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The preoperative MRI study included post-contrast high-resolution T1-weighted images acquired in all patients. MRI-based depth of invasion (DOI) and tumor dimension\u2014together with shape-based and intensity-based features\u2014were extracted from the lesion volume segmentation. The entire dataset was randomly divided into a training set and a validation set, and the performances of different types of ML algorithms were evaluated and compared.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>MRI-based DOI and tumor dimension together with several shape-based and intensity-based signatures significantly discriminated the pT stage and LN status. The overall accuracy of the model for predicting the pT stage was 0.86 (95%CI, 0.78\u20130.92) and 0.81 (0.64\u20130.91) in the training and validation sets, respectively. There was no improvement in the model performance upon including shape-based and intensity-based features. The model for predicting CLNM based on DOI and tumor dimensions had a fair accuracy of 0.68 (0.57\u20130.78) and 0.69 (0.51\u20130.84) in the training and validation sets, respectively. The shape-based and intensity-based signatures have shown potential for improving the model sensitivity, with a comparable accuracy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusion\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>MRI-based models driven by ML algorithms could stratify patients with OTSCC according to the pT stages. They had a moderate ability to predict cervical lymph node metastasis.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1016\/j.csbj.2023.08.020","type":"journal-article","created":{"date-parts":[[2023,8,24]],"date-time":"2023-08-24T02:18:08Z","timestamp":1692843488000},"page":"4277-4287","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":11,"title":["Magnetic resonance imaging-based prediction models for tumor stage and cervical lymph node metastasis of tongue squamous cell carcinoma"],"prefix":"10.34133","volume":"21","author":[{"given":"Antonello","family":"Vidiri","sequence":"first","affiliation":[{"name":"Radiology and Diagnostic Imaging Department, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi 53, 00144 Rome,Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simona","family":"Marzi","sequence":"additional","affiliation":[{"name":"Medical Physics Laboratory, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi 53, 0 0144 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesca","family":"Piludu","sequence":"additional","affiliation":[{"name":"Radiology and Diagnostic Imaging Department, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi 53, 00144 Rome,Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sonia","family":"Lucchese","sequence":"additional","affiliation":[{"name":"Radiology and Diagnostic Imaging Department, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi 53, 00144 Rome,Italy"},{"name":"Scuola di Specializzazione in Radiodiagnostica, Sapienza University of Rome, Policlinico Umberto I, Viale Regina Elena 324, 00161 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincenzo","family":"Dolcetti","sequence":"additional","affiliation":[{"name":"Radiology and Diagnostic Imaging Department, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi 53, 00144 Rome,Italy"},{"name":"Scuola di Specializzazione in Radiodiagnostica, Sapienza University of Rome, Policlinico Umberto I, Viale Regina Elena 324, 00161 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eleonora","family":"Polito","sequence":"additional","affiliation":[{"name":"Radiology and Diagnostic Imaging Department, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi 53, 00144 Rome,Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Mazzola","sequence":"additional","affiliation":[{"name":"Department of Otolaryngology and Head and Neck Surgery, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi 53, 00144 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paolo","family":"Marchesi","sequence":"additional","affiliation":[{"name":"Department of Otolaryngology and Head and Neck Surgery, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi 53, 00144 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elisabetta","family":"Merenda","sequence":"additional","affiliation":[{"name":"Department of Radiological, Oncological and Pathological Sciences, Sapienza University of Rome, Policlinico Umberto I, 00161 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isabella","family":"Sperduti","sequence":"additional","affiliation":[{"name":"Biostatistics Unit, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi 53, 00144 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raul","family":"Pellini","sequence":"additional","affiliation":[{"name":"Department of Otolaryngology and Head and Neck Surgery, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi 53, 00144 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Renato","family":"Covello","sequence":"additional","affiliation":[{"name":"Department of Pathology, IRCCS Regina Elena National Cancer Institute, Via Elio Chianesi 53, 00144 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"221","published-online":{"date-parts":[[2023,9,4]]},"reference":[{"key":"e_1_3_4_2_2","first-page":"7","article-title":"Cancer statistics, 2022","volume":"72","author":"Siegel R.L.","year":"2022","unstructured":"Siegel R.L., Miller K.D., Fuchs H.E. and Jemal A.: Cancer statistics, 2022. 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