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Cited by in CrossRef
For: Polk SL, Choi JW, McGettigan MJ, Rose T, Ahmed A, Kim J, Jiang K, Balagurunathan Y, Qi J, Farah PT, Rathi A, Permuth JB, Jeong D. Multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy. World J Gastroenterol 2020; 26(24): 3458-3471 [PMID: 32655269 DOI: 10.3748/wjg.v26.i24.3458]
URL: https://www.wjgnet.com/1007-9327/full/v26/i24/3458.htm
Number Citing Articles
1
Federica Flammia, Tommaso Innocenti, Antonio Galluzzo, Ginevra Danti, Giuditta Chiti, Giulia Grazzini, Silvia Bettarini, Paolo Tortoli, Simone Busoni, Gabriele Dragoni, Matteo Gottin, Andrea Galli, Vittorio Miele. Branch duct-intraductal papillary mucinous neoplasms (BD-IPMNs): an MRI-based radiomic model to determine the malignant degeneration potentialLa radiologia medica 2023; 128(4): 383 doi: 10.1007/s11547-023-01609-6
2
Toshifumi Kin, Yasuhiro Shimizu, Susumu Hijioka, Kazuo Hara, Akio Katanuma, Masafumi Nakamura, Reiko Yamada, Takao Itoi, Toshiharu Ueki, Atsushi Masamune, Seiko Hirono, Shinsuke Koshita, Keiji Hanada, Ken Kamata, Akio Yanagisawa, Yoshifumi Takeyama. A comparative study between computed tomography and endoscopic ultrasound in the detection of a mural nodule in intraductal papillary mucinous neoplasm –Multicenter observational study in JapanPancreatology 2023; 23(5): 550 doi: 10.1016/j.pan.2023.05.010
3
Mahip Grewal, Taha Ahmed, Ammar Asrar Javed. Current state of radiomics in hepatobiliary and pancreatic malignanciesArtificial Intelligence Surgery 2023; 3(4): 217 doi: 10.20517/ais.2023.28
4
Kiersten Preuss, Nate Thach, Xiaoying Liang, Michael Baine, Justin Chen, Chi Zhang, Huijing Du, Hongfeng Yu, Chi Lin, Michael A. Hollingsworth, Dandan Zheng. Using Quantitative Imaging for Personalized Medicine in Pancreatic Cancer: A Review of Radiomics and Deep Learning ApplicationsCancers 2022; 14(7): 1654 doi: 10.3390/cancers14071654
5
F. N. Paramzin, V. V. Kakotkin, D. A. Burkin, M. A. Agapov. Radiomics and artificial intelligence in the differential diagnosis of tumor and non-tumor diseases of the pancreas. ReviewSurgical practice 2023; (1): 53 doi: 10.38181/2223-2427-2023-1-5
6
Taha M. Ahmed, Satomi Kawamoto, Ralph H. Hruban, Elliot K. Fishman, Philippe Soyer, Linda C. Chu. A primer on artificial intelligence in pancreatic imagingDiagnostic and Interventional Imaging 2023; 104(9): 435 doi: 10.1016/j.diii.2023.03.002
7
Palash Rawlani, Nalini Kanta Ghosh, Ashok Kumar. Role of artificial intelligence in the characterization of indeterminate pancreatic head mass and its usefulness in preoperative diagnosisArtificial Intelligence in Gastroenterology 2023; 4(3): 48-63 doi: 10.35712/aig.v4.i3.48
8
Linda C. Chu, Seyoun Park, Sahar Soleimani, Daniel F. Fouladi, Shahab Shayesteh, Jin He, Ammar A. Javed, Christopher L. Wolfgang, Bert Vogelstein, Kenneth W. Kinzler, Ralph H. Hruban, Elham Afghani, Anne Marie Lennon, Elliot K. Fishman, Satomi Kawamoto. Classification of pancreatic cystic neoplasms using radiomic feature analysis is equivalent to an experienced academic radiologist: a step toward computer-augmented diagnostics for radiologistsAbdominal Radiology 2022; 47(12): 4139 doi: 10.1007/s00261-022-03663-6
9
Chenchan Huang, Sumit Chopra, Candice W. Bolan, Hersh Chandarana, Nassier Harfouch, Elizabeth M. Hecht, Grace C. Lo, Alec J. Megibow. Pancreatic Cystic LesionsGastrointestinal Endoscopy Clinics of North America 2023; 33(3): 533 doi: 10.1016/j.giec.2023.03.004
10
Eizaburo Ohno, Alberto Balduzzi, Susumu Hijioka, Matteo De Pastena, Giovanni Marchegiani, Hironari Kato, Mamoru Takenaka, Shin Haba, Roberto Salvia. Association of high-risk stigmata and worrisome features with advanced neoplasia in intraductal papillary mucinous neoplasms (IPMN): A systematic reviewPancreatology 2024; 24(1): 48 doi: 10.1016/j.pan.2023.12.002
11
Michael E. Egger. Incremental Improvements in the Ability to Distinguish High-Risk Intraductal Papillary Mucinous NeoplasmsAnnals of Surgical Oncology 2023; 30(6): 3186 doi: 10.1245/s10434-023-13202-2
12
Ryota Sagami, Kentaro Yamao, Jun Nakahodo, Ryuki Minami, Masakatsu Tsurusaki, Kazunari Murakami, Yuji Amano. Pre-Operative Imaging and Pathological Diagnosis of Localized High-Grade Pancreatic Intra-Epithelial Neoplasia without Invasive CarcinomaCancers 2021; 13(5): 945 doi: 10.3390/cancers13050945
13
Huifeng Zhang, Yingying Cao, Shuai Ren, Kai Guo, Yaping Zhang, Tingting Lin, Yaohui Wang, Xiao Chen, Zhongqiu Wang. Threshold of Main Pancreatic Duct Diameter in Identifying Malignant Intraductal Papillary Mucinous Neoplasm by Magnetic Resonance ImagingTechnology in Cancer Research & Treatment 2023; 22: 153303382311709 doi: 10.1177/15330338231170942
14
Kuan-Zheng Mao, Chao Ma, Bin Song. Radiomics advances in the evaluation of pancreatic cystic neoplasmsHeliyon 2024; 10(3): e25535 doi: 10.1016/j.heliyon.2024.e25535
15
Travis L. Williams, Lily V. Saadat, Mithat Gonen, Alice Wei, Richard K. G. Do, Amber L. Simpson. Radiomics in surgical oncology: applications and challengesComputer Assisted Surgery 2021; 26(1): 85 doi: 10.1080/24699322.2021.1994014
16
Calogero Casà, Antonio Piras, Andrea D’Aviero, Francesco Preziosi, Silvia Mariani, Davide Cusumano, Angela Romano, Ivo Boskoski, Jacopo Lenkowicz, Nicola Dinapoli, Francesco Cellini, Maria Antonietta Gambacorta, Vincenzo Valentini, Gian Carlo Mattiucci, Luca Boldrini. The impact of radiomics in diagnosis and staging of pancreatic cancerTherapeutic Advances in Gastrointestinal Endoscopy 2022; 15: 263177452210815 doi: 10.1177/26317745221081596
17
Javier Padillo-Ruiz. Recent Innovations in Surgical Procedures of Pancreatic Neoplasms2023; : 1 doi: 10.1007/978-3-031-21351-9_1
18
Doo Young Lee, Jaeseung Shin, Sungwon Kim, Song-Ee Baek, Suji Lee, Nak-Hoon Son, Mi-Suk Park. Radiomics model versus 2017 revised international consensus guidelines for predicting malignant intraductal papillary mucinous neoplasmsEuropean Radiology 2023; 34(2): 1222 doi: 10.1007/s00330-023-10158-5
19
Linda C. Chu, Elliot K. Fishman. The Pancreas2023; : 680 doi: 10.1002/9781119876007.ch88
20
Jennifer B. Permuth, Shraddha Vyas, Jiannong Li, Dung-Tsa Chen, Daniel Jeong, Jung W. Choi. Comparison of Radiomic Features in a Diverse Cohort of Patients With Pancreatic Ductal AdenocarcinomasFrontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.712950
21
Wen-peng Huang, Si-yun Liu, Yi-jing Han, Li-ming Li, Pan Liang, Jian-bo Gao. Development of CT-Based Imaging Signature for Preoperative Prediction of Invasive Behavior in Pancreatic Solid Pseudopapillary NeoplasmFrontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.677814
22
David Tobaly, Joao Santinha, Riccardo Sartoris, Marco Dioguardi Burgio, Celso Matos, Jérôme Cros, Anne Couvelard, Vinciane Rebours, Alain Sauvanet, Maxime Ronot, Nikolaos Papanikolaou, Valérie Vilgrain. CT-Based Radiomics Analysis to Predict Malignancy in Patients with Intraductal Papillary Mucinous Neoplasm (IPMN) of the PancreasCancers 2020; 12(11): 3089 doi: 10.3390/cancers12113089
23
Xiu‐Ping Zhang, Shuai Xu, Yang Wang, Zi‐Zheng Wang, Xiang‐Long Tan, Yuan‐Xing Gao, Guo‐Dong Zhao, Qu Liu, Zhi‐Ming Zhao, Rong Liu. Robotic pancreatectomy for intraductal papillary mucinous neoplasm of the pancreas: A large‐scale studyJournal of Hepato-Biliary-Pancreatic Sciences 2021; 28(11): 942 doi: 10.1002/jhbp.864
24
Shenhao Cheng, Hongyuan Shi, Ming Lu, Chen Wang, Shaofeng Duan, Qing Xu, Haibin Shi. Radiomics Analysis for Predicting Malignant Potential of Intraductal Papillary Mucinous Neoplasms of the Pancreas: Comparison of CT and MRIAcademic Radiology 2022; 29(3): 367 doi: 10.1016/j.acra.2021.04.013
25
Alberto Balduzzi, Boris V Janssen, Matteo De Pastena, Tommaso Pollini, Giovanni Marchegiani, Henk Marquering, Jaap Stoker, Inez Verpalen, Claudio Bassi, Marc G Besselink, Roberto Salvia. Artificial intelligence-based models to assess the risk of malignancy on radiological imaging in patients with intraductal papillary mucinous neoplasm of the pancreas: scoping reviewBritish Journal of Surgery 2023; 110(12): 1623 doi: 10.1093/bjs/znad201
26
Vincenza Granata, Roberta Fusco, Sergio Venanzio Setola, Roberta Galdiero, Nicola Maggialetti, Lucrezia Silvestro, Mario De Bellis, Elena Di Girolamo, Giulia Grazzini, Giuditta Chiti, Maria Chiara Brunese, Andrea Belli, Renato Patrone, Raffaele Palaia, Antonio Avallone, Antonella Petrillo, Francesco Izzo. Risk Assessment and Pancreatic Cancer: Diagnostic Management and Artificial IntelligenceCancers 2023; 15(2): 351 doi: 10.3390/cancers15020351
27
Zhiwei Huang, Mo Lyu, Zhu Ai, Yirong Chen, Yuying Liang, Zhiming Xiang. Pre-operative Prediction of Ki-67 Expression in Various Histological Subtypes of Lung Adenocarcinoma Based on CT Radiomic FeaturesFrontiers in Surgery 2021; 8 doi: 10.3389/fsurg.2021.736737
28
Veronica Frank, Sonaz Shariati, Bettina Katalin Budai, Bence Fejér, Ambrus Tóth, Vince Orbán, Viktor Bérczi, Pál Novák Kaposi. CT texture analysis of abdominal lesions – Part II: Tumors of the Kidney and PancreasImaging 2021; 13(1): 25 doi: 10.1556/1647.2021.00020
29
Miłosz Caban, Ewa Małecka-Wojciesko. Pancreatic IncidentalomaJournal of Clinical Medicine 2022; 11(16): 4648 doi: 10.3390/jcm11164648
30
Wenjie Liang, Wuwei Tian, Yifan Wang, Pan Wang, Yubizhuo Wang, Hongbin Zhang, Shijian Ruan, Jiayuan Shao, Xiuming Zhang, Danjiang Huang, Yong Ding, Xueli Bai. Classification prediction of pancreatic cystic neoplasms based on radiomics deep learning modelsBMC Cancer 2022; 22(1) doi: 10.1186/s12885-022-10273-4