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Abstract #4370

Whole Brain Source Separation for Neurodegeneration

Alexandra Grace Roberts1, Mert Sisman1, Alexey Dimov2, Thanh Nguyen2, Susan Gauthier3, Pascal Spincemaille2, and Yi Wang2,4
1Electrical and Computer Engineering, Cornell University, New York, NY, United States, 2Radiology, Weill Cornell Medicine, New York, NY, United States, 3Neurology, Weill Cornell Medicine, New York, NY, United States, 4Biomedical Engineering, Cornell University, New York, NY, United States

Synopsis

Keywords: Other Neurodegeneration, Artifacts

Motivation: Cortex and spinal cord tissue are of interest in a variety of neurodegenerative diseases including Multiple Sclerosis (MS), Alzheimer’s Disease (AD), and Amyotrophic Lateral Sclerosis (ALS). These regions are low in signal to noise ratio (SNR) and generate artifacts on quantitative susceptibility maps (QSMs).

Goal(s): To demonstrate the maximum Spherical Mean Value (mSMV) algorithm as a tissue preserving initialization for susceptibility source separation.

Approach: Whole brain source separation enabled by mSMV is applied to patients with MS, AD, and ALS.

Results: The mSMV algorithm reconstructs the whole brain volume in source separations and generates susceptibility maps in agreement with existing methods.

Impact: Whole brain source separation using the maximum Spherical Mean Value (mSMV) algorithm successfully preserves full tissue volume and produces susceptibility map in strong agreement with existing methods.

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Keywords