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Abstract #2447

Deep learning accelerated ultrafast MR imaging of the pelvis to screen for pelvic metastases in patients with suspicion for prostate cancer.

Andrea Lynn Nedelcu1, Caroline Wilpert1, Benedict Oerther1, Dominik Nickel2, Ralph Strecker3, Fabian Bamberg1, Jakob Benedikt Weiss1, Maximilian Frederik Russe1, and Hannes Engel1
1Department of Radiology, University Hospital of Freiburg, Freiburg im Breisgau, Germany, 2MR Application Predevelopment, Siemens Healthineers AG, Forchheim, Germany, 3EMEA Scientific Partnerships, Siemens Healthineers AG, Forchheim, Germany

Synopsis

Keywords: Prostate, Urogenital, Prostate, Cancer screening, Arificial intelligence, Deep Learning, image reconstruction

Motivation: Deep learning (DL) accelerated image reconstruction in prostate MRI can improve the problem of limited scan capacity, while maintaining image quality.

Goal(s): To demonstrate the feasibility of a research post-contrast T1w VIBE Dixon sequence with DL acceleration.

Approach: Radiologists compared 2 DL accelerated sequences (15 and 45 seconds) to the standard sequence (2:23 minutes) for image quality and diagnostic confidence in detecting pelvic metastases. Additionally, signal homogeneity was measured in the piriformis muscle.


Results: The faster DL sequence proves equal or better in all aspects. The slower DL sequence demonstrates more artifacts, slightly lower signal homogeneity, but improved sharpness and equal diagnostic confidence.

Impact: Deep learning accelerated T1w VIBE Dixon imaging with drastically shortened acquisition time of 15 seconds demonstrates equal or superior image quality and equal diagnostic confidence for pelvic lymph nodes and bone lesions in patients with suspicion for prostate cancer.

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