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Abstract #1628

Multishot EPI and a Deep Learning-Based Noise Reduction Strategy for High Resolution Pancreatic DWI

Matthew J. Middione1, Alimohammad S. Moalem1, Cheng William Hong1, Arnaud Guidon2, Daniel B. Ennis1, and Ryan L. Brunsing1
1Department of Radiology, Stanford University, Stanford, CA, United States, 2GE Healthcare, Boston, MA, United States


DWI of the pancreas is challenging due to artifacts from physiologic motion, image distortion, and blurring, but has promising applications in pancreatic cancer detection. We conducted a pilot study of pancreatic DWI comparing single-shot and multi-shot EPI protocols as well as multi-shot EPI protocols with and without a new commercially available deep learning (DL) based denoising reconstruction method. Image quality was subjectively scored with key metrics. Multi-shot EPI reduced perceived distortion within the pancreatic bed, while the combination of multi-shot EPI and DL reconstruction subjectively reduced noise.

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