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Congress: ECR25
Poster Number: C-13492
Type: Poster: EPOS Radiologist (scientific)
Authorblock: F. Pivetta, J. Kolck, D. Geisel; Berlin/DE
Disclosures:
Fabio Pivetta: Nothing to disclose
Johannes Kolck: Nothing to disclose
Dominik Geisel: Nothing to disclose
Keywords: Abdomen, Artificial Intelligence, Pancreas, MR, MR-Cholangiography, Comparative studies, Cysts, Neoplasia
Methods and materials

Patients undergoing MRI of the abdomen from May 1, 2023, to December 31, 2023 were prospectively enrolled. MRI images were independently assessed and rated on a four-point Likert scale by two experienced radiologists. Quantitative analysis was focused on determining the size of the smallest detectable lesion and assessing signal contrast. Qualitative analysis examined various aspects, including the depiction of communication with the main pancreatic duct (MPD), identification of complex features such as dilated MPD, mural nodules and septa, as well as the identification of peripancreatic lymph nodes. The comparison between HASTE and DL HASTE sequences was conducted using a paired Wilcoxon signed-rank test. Statistical significance was assumed at a level of p < 0.05.

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