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Abstract #1111

MR Multitasking-driven Abdominal Integrated Imaging (MT-AI2)

Junzhou Chen1,2, Qingle Kong1, Yang Chen1, Diane Chushin Ling3, Eric Chang3, Anthony Christodoulou4, Debiao Li5, Wensha Yang6, and Zhaoyang Fan1,3
1Radiology, University of Southern California, Los Angeles, CA, United States, 2University of California, Los Angeles, Los Angeles, CA, United States, 3Radiation Oncology, University of Southern California, Los Angeles, CA, United States, 4Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, United States, 5Biological Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 6Radiation Oncology, University of California, San Francisco, San Francisco, CA, United States

Synopsis

Keywords: Quantitative Imaging, Radiotherapy, Abdominal imaging, T1 mapping, abdominal T2 mapping, free-breathing, motion-resolved.

Motivation: The inefficiencies of traditional Abdominal MR protocols highlight the need for advanced imaging techniques that can produce high-quality images and quantitative maps more effectively.

Goal(s): To develop an MR technique called MT-AI2 that integrates MR Multitasking to produce motion-resolved, multi-contrast 3D images and multi-parametric quantitative maps from a single scan.

Approach: MT-AI2 employs a four-stage FLASH readout sequence combined with stack-of-stars trajectory to enhance robustness to motion.

Results: Phantom and volunteer studies indicate that quantitative maps generated by MT-AI2 correlate highly with reference methods. The method significantly reduces reconstruction and map fitting times, demonstrating potential for practical clinical use.

Impact: The MT-AI2 technique has the potential to transform clinical abdominal MRI practices by enabling faster, more efficient imaging. This advancement opens new avenues for MR-guided radiation therapy planning and other MR applications in the abdomin.

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Abstract

Keywords