Share Email Print
cover

Proceedings Paper

Longitudinal connectome-based predictive modeling for REM sleep behavior disorder from structural brain connectivity
Author(s): Luca Giancardo; Timothy M. Ellmore; Jessika Suescun; Laura Ocasio; Arash Kamali; Roy Riascos-Castaneda; Mya C. Schiess
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Methods to identify neuroplasticity patterns in human brains are of the utmost importance in understanding and potentially treating neurodegenerative diseases. Parkinson disease (PD) research will greatly benefit and advance from the discovery of biomarkers to quantify brain changes in the early stages of the disease, a prodromal period when subjects show no obvious clinical symptoms. Diffusion tensor imaging (DTI) allows for an in-vivo estimation of the structural connectome inside the brain and may serve to quantify the degenerative process before the appearance of clinical symptoms. In this work, we introduce a novel strategy to compute longitudinal structural connectomes in the context of a whole-brain data-driven pipeline. In these initial tests, we show that our predictive models are able to distinguish controls from asymptomatic subjects at high risk of developing PD (REM sleep behavior disorder, RBD) with an area under the receiving operating characteristic curve of 0.90 (p<0.001) and a longitudinal dataset of 46 subjects part of the Parkinson’s Progression Markers Initiative. By analyzing the brain connections most relevant for the predictive ability of the best performing model, we find connections that are biologically relevant to the disease.

Paper Details

Date Published: 27 February 2018
PDF: 7 pages
Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 105750J (27 February 2018); doi: 10.1117/12.2293835
Show Author Affiliations
Luca Giancardo, The Univ. of Texas Health Science Ctr. at Houston (United States)
Timothy M. Ellmore, The City College of New York (United States)
Jessika Suescun, The Univ. of Texas Health Science Ctr. at Houston (United States)
Laura Ocasio, Memorial Hermann Texas Medical Ctr. (United States)
Arash Kamali, The Univ. of Texas Health Science Ctr. at Houston (United States)
Memorial Herman Hospital (United States)
Roy Riascos-Castaneda, The Univ. of Texas Health Science Ctr. at Houston (United States)
Memorial Herman Hospital (United States)
Mya C. Schiess, The Univ. of Texas Health Science Ctr. at Houston (United States)


Published in SPIE Proceedings Vol. 10575:
Medical Imaging 2018: Computer-Aided Diagnosis
Nicholas Petrick; Kensaku Mori, Editor(s)

© SPIE. Terms of Use
Back to Top