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However, 30 % of patients require active treatment. Identifying these patients will help upfront to define a personalized treatment approach. This study assessed whether radiomics can predict AS failure in patients with DTF.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This multicenter study included data from the Netherlands (NL), Italy (ITA), and Canada (CAN). The study included patients with extra-abdominal DTF initially managed with AS and baseline MRI. Tumors were segmented using a minimally interactive deep-learning method, and radiomics features were extracted from T1-weighted (T1W) and T2-weighted (T2W) MRI scans. Prediction models to predict AS failure versus no failure were created using various machine-learning approaches. Both an internal cross-validation using all available data and an external leave-one-country-out cross-validation were used to assess model performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The cohort included 200 patients (72 NL, 62 ITA, 66 CAN), with AS failing for 26 % of the patients. Internal validation of the T1W+T2W imaging model resulted in an overall area under the curve (AUC) of 0.69 (95 % confidence interval [CI] 0.60\u20130.79). External validation resulted in an AUC of 0.58 (95 % CI 0.42\u20130.74) in the Dutch cohort, 0.76 (95 % CI 0.60\u20130.91) in the Italian cohort, and 0.77 (95 % CI 0.65\u20130.89) in the Canadian cohort. Adding clinical features did not improve the models\u2019 performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Predicting AS failure with radiomics showed reasonable performance and generalized well to the Italian and Canadian cohorts. Pending improvements to the model or patient selection, the authors\u2019 model shows potential to better identify which DTF patients will benefit from AS and which will not.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1245\/s10434-026-19931-4","type":"journal-article","created":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T16:19:38Z","timestamp":1781194778000},"page":"8591-8600","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Predicting Failure of Active Surveillance in Desmoid-Type Fibromatosis Using Radiomics: An International Multi-center Cohort Study"],"prefix":"10.1245","volume":"33","author":[{"given":"Stefanie N.","family":"Hakkesteegt","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Douwe J.","family":"Spaanderman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chiara","family":"Colombo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne-Rose W.","family":"Schut","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Vanzulli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Barretta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C.","family":"Morosi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Fiore","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Ferguson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harini","family":"Suraweera","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anthony M.","family":"Griffin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lawrence M.","family":"White","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joel","family":"Shapiro","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Danchen","family":"Ge","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dirk J.","family":"Gr\u00fcnhagen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Geert J. 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Niessen is the founder of Quantib and was the scientific lead until 31 January 2023. Jacob J. Visser received a grant to institution from Qure.ai\/Enlitic, consulting fees from Tegus, payment to institution for lectures from Roche, and a travel grant from Qure.ai. He reports participation in a data safety monitoring board or advisory board from Contextflow, Noaber Foundation, and NLC Ventures; leadership or fiduciary role on the steering committee of the PINPOINT Project (payment to institution from AstraZeneca) and RSNA Common Data Elements Steering Committee (unpaid); phantom shares in Contextflow and Quibim; chair of scientific committee EuSoMII (unpaid); chair of ESR value-based radiology subcommittee (unpaid); and membership on an editorial board of\n                      European Journal of Radiology\n                      (unpaid). Stefan Klein is the scientific director of the ICAI lab \u201cTrustworthy AI for MRI,\u201d a public-private research program partially funded by General Electric Healthcare. Douwe J. Spaanderman, Stefan Klein, and Martijn P. A. Starmans received an unrestricted research grant from Stichting Hanarth Fonds, and The Netherlands. Stefan Klein and Martijn P. A. Starmans received funding from the Dutch Research Council (NWO) under the AiNed Fellowship Grants program (project no. NGF.1607.22.025). The remaining authors have no conflicts of interest.","order":1,"name":"Ethics","label":"Disclosure","group":{"name":"EthicsHeading","label":"Ethics"}}]}}