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Abstract #3015

Optimizing QSM-T1w Neuroimaging Templates: Exploring the Impact of the Number of Subjects on Template Quality

Fahad Salman1, Niels Bergsland1, Michael G. Dwyer1,2, Bianca Weinstock-Guttman3, Robert Zivadinov1,2, and Ferdinand Schweser1,2
1Buffalo Neuroimaging Analysis Center, Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States, 2Center for Biomedical Imaging, Clinical and Translational Science Institute, University at Buffalo, The State University of New York, Buffalo, NY, United States, 3Jacobs Multiple Sclerosis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States

Synopsis

Keywords: Segmentation, Susceptibility, QSM template, QSM-T1w, Segmentation, Quantitative, QSM, Normalization

Motivation: Previously, automated delineation of deep gray matter (DGM) regions predominantly relied on T1-weighted (T1w) brain images with limited iron-rich DGM contrast. Multi-contrast atlases incorporating quantitative susceptibility mapping (QSM) have been introduced to overcome this issue and are increasingly being used in multi-atlas segmentation methods.

Goal(s): To determine a generalizable minimum number of subjects to be used for generating high quality QSM-T1w templates.

Approach: We quantitatively investigated the effect of increasing (factor=2) the number of subjects (N=10-160) used for template construction on resulting template quality.

Results: In highly heterogeneous cohorts, more than 40 subjects result in a diminishing return for QSM-T1w template generation.

Impact: Using a small number of subjects for template generation ensures economic use of resources and facilitates the creation of more sub-group templates from the same cohort, to be used in advanced multi-atlas techniques.

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