Anatomy-Guided Surface Diffusion Model for Alzheimer’s Disease Normative Modeling

Jianwei Zhang, Yonggang Shi

Keywords: Diffusion Model, Alzheimer's Disease, Cortical Surface

TL;DR: A novel Surface diffusion model conditioned on anatomy of the cortical surface structure for Alzheimer's Disease normative modeling.

Abstract:

Normative modeling has emerged as a pivotal approach for
characterizing heterogeneity and individual variance in neurodegenera-
tive diseases, notably Alzheimer’s disease(AD). One of the challenges of
cortical normative modeling is the anatomical structure mismatch due
to folding pattern variability. Traditionally, registration is applied to ad-
dress this issue and recently many studies have utilized deep generative
models to generate anatomically aligned samples for analyzing disease
progression; however, these models are predominantly applied to volume-
based data, which often falls short in capturing intricate morphological
changes on the brain cortex. As an alternative, surface-based analysis
has been proven to be more sensitive in disease modeling such as AD,
yet, like volume-based data, it also suffers from the mismatch problem.
To address these limitations, we propose a novel generative normative
modeling framework by transferring the conditional diffusion generative
model to the spherical domain. Furthermore, the proposed model gener-
ates normal feature map distributions by explicitly conditioning on indi-
vidual anatomical segmentation to ensure better geometrical alignment
which helps to reduce variance between subjects in normative analyses.
We find that our model can generate samples that are better anatomi-
cally aligned than registered reference data and through ablation study
and normative assessment experiments, the samples are able to better
measure individual differences from the normal distribution and increase
sensitivity in differentiating cognitively normal (CN), mild cognitive im-
pairment (MCI), and Alzheimer’s disease (AD) patients.

Primary Subject Area: Image Synthesis

Secondary Subject Area: Detection and Diagnosis

Paper Type: Methodological Development

Registration Requirement: Yes

Visa & Travel: Yes

Submission Number: 83