Abstract #0104

Value of Deep Learning-Accelerated T1-w Dixon MRI for Upper Abdominal Imaging

Johannes Beat Fingerhut¹, Tobias Scheef¹, Hannes Engel¹, Alexander Rau¹, Lorenz Kolbe¹, Caroline Wilpert¹, Ralph Strecker², Marcel Dominik Nickel³, Fabian Bamberg¹, Jakob Weiss¹, and Niklas Verloh¹

¹Radiology, Medical Center – University of Freiburg, Freiburg, Germany, ²EMEA Scientific Partnerships, Siemens Healthineers AG, Forchheim, Germany, ³MR Application Predevelopment, Siemens Healthineers AG, Forchheim, Germany

Synopsis

Keywords: Hepatobiliary, AI/ML Image Reconstruction

Motivation: MRI is crucial for abdominal imaging due to its soft tissue contrast, but conventional sequences are limited by scan time and resolution. Deep-Learning-(DL)-based reconstruction may improve image quality and speed.

Goal(s): Does a DL-accelerated T1-weighted sequence (T1_DL) enhance image quality and acquisition time for liver, spleen, and pancreas imaging?

Approach: This single-center study of 98 patients undergoing post-contrast 3T MRI with standard and T1_DL sequences, with qualitative and independent quantitative image assessments.

Results: T1_DL shortened the examination time from 17s to 13s and enhanced image quality.

Impact: DL-accelerated MRI optimizes scan time and image quality, especially benefiting patients with breath-holding difficulties.

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