Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
560-06-008 ISMRM Abstract

Magnetic resonance T2-weighted images radiomics deep learning models to predict malignant pancreatic mucinous neoplasm

Primary: Body - Pancreas
Secondary: Acquisition & Reconstruction - AI methods
560-06-008 · AI Image Processing · Wednesday, 13 May, 4:55 PM–5:50 PM · Digital Posters Row A
Keywords: Magnetic resonance imaging Deep learning Pancreatic cystic neoplasms Intraductal papillary mucinous neoplasm Mucinous
Accepted
Xu Fang 1, Yun Bian1, Li Wang1, Chengwei Shao1, Jianping Lu1
1Radiology, Changhai Hospital, Naval Medical University, Shanghai, China
Presenting Author: Xu Fang

Synopsis

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References

1. Miller FH, Lopes Vendrami C, Recht HS, Wood CG, Mittal P, Keswani RN, Gabriel H, Borhani AA, Nikolaidis P, Hammond NA. Pancreatic Cystic Lesions and Malignancy: Assessment, Guidelines, and the Field Defect. Radiographics : a review publication of the Radiological Society of North America, Inc, 2022, 42(1):87-105.
2. Hozaka Y, Ohtsuka T, Nakamura M, Hijioka S, Unno M, Shimizu Y, Tanabe M, Nagakawa Y, Hatano E, Kawai M, Sano T, Koshita S, Katanuma A, Kita E, Hanada K, Nakai Y, Aoki T, Serikawa M, Okamoto K, Takeyama Y. Feasibility of Surveillance for Mucinous Cystic Neoplasm of the Pancreas: A Multi-Institutional Retrospective Study of 328 Patients by the Japanese Pancreatic Society. Pancreas, 2023, 52(5):e288-e292.
3. European Study Group on Cystic Tumours of the Pancreas. European evidence-based guidelines on pancreatic cystic neoplasms. Gut, 2018, 67(5):789-804.
4. Udare A, Agarwal M, Alabousi M, McInnes M, Rubino JG, Marcaccio M, van der Pol CB. Diagnostic Accuracy of MRI for Differentiation of Benign and Malignant Pancreatic Cystic Lesions Compared to CT and Endoscopic Ultrasound: Systematic Review and Meta-analysis. Journal of magnetic resonance imaging : JMRI, 2021, 54(4):1126-1137.
5. Assessment of malignant potential in intraductal papillary mucinous neoplasms of the pancreas using MR findings and texture analysis. European radiology, 2021, 31(5):3394-3404.
6. Zhang L, Diao B, Fan Z, Zhan H. Radiomics for differentiating pancreatic Mucinous Cystic Neoplasm from Serous Cystic Neoplasm: Systematic Review and Meta-Analysis. Academic radiology, 2024:S1076-6332(24)00892-00894.
7. Fang X, Zhang Q, Liu F, Li J, Wang T, Cao K, Zhang H, Li Q, Yu J, Zhou J, Zhu M, Li N, Jiang H, Shao C, Lu J, Wang L, Bian Y. T2-Weighted Image Radiomics Nomogram to Predict Pancreatic Serous and Mucinous Cystic Neoplasms. Academic radiology, 2023, 30(8):1562-1571.
8. Liang W, Tian W, Wang Y, Wang P, Wang Y, Zhang H, Ruan S, Shao J, Zhang X, Huang D, Ding Y, Bai X. Classification prediction of pancreatic cystic neoplasms based on radiomics deep learning models. BMC cancer, 2022, 22(1):1237.
9. Hozaka Y, Ohtsuka T, Nakamura M, Hijioka S, Unno M, Shimizu Y, Tanabe M, Nagakawa Y, Hatano E, Kawai M, Sano T, Koshita S, Katanuma A, Kita E, Hanada K, Nakai Y, Aoki T, Serikawa M, Okamoto K, Takeyama Y. Feasibility of Surveillance for Mucinous Cystic Neoplasm of the Pancreas: A Multi-Institutional Retrospective Study of 328 Patients by the Japanese Pancreatic Society. Pancreas, 2023, 52(5):e288-e292.
10. Zhang Y, Wu J, He J, Xu S. Preoperative differentiation of pancreatic cystic neoplasm subtypes on computed tomography radiomics. Quantitative imaging in medicine and surgery, 2023, 13(10):6395-6411.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/560-06-008