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Abstract #2395

High Resolution Prostate T2-weighted MRI with Deep Learning and without an Endorectal Coil

Xinzeng Wang1, Jong Bum Son2, Priya Bhosale3, Aliya Qayyum3, Juan Jose Ibarra-Rovira3, Ken-Ping Hwang2, Jason Stafford2, Mark David Pagel4, Marc Lebel5, Ersin Bayram1, Jingfei Ma2, and Janio Szklaruk3
1Global MR Applications & Workflow, GE Healthcare, Houston, TX, United States, 2Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, United States, 3Department of Abdominal Imaging, MD Anderson Cancer Center, Houston, TX, United States, 4Department of Cancer Systems Imaging, MD Anderson Cancer Center, Houston, TX, United States, 5Global MR Applications & Workflow, GE Healthcare, Calgary, AB, Canada

Endorectal coil (ERC) offers high SNR that is needed for high-resolution prostate MRI, which is essential for accurate visualization of prostate and detection of prostate cancer. Unfortunately, use of an ERC is cumbersome, costly, and discomforting or even intolerable to some patients. Further, ERC often has exacerbated motion artifacts due to its proximity to the regions of interests. In this work, we applied a novel deep learning-based MR reconstruction method to clinical prostate T2-weighted imaging without an ERC (non-ERC). DL Recon improved non-ERC image SNR, reduced artifacts, and improved overall image quality compared to conventional reconstruction with/without endorectal coil.

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