Impact of White Matter Damage After Stroke

Lindenberg, Robert; Seitz, Rüdiger J.

doi:10.5772/23204

Cited by 4 publications

(3 citation statements)

References 76 publications

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“…However, white matter injury is observed after ischemic insult and the discrepancy between the infarct volume and functional outcome in stroke patients is suggested to be partly due to the contribution of white matter degeneration after stroke onset [15,16]. Recent studies suggest that structures in white matter play a critical role in stroke recovery, especially in function recovery by brain remodeling [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of neuregulin-1's neuroprotection against ischemic injury in rats using diffusion tensor imaging

Wang

Paudyal

et al. 2018

Magnetic Resonance Imaging

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Stroke is a devastating neurovascular disorder that results in damage to neurons and white matter tracts. It has been previously demonstrated that neuregulin-1 (NRG-1) protects neurons from ischemic injury following stroke. Here, diffusion tensor imaging (DTI) was utilized to characterize the effects of NRG-1 treatment on cererbral infarction and integrity of white matter after ischemic insult using a permanent middle celebral artery occlusion (pMCAo) rat model. In the present study, sixteen Sprague-Dawley rats underwent pMCAo surgery and received either a single intra-arterial bolus (20 μg/kg) dose of NRG-1 or saline immediately prior to pMCAo. MRI including T2-weighted imaging and DTI was performed in the first 3 h post stroke, and repeated 48 h later. It is found that the stroke infarction was significantly reduced in the NRG-1 treated group. Also, NRG-1 prevented the reduction of fractional anisotropy (FA) in white matter tracts of fornix and corpus callosum (CC), indicating its protection of CC and fornix white matter bundles from ischemia insult. As a conclusion, the present DTI results demonstrate that NRG-1 has significantly neuroprotective effects in both cerebral cortex and white matter including corpus callosum and fornix during acute stroke. In particular, NRG-1 is more effective on stroke lesion with mild ischemia. As CC and fornix white matter bundles play critical roles in transcallosal connectivity and hippocampal projections respectively in the central nervous system, the findings could provide complementary information for better understanding the biological mechanism of NRG-1's neuroprotection in ischemic tissues and neurobehavioral effects.

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Section: Introductionmentioning

confidence: 99%

Evaluation of neuregulin-1's neuroprotection against ischemic injury in rats using diffusion tensor imaging

Wang

Paudyal

et al. 2018

Magnetic Resonance Imaging

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“…In fact silent brain infarcts and white matter (WM) lesions are common in healthy elderly people (Vermeer et al, 2003;Norrving, 2008) with an estimated 7%-28% of the patients with known stroke history and aged over 65 years having evidence of silent lesions (Vernooij et al, 2007;Bernick et al, 2001). Further, white matter changes may be observed in late stages post-stroke (Lindenberg and Seitz, 2012). Therefore, patients with clinically…”

Section: Introductionmentioning

confidence: 99%

Lesion segmentation from multimodal MRI using random forest following ischemic stroke

et al. 2014

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Understanding structure-function relationships in the brain after stroke is reliant not only on the accurate anatomical delineation of the focal ischemic lesion, but also on previous infarcts, remote changes and the presence of white matter hyperintensities. The robust definition of primary stroke boundaries and secondary brain lesions will have significant impact on investigation of brain-behavior relationships and lesion volume correlations with clinical measures after stroke. Here we present an automated approach to identify chronic ischemic infarcts in addition to other white matter pathologies, that may be used to aid the development of post-stroke management strategies. Our approach uses Bayesian-Markov Random Field (MRF) classification to segment probable lesion volumes present on fluid attenuated inversion recovery (FLAIR) MRI. Thereafter, a random forest classification of the information from multimodal (T1-weighted, T2-weighted, FLAIR, and apparent diffusion coefficient (ADC)) MRI images and other context-aware features (within the probable lesion areas) was used to extract areas with high likelihood of being classified as lesions. The final segmentation of the lesion was obtained by thresholding the random forest probabilistic maps. The accuracy of the automated lesion delineation method was assessed in a total of 36 patients (24 male, 12 female, mean age: 64.57±14.23yrs) at 3months after stroke onset and compared with manually segmented lesion volumes by an expert. Accuracy assessment of the automated lesion identification method was performed using the commonly used evaluation metrics. The mean sensitivity of segmentation was measured to be 0.53±0.13 with a mean positive predictive value of 0.75±0.18. The mean lesion volume difference was observed to be 32.32%±21.643% with a high Pearson's correlation of r=0.76 (p<0.0001). The lesion overlap accuracy was measured in terms of Dice similarity coefficient with a mean of 0.60±0.12, while the contour accuracy was observed with a mean surface distance of 3.06mm±3.17mm. The results signify that our method was successful in identifying most of the lesion areas in FLAIR with a low false positive rate.

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“…Not only this is evident for motor and sensory deficits, where the lack of recovery in patients with extensive subcortical damage is a consistent finding (Heiss & Kidwell, 2014;Lindenberg & Seitz, 2012), but also cognitive performance requires participation of white matter fiber tracts (Duffau, 2014;this Special Section). Naming famous people is definitely impaired when a white matter tract is removed (Papagno, Miracapillo, et al, 2011).…”

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confidence: 91%