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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