{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T05:11:53Z","timestamp":1789017113319,"version":"build-2803163510"},"reference-count":27,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T00:00:00Z","timestamp":1771200000000},"content-version":"vor","delay-in-days":15,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Colorectal Disease"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>Completeness of cytoreduction (CC) remains the strongest prognostic determinant after cytoreductive surgery (CRS)\u2009\u00b1\u2009hyperthermic intraperitoneal chemotherapy (HIPEC) for colorectal peritoneal metastases (CPM) yet accurate pre\u2010operative prediction remains difficult. This study aimed to develop and validate a radiomic\u2013clinical machine\u2010learning model to predict cytoreduction completeness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>83 patients who underwent CRS\u2009\u00b1\u2009HIPEC for CPM (2008\u20132025) were retrospectively analysed. Pre\u2010operative contrast\u2010enhanced CT scans were manually segmented in ITK\u2010SNAP, and radiomic features were extracted using PyRadiomics. Clinical variables were modelled alone and in combination with radiomics features using a nested five\u2010fold cross\u2010validated machine\u2010learning pipeline incorporating least absolute shrinkage and selection operator (LASSO) logistic regression, random forest (RF) and gradient\u2010boosted classifiers (GBC) algorithms. The primary endpoint was incomplete cytoreduction (iCC). Model discrimination (AUROC, AUPRC), Brier score and calibration were assessed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>iCC occurred in 17 of 83 patients (20.5%). Independent predictors of iCC were high radiological PCI (\u226515), upper\u2010abdominal disease, absence of pre\u2010operative chemotherapy and normal CEA (\u22645\u2009ng\/mL). The radiomic\u2013clinical model achieved the best performance (AUROC 0.90, AUPRC 0.69, Brier 0.077, sensitivity 0.83, specificity 0.92), outperforming clinical\u2010only (AUROC 0.82\u20130.86) and radiomic\u2010only (AUROC 0.69\u20130.75) models. Key radiomic predictors of iCC\u2014low sphericity, high maximum 2D diameter and high zone entropy\u2014reflected morphological irregularity and heterogeneity of CPM. Integrated models demonstrated superior calibration indicating stable and reliable probability estimates.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>A CT\u2010based radiomic\u2013clinical model accurately predicts CC pre\u2010operatively. This exploratory proof\u2010of\u2010concept model supports multicentre external validation to enhance decision\u2010making for CRS\u2009\u00b1\u2009HIPEC in CPM.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/codi.70409","type":"journal-article","created":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T04:38:20Z","timestamp":1771303100000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["<scp>CT<\/scp>\n                    \u2010based radiomics\u2013clinical machine\u2010learning model to predict completeness of cytoreduction in colorectal peritoneal metastases"],"prefix":"10.1111","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3219-3938","authenticated-orcid":false,"given":"Samuel","family":"Pau","sequence":"first","affiliation":[{"name":"Waikato Clinical Campus, Faculty of Medical and Health Sciences University of Auckland  Hamilton New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy","family":"Eglinton","sequence":"additional","affiliation":[{"name":"Department of Surgery and Critical Care University of Otago  Christchurch New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1610-2397","authenticated-orcid":false,"given":"Alan","family":"Wang","sequence":"additional","affiliation":[{"name":"Auckland Bioengineering Institute University of Auckland  Auckland New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ghazal","family":"Mehri\u2010Kakavand","sequence":"additional","affiliation":[{"name":"Department of Anatomy and Medical Imaging, Faculty of Medical and Health Sciences University of Auckland  Auckland New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3366-5629","authenticated-orcid":false,"given":"Jesse","family":"Fischer","sequence":"additional","affiliation":[{"name":"Waikato Clinical Campus, Faculty of Medical and Health Sciences University of Auckland  Hamilton New Zealand"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,2,16]]},"reference":[{"key":"e_1_2_17_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/ans.18777"},{"key":"e_1_2_17_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/DCR.0b013e318202f026"},{"key":"e_1_2_17_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejso.2010.01.006"},{"key":"e_1_2_17_5_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2011.39.7166"},{"key":"e_1_2_17_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jamcollsurg.2006.08.024"},{"key":"e_1_2_17_7_1","doi-asserted-by":"publisher","DOI":"10.1245\/s10434\u2010015\u20104627\u20108"},{"key":"e_1_2_17_8_1","doi-asserted-by":"publisher","DOI":"10.1245\/s10434\u2010014\u20104148\u2010x"},{"key":"e_1_2_17_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11605\u2010015\u20102880\u20106"},{"key":"e_1_2_17_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejso.2025.110537"},{"key":"e_1_2_17_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isci.2022.103798"},{"key":"e_1_2_17_12_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2015151169"},{"key":"e_1_2_17_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejso.2025.109760"},{"key":"e_1_2_17_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2016.03.001"},{"key":"e_1_2_17_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2006.01.015"},{"key":"e_1_2_17_16_1","doi-asserted-by":"publisher","DOI":"10.1186\/1477\u20107800\u20102\u20103"},{"key":"e_1_2_17_17_1","volume-title":"Miniconda documentation. Version 3.13.0","author":"Anaconda Inc","year":"2016"},{"key":"e_1_2_17_18_1","volume-title":"Python language reference. Version 3.13.0","author":"Python Software Foundation","year":"2025"},{"key":"e_1_2_17_19_1","doi-asserted-by":"publisher","DOI":"10.1158\/0008\u20105472.CAN\u201017\u20100339"},{"key":"e_1_2_17_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.crad.2018.03.011"},{"key":"e_1_2_17_21_1","doi-asserted-by":"publisher","DOI":"10.1002\/bjs.10989"},{"key":"e_1_2_17_22_1","doi-asserted-by":"publisher","DOI":"10.3889\/oamjms.2019.442"},{"key":"e_1_2_17_23_1","doi-asserted-by":"publisher","DOI":"10.18383\/j.tom.2020.00016"},{"key":"e_1_2_17_24_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010019\u201040437\u20105"},{"key":"e_1_2_17_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278\u2010023\u201000799\u20109"},{"key":"e_1_2_17_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330\u2010021\u201007902\u20100"},{"key":"e_1_2_17_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00261\u2010023\u201003802\u20107"},{"key":"e_1_2_17_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2022.12.009"}],"container-title":["Colorectal Disease"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/codi.70409","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/codi.70409","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/codi.70409","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T17:05:09Z","timestamp":1772989509000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/codi.70409"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":27,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["10.1111\/codi.70409"],"URL":"https:\/\/doi.org\/10.1111\/codi.70409","archive":["Portico"],"relation":{},"ISSN":["1462-8910","1463-1318"],"issn-type":[{"value":"1462-8910","type":"print"},{"value":"1463-1318","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2]]},"assertion":[{"value":"2025-11-23","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-02-02","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-02-16","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70409"}}