An image-based model of brain volume biomarker changes in Huntington's disease.

ABSTRACT:

Objective

Determining the sequence in which Huntington's disease biomarkers become abnormal can provide important insights into the disease progression and a quantitative tool for patient stratification. Here, we construct and present a uniquely fine-grained model of temporal progression of Huntington's disease from premanifest through to manifest stages.

Methods

We employ a probabilistic event-based model to determine the sequence of appearance of atrophy in brain volumes, learned from structural MRI in the Track-HD study, as well as to estimate the uncertainty in the ordering. We use longitudinal and phenotypic data to demonstrate the utility of the patient staging system that the resulting model provides.

Results

The model recovers the following order of detectable

SUBMITTER: Wijeratne PA 

PROVIDER: S-EPMC5945962 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature