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Abstract #1867

Optimally-truncated SVD and PCA applied to spatio-temporal hyperpolarized 13C cardiac data

Anna Bennett1, Hayden Shinn2, Avantika Sinha3, Roselle Abraham3, and Peder EZ Larson3
1Radiology, University of California, San Francisco, San Francisco, CA, United States, 2University of California, Berkeley, Berkeley, CA, United States, 3University of California, San Francisco, San Francisco, CA, United States

Synopsis

Keywords: Hyperpolarized MR (Non-Gas), Cardiovascular

Motivation: Current hyperpolarized data analysis techniques, first validated for interrogating cancer, are now being utilized for HP 13C cardiac MRI which is metabolically diverse.

Goal(s): Our goal was to explore the viability of applying advanced data analysis techniques to previously acquired HP 13C cardiac data to derive novel and potentially impactful information.

Approach: We applied optimally-truncated SVD based PCA to fasted and fed state [1-13C] pyruvate images and k-means clustering on resulting data.

Results: Low-rank (r=3) PCA results captured sufficient data to represent the pyruvate images and identify plausible separable components of interest. Clustering spatially resolving data sufficiently for potential further constrained analyses.

Impact: Hyperpolarized 13C cardiac MRI can be analyzed using PCA to derive novel and potentially impactful voxel-wise analysis. As use of HP 13C MRI expands to new applications, advanced analysis techniques can be utilized to better characterize complex alterations in metabolism.

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Keywords