Keywords: Data Processing, Quantitative Imaging
Motivation: This study aims to clarify disease-specific hippocampal atrophy patterns to enhance diagnostic accuracy in neuroinflammatory diseases.
Goal(s): The goal is to identify hippocampal atrophy patterns in MS, NMOSD, and MOGAD using normative modeling for better diagnosis and clinical insight.
Approach: We used normative modeling of hippocampal subfield volumes from MRI data to compare atrophy patterns in MS, NMOSD, and MOGAD against healthy controls.
Results: The study revealed distinct atrophy patterns in hippocampal subfields, especially in MS, with strong correlations to clinical measures, supporting centile scores as effective biomarkers for diagnosis and monitoring.
Impact: This study underscores the value of hippocampal subfield metrics as potential biomarkers for diagnosing and monitoring neuroinflammatory diseases. By revealing disease-specific atrophy patterns, it advances understanding of hippocampal vulnerability,guiding precision diagnostics and individualized treatment strategies for improved patient outcomes.
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