Cone-beam computed tomography radiomics for differentiating clinicoradiologic labels of osteosclerosis, cemento-osseous dysplasia and odontoma: an internal model-development study

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ID: 333792
2026
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Abstract
Abstract Objectives To develop and internally validate cone-beam computed tomography radiomics for recorded clinicoradiologic classification of osteosclerosis, cemento-osseous dysplasia and odontoma, with secondary same-case three-dimensional convolutional neural-network benchmarking. Methods This retrospective single-centre study included 126 lesions from 126 patients. From manual three-dimensional segmentations, 107 original radiomics features were extracted. A class-weighted least absolute shrinkage and selection operator one-vs-rest logistic-regression model was evaluated using 100 repeats of stratified five-fold held-out resampling. No independent histopathology report was retrievable in the retained study archive. A secondary strict 124-lesion three-dimensional analysis used 0.30-mm isotropic variable-size lesion-centred inputs, at least 5 mm of physical context and nested architecture/epoch selection; locked radiomics was evaluated on the same cases and outer folds. Results Primary radiomics achieved accuracy 0.825, balanced accuracy 0.842, macro F1-score 0.834 and macro area under the curve 0.932. In the matched 124-lesion analysis, macro area under the curve was 0.935 (95% bias-corrected and accelerated confidence interval 0.889-0.963) for radiomics and 0.601 (0.516-0.682) for the nested three-dimensional network. The network showed marked odontoma-class collapse (sensitivity 1/22, 0.045). Conclusions Radiomics showed promising internal discrimination of the recorded labels, whereas the secondary three-dimensional benchmark was unstable for odontoma in this small cohort. These findings do not establish diagnostic accuracy against histopathology or general algorithmic superiority; external validation, standardised imaging and stronger reference standards are required. Advances in knowledge This study extends cone-beam computed tomography radiomics to radiopaque/mineralised jaw-lesion recorded labels and reports a same-case nested three-dimensional benchmark with explicit disclosure of class-specific failure.
Reference Key
openalex_W7223474601 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Alperen Tekın, Belde Arsan, Büşra Erdoğan, Burcu Sümer
Journal dentomaxillofacial radiology
Year 2026
DOI
10.1093/dmfr/twag067
URL
https://doi.org/10.1093/dmfr/twag067
Keywords Keywords not found

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