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Abstract #0222

Multi-Parametric Subtype and Stage Inference improves spatiotemporal subtyping of Alzheimer's Disease

Yongquan Huang1, Haoan Xu1, Yiwei Chen1, Sihui Li1, Yao Shen1, Yiqi Shen1, Zuozhen Cao1, Zhiyong Zhao2, Mingyang Li1, and Dan Wu1
1Zhejiang University, Hangzhou Shi, China, 2Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China

Synopsis

Keywords: Diagnosis/Prediction, Alzheimer's Disease

Motivation: Subtype and Stage Inference (SuStaIn) model is widely used to reveal spatiotemporal heterogeneity in cross-sectional datasets. But SuStaIn does not account for correlations between biomarkers.

Goal(s): We attempt to modify SuStaIn model to utilize highly correlated biomarkers in the analysis of neurodegenerative diseases’ heterogeneity.

Approach: We propose Multi-Parametric SuStaIn (MP-SuStaIn), an alternative SuStaIn model that incorporates biomarker correlations into spatiotemporal analysis. We apply MP-SuStaIn to analyze Alzheimer's disease (AD) based on multiple morphological features using the ADNI dataset.

Results: MP-SuStaIn identified three subtypes of AD, each with distinct progression patterns, morphological characteristics, clinical symptoms, and prognostic results.

Impact: We identified three subtypes of Alzheimer's disease with distinct progression patterns and morphological characteristics by using multiple brain morphologic biomarkers and a modified Subtype and Stage Inference model, which can analyze the spatiotemporal heterogeneity of neurodegenerative diseases.

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Keywords