{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T18:56:02Z","timestamp":1788548162595,"version":"build-2803163510"},"reference-count":35,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T00:00:00Z","timestamp":1778716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100015550","name":"Ministry of Health","doi-asserted-by":"publisher","award":["CUP J33C23001590001"],"award-info":[{"award-number":["CUP J33C23001590001"]}],"id":[{"id":"10.13039\/501100015550","id-type":"DOI","asserted-by":"publisher"}]},{"award":["CUP J33C23001590001"],"award-info":[{"award-number":["CUP J33C23001590001"]}],"id":[{"id":"https:\/\/ror.org\/00789fa95","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Background\/Objectives: Dental metallic implants cause severe streaking artifacts in kilovoltage CT (kVCT), compromising dose calculation in radiotherapy (RT) treatment planning. The purpose of this study is to assess the dosimetric agreement of synthetic MVCT (sMVCT) images generated from artifact-affected kVCT using a deep learning network with respect to true MVCT (tMVCT) acquired at the treatment machine. Methods: Nineteen head and neck cancer patients with dental metallic implants treated with RT were included. Planning kVCT images were converted to sMVCT using Metal Artifact Reduction through Domain Transformation Network (MAR-DTN), a UNet-inspired deep learning network. The sMVCT images were rigidly registered to true MVCT (tMVCT) acquired on the Hi-Art II Tomotherapy system. Mean Hounsfield Unit (HU) values were compared across seven structures (thyroid, bilateral parotids, brainstem, spinal cord, GTV, PTV70) using pairwise Wilcoxon tests and Two One-Sided Tests (TOST) for statistical equivalence within a pre-specified margin of \u00b120 HU (corresponding to a 2% deviation in physical density). Dose distributions were recalculated on sMVCT using the AAA algorithm and compared to reference tMVCT-based plans via dose\u2013volume histogram (DVH) metrics, evaluated for equivalence by TOST within a margin of \u00b12% of the prescribed dose (\u00b1142 cGy of 70.95 Gy), and via 3D gamma index, evaluated by one-sided non-inferiority test against the clinically accepted thresholds of 90% (2 mm\/2%) and 95% (3 mm\/3%). A pre-specified sensitivity analysis was performed by repeating all comparisons on the strictly independent sub-cohort (n = 16) excluding three patients drawn from the MAR-DTN training set. Results: All seven anatomical structures showed statistical equivalence between sMVCT and tMVCT under the \u00b120 HU margin (TOST p &lt; 0.05; mean HU differences in the range \u22121.1 to +8.4 HU; all Wilcoxon p &gt; 0.05). All nine DVH metrics achieved formal dosimetric equivalence within \u00b12% of the prescribed dose (TOST p &lt; 0.05). Mean 3D gamma pass rates were 94.3% (95% CI: 89.3\u201397.1) for the 2 mm\/2% criterion and 97.6% (95% CI: 94.8\u201399.0) for the 3 mm\/3% criterion, both formally non-inferior to the respective clinical thresholds (p &lt; 0.0001). Residual gamma failures were concentrated at the patient surface, consistent with inter-session repositioning uncertainty rather than errors in synthetic image generation. Sensitivity analysis on the n = 16 sub-cohort confirmed all conclusions, with mean HU and DVH differences smaller than in the full cohort for the structures showing the largest mean differences, and comparable for the remaining structures, with all TOST equivalence and gamma non-inferiority tests confirmed in both cohorts. Conclusions: sMVCT images generated via MAR-DTN show dosimetric agreement with physically acquired tMVCT in head and neck patients with dental implants, formally demonstrated by TOST equivalence within \u00b12% of prescribed dose for all DVH metrics. The combined HU and gamma index framework presented here represents a promising quality assurance approach for AI-based synthetic imaging tools in radiotherapy, pending validation in larger prospective multicentre cohorts.<\/jats:p>","DOI":"10.3390\/cancers18101603","type":"journal-article","created":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T16:27:56Z","timestamp":1778776076000},"page":"1603","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Validation of Synthetic Megavoltage Computed Tomography (MVCT) for Dose Calculation in Radiotherapy Treatment Planning"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-4115-2732","authenticated-orcid":false,"given":"Aurora","family":"Corso","sequence":"first","affiliation":[{"name":"Medical Physics Department, Centro di Riferimento Oncologico di Aviano IRCCS, 33081 Aviano, Italy"},{"name":"Scuola di Specializzazione di Fisica Sanitaria, Universit\u00e0 di Padova, 35122 Padova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6962-8643","authenticated-orcid":false,"given":"Niki","family":"Martinel","sequence":"additional","affiliation":[{"name":"Machine Learning and Perception Lab, Universit\u00e0 degli Studi di Udine, 33100 Udine, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2935-0409","authenticated-orcid":false,"given":"Mubashara","family":"Rehman","sequence":"additional","affiliation":[{"name":"Machine Learning and Perception Lab, Universit\u00e0 degli Studi di Udine, 33100 Udine, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7452-347X","authenticated-orcid":false,"given":"Joseph","family":"Stancanello","sequence":"additional","affiliation":[{"name":"Elekta SA, 92100 Boulogne-Billancourt, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4503-7483","authenticated-orcid":false,"given":"Christian","family":"Micheloni","sequence":"additional","affiliation":[{"name":"Machine Learning and Perception Lab, Universit\u00e0 degli Studi di Udine, 33100 Udine, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cristian","family":"Deana","sequence":"additional","affiliation":[{"name":"Medical Physics Department, Centro di Riferimento Oncologico di Aviano IRCCS, 33081 Aviano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7664-883X","authenticated-orcid":false,"given":"Cristina","family":"Cappelletto","sequence":"additional","affiliation":[{"name":"Medical Physics Department, Centro di Riferimento Oncologico di Aviano IRCCS, 33081 Aviano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1802-0627","authenticated-orcid":false,"given":"Paola","family":"Chiovati","sequence":"additional","affiliation":[{"name":"Medical Physics Department, Centro di Riferimento Oncologico di Aviano IRCCS, 33081 Aviano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7772-0960","authenticated-orcid":false,"given":"Riccardo","family":"Spizzo","sequence":"additional","affiliation":[{"name":"Molecular Oncology Division, Centro di Riferimento Oncologico di Aviano IRCCS, 33081 Aviano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9677-3176","authenticated-orcid":false,"given":"Giuseppe","family":"Fanetti","sequence":"additional","affiliation":[{"name":"Radiation Oncology Department, Centro di Riferimento Oncologico di Aviano IRCCS, 33081 Aviano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8295-3037","authenticated-orcid":false,"given":"Andrea","family":"Dassie","sequence":"additional","affiliation":[{"name":"Medical Physics Department, Centro di Riferimento Oncologico di Aviano IRCCS, 33081 Aviano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1711-4242","authenticated-orcid":false,"given":"Michele","family":"Avanzo","sequence":"additional","affiliation":[{"name":"Medical Physics Department, Centro di Riferimento Oncologico di Aviano IRCCS, 33081 Aviano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/s13246-013-0197-x","article-title":"The Appearance and Effects of Metallic Implants in CT Images","volume":"36","author":"Kairn","year":"2013","journal-title":"Australas. 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