Abstract #0363

Accelerated Joint T1-T2 Fitting in Cardiac Magnetic Resonance Multitasking Using Extended Phase Graph Dictionaries

Katerina Eyre¹, Anthony G. Christodoulou², Xianglun Mao³, Tianle Cao⁴, Zihao Chen⁴, Pauline Calarnou⁵, Christopher W. Roy⁵, Mitchel Benovoy⁶, Matthias G. Friedrich^6,7, Michael Chetrit⁷, and Jérôme Yerly^5,8

¹Radiology, McGill University Health Centre, Montreal, QC, Canada, ²School of Medicine at UCLA, Los Angeles, CA, United States, ³GE Healthcare, San Francisco, CA, United States, ⁴University of California, Los Angeles, Los Angeles, CA, United States, ⁵Lausanne University Hospital, Lausanne, Switzerland, ⁶Area19 Medical, Montreal, QC, Canada, ⁷McGill University Health Centre, Montreal, QC, Canada, ⁸Center for Biomedical Imaging, Lausanne, Switzerland

Synopsis

Keywords: In Silico, Tissue Characterization

Motivation: Cardiac magnetic resonance 3D Multitasking can streamline clinical workflows through simultaneous T1-T2 fitting across the ventricle, but prolonged fitting times hinder widespread adoption of the technology.

Goal(s): We aimed to determine if an extended phase graph (EPG) dictionary matching approach could reduce T1-T2 fitting times while maintaining measurement accuracy.

Approach: We developed a numerical simulation to compare the original Bloch equation-based fitting model with the EPG dictionary matching approach against ground truth T1-T2 values. We subsequently compared the two fitting methods in-vivo.

Results: The EPG dictionary matching significantly reduced T1-T2 fitting times without compromising the accuracy or precision of T1-T2 measurements.

Impact: The significant reduction of T1-T2 fitting times through EPG dictionary matching improves the post-processing workflow of 3D Multitasking, potentially bringing the technology closer to clinical workflow integration.

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