Revealing the Timeline of Structural MRI Changes in Premanifest to Manifest Huntington Disease. (11th October 2021)

• Record Type: Journal Article
• Authors: Wijeratne, Peter A.; Garbarino, Sara; Gregory, Sarah; Johnson, Eileanoir B.; Scahill, Rachael I.; Paulsen, Jane S.; Tabrizi, Sarah J.; Lorenzi, Marco; Alexander, Daniel C.
• Is Part Of: Neurology. Volume 7:Number 5(2021)
• Publication Date: 2021-10-11
• Subjects: Neurogenetics -- Periodicals; 616.80442
• DOI: 10.1212/NXG.0000000000000617
• Languages: English
• ISSNs: 2376-7839

Abstract

Abstract : Background and Objectives: Longitudinal measurements of brain atrophy using structural MRI (sMRI) can provide powerful markers for tracking disease progression in neurodegenerative diseases. In this study, we use a disease progression model to learn individual-level disease times and hence reveal a new timeline of sMRI changes in Huntington disease (HD). Methods: We use data from the 2 largest cohort imaging studies in HD—284 participants from TRACK-HD (100 control, 104 premanifest, and 80 manifest) and 159 participants from PREDICT-HD (36 control and 128 premanifest)—to train and test the model. We longitudinally register T1-weighted sMRI scans from 3 consecutive time points to reduce intraindividual variability and calculate regional brain volumes using an automated segmentation tool with rigorous manual quality control. Results: Our model reveals, for the first time, the relative magnitude and timescale of subcortical and cortical atrophy changes in HD. We find that the largest (∼20% average change in magnitude) and earliest (∼2 years before average abnormality) changes occur in the subcortex (pallidum, putamen, and caudate), followed by a cascade of changes across other subcortical and cortical regions over a period of ∼11 years. We also show that sMRI, when combined with our disease progression model, provides improved prediction of onset over the current best method (root mean square error = 4.5 years and maximum error = 7.9 years vs root mean square error = 6.6 years and maximum error = 18.2 years). Discussion: Our findings support the use of disease progression modeling to reveal new information from sMRI, which can potentially inform imaging marker selection for clinical trials.