Abstract #0248
Unsupervised Ischemia Detection at Rest with CP-BOLD Cardiac MRI: A Simulation Study Employing Independent Component Analysis
Rita Morisi 1 , Rohan Dharmakumar 2,3 , and Sotirios A. Tsaftaris 1,4
1
IMT Institute for Advanced Studies, Lucca,
LU, Italy,
2
Biomedical
Imaging Research Institute, Cedars-Sinai Medical Center,
Los Angeles, California, United States,
3
Medicine,
University of California, Los Angeles, California,
United States,
4
Electrical
Engineering and Computer Science, Northwestern
University, Evanston, Evanston, IL, United States
Cardiac-phase resolved Blood Oxygen-Level-Dependent
(CP-BOLD) MRI is a new approach capable of detecting an
ongoing ischemia without the need for provocative
stress. Current disease assessment relies on segmental
analysis and uses only a few cardiac phases of the cine
acquisition. It is expected that using all phases can
permit pixel-level characterization. This work explores
Independent Component Analysis (ICA) for pixel-level
ischemia characterization. Using simulated data we
demonstrate the potential utility of ICA for overcoming
existing limitations in discriminating ischemic
territories on the basis of CP-BOLD
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