Tejal Somvanshi
UPenn researchers mapped 135 human brain specimens using 7-Tesla MRI scans - what their ultra-high resolution images revealed about dementia could alter medical understanding.
Photo Source- Pulkit Khandelwal
How did scientists analyze brain tissue at 160 microns precision, capturing details invisible to standard imaging?
University of Pennsylvania's 7-Tesla High-Res MRI Study
Three distinct MRI sequences were utilized: T2-weighted at 300 microns, KISS at 500 microns, and T2-star F at 160 microns - each revealing unique neural patterns.
Specimens from patients with Lewy body dementia, frontotemporal degeneration, and cerebrovascular disease contributed to a comprehensive dataset, with 82 specimens specifically focused on Alzheimer's progression.
Deep learning algorithms segmented cortical regions while identifying four key subcortical structures: caudate, putamen, globus pallidus, and thalamus.
Which brain regions showed the strongest correlations between cortical thickness and pathological indicators?
The entorhinal cortex, parahippocampal, and medial orbital frontal areas displayed notable tissue changes linked to dementia markers.
Scientists developed an automated surface-based pipeline adapting the Desikan-Killiany-Tourville brain atlas for ultra-high resolution analysis.
The entire research dataset and analysis tools are now publicly accessible via GitHub - what patterns will future researchers detect?
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