Longitudinal Boundary Sharpness Coefficient Slopes Predict Time to Alzheimer's Disease Conversion in Mild Cognitive Impairment: A Survival Analysis Using the ADNI Cohort

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Main Author: Cherukuri
Format: Recurso digital
Language:English
Published: Zenodo 2026
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_version_ 1866901201172299776
author Cherukuri
author_facet Cherukuri
contents <p>This study predicts when people with mild cognitive impairment (MCI) will convert to Alzheimer's disease using a novel MRI-based biomarker. Instead of looking at brain scans at a single timepoint, the analysis looks at how the gray-white matter interface degrades over time. The Boundary Sharpness Coefficient (BSC) measures how sharp this boundary looks on structural MRI. By computing slopes (annual rates of change) across 4+ longitudinal scans per subject, the study captures disease progression dynamics that static images disregard.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_18829786
institution Zenodo
language eng
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Longitudinal Boundary Sharpness Coefficient Slopes Predict Time to Alzheimer's Disease Conversion in Mild Cognitive Impairment: A Survival Analysis Using the ADNI Cohort
Cherukuri
Neurons
Neurons/pathology
Neurons/classification
<p>This study predicts when people with mild cognitive impairment (MCI) will convert to Alzheimer's disease using a novel MRI-based biomarker. Instead of looking at brain scans at a single timepoint, the analysis looks at how the gray-white matter interface degrades over time. The Boundary Sharpness Coefficient (BSC) measures how sharp this boundary looks on structural MRI. By computing slopes (annual rates of change) across 4+ longitudinal scans per subject, the study captures disease progression dynamics that static images disregard.</p>
title Longitudinal Boundary Sharpness Coefficient Slopes Predict Time to Alzheimer's Disease Conversion in Mild Cognitive Impairment: A Survival Analysis Using the ADNI Cohort
topic Neurons
Neurons/pathology
Neurons/classification
url https://doi.org/10.5281/zenodo.18829786