{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T19:57:20Z","timestamp":1792180640811,"version":"4.4.0"},"reference-count":30,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T00:00:00Z","timestamp":1701216000000},"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":"Purpose<\/jats:title>Early judgment of the progress of acute pancreatitis (AP) and timely intervention are crucial to the prognosis of patients. The purpose of this study was to investigate the application value of CT-based radiomics of pancreatic parenchyma in predicting the prognosis of early AP.<\/jats:p><\/jats:sec>Materials and methods<\/jats:title>This retrospective study enrolled 137 patients diagnosed with AP (95 cases in the progressive group and 42 cases in the non-progressive group) who underwent CT scans. Patients were randomly divided into a training set (n<\/jats:italic>\u2009=\u200995) and a validation set (n<\/jats:italic>\u2009=\u200942) in a ratio of 7: 3. The region of interest (ROI) was outlined along the inner edge of the pancreatic parenchyma manually, and the Modified CT Severity Index (MCTSI) was assessed. After resampling and normalizing the CT image, a total of 2,264 radiomics features were extracted from the ROI. The radiomics features were downscaled and filtered using minimum redundancy maximum correlation (mRMR) and the least absolute shrinkage and selection operator algorithm (LASSO) regression, in turn, and the more optimal subset of radiomics features was selected. In addition, the radiomics score (rad-score) was calculated for each patient by the LASSO method. Clinical data were also analyzed to predict the prognosis of AP. Three prediction models, including clinical model, radiomics model, and combined clinical\u2013radiomics model, are constructed. The effectiveness of each model was evaluated using receiver operating characteristic (ROC) curve analysis. The DeLong test was employed to compare the differences between the ROC curves. The decision curve analysis (DCA) is used to assess the net benefit of the model.<\/jats:p><\/jats:sec>Results<\/jats:title>The mRMR algorithm and LASSO regression were used to select 13 radiomics features with high values. The rad-score of each texture feature was calculated to fuse MCTSI to establish the radiomics model, and both the clinical model and clinical\u2013radiomics model were established. The clinical\u2013radiomics model showed the best performance, the AUC and 95% confidence interval, accuracy, sensitivity, and specificity of the clinical\u2013radiomics model in the training set were 0.984 (0.964\u20131.000), 0.947, 0.955, and 0.931, respectively. In the validation set, they were 0.942 (0.870\u20131.000), 0.929, 0.966, and 0.846, respectively. The Delong test showed that the predictive efficacy of the clinical\u2013radiomics model was higher than that of the clinical model (Z<\/jats:italic>\u2009=\u20092.767, p<\/jats:italic>\u2009=\u20090.005) and the radiomics model (Z<\/jats:italic>\u2009=\u20092.033, p<\/jats:italic>\u2009=\u20090.042) in the validation set. Decision curve analysis demonstrated higher net clinical benefit for the clinical\u2013radiomics model.<\/jats:p><\/jats:sec>Conclusion<\/jats:title>The pancreatic parenchymal CT clinical\u2013radiomics model has high diagnostic efficacy in predicting the progression of early AP patients, which is significantly better than the clinical or radiomics model. The combined model can help identify and determine the progression trend of patients with AP and improve the prognosis and survival of patients as early as possible.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fmed.2023.1289295","type":"journal-article","created":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T05:02:29Z","timestamp":1701234149000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":17,"title":["The value of CT-based radiomics in predicting the prognosis of acute pancreatitis"],"prefix":"10.3389","volume":"10","author":[{"given":"Ming","family":"Xue","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuai","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dexuan","family":"Xie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongzhen","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Zou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xigang","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yulin","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,11,29]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1493","DOI":"10.1007\/s40618-020-01233-5","article-title":"Primary hyperparathyroidism and pancreatitis","volume":"43","author":"Misgar","year":"2020","journal-title":"J Endocrinol Investig"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1136\/gutjnl-2012-302779","article-title":"Acute pancreatitis classification working group. 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":"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":"484","DOI":"10.1016\/j.pan.2014.09.004","article-title":"The predictive value of proteinuria in acute pancreatitis","volume":"14","author":"Zuidema","year":"2014","journal-title":"Pancreatology"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"797","DOI":"10.1038\/ajg.2017.40","article-title":"Early aggressive hydration hastens clinical improvement in mild acute pancreatitis","volume":"112","author":"Buxbaum","year":"2017","journal-title":"Am J Gastroenterol"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.pan.2019.11.010","article-title":"Site and size of extrapancreatic necrosis are associated with clinical outcomes in patients with acute necrotizing pancreatitis","volume":"20","author":"Gupta","year":"2020","journal-title":"Pancreatology"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"586","DOI":"10.1001\/archsurg.1993.01420170122019","article-title":"A clinically based classification system for acute pancreatitis","volume":"128","author":"Bradley","year":"1993","journal-title":"Arch Surg."},{"key":"ref8","first-page":"403","article-title":"Morphological and functional consequences and quality of life following severe acute pancreatitis","volume":"6","author":"Koziel","year":"2017","journal-title":"Ann Ital Chir"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"1165","DOI":"10.1097\/MPA.0000000000001149","article-title":"The role of endoscopic ultrasonography and magnetic resonance cholangiopancreatography in patients with acute pancreatitis after negative computed tomography findings of the etiology","volume":"47","author":"Kim","year":"2018","journal-title":"Pancreas"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"367581","DOI":"10.1155\/2013\/367581","article-title":"Comparison of Ranson, Glasgow, MOSS, SIRS, BISAP, APACHE-II, CTSI scores, IL-6, CRP, and Procalcitonin in predicting severity, organ failure, pancreatic necrosis, and mortality in acute pancreatitis","volume":"2013","author":"Khanna","year":"2013","journal-title":"HPB Surg"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1093\/gastro\/gox029","article-title":"A comparison of APACHE II, BISAP, Ranson\u2019s score and modified CTSI in predicting the severity of acute pancreatitis based on the 2012 revised Atlanta classification","volume":"6","author":"Harshit Kumar","year":"2018","journal-title":"Gastroenterol Rep"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1038\/ajg.2009.622","article-title":"Comparison of BISAP, Ranson\u2019s, APACHE-II, and CTSI scores in predicting organ failure, complications, and mortality in acute pancreatitis","volume":"105","author":"Papachristou","year":"2010","journal-title":"Am J Gastroenterol"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1111\/1751-2980.12961","article-title":"Evaluation of the modified computed tomography severity index (MCTSI) and computed tomography severity index (CTSI) in predicting severity and clinical outcomes in acute pancreatitis","volume":"22","author":"Alberti","year":"2021","journal-title":"J Dig Dis"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"2387","DOI":"10.3748\/wjg.v21.i8.2387","article-title":"Comparison of scoring systems in predicting the severity of acute pancreatitis","volume":"21","author":"Cho","year":"2015","journal-title":"World J Gastroenterol"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1038\/ajg.2009.623","article-title":"The difficulty in predicting outcome in acute pancreatitis","volume":"105","author":"Chauhan","year":"2010","journal-title":"Am J Gastroenterol"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"1243","DOI":"10.1007\/s00261-019-02236-4","article-title":"CT imaging, classification, and complications of acute pancreatitis","volume":"45","author":"Fung","year":"2020","journal-title":"Abdom Radiol (NY)"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1148\/radiol.2015151169","article-title":"Radiomics: images are more than pictures, they are data","volume":"278","author":"Gillies","year":"2016","journal-title":"Radiology"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"4408","DOI":"10.1007\/s00330-018-5824-1","article-title":"Radiomics model of contrast-enhanced computed tomography for predicting the recurrence of acute pancreatitis","volume":"29","author":"Chen","year":"2019","journal-title":"Eur Radiol"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1002\/jmri.26798","article-title":"Radiomics model of contrast-enhanced MRI for early prediction of acute pancreatitis severity","volume":"51","author":"Lin","year":"2020","journal-title":"J Magn Reson Imaging"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"3200","DOI":"10.1007\/s00330-018-5763-x","article-title":"Preoperative radiomic signature based on multiparametric magnetic resonance imaging for noninvasive evaluation of biological characteristics in rectal cancer","volume":"29","author":"Meng","year":"2019","journal-title":"Eur Radiol"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1053\/j.gastro.2018.08.063","article-title":"Burden and cost of gastrointestinal, liver, and pancreatic diseases in the United States: update 2018","volume":"156","author":"Peery","year":"2019","journal-title":"Gastroenterology"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"1247","DOI":"10.1016\/j.cgh.2009.08.012","article-title":"Early systemic inflammatory response syndrome is associated with severe acute pancreatitis","volume":"7","author":"Singh","year":"2009","journal-title":"Clin Gastroenterol Hepatol"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"727","DOI":"10.14423\/SMJ.0000000000000727","article-title":"Acute pancreatitis: etiology, pathology, diagnosis, and treatment","volume":"110","author":"Majidi","year":"2017","journal-title":"South Med J"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1148\/radiology.174.2.2296641","article-title":"Acute pancreatitis: value of CT in establishing prognosis","volume":"174","author":"Balthazar","year":"1990","journal-title":"Radiology"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1148\/radiol.2233010680","article-title":"Acute pancreatitis: assessment of severity with clinical and CT evaluation","volume":"223","author":"Balthazar","year":"2002","journal-title":"Radiology"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1148\/radiology.193.2.7972730","article-title":"Imaging and intervention in acute pancreatitis","volume":"193","author":"Balthazar","year":"1994","journal-title":"Radiology"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"1261","DOI":"10.2214\/ajr.183.5.1831261","article-title":"A modified CT severity index for evaluating acute pancreatitis: improved correlation with patient outcome","volume":"183","author":"Mortele","year":"2004","journal-title":"Am. J. Radiol."},{"key":"ref28","doi-asserted-by":"publisher","first-page":"TC01","DOI":"10.7860\/JCDR\/2015\/14824.6368","article-title":"Modified computed tomography severity index for evaluation of acute pancreatitis and its correlation with clinical outcome: a tertiary care hospital based observational study","volume":"9","author":"Banday","year":"2015","journal-title":"J Clin Diagn Res"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"2495","DOI":"10.1109\/TIP.2013.2246524","article-title":"2-D wavelet packet spectrum for texture analysis","volume":"22","author":"Atto","year":"2013","journal-title":"IEEE Trans Image Process"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"2633","DOI":"10.1016\/j.patcog.2015.02.024","article-title":"A scale-and orientation-adaptive extension of local binary patterns for texture classification","volume":"48","author":"Hegenbart","year":"2015","journal-title":"Pattern Recogn"}],"container-title":["Frontiers in Medicine"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2023.1289295\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T05:02:31Z","timestamp":1701234151000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fmed.2023.1289295\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,29]]},"references-count":30,"alternative-id":["10.3389\/fmed.2023.1289295"],"URL":"https:\/\/doi.org\/10.3389\/fmed.2023.1289295","relation":{},"ISSN":["2296-858X"],"issn-type":[{"value":"2296-858X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,29]]},"article-number":"1289295"}}