Osseous Tumor Reporting and Data System—Multireader Validation Study. Issue 4 (July 2021) - Chhabra, Avneesh; Gupta, Anurag; Thakur, Uma; Pezeshk, Parham; Dettori, Nathan; Callan, Alexandra; Xi, Yin; Weatherall, Paul
Abstract : Objective: To develop and validate an Osseous Tumor Reporting and Data System (OT-RADS) with the hypothesis that the proposed guideline is reliable and assists in separating benign from malignant osseous tumors with a good area under the curve, and that could assist further patient management. Methods: In this multireader cross-sectional validation study, an agreement was reached for OT-RADS categories based on previously described magnetic resonance imaging features and consensus of expert musculoskeletal radiologists. World Health Organization classification was used, and a wide spectrum of benign and malignant osseous tumors was evaluated. Magnetic resonance imaging categories were as follows: OT-RADS 0—incomplete imaging; OT-RADS I—negative; OT-RADS II—definitely benign; OT-RADS III—probably benign; OT-RADS IV—suspicious for malignancy or indeterminate; OT-RADS V—highly suggestive of malignancy; and OT-RADS VI—known biopsy-proven malignancy or recurrent malignancy in the tumor bed. Four blinded readers categorized each tumor according to OT-RADS classification. Intraclass correlation (ICC) and Conger κ were used. Diagnostic performance measures including area under the receiver operating curve were reported. Osseous Tumor Reporting and Data System was dichotomized as benign (I–III) and malignant (IV and V) for calculating sensitivity and specificity. Results: Interreader agreement for OT-RADS (ICC = 0.78) and binary distinction of benign versus malignant (κ = 0.67) were good to excellent, while agreement for individual tumor feature characteristics were poor to fair (ICC = 0.25–0.36; κ = 0.16–0.39). The sensitivities, specificities, and area under the receiver operating curve of the readers ranged from 0.93–1.0, 0.71–0.86, and 0.92–0.97, respectively. Conclusions: Osseous Tumor Reporting and Data System lexicon is reliable and helps stratify tumors into benign and malignant categories. It can be practically used by radiologists to guide patient management, improve multidisciplinary communications, and potentially impact outcomes.