{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T22:17:21Z","timestamp":1783117041028,"version":"3.54.6"},"reference-count":25,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T00:00:00Z","timestamp":1776297600000},"content-version":"vor","delay-in-days":15,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The efficacy of neoadjuvant therapy (NAT) and surgical prognosis stratification in patients with colorectal cancer liver metastasis (CRLM) remain unclear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aims to develop and validate two radiomics models using baseline and delta radiomics features to predict the response to NAT and prognosis in CRLM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Baseline and Delta MRI radiomics features were extracted from 116 CRLM patients who underwent NAT combined with hepatectomy in the training set. Radiomics and clinical features were selected using Boruta\n                      <jats:styled-content>algorithm<\/jats:styled-content>\n                      to construct predictive models. In the external test set, the predictive performance of both models was evaluated using the area under the curve (AUC), decision curve analysis (DCA), calibration curves, and Brier score. Additionally, the delta model was compared with the clinical risk score (CRS).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The two models contain 6 and 4 variables, respectively, for predicting treatment response and progression\u2010free survival (PFS). Both the response model and delta model demonstrated comparable predictive performance in the external test set (AUC\u00a0=\u00a00.806 for both). Furthermore, the delta model demonstrated superior performance to CRS in predicting PFS (AUC: 0.806\u00a0vs. 0.623).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Radiomics models based on baseline and delta MRI effectively predicted treatment response and postoperative PFS in CRLM patients, with the delta model showing superior accuracy for PFS prediction compared to CRS.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70445","type":"journal-article","created":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T09:03:01Z","timestamp":1776330181000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Support vector machine\u2010based MRI radiomics predict response to neoadjuvant therapy and progression\u2010free\u2010survival of Colorectal Liver Metastases patients"],"prefix":"10.1002","volume":"53","author":[{"given":"Zhuo\u2010fu","family":"Li","sequence":"first","affiliation":[{"name":"Department of Radiology, Medical Artificial General Intelligence for Computation (MAGIC) Lab Tianjin Medical University Cancer Institute and Hospital National Clinical Research Center for Cancer. Tianjin's Clinical Research Center for Cancer *State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine *Tianjin Key Laboratory of Digestive Cancer  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Radiology The Fourth Hospital of Hebei Medical University  Shijiazhuang China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Radiology Tianjin Union Medical Center The First Affiliated Hospital of Nankai University  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Song","family":"Tian","sequence":"additional","affiliation":[{"name":"Philips HealthCare  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zi\u2010long","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Radiology, Medical Artificial General Intelligence for Computation (MAGIC) Lab Tianjin Medical University Cancer Institute and Hospital National Clinical Research Center for Cancer. Tianjin's Clinical Research Center for Cancer *State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine *Tianjin Key Laboratory of Digestive Cancer  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhao\u2010xiang","family":"Ye","sequence":"additional","affiliation":[{"name":"Department of Radiology, Medical Artificial General Intelligence for Computation (MAGIC) Lab Tianjin Medical University Cancer Institute and Hospital National Clinical Research Center for Cancer. Tianjin's Clinical Research Center for Cancer *State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine *Tianjin Key Laboratory of Digestive Cancer  Tianjin China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,4,16]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140\u20106736(24)00360\u2010X"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21772"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21660"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21395"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/clinpract12060112"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.3748\/wjg.v20.i20.6113"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejca.2016.03.081"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.23736\/S1824\u20104785.17.03038\u20102"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.crad.2010.04.005"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejca.2011.11.036"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms5006"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41571\u2010021\u201000560\u20107"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1245\/s10434\u2010020\u201009581\u20105"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11547\u2010021\u201001436\u20107"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11547\u2010024\u201001853\u20104"},{"issue":"1","key":"e_1_2_10_17_1","first-page":"41","article-title":"Applications of support vector machine (svm) learning in cancer genomics","volume":"15","author":"Huang S","year":"2018","journal-title":"Cancer Genomics Proteomics"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0161501"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020191145"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1097\/00000658\u2010199909000\u201000004"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.18632\/oncotarget.8671"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00270\u2010023\u201003602\u2010y"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1245\/s10434\u2010024\u201015196\u2010x"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.annonc.2022.10.003"},{"issue":"1","key":"e_1_2_10_25_1","first-page":"1","article-title":"China guideline for diagnosis and comprehensive treatment of colorectal liver metastases (version 2023)","volume":"26","year":"2023","journal-title":"Zhonghua Wei Chang Wai Ke Za Zhi"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2023.10.020"}],"container-title":["Medical Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.70445","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/mp.70445","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/mp.70445","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T21:25:20Z","timestamp":1783113920000},"score":1,"resource":{"primary":{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/mp.70445"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":25,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["10.1002\/mp.70445"],"URL":"https:\/\/doi.org\/10.1002\/mp.70445","archive":["Portico"],"relation":{},"ISSN":["0094-2405","2473-4209"],"issn-type":[{"value":"0094-2405","type":"print"},{"value":"2473-4209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"2025-07-30","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-05","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-16","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70445"}}