{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T03:56:47Z","timestamp":1776139007016,"version":"3.50.1"},"reference-count":52,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T00:00:00Z","timestamp":1759363200000},"content-version":"vor","delay-in-days":1,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"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":["Veterinary Surgery"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To develop a computed tomography (CT)\u2010radiomics\u2010based machine\u2010learning algorithm for prediction of functional recovery in paraplegic dogs with acute intervertebral disc extrusion (IVDE).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study design<\/jats:title>\n                    <jats:p>Multivariable prediction model development.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Sample population<\/jats:title>\n                    <jats:p>Paraplegic dogs with acute IVDE: 128 deep\u2010pain positive and 86 deep\u2010pain negative (DPN).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Radiomics features from noncontrast CT were combined with deep\u2010pain perception in an extreme gradient algorithm using an 80:20 train\u2013test split. Model performance was assessed on the independent test set (Test\n                      <jats:sub>full<\/jats:sub>\n                      ) and on the test set of DPN dogs (Test\n                      <jats:sub>DPN<\/jats:sub>\n                      ). Deep\u2010pain perception alone served as the control.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Recovery of ambulation was recorded in 165\/214 dogs (77.1%) after decompressive surgery. The model had an area under the receiver operating characteristic curve (AUC) of .9118 (95% CI: .8366\u2013.9872), accuracy of 86.1% (95% CI: 74.4%\u201395.4%), sensitivity of 82.4% (95% CI: 68.6%\u201393.9%), and specificity of 100.0% (95% CI: 100.0%\u2013100.0%) on Test\n                      <jats:sub>full<\/jats:sub>\n                      , and an AUC of .7692 (95% CI: .6250\u2013.9000), accuracy of 72.7% (95% CI: 50.0%\u201390.9%), sensitivity of 53.8% (95% CI: 25.0%\u201380.0%), and specificity of 100.0% (95% CI: 100.0%\u2013100.0%) on Test\n                      <jats:sub>DPN<\/jats:sub>\n                      . Deep\u2010pain perception had an AUC of .8088 (95% CI: .7273\u2013.8871), accuracy of 69.8% (95% CI: 55.8%\u201383.7%), sensitivity of 61.8% (95% CI: 45.5%\u201377.4%), and specificity of 100.0% (95% CI: 100.0%\u2013100.0%), which was different from that of the model (\n                      <jats:italic>p<\/jats:italic>\n                      = .02).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Noncontrast CT\u2010based radiomics provided prognostic information in dogs with severe spinal cord injury secondary to acute intervertebral disc extrusion. The model outperformed deep\u2010pain perception alone in identifying dogs that recovered ambulation following decompressive surgery.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Clinical significance<\/jats:title>\n                    <jats:p>Radiomics features from noncontrast CT, when integrated into a multimodal machine\u2010learning algorithm, may be useful as an assistive tool for surgical decision making.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/vsu.70016","type":"journal-article","created":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T08:10:32Z","timestamp":1759392632000},"page":"1305-1315","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine learning and quantitative computed tomography radiomics prediction of postoperative functional recovery in paraplegic dogs"],"prefix":"10.1111","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0215-4997","authenticated-orcid":false,"given":"Daniel","family":"Low","sequence":"first","affiliation":[{"name":"Frank. 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