Predictive Modeling of Anatomy with Genetic and Clinical Data

• URL: http://arxiv.org/abs/2010.04757v1
• Date: Fri, 9 Oct 2020 18:30:15 GMT
• Title: Predictive Modeling of Anatomy with Genetic and Clinical Data
• Authors: Adrian V. Dalca, Ramesh Sridharan, Mert R. Sabuncu, Polina Golland
• Abstract summary: We present a semi-parametric generative model for predicting anatomy of a patient in subsequent scans following a single baseline image. We capture anatomical change through a combination of population-wide regression and a non-parametric model of the subject's health based on individual genetic and clinical indicators.
• Score: 18.062331119075928
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a semi-parametric generative model for predicting anatomy of a patient in subsequent scans following a single baseline image. Such predictive modeling promises to facilitate novel analyses in both voxel-level studies and longitudinal biomarker evaluation. We capture anatomical change through a combination of population-wide regression and a non-parametric model of the subject's health based on individual genetic and clinical indicators. In contrast to classical correlation and longitudinal analysis, we focus on predicting new observations from a single subject observation. We demonstrate prediction of follow-up anatomical scans in the ADNI cohort, and illustrate a novel analysis approach that compares a patient's scans to the predicted subject-specific healthy anatomical trajectory. The code is available at https://github.com/adalca/voxelorb.

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