Feasibility of deep learning-accelerated HASTE-FS for pancreatic cystic lesion surveillance: comparison with conventional HASTE and MRCP

深度学习加速的HASTE-FS在胰腺囊性病变监测中的可行性:与传统HASTE和MRCP的比较

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Abstract

PURPOSE: Pancreatic cystic lesions (PCL) commonly undergo surveillance using MRI with MR cholangiopancreatography (MRCP). Our objective is to compare the performance of a single-shot fat-saturated T2-weighted technique with deep-learning reconstruction (DL HASTE-FS) to a conventional T2-weighted Half fourier Single-shot Turbo spin-Echo (HASTE) sequence and to MRCP for the purpose of PCL detection, characterization, and surveillance. METHODS: In this retrospective study, 91 consecutive patients underwent 3T abdominal MRI with MRCP protocol including DL HASTE-FS and conventional HASTE between 8/2/2023 and 10/3/2023. Three abdominal radiologists rated overall and lesion-specific image quality on a 5-point Likert scale, including pancreatic margin and duct sharpness, and PCL conspicuity. A subset of 70 preselected index PCLs were evaluated for cyst features, confidence of diagnosing side-branch IPMN, and suitability of DL HASTE-FS in replacing MRCP for PCL surveillance. RESULTS: DL HASTE-FS received higher scores for pancreatic duct border sharpness (4.1 vs. 3.9; p = .004), pancreatic duct visibility compared to MRCP (2.0 vs. 1.9; p = .04), cyst conspicuity (4.4 vs. 3.9; p < .001), and sharpness of cyst wall and internal septations (4.3 vs. 3.7; p < .001) compared to conventional HASTE. In contrast, conventional HASTE received higher scores for pancreatic margin sharpness (4.2 vs. 3.8; p < .001) and peripancreatic vessel clarity (4.2 vs. 3.4; p < .001). For the 70 preselected index PCLs, readers visualized more PCLs and had higher confidence in diagnosing SB-IPMN on DL HASTE-FS than on conventional HASTE (3.6 vs. 3.4; p < .001). Finally, DL HASTE-FS was deemed a suitable replacement to MRCP for more cases than conventional HASTE (83% vs. 48%; p < .001). CONCLUSION: DL HASTE-FS outperforms conventional HASTE for PCL detection and characterization, and is a suitable alternative to 3D MRCP in the context of PCL surveillance, potentially reducing exam time and cost.

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