Diagnostic validity and reliability of Osseous Tumour reporting and data system (OT-RADS) in the management of primary bone Tumour.
Year: 2025
Type: article
Study design: Observational Study
Abstract: Purpose: To validate an Osseous Tumour Reporting and Data System (OT-RADS) with the hypothesis that the suggested principles can be used as a trusted guidelines and differentiate benign and malignant bone tumours in a reliable way with a good area under the curve. Methods: This multi-reader cross-sectional validation study focused on evaluating osseous tumours using the OT-RADS classification based on magnetic resonance imaging features and expert consensus. The OT-RADS categories ranged from 0 (incomplete imaging) to VI (known biopsy-proven malignancy). Three blinded readers categorized each tumour, and inter-reader agreement was measured using Intra Class Correlation (ICC) and Conger κ. Diagnostic performance was assessed with the area under the receiver operating curve. The system was dichotomized into benign (I–III) and malignant (IV–V) categories to calculate sensitivity and specificity for accurate tumour classification. Results: Inter reader agreement for OT-RADS (ICC = 0.913), with confidence interval range (0.892:0.942) and binary distinction of benign versus malignant (κ = 0.58) were good to excellent. The sensitivities, specificities, and area under the receiver operating curve of the readers ranged from 81.3-87.5 %,76.5-82.3 and 0.844–0.886 respectively. Conclusions: Osseous Tumour Reporting and Data System lexicon has a great reliability and helps in stratification of tumours into benign and malignant categories. It can be prudently used for accurate characterization of bone tumours. The radiologists can use it in a practical way to guide the management of the patients, improve multidisciplinary communications and impacts. Referring consultants considered OT-RADS a helpful classification for clinical decision –making in bone tumours.
Source: Benha Medical Journal
Institutions: Benha University, Zagazig University
Language: English
Subfield: Rheumatology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4413598941