Change of diffusion anisotropy in patients with acute cerebral infarction using statistical parametric analysis

Morita, Naomi; Harada, Masafumi; Uno, Masaaki; Furutani, Kaori; Nishitani, Hiromu

doi:10.1007/s11604-005-1535-z

Cited by 9 publications

(6 citation statements)

References 12 publications

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“…39 However, there have been few studies of ischemic lesions themselves using FA values. Morita and colleagues reported that signiˆcant changes in diŠusion anisotropy were limited to the severely infarcted core of the white matter, 40 and those changes were observed in only 3 patients. Assaf and Pasternak reported apparently limited radiological beneˆts of diŠusion tensor imaging (DTI).…”

Section: Cerebral Ischemiamentioning

confidence: 99%

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Hori

Fukunaga

Masutani

et al. 2012

MRMS

105

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Recently, non-Gaussian diŠusion-weighted imaging (DWI) techniques, including qspace imaging (QSI) and diŠusional kurtosis imaging (DKI), have emerged as advanced methods to evaluate tissue microstructure in vivo using water diŠusion. QSI and DKI have shown promising results in clinical applications, such as in the evaluation of brain tumors (e.g., grading gliomas), degenerative diseases (e.g., speciˆc diagnosis of Parkinson disease), demyelinating diseases (e.g., assessment of normal-appearing tissue of multiple sclerosis), and cerebrovascular diseases (e.g., assessment of the microstructural environment of fresh infarctions). Representative metrics in clinical use are the full width at half maximum, also known as the mean displacement of the probability density function curve, which is derived from QSI, and diŠusional kurtosis, which is derived from DKI. These new metrics may provide information on tissue structure in addition to that provided by conventional Gaussian DWI investigations that use the apparent diŠusion coe‹cient and fractional anisotropy, recognized indices for evaluating disease and normal development in the brain and spine. In some clinical situations, sensitivity for detecting pathological conditions is higher using QSI and DKI than conventional DWI and diŠusion tensor imaging (DTI) because DWI and DTI calculations are based on the assumption that water molecules follow a Gaussian distribution, whereas hindrance of the distribution of water molecules by complex and restricted structures in actual neural tissues produces distributions that are far from Gaussian. We review the technical aspects and clinical applications of QSI and DKI, focusing on clinical use and in vivo studies and highlighting diŠerences from conventional diŠusional metrics.

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Section: Cerebral Ischemiamentioning

confidence: 99%

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Hori

Fukunaga

Masutani

et al. 2012

MRMS

105

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“…Although FA has consistently been shown to decrease after stroke as gray and white matter disintegrate (Buffon et al, 2005), some variability in FA has been observed acutely. Decreases (Morita et al, 2006;Zelaya et al, 1999) and increases (Bhagat et al, 2008;Ozsunar et al, 2004) have been observed, and though the exact mechanism of the increase remains unclear, it is possible that perpendicular diffusion is restricted hyperacutely. Recovery of FA values 3 years after stroke has been observed in the internal capsule of patients with upper limb impairments subjected to 30 days of motor training (Stinear et al, 2007).…”

Section: Diffusion Tensor Imagingmentioning

confidence: 99%

Use of Magnetic Resonance Imaging to Predict Outcome after Stroke: A Review of Experimental and Clinical Evidence

Farr

Wegener

2010

J Cereb Blood Flow Metab

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Despite promising results in preclinical stroke research, translation of experimental data into clinical therapy has been difficult. One reason is the heterogeneity of the disease with outcomes ranging from complete recovery to continued decline. A successful treatment in one situation may be ineffective, or even harmful, in another. To overcome this, treatment must be tailored according to the individual based on identification of the risk of damage and estimation of potential recovery. Neuroimaging, particularly magnetic resonance imaging (MRI), could be the tool for a rapid comprehensive assessment in acute stroke with the potential to guide treatment decisions for a better clinical outcome. This review describes current MRI techniques used to characterize stroke in a preclinical research setting, as well as in the clinic. Furthermore, we will discuss current developments and the future potential of neuroimaging for stroke outcome prediction.

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“…Among the various DT parameters, FA has been examined extensively in both human stroke studies and animal models as a potential imaging biomarker ( 8 9 11 17 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 ). However, the evolution of FA during hyperacute stroke has not yielded consistent results, with studies reporting both increases and decreases in FA during the initial hours, as well as findings showing no significant changes at all ( 16 25 26 27 28 29 30 31 32 33 ). Nevertheless, our results are in agreement with those of a recent study by Kuo et al ( 11 ) in that rFA was paradoxically elevated in IC during the first hour post-pMCAO, regardless of its cortical or subcortical involvement.…”

Section: Discussionmentioning

confidence: 99%

Diffusion Tensor-Derived Properties of Benign Oligemia, True “at Risk” Penumbra, and Infarct Core during the First Three Hours of Stroke Onset: A Rat Model

et al. 2018

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ObjectiveThe aim of this study was to investigate diffusion tensor (DT) imaging-derived properties of benign oligemia, true “at risk” penumbra (TP), and the infarct core (IC) during the first 3 hours of stroke onset.Materials and MethodsThe study was approved by the local animal care and use committee. DT imaging data were obtained from 14 rats after permanent middle cerebral artery occlusion (pMCAO) using a 7T magnetic resonance scanner (Bruker) in room air. Relative cerebral blood flow and apparent diffusion coefficient (ADC) maps were generated to define oligemia, TP, IC, and normal tissue (NT) every 30 minutes up to 3 hours. Relative fractional anisotropy (rFA), pure anisotropy (rq), diffusion magnitude (rL), ADC (rADC), axial diffusivity (rAD), and radial diffusivity (rRD) values were derived by comparison with the contralateral normal brain.ResultsThe mean volume of oligemia was 24.7 ± 14.1 mm3, that of TP was 81.3 ± 62.6 mm3, and that of IC was 123.0 ± 85.2 mm3 at 30 minutes after pMCAO. rFA showed an initial paradoxical 10% increase in IC and TP, and declined afterward. The rq, rL, rADC, rAD, and rRD showed an initial discrepant decrease in IC (from −24% to −36%) as compared with TP (from −7% to −13%). Significant differences (p < 0.05) in metrics, except rFA, were found between tissue subtypes in the first 2.5 hours. The rq demonstrated the best overall performance in discriminating TP from IC (accuracy = 92.6%, area under curve = 0.93) and the optimal cutoff value was −33.90%. The metric values for oligemia and NT remained similar at all time points.ConclusionBenign oligemia is small and remains microstructurally normal under pMCAO. TP and IC show a distinct evolution of DT-derived properties within the first 3 hours of stroke onset, and are thus potentially useful in predicting the fate of ischemic brain.

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Change of diffusion anisotropy in patients with acute cerebral infarction using statistical parametric analysis

Abstract: We believe statistical comparison of FA maps to be useful for detecting different regions of diffusion anisotropy.

Cited by 9 publications

References 12 publications

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Use of Magnetic Resonance Imaging to Predict Outcome after Stroke: A Review of Experimental and Clinical Evidence

Diffusion Tensor-Derived Properties of Benign Oligemia, True “at Risk” Penumbra, and Infarct Core during the First Three Hours of Stroke Onset: A Rat Model

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