ArticleMagnetic resonance in medicine2026
A Voxel-Wise T2 Distribution Framework for Lesion Severity Stratification and Treatment-Response Assessment in Stroke: Insights Into Suberoylanilide Hydroxamic Acid-Induced Neuroprotection.
Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeTo evaluate lesion severity distribution in ischaemic brain lesions in spontaneously hypertensive rats (SHR) subjected to 90-min transient middle cerebral artery occlusion (tMCAO), and to determine whether epigenetically based neuroprotection modifies lesion severity profiles using a voxel-wise T2 distribution framework. THEORY AND
methodsStroke treatments are commonly evaluated by quantifying infarct size using histology or MRI, approaches that average across lesions and may obscure heterogeneous tissue responses. SHR underwent 90-min intraluminal MCAO and received suberoylanilide hydroxamic acid (SAHA) 4 h after reperfusion. Quantitative T2 maps were acquired at Days 1 and 8 postocclusion. Voxel-wise histogram analysis defined severity thresholds (T2 < 70 ms mild; 70-90 ms moderate; > 90 ms severe). Region-stratified RT-qPCR assessing neuronal, inflammatory, and apoptotic markers provided complementary biological context for interpreting region- and severity-resolved MRI patterns.
resultsSeverity-bin stratification of voxel-wise T2 values quantified how lesion composition redistributed from severe toward moderate/mild classes across time and regions (cortex vs. subcortex) in association with SAHA treatment. Cortical molecular markers corroborated imaging-defined tissue preservation but did not resolve subcortical differences detected by voxel-wise MRI. Untreated animals exhibited partial spontaneous attenuation of extreme subcortical T2 abnormalities. Histogram descriptors correlated with behavioral outcomes.
conclusionVoxel-wise T2 distribution analysis provides a complementary, severity-stratified description of lesion composition and its evolution over time, alongside conventional endpoints such as infarct volume and mean/median T2. The approach is readily applicable in preclinical MRI and is potentially translatable, warranting further validation across broader imaging settings.
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