time and better spatial resolution of susceptibility contrast studies make this technique optimal for current clinical use.
REFERENCES
Fig. 6 – A large arteriovenous malformation (AVM) is seen in the right posterior parietal region with conventional T2-weighted imaging (a). The corresponding rCBV perfusion map (b) highlights the markedly increased blood volume within this lesion. The black area in the centre of the lesion is due to threshold levels set for the image and does not represent an area of zero flow. Similar appearances were seen with the rCBF map. A role for perfusion imaging in the follow up of AVM to ensure obliteration of abnormal flow following treatment has been suggested.
migraine attacks [80,81]. In Moyamoya [82 – 84], there are gross, patchy areas of altered blood flow, volume and transit time. Although in the above situations DSC-MRI is not of diagnostic importance, it is conceivable that the functional information would be of value in the planning of treatment. For example, DSC-MRI during the test occlusion of a carotid vessel has been shown to be of value in ensuring adequate postocclusion blood flow [85] and improved perfusion after
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