The role of diffusion tensor imaging in the evaluation of ischemic brain injury – a review

Water diffusion in brain tissue is affected by the presence of barriers to translational motion such as cell membranes and myelin fibers. The measured water apparent diffusion coefficient (ADC) value is therefore frequently anisotropic and varies depending upon the orientation of restricting barriers (such as white matter tracts) relative to the diffusion‐sensitive‐gradient direction. Anisotropic water diffusion can be specified using indices of diffusion anisotropy [e.g. standard deviation of the individual ADC values, fractional anisotropy (FA), lattice index (LI)], which are derived from measurements of the full diffusion tensor. The rotationally invariant nature of particular diffusion anisotropy indices (e.g. FA, LI) allows orientation‐independent comparisons of these parameters between different subjects. Pathophysiological processes (such as cerebral ischemia) that modify the integrity of the tissue microstructure result in significant alterations in tissue anisotropy and make this metric a useful endpoint for characterizing the temporal evolution of the disease. Diffusion‐tensor imaging (DTI) studies of both experimental and human stroke suggest that DTI may provide additional information about the evolution of the disease that is not available from diffusion‐weighted MRI (DWI) alone. Acute reductions in the average diffusivity [ = (λ1 + λ2 + λ3)/3 where λ1, λ2, and λ3 are the eigenvalues of the diffusion tensor] following the onset of cerebral ischemia are often accompanied by increases in diffusion anisotropy. In the transition from acute to sub‐acute and chronic stroke, renormalizes and subsequently increases whereas diffusion anisotropy measures (e.g. FA) decline and remained reduced in chronic infarcts. Overall isotropic ADC changes during infarct evolution have been observed to be greater in white matter (WM) than in gray matter (GM) lesions (although there have been conflicting reports on this issue) and GM lesions tend to renormalize prior to WM lesions as the infarct evolves. Ischemic WM exhibits a significant decrease in diffusion anisotropy (relative to normal WM) during ischemic evolution whereas that of ischemic GM remains statistically unchanged. Furthermore, the percentage decrease in ischemic WM is largely determined by reductions in λ1, the eigenvalue that coincides with the long axis of the WM fiber tract. Variations in unidirectional ADC or over the ischemic time course limit the usefulness of this parameter alone as a predictor of ischemic injury. Consequently, ADC information has been combined with that of other MR parameters (including DTI) to unambiguously stage and predict ischemic brain injury over its entire temporal evolution. Combined and diffusion anisotropy measurements have identified three phases of diffusion abnormality: (1) reduced and elevated anisotropy; (2) reduced and reduced anisotropy; and (3) elevated and reduced anisotropy. However, variations in the differential patterns of and diffusion anisotropy evolution have been observed by a number of investigators and more work is needed to clarify the role of these measurements in characterizing the severity of the ischemic insult as well as the potential outcome in response to the initial ischemic injury. The use of DTI, in combination with more sophisticated analysis methods for performing multiparametric segmentation, such as multispectral analysis, may enhance the use of MRI for accurate diagnosis and prognosis of stroke. Furthermore, these techniques may also play an important role in the clinical evaluation of new stroke treatments. Copyright © 2002 John Wiley & Sons, Ltd.

[1]  P. Booker,et al.  A model to predict the histopathology of human stroke using diffusion and T2-weighted magnetic resonance imaging. , 1995, Stroke.

[2]  R R Edelman,et al.  Clinical Outcome in Ischemic Stroke Predicted by Early Diffusion-Weighted and Perfusion Magnetic Resonance Imaging: A Preliminary Analysis , 1996, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[3]  A. Song,et al.  Optimized isotropic diffusion weighting , 1995, Magnetic resonance in medicine.

[4]  G. McLachlan,et al.  A Strategy towards the Automated Estimation of Stroke Evolution Utilising a Diffusion and Perfusion MRI based Predictive Model , 2001 .

[5]  C. Sotak,et al.  Comparison of the Temporal and Spatial Evolution of the Water Apparent Diffusion Coefficient and T2 Following Transient Middle Cerebral Artery Occlusion in Rats , 2001 .

[6]  J. Ulatowski,et al.  Rapid monitoring of changes in water diffusion coefficients during reversible ischemia in cat and rat brain , 1994, Magnetic resonance in medicine.

[7]  F Calamante,et al.  Effects of diffusion anisotropy on lesion delineation in a rat model of cerebral ischemia , 1997, Magnetic resonance in medicine.

[8]  H Soltanian-Zadeh,et al.  Time course of ADCw changes in ischemic stroke: beyond the human eye! , 1998, Stroke.

[9]  H. Lutsep,et al.  Clinical utility of diffusion‐weighted magnetic resonance imaging in the assessment of ischemic stroke , 1997, Annals of neurology.

[10]  M. Chopp,et al.  Multiparametric MRI Tissue Characterization in Clinical Stroke With Correlation to Clinical Outcome: Part 2 , 2001, Stroke.

[11]  M Hoehn-Berlage,et al.  Diffusion‐weighted NMR imaging: Application to experimental focal cerebral ischemia , 1995, NMR in biomedicine.

[12]  T E Conturo,et al.  Differences between gray matter and white matter water diffusion in stroke: diffusion-tensor MR imaging in 12 patients. , 2000, Radiology.

[13]  T. Nagaoka,et al.  Different apparent diffusion coefficient: water content correlations of gray and white matter during early ischemia. , 1998, Stroke.

[14]  M V Lareu,et al.  Genetic markers in alcoholic liver cirrhosis. , 1992, Human heredity.

[15]  K Minematsu,et al.  Diffusion‐weighted magnetic resonance imaging , 1992, Neurology.

[16]  I. Klatzo Pathophysiological aspects of brain edema , 2004, Acta Neuropathologica.

[17]  T Tolxdorff,et al.  Histogram‐based characterization of healthy and ischemic brain tissues using multiparametric MR imaging including apparent diffusion coefficient maps and relaxometry , 2000, Magnetic resonance in medicine.

[18]  M E Moseley,et al.  Comparison of diffusion‐ and T2‐weighted MRI for the early detection of cerebral ischemia and reperfusion in rats , 1991, Magnetic resonance in medicine.

[19]  R A Knight,et al.  Unsupervised segmentation of multiparameter MRI in experimental cerebral ischemia with comparison to T2, diffusion, and ADC MRI parameters and histopathological validation , 2000, Journal of magnetic resonance imaging : JMRI.

[20]  R N Bryan,et al.  Absolute quantitation of diffusion constants in human stroke. , 1997, Stroke.

[21]  C. Sotak,et al.  Reversal of acute apparent diffusion coefficient abnormalities and delayed neuronal death following transient focal cerebral ischemia in rats , 1999, Annals of neurology.

[22]  T. L. Davis,et al.  Human acute cerebral ischemia: detection of changes in water diffusion anisotropy by using MR imaging. , 1999, Radiology.

[23]  J. Garcìa,et al.  Cerebral white matter is highly vulnerable to ischemia. , 1996, Stroke.

[24]  P. Basser,et al.  Toward a quantitative assessment of diffusion anisotropy , 1996, Magnetic resonance in medicine.

[25]  F. Buonanno,et al.  Predicting Tissue Outcome in Acute Human Cerebral Ischemia Using Combined Diffusion- and Perfusion-Weighted MR Imaging , 2001, Stroke.

[26]  R. Ordidge,et al.  Magnetic Resonance Imaging Assessment of Evolving Focal Cerebral Ischemia Comparison With Histopathology in Rats , 1994, Stroke.

[27]  C. Sotak,et al.  MR imaging of anisotropic and restricted diffusion by simultaneous use of spin and stimulated echoes , 1992, Magnetic resonance in medicine.

[28]  J. Petruccelli,et al.  Determination of focal ischemic lesion volume in the rat brain using multispectral analysis , 1998, Journal of magnetic resonance imaging : JMRI.

[29]  Michael Chopp,et al.  MAGNETIC-RESONANCE-IMAGING ASSESSMENT OF EVOLVING FOCAL CEREBRAL-ISCHEMIA - COMPARISON WITH HISTOPATHOLOGY IN RATS (VOL 25, PG 1252, 1994) , 1994 .

[30]  A G Sorensen,et al.  Time course of diffusion imaging abnormalities in human stroke. , 1996, Stroke.

[31]  T. L. Davis,et al.  Hyperacute stroke: evaluation with combined multisection diffusion-weighted and hemodynamically weighted echo-planar MR imaging. , 1996, Radiology.

[32]  D. Graham,et al.  Topographical and quantitative assessment of white matter injury following a focal ischaemic lesion in the rat brain. , 1998, Brain research. Brain research protocols.

[33]  P. Basser,et al.  MR diffusion tensor spectroscopy and imaging. , 1994, Biophysical journal.

[34]  S. Warach,et al.  Pitfalls and potential of clinical diffusion-weighted MR imaging in acute stroke. , 1997, Stroke.

[35]  Michael Chopp,et al.  The temporal evolution of MRI tissue signatures after transient middle cerebral artery occlusion in rat , 1997, Journal of the Neurological Sciences.

[36]  R. Auer,et al.  Biological differences between ischemia, hypoglycemia, and epilepsy , 1988, Annals of neurology.

[37]  N. van Bruggen,et al.  Secondary Reduction in the Apparent Diffusion Coefficient of Water, Increase in Cerebral Blood Volume, and Delayed Neuronal Death after Middle Cerebral Artery Occlusion and Early Reperfusion in the Rat , 1999, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[38]  B. Siewert,et al.  Acute human stroke studied by whole brain echo planar diffusion‐weighted magnetic resonance imaging , 1995, Annals of neurology.

[39]  David H. Miller,et al.  Diffusion tensor imaging can detect and quantify corticospinal tract degeneration after stroke , 2000, Journal of neurology, neurosurgery, and psychiatry.

[40]  C. Sotak,et al.  Multispectral analysis of the temporal evolution of cerebral ischemia in the rat brain , 2000, Journal of magnetic resonance imaging : JMRI.

[41]  D M Doddrell,et al.  An evaluation of the time dependence of the anisotropy of the water diffusion tensor in acute human ischemia. , 1999, Magnetic resonance imaging.

[42]  C. Sotak,et al.  Investigation of Techniques to Quantify III Vivo Lesion Volume Based on Comparison of ADL Maps with Histology in Focal Cerebral Ischemia Studies of Rats , 2000 .

[43]  J D Fenstermacher,et al.  Transient and permanent resolution of ischemic lesions on diffusion-weighted imaging after brief periods of focal ischemia in rats : correlation with histopathology. , 2000, Stroke.

[44]  A study of the apparent diffusion coefficient of grey and white matter in human ischaemic stroke , 2000, Neuroreport.

[45]  P. Basser Inferring microstructural features and the physiological state of tissues from diffusion‐weighted images , 1995, NMR in biomedicine.

[46]  M Fisher,et al.  Characterizing the target of acute stroke therapy. , 1997, Stroke.

[47]  M E Moseley,et al.  Acute and chronic stroke: navigated spin-echo diffusion-weighted MR imaging. , 1996, Radiology.

[48]  J S Thornton,et al.  Anisotropic water diffusion in white and gray matter of the neonatal piglet brain before and after transient hypoxia-ischaemia. , 1997, Magnetic Resonance Imaging.

[49]  C. Sotak,et al.  Temporal evolution of ischemic injury evaluated with diffusion-, perfusion-, and T2-weighted MRI , 2000, Neurology.

[50]  P van Gelderen,et al.  Water diffusion and acute stroke , 1994, Magnetic resonance in medicine.

[51]  Temporal evolution of average apparent diffusion coefficient threshold to define ischemic abnormalities in a rat permanent occlusion model , 2000 .

[52]  R A Knight,et al.  Histopathological correlations of nuclear magnetic resonance imaging parameters in experimental cerebral ischemia. , 1993, Magnetic resonance imaging.

[53]  H Soltanian-Zadeh,et al.  A Model for Multiparametric MRI Tissue Characterization in Experimental Cerebral Ischemia With Histological Validation in Rat: Part 1 , 2001, Stroke.

[54]  S M Davis,et al.  Serial study of apparent diffusion coefficient and anisotropy in patients with acute stroke. , 1999, Stroke.

[55]  J. Kucharczyk,et al.  Early detection of regional cerebral ischemia in cats: Comparison of diffusion‐ and T2‐weighted MRI and spectroscopy , 1990, Magnetic resonance in medicine.

[56]  J. Kucharczyk,et al.  Anisotropy in diffusion‐weighted MRI , 1991, Magnetic resonance in medicine.

[57]  L H Schwamm,et al.  Time course of lesion development in patients with acute stroke: serial diffusion- and hemodynamic-weighted magnetic resonance imaging. , 1998, Stroke.

[58]  B. Dardzinski,et al.  Apparent diffusion coefficient mapping of experimental focal cerebral ischemia using diffusion‐weighted echo‐planar imaging , 1993, Magnetic resonance in medicine.

[59]  J D Fenstermacher,et al.  Secondary decline in apparent diffusion coefficient and neurological outcomes after a short period of focal brain ischemia in rats , 2000, Annals of neurology.

[60]  P. V. van Zijl,et al.  Diffusion Weighting by the Trace of the Diffusion Tensor within a Single Scan , 1995, Magnetic resonance in medicine.