Trevor K. Carpenter

Comparison of 10 Different Magnetic Resonance Perfusion Imaging Processing Methods in Acute Ischemic Stroke Effect on Lesion Size, Proportion of Patients With Diffusion/Perfusion Mismatch, Clinical Scores, and Radiologic Outcomes

Background and Purpose— Several methods are available to assess the magnetic resonance perfusion lesion in acute ischemic stroke. We tested 10 of these to compare perfusion lesion sizes and to assess the relation to clinical scores and final infarct extent. Methods— We recruited patients with acute ischemic stroke, performed diffusion- and perfusion-weighted imaging, and recorded stroke severity at baseline, final infarct size on T2-weighted imaging at ≥1 month, and Rankin Scale score at 3 months. We calculated 10 perfusion parameters (6 of mean transit time, MTT; 3 of cerebral blood flow; 1 of cerebral blood volume; 7 relative and 3 quantitative), measured the perfusion-weighted imaging lesion and diffusion/perfusion mismatch volumes, and compared each with clinical and radiologic outcomes. Results— Among 32 patients, the median perfusion lesion volume varied from 0 to 14 882 voxels (P<0.0001); the proportion of patients with mismatch varied from 9% to 72% (P<0.05), depending on the perfusion parameter. Five measures of relative MTT were associated with baseline National Institutes of Health Stroke Scale score; 1 (arrival time fitted) was also associated with clinical outcome. Final infarct size was most strongly associated with MTT measures, including arrival time fitted. There was no advantage of quantitative perfusion measures and no relation between mismatch presence/absence and infarct expansion with any of the 10 perfusion measures. Conclusions— Perfusion lesion size differs markedly depending on the parameter calculated. Relative perfusion parameters performed as well as quantitative ones. Some parameters (mainly representing MTT measures) were correlated with clinical scores; others were correlated with final infarct size; and arrival time fitted was correlated with both. These findings should be validated in other datasets. A consensus is required on which perfusion measurement and processing methods should be used.

Do Acute Diffusion- and Perfusion-Weighted MRI Lesions Identify Final Infarct Volume in Ischemic Stroke?

Background and Purpose— An acute mismatch on diffusion-weighted MRI (DWI) and perfusion-weighted MRI (PWI) may represent the “tissue-at-risk.” It is unclear which “semiquantitative” perfusion parameter most closely identifies final infarct volume. Methods— Acute stroke patients underwent DWI and PWI (dynamic-susceptibility contrast imaging) on admission (baseline), and T2-weighted imaging (T2WI) at 1 or 3 months after stroke. “Semiquantitative” mean transit time (MTTsq=first moment of concentration/time curve), cerebral blood volume (CBVsq=area under concentration/time curve), and cerebral blood flow (CBFsq=CBVsq/MTTsq) were calculated. DWI and PWI lesions were measured at baseline and final infarct volume on T2WI acquired ≥1 month after stroke. Baseline DWI, CBFsq, and MTTsq lesion volumes were compared with final T2WI lesion volume. Results— Among 46 patients, baseline DWI and CBFsq lesions were not significantly different from final T2WI lesion volume, but baseline MTTsq lesions were significantly larger. The correlation with final T2WI lesion volume was strongest for DWI (Spearman rank correlation coefficient &rgr;=0.68), intermediate for CBFsq (&rgr;=0.55), and weakest for MTTsq (&rgr;=0.49) baseline lesion volumes. Neither DWI/CBFsq nor DWI/MTTsq mismatch predicted lesion growth; lesion growth was equally common in those with and without mismatch. Conclusions— Of the 2 PWI parameters, CBFsq lesions most closely identifies, and MTTsq overestimates, final T2WI lesion volume. “DWI/PWI mismatch” does not identify lesion growth. Patients without “DWI/PWI mismatch” are equally likely to have lesion growth as those with mismatch and should not be excluded from acute stroke treatment.

Temporal evolution of water diffusion parameters is different in grey and white matter in human ischaemic stroke

Objectives: Our purpose was to investigate whether differences exist in the values and temporal evolution of mean diffusivity () and fractional anisotropy (FA) of grey and white matter after human ischaemic stroke. Methods: Thirty two patients with lesions affecting both grey and white matter underwent serial diffusion tensor magnetic resonance imaging (DT-MRI) within 24 hours, and at 4–7 days, 10–14 days, 1 month, and 3 months after stroke. Multiple small circular regions of interest (ROI) were placed in the grey and white matter within the lesion and in the contralateral hemisphere. Values of {grey}, {white}, FA{grey} and FA{white} were measured in these ROI at each time point and the ratios of ischaemic to normal contralateral values (R and FAR) calculated. Results: and FA showed different patterns of evolution after stroke. After an initial decline, the rate of increase of {grey} was faster than {white} from 4–7 to 10–14 days. FA{white} decreased more rapidly than FA{grey} during the first week, thereafter for both tissue types the FA decreased gradually. However, FA{white} was still higher than FA{grey} at three months indicating that some organised axonal structure remained. This effect was more marked in some patients than in others. R{grey} was significantly higher than R{white} within 24 hours and at 10–14 days (p<0.05), and FAR{white} was significantly more reduced than FAR{grey} at all time points (p<0.001). Conclusions: The values and temporal evolution of and FA are different for grey and white matter after human ischaemic stroke. The observation that there is patient-to-patient variability in the degree of white matter structure remaining within the infarct at three months may have implications for predicting patient outcome.

Changes in Background Blood–Brain Barrier Integrity Between Lacunar and Cortical Ischemic Stroke Subtypes

Background and Purpose— Lacunar stroke is associated with endothelial dysfunction and histologically with intrinsic cerebral microvascular disease of unknown cause. Endothelial dysfunction could impair blood–brain barrier integrity. We assessed background blood–brain barrier leakage in patients with lacunar ischemic stroke compared with cortical stroke controls. Methods— We recruited patients with lacunar or mild cortical ischemic stroke and assessed generalized cerebral blood–brain barrier leak with MRI and intravenous gadolinium at least 1 month after stroke. We used detailed image processing to compare signal change before and for 30 minutes postcontrast throughout gray matter, white matter, and cerebrospinal fluid with summary analyses and general linear modeling. Results— Among 48 patients (29 lacunar, 19 cortical), postcontrast enhancement was significantly higher in cerebrospinal fluid (P=0.04, Mann-Whitney U), and nonsignificantly higher in white matter, in lacunar than in cortical strokes, with no difference in gray matter. General linear modeling confirmed significantly greater postcontrast enhancement in cerebrospinal fluid in lacunar patients than in cortical controls (t=3.37, P<0.0008). Conclusion— These preliminary data suggest that the blood–brain barrier may be dysfunctional throughout subcortical white matter (white matter drains via interstitial spaces to cerebrospinal fluid) in patients with lacunar stroke. Further studies are required to confirm these findings and determine whether abnormal blood–brain barrier might predate development of lacunar disease. Blood–brain barrier dysfunction may be an important mechanism for brain damage in cerebral microvascular disease.

Medical image analysis methods in MR/CT-imaged acute-subacute ischemic stroke lesion: Segmentation, prediction and insights into dynamic evolution simulation models. A critical appraisal☆

Over the last 15 years, basic thresholding techniques in combination with standard statistical correlation-based data analysis tools have been widely used to investigate different aspects of evolution of acute or subacute to late stage ischemic stroke in both human and animal data. Yet, a wave of biology-dependent and imaging-dependent issues is still untackled pointing towards the key question: “how does an ischemic stroke evolve?” Paving the way for potential answers to this question, both magnetic resonance (MRI) and CT (computed tomography) images have been used to visualize the lesion extent, either with or without spatial distinction between dead and salvageable tissue. Combining diffusion and perfusion imaging modalities may provide the possibility of predicting further tissue recovery or eventual necrosis. Going beyond these basic thresholding techniques, in this critical appraisal, we explore different semi-automatic or fully automatic 2D/3D medical image analysis methods and mathematical models applied to human, animal (rats/rodents) and/or synthetic ischemic stroke to tackle one of the following three problems: (1) segmentation of infarcted and/or salvageable (also called penumbral) tissue, (2) prediction of final ischemic tissue fate (death or recovery) and (3) dynamic simulation of the lesion core and/or penumbra evolution. To highlight the key features in the reviewed segmentation and prediction methods, we propose a common categorization pattern. We also emphasize some key aspects of the methods such as the imaging modalities required to build and test the presented approach, the number of patients/animals or synthetic samples, the use of external user interaction and the methods of assessment (clinical or imaging-based). Furthermore, we investigate how any key difficulties, posed by the evolution of stroke such as swelling or reperfusion, were detected (or not) by each method. In the absence of any imaging-based macroscopic dynamic model applied to ischemic stroke, we have insights into relevant microscopic dynamic models simulating the evolution of brain ischemia in the hope to further promising and challenging 4D imaging-based dynamic models. By depicting the major pitfalls and the advanced aspects of the different reviewed methods, we present an overall critique of their performances and concluded our discussion by suggesting some recommendations for future research work focusing on one or more of the three addressed problems.

Use of dynamic contrast-enhanced MRI to measure subtle blood-brain barrier abnormalities

There is growing interest in investigating the role of subtle changes in blood–brain barrier (BBB) function in common neurological disorders and the possible use of imaging techniques to assess these abnormalities. Some studies have used dynamic contrast-enhanced MR imaging (DCE-MRI) and these have demonstrated much smaller signal changes than obtained from more traditional applications of the technique, such as in intracranial tumors and multiple sclerosis. In this work, preliminary results are presented from a DCE-MRI study of patients with mild stroke classified according to the extent of visible underlying white matter abnormalities. These data are used to estimate typical signal enhancement profiles in different tissue types and by degrees of white matter abnormality. The effect of scanner noise, drift and different intrinsic tissue properties on signal enhancement data is also investigated and the likely implications for interpreting the enhancement profiles are discussed. No significant differences in average signal enhancement or contrast agent concentration were observed between patients with different degrees of white matter abnormality, although there was a trend towards greater signal enhancement with more abnormal white matter. Furthermore, the results suggest that many of the factors considered introduce uncertainty of a similar magnitude to expected effect sizes, making it unclear whether differences in signal enhancement are truly reflective of an underlying BBB abnormality or due to an unrelated effect. As the ultimate aim is to achieve a reliable quantification of BBB function in subtle disorders, this study highlights the factors which may influence signal enhancement and suggests that further work is required to address the challenging problems of quantifying contrast agent concentration in healthy and diseased living human tissue and of establishing a suitable model to enable quantification of relevant physiological parameters. Meanwhile, it is essential that future studies use an appropriate control group to minimize these influences.

Persistent Infarct Hyperintensity on Diffusion-Weighted Imaging Late After Stroke Indicates Heterogeneous, Delayed, Infarct Evolution

Background and Purpose— Some infarcts have persistently hyperintense areas on diffusion-weighted MRI (DWI) even at 1 month after stroke, whereas others have become isointense to normal brain. We hypothesized that late DWI hyperintensity reflected different infarct evolution compared with areas that were isointense by 1 month. Methods— We recruited patients prospectively with ischemic stroke, performed DWI and perfusion-weighted MRI (PWI) on admission, at 5 days, 14 days, and 1 month after stroke, and assessed functional outcome at 3 months (Rankin Scale). Patient characteristics and DWI/PWI values were compared for patients with or without “still hyperintense” infarct areas on 1-month DWI. Results— Among 42 patients, 27 (64%) had “still hyperintense” infarct regions at 1 month, mostly in white matter. Patients with “still hyperintense” regions at 1 month had lower baseline apparent diffusion coefficient ratio (ADCr; mean±SD 0.76±0.12 versus 0.85±0.12; hyperintense versus isointense; P<0.05), prolonged reduction of ADCr (repeated-measures ANOVA; P<0.01), no difference in baseline perfusion but delayed normalization of mean transit time (P<0.05) and cerebral blood flow ratios (repeated measures ANOVA; P<0.05), initially more severe stroke, and worse 3-month outcome than patients whose lesions were isointense by 1 month. Conclusion— The late DWI lesion hyperintensity emphasizes the heterogeneity in temporal evolution of stroke injury and suggests ongoing “ischemia.” Lower baseline ADCr precedes delayed perfusion normalization, suggesting that worse cell swelling impedes reperfusion. Further study is required to determine underlying mechanisms and any potential for subacute intervention to improve recovery.

MR diffusion and perfusion parameters: relationship to metabolites in acute ischaemic stroke

Background Magnetic resonance (MR) diffusion and perfusion imaging are used to identify ischaemic penumbra, but there are few comparisons with neuronal loss and ischaemia in vivo. The authors compared N-acetyl aspartate (NAA, found in intact neurons) and lactate (anaerobic metabolism) with diffusion/perfusion parameters. Methods The authors prospectively recruited patients with acute ischaemic stroke and performed MR diffusion tensor, perfusion (PWI) and proton chemical shift spectroscopic imaging (CSI). We superimposed a 0.5 cm voxel grid on the diffusion-weighted images (DWI) and classified voxels as ‘definitely abnormal,’ ‘possibly abnormal’ or normal on DWI appearance, and ‘mismatch’ for voxels in DWI/PWI mismatch areas. The authors compared metabolite (NAA, lactate), perfusion and apparent diffusion coefficient (ADC) values in each voxel type. Results NAA differentiated ‘definitely’ from ‘possibly abnormal,’ and ‘possibly abnormal’ from ‘mismatch’ (both comparisons p<0.01) voxels, but not ‘mismatch’ from ‘normal’ voxels. Lactate was highest in ‘definitely abnormal,’ and progressively lower in ‘possibly abnormal,’ ‘mismatch,’ than ‘normal’ voxels (all differences p<0.01). There was no correlation between NAA and ADC or PWI values, but high lactate correlated with low ADC (Spearman r=−0.41, p=0.02) and prolonged mean transit time (Spearman r=0.42, p=0.02). Conclusion ADC and mean transit time indicate the presence of ischaemia (lactate) but not cumulative total neuronal damage (NAA) in acute ischaemic stroke, suggesting that caution is required if using ADC and PWI parameters to differentiate salvageable from non-salvageable tissue. Further refinement of the DWI/PWI concept is required prior to more widespread use.

DSC perfusion MRI-Quantification and reduction of systematic errors arising in areas of reduced cerebral blood flow.

Dynamic susceptibility contrast (DSC)‐MRI is commonly used to measure cerebral perfusion in acute ischemic stroke. Quantification of perfusion parameters involves deconvolution of the tissue concentration‐time curves with an arterial input function (AIF), typically with the use of singular value decomposition (SVD). To mitigate the effects of noise on the estimated cerebral blood flow (CBF), a regularization parameter or threshold is used. Often a single global threshold is applied to every voxel, and its value has a dramatic effect on the CBF values obtained. When a single global threshold was applied to simulated concentration‐time curves produced using exponential, triangular, and boxcar residue functions, significant systematic errors were found in the measured perfusion parameters. We estimate the errors obtained for different sampling intervals and signal‐to‐noise ratios (SNRs), and discuss the source of the systematic error. We present a method that partially corrects for the systematic error in the presence of an exponential residue function by applying a linear fit, which removes underestimates of long mean transit time (MTT) and overestimates of short MTT. For example, the correction reduced the error at a temporal resolution of 2.5 s and an SNR of 30 from 29.1% to 11.7%. However, the error is largest in the presence of noise and at MTTs that are likely to be encountered in areas of hypoperfusion; furthermore, even though it is reduced, it cannot be corrected for exactly. Magn Reson Med, 2006.

Associations Between Diffusion and Perfusion Parameters, N-Acetyl Aspartate, and Lactate in Acute Ischemic Stroke

Background and Purpose— In acute ischemic stroke, the amount of neuronal damage in hyperintense areas on MR diffusion imaging (DWI) is unclear. We used spectroscopic imaging to measure N-acetyl aspartate (NAA, a marker of normal neurons) and lactate (a marker of ischemia) to compare with diffusion and perfusion values in the diffusion lesion in acute ischemic stroke. Methods— We recruited patients with acute ischemic stroke prospectively and performed MR diffusion weighted (DWI), perfusion, and spectroscopic imaging. We coregistered the images, outlined the visible diffusion lesion, and extracted metabolite, perfusion, and apparent diffusion coefficient (ADC) values from the diffusion lesion. Results— 42 patients were imaged, from 1.5 to 24 hours after stroke. In the DWI lesion, although NAA was reduced, there was no correlation between NAA and ADC or perfusion values. However, raised lactate correlated with reduced ADC (Spearman &rgr;=0.32, P=0.04) and prolonged mean transit time (MTT, &rgr;=0.31, P=0.04). Increasing DWI lesion size was associated with lower NAA and higher lactate (&rgr;=−0.44, P=0.003; &rgr;=0.49, P=0.001 respectively); NAA fell with increasing times to imaging (&rgr;=−0.3, P=0.03), but lactate did not change. Conclusion— Although larger confirmatory studies are needed, the correlation of ADC and MTT with lactate but not NAA suggests that ADC and MTT are better markers of the presence of ischemia than of cumulative neuronal loss. Further studies should define more precisely the rate of neuronal loss and relationship to diffusion and perfusion parameters with respect to the depth and duration of ischemia.