{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T06:55:46Z","timestamp":1793861746157,"version":"4.6.1"},"reference-count":48,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T00:00:00Z","timestamp":1741219200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study sought to clarify the utility of T2-weighted imaging (T2WI)-based radiomics to predict the recurrence of acute pancreatitis (AP) in subjects with metabolic syndrome (MetS).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Data from 196 patients with both AP and MetS from our hospital were retrospectively analyzed. These patients were separated into two groups according to their clinical follow-up outcomes, including those with first-onset AP (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f114) and those with recurrent AP (RAP) (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f82). The 196 cases were randomly divided into a training set (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f137) and a test set (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f59) at a 7:3 ratio. The clinical characteristics of these patients were systematically compiled for further analysis. For each case, the pancreatic parenchyma was manually delineated slice by slice using 3D Slicer software, and the appropriate radiomics characteristics were retrieved. The K-best approach, the least absolute shrinkage and selection operator (LASSO) algorithm, and variance thresholding were all used in the feature selection process. The establishment of clinical, radiomics, and combined models for forecasting AP recurrence in patients with MetS was then done using a random forest classifier. Model performance was measured using the area under the receiver operating characteristic curve (AUC), and model comparison was done using the DeLong test. The clinical utility of these models was evaluated using decision curve analysis (DCA), and the optimal model was determined via a calibration curve.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In the training set, the clinical, radiomics, and combined models yielded respective AUCs of 0.651, 0.825, and 0.883, with corresponding test sets of AUCs of 0.606, 0.776, and 0.878. Both the radiomics and combined models exhibited superior predictive effectiveness compared to the clinical model in both the training (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.001,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.001) and test sets (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.04,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.001). The combined model outperformed the radiomics model (training set:\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.025, test set:\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u202f0.019). The DCA demonstrated that the radiomics and combined models had greater clinical efficacy than the clinical model. The calibration curve for the combined model demonstrated good agreement between the predicted probability of AP recurrence and the observed outcomes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>These findings highlight the superior predictive power of a T2WI-based radiomics model for predicting AP recurrence in patients with MetS, potentially supporting early interventions that can mitigate or alleviate RAP.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmed.2025.1502315","type":"journal-article","created":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T01:51:22Z","timestamp":1741225882000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Radiomics-based prediction of recurrent acute pancreatitis in individuals with metabolic syndrome using T2WI magnetic resonance imaging data"],"prefix":"10.3389","volume":"12","author":[{"given":"Yuan","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiyao","family":"Wan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyi","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohua","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,3,6]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1186\/s12944-024-02057-5","article-title":"Analysis of the clinical profile and treatment efficiency of hyperlipidemic acute pancreatitis","volume":"23","author":"Zhou","year":"2024","journal-title":"Lipids Health Dis"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1927","DOI":"10.21037\/qims-22-821","article-title":"Early prediction of acute pancreatitis severity based on changes in pancreatic and peripancreatic computed tomography radiomics nomogram","volume":"13","author":"Zhao","year":"2023","journal-title":"Quant Imaging Med Surg"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1038\/s41575-018-0087-5","article-title":"Global epidemiology and holistic prevention of pancreatitis","volume":"16","author":"Petrov","year":"2019","journal-title":"Nat Rev Gastroenterol Hepatol"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"1251","DOI":"10.1007\/s40265-022-01766-4","article-title":"Acute pancreatitis: diagnosis and treatment","volume":"82","author":"Szatmary","year":"2022","journal-title":"Drugs"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"873","DOI":"10.1097\/MPA.0000000000001839","article-title":"Individualized prediction of acute pancreatitis recurrence using a nomogram","volume":"50","author":"Hu","year":"2021","journal-title":"Pancreas"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"1683","DOI":"10.1007\/s10620-017-4510-5","article-title":"Epidemiology of recurrent acute and chronic pancreatitis: similarities and differences","volume":"62","author":"Machicado","year":"2017","journal-title":"Dig Dis Sci"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"1711","DOI":"10.1038\/s41395-018-0255-9","article-title":"Pancreatic Cancer following acute pancreatitis: a population-based matched cohort study","volume":"113","author":"Sadr-Azodi","year":"2018","journal-title":"Am J Gastroenterol"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"10549","DOI":"10.18632\/aging.205094","article-title":"Identifying endoplasmic reticulum stress-related molecular subtypes and prognostic model for predicting the immune landscape and therapy response in pancreatic cancer","volume":"15","author":"Zhang","year":"2023","journal-title":"Aging (Albany NY)"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"1289","DOI":"10.2147\/DMSO.S249128","article-title":"Association between metabolic syndrome and its components with severity of acute pancreatitis","volume":"13","author":"Niknam","year":"2020","journal-title":"Diab Metab Syndr Obes"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1007\/s11906-018-0812-z","article-title":"The global epidemic of the metabolic syndrome","volume":"20","author":"Saklayen","year":"2018","journal-title":"Curr Hypertens Rep"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"686","DOI":"10.1186\/s12889-023-15584-0","article-title":"Gender differences in metabolic syndrome and its components in southern China using a healthy lifestyle index: a cross-sectional study","volume":"23","author":"Ye","year":"2023","journal-title":"BMC Public Health"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.clindermatol.2017.09.004","article-title":"Pathophysiology of the metabolic syndrome","volume":"36","author":"McCracken","year":"2018","journal-title":"Clin Dermatol"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"e13916","DOI":"10.1111\/apha.13916","article-title":"Mechanisms linking hypertriglyceridemia to acute pancreatitis","volume":"237","author":"Kiss","year":"2023","journal-title":"Acta Physiol (Oxf)"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"3996","DOI":"10.3748\/wjg.v30.i35.3996","article-title":"Impact of metabolic syndrome components on clinical outcomes in hypertriglyceridemia-induced acute pancreatitis","volume":"30","author":"Fu","year":"2024","journal-title":"World J Gastroenterol"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"23","DOI":"10.3390\/ijms23020786","article-title":"Metabolic syndrome: updates on pathophysiology and management in 2021","volume":"23","author":"Fahed","year":"2022","journal-title":"Int J Mol Sci"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.ejim.2016.04.004","article-title":"Metabolic syndrome and acute pancreatitis","volume":"32","author":"Mikolasevic","year":"2016","journal-title":"Eur J Intern Med"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"e16854","DOI":"10.7717\/peerj.16854","article-title":"A retrospective study investigating the clinical significance of body mass index in acute pancreatitis","volume":"12","author":"Bai","year":"2024","journal-title":"PeerJ"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"282","DOI":"10.4103\/sjg.sjg_324_21","article-title":"Different clinical characteristics between recurrent and non - recurrent acute pancreatitis: a retrospective cohort study from a tertiary hospital","volume":"28","author":"Song","year":"2022","journal-title":"Saudi J Gastroenterol"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12944-023-01972-3","article-title":"Identification of novel biomarkers based on lipid metabolism-related molecular subtypes for moderately severe and severe acute pancreatitis","volume":"23","author":"Liu","year":"2024","journal-title":"Lipids Health Dis"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"488","DOI":"10.2967\/jnumed.118.222893","article-title":"Introduction to Radiomics","volume":"61","author":"Mayerhoefer","year":"2020","journal-title":"J Nucl Med"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"1289295","DOI":"10.3389\/fmed.2023.1289295","article-title":"The value of CT-based radiomics in predicting the prognosis of acute pancreatitis","volume":"10","author":"Xue","year":"2023","journal-title":"Front Med (Lausanne)"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"777368","DOI":"10.3389\/fmed.2022.777368","article-title":"Three-dimensional Radiomics features of magnetic resonance T2-weighted imaging combined with clinical characteristics to predict the recurrence of acute pancreatitis","volume":"9","author":"Hu","year":"2022","journal-title":"Front Med (Lausanne)"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"718","DOI":"10.3390\/diagnostics14070718","article-title":"Radiomics-based machine learning model for diagnosis of acute pancreatitis using computed tomography","volume":"14","author":"Bette","year":"2024","journal-title":"Diagnostics (Basel)"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"1909","DOI":"10.21037\/qims-20-280","article-title":"Early-phase vascular involvement is associated with acute pancreatitis severity: a magnetic resonance imaging study","volume":"11","author":"Jiang","year":"2021","journal-title":"Quant Imaging Med Surg"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1097\/MPA.0000000000001425","article-title":"Extrapancreatic inflammation on magnetic resonance imaging for the early prediction of acute pancreatitis severity","volume":"49","author":"Zhou","year":"2020","journal-title":"Pancreas"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1136\/gutjnl-2012-302779","article-title":"Classification of acute pancreatitis--2012: revision of the Atlanta classification and definitions by international consensus","volume":"62","author":"Banks","year":"2013","journal-title":"Gut"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1097\/MPA.0000000000001053","article-title":"Recurrent acute pancreatitis: international state-of-the-science conference with recommendations","volume":"47","author":"Guda","year":"2018","journal-title":"Pancreas"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"1640","DOI":"10.1161\/CIRCULATIONAHA.109.192644","article-title":"Harmonizing the metabolic syndrome: a joint interim statement of the international diabetes federation task force on epidemiology and prevention; National Heart, Lung, and Blood Institute; American Heart Association; world heart federation; international atherosclerosis society; and International Association for the Study of obesity","volume":"120","author":"Alberti","year":"2009","journal-title":"Circulation"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1016\/S2213-8587(21)00047-4","article-title":"Clinical management and treatment of obesity in China","volume":"9","author":"Zeng","year":"2021","journal-title":"Lancet Diabetes Endocrinol"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1186\/s12876-020-01579-3","article-title":"Metabolic syndrome components and acute pancreatitis: a case-control study in China","volume":"21","author":"Shen","year":"2021","journal-title":"BMC Gastroenterol"},{"key":"ref31","doi-asserted-by":"publisher","first-page":"104504","DOI":"10.1016\/j.amsu.2022.104504","article-title":"Health-related quality of life among acute pancreatitis patients correlates with metabolic variables and associated factors","volume":"82","author":"Sardana","year":"2022","journal-title":"Ann Med Surg (Lond)"},{"key":"ref32","doi-asserted-by":"publisher","first-page":"901","DOI":"10.2147\/JHC.S366937","article-title":"A novel nomogram for prediction of post-hepatectomy liver failure in patients with Resectable hepatocellular carcinoma: a multicenter study","volume":"9","author":"Wang","year":"2022","journal-title":"J Hepatocell Carcinoma"},{"key":"ref33","doi-asserted-by":"publisher","first-page":"106609","DOI":"10.1016\/j.cmpb.2021.106609","article-title":"Interpretation of radiomics features\u2013a pictorial review","volume":"215","author":"Abbasian Ardakani","year":"2022","journal-title":"Comput Methods Prog Biomed"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"1189157","DOI":"10.3389\/fvets.2023.1189157","article-title":"Machine learning-based risk prediction model for canine myxomatous mitral valve disease using electronic health record data","volume":"10","author":"Kim","year":"2023","journal-title":"Front Vet Sci"},{"key":"ref35","doi-asserted-by":"publisher","first-page":"e0206062","DOI":"10.1371\/journal.pone.0206062","article-title":"Clinico-radiological comparison and short-term prognosis of single acute pancreatitis and recurrent acute pancreatitis including pancreatic volumetry","volume":"13","author":"Avanesov","year":"2018","journal-title":"PLoS One"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"1292","DOI":"10.1053\/j.gastro.2013.01.069","article-title":"Genetic risk factors for pancreatic disorders","volume":"144","author":"Whitcomb","year":"2013","journal-title":"Gastroenterology"},{"key":"ref37","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1038\/nrgastro.2010.6","article-title":"The role of alcohol and smoking in pancreatitis","volume":"7","author":"Yadav","year":"2010","journal-title":"Nat Rev Gastroenterol Hepatol"},{"key":"ref38","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1007\/s00330-019-06381-8","article-title":"Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation","volume":"30","author":"Yamashita","year":"2020","journal-title":"Eur Radiol"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"1303","DOI":"10.7150\/thno.30309","article-title":"The applications of Radiomics in precision diagnosis and treatment of oncology: opportunities and challenges","volume":"9","author":"Liu","year":"2019","journal-title":"Theranostics"},{"key":"ref40","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1186\/s12887-023-03896-4","article-title":"Bioinformatic analysis of underlying mechanisms of Kawasaki disease via weighted gene correlation network analysis (WGCNA) and the least absolute shrinkage and selection operator method (LASSO) regression model","volume":"23","author":"Xie","year":"2023","journal-title":"BMC Pediatr"},{"key":"ref41","doi-asserted-by":"publisher","first-page":"2762","DOI":"10.1038\/s41598-022-13650-y","article-title":"Radiomics analysis of contrast-enhanced T1W MRI: predicting the recurrence of acute pancreatitis","volume":"13","author":"Tang","year":"2023","journal-title":"Sci Rep"},{"key":"ref42","doi-asserted-by":"publisher","first-page":"11340","DOI":"10.1038\/s41598-022-15609-5","article-title":"Applying logistic LASSO regression for the diagnosis of atypical Crohn\u2019s disease","volume":"12","author":"Li","year":"2022","journal-title":"Sci Rep"},{"key":"ref43","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1097\/MPA.0000000000001235","article-title":"Severe hypertriglyceridemia-related pancreatitis: characteristics and predictors of recurrence","volume":"48","author":"Zafrir","year":"2019","journal-title":"Pancreas"},{"key":"ref44","doi-asserted-by":"publisher","first-page":"890","DOI":"10.1007\/s10620-018-5226-x","article-title":"Influence of ambulatory triglyceride levels on risk of recurrence in patients with Hypertriglyceridemic pancreatitis","volume":"64","author":"Wu","year":"2019","journal-title":"Dig Dis Sci"},{"key":"ref45","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1186\/s12944-021-01488-8","article-title":"The association of triglyceride levels with the incidence of initial and recurrent acute pancreatitis","volume":"20","author":"Sanchez","year":"2021","journal-title":"Lipids Health Dis"},{"key":"ref46","doi-asserted-by":"publisher","first-page":"2265939","DOI":"10.1080\/07853890.2023.2265939","article-title":"Comprehensive review on the pathogenesis of hypertriglyceridaemia-associated acute pancreatitis","volume":"55","author":"Qiu","year":"2023","journal-title":"Ann Med"},{"key":"ref47","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1016\/j.ejim.2014.08.008","article-title":"Current knowledge of hypertriglyceridemic pancreatitis","volume":"25","author":"Valdivielso","year":"2014","journal-title":"Eur J Intern Med"},{"key":"ref48","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1186\/1471-230X-9-46","article-title":"Lipoprotein lipase activity and mass, apolipoprotein C-II mass and polymorphisms of apolipoproteins E and A5 in subjects with prior acute hypertriglyceridaemic pancreatitis","volume":"9","author":"Coca-Prieto","year":"2009","journal-title":"BMC Gastroenterol"}],"container-title":["Frontiers in Medicine"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2025.1502315\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T01:51:24Z","timestamp":1741225884000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2025.1502315\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,6]]},"references-count":48,"alternative-id":["10.3389\/fmed.2025.1502315"],"URL":"https:\/\/doi.org\/10.3389\/fmed.2025.1502315","relation":{},"ISSN":["2296-858X"],"issn-type":[{"value":"2296-858X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,6]]},"article-number":"1502315"}}