{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T09:39:54Z","timestamp":1783330794166,"version":"3.54.6"},"reference-count":27,"publisher":"SAGE Publications","issue":"8","license":[{"start":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T00:00:00Z","timestamp":1751932800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"the General Program of Inner Mongolia Medical University","award":["grant number YKD2021MS045"],"award-info":[{"award-number":["grant number YKD2021MS045"]}]},{"name":"This work was supported by the Natural Science Foundation of Inner Mongolia","award":["grant number 2021MS08026"],"award-info":[{"award-number":["grant number 2021MS08026"]}]},{"name":"Key laboratory of Affiliated Hospital of Inner Mongolia Medical University open fund","award":["grant number 2022NYFYSY006"],"award-info":[{"award-number":["grant number 2022NYFYSY006"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Acta Radiol"],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The prognosis for hepatocellular carcinoma (HCC) is unfavorable, primarily attributable to the high incidence of recurrence.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To assess the prognostic value of multiparametric magnetic resonance imaging (mp-MRI) based on radiomic features for overall survival (OS) in patients with HCC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Material and Methods<\/jats:title>\n                    <jats:p>Patients who underwent abdominal mp-MRI examination before hepatectomy in our hospital between January 2016 and December 2019 were retrospectively collected and divided into a training group and a verification group at a ratio of 7:3. The patients\u2019 images, clinical parameters, and semantic features were collected. A three-dimensional volume of interest was delineated and radiomics features were screened. Independent predictors of clinical imaging were screened and combined with radiomics features to construct a combinatorial model and draw a nomogram. The predictive efficacy of the model was evaluated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The Harrell's C-index values were 0.737 and 0.711 for the clinical imaging model and 0.705 and 0.704 for the full sequence model in the training group and validation group, respectively. The combinatorial model had higher efficiency, and the C-index values in the training group and the validation group were 0.779 and 0.756, respectively. The survival curve showed that the low-risk group defined by the radiomics signature had significantly better OS than the high-risk group (3-year OS: 61.54% vs. 30.77%;\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090.05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The combined model can predict the OS of patients with HCC non-invasively before surgical resection and can be used as a clinical tool to guide individualized treatment.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/02841851251324572","type":"journal-article","created":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T03:09:23Z","timestamp":1751944163000},"page":"805-815","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Multiparametric MRI radiomics predicts overall survival in hepatocellular carcinoma"],"prefix":"10.1177","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2247-0970","authenticated-orcid":false,"given":"Tong","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Radiology, Linfen Central Hospital, Linfen, Shanxi, \rPR China"},{"name":"Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jialiang","family":"Ren","sequence":"additional","affiliation":[{"name":"Department of Pharmaceuticals Diagnosis, GE Healthcare (China), Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1620-5321","authenticated-orcid":false,"given":"Hui","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"He","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yushan","family":"Jia","sequence":"additional","affiliation":[{"name":"Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjia","family":"Wang","sequence":"additional","affiliation":[{"name":"MR Research Center China, GE HealthCare, Beijing, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,7,8]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21660"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1001\/archsurg.2007.39"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhep.2021.11.018"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1002\/bjs.6358"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1499-3872(16)60181-9"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1470-2045(15)00198-9"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.amjsurg.2018.07.054"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1097\/SLA.0000000000000858"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2407-11-481"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12072-019-09978-9"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.15142394"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21552"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejca.2011.11.036"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2015151169"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1159\/000494099"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2018.10.011"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.15142394"},{"key":"e_1_3_2_19_2","article-title":"Computational radiomics system to decode the radiographic phenotype","volume":"77","author":"Griethuysen JJM","year":"2017","unstructured":"Griethuysen JJM, Fedorov A, Parmar C, et al. 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