RESUMO
PURPOSE: Focal pattern in multiple myeloma (MM) seems to be related to poorer survival and differentiation from diffuse to focal pattern on computed tomography (CT) has inter-reader variability. We postulated that a Radiomic approach could help radiologists in differentiating diffuse from focal patterns on CT. METHODS: We retrospectively reviewed imaging data of 70 patients with MM with CT, PET-CT or MRI available before bone marrow transplant. Two general radiologist evaluated, in consensus, CT images to define a focal (at least one lytic lesion >5â¯mm in diameter) or a diffuse (lesions <5â¯mm, not osteoporosis) pattern. Nâ¯=â¯104 Radiomics features were extracted and evaluated with an open source software. RESULTS: The pathological group included: 22 diffuse and 39 focal patterns. After feature reduction, 9 features were different (pâ¯<â¯0.05) in the diffuse and focal patterns (nâ¯=â¯2/9 features were Shape-based: MajorAxisLength and Sphericity; nâ¯=â¯7/9 were Gray Level Run Length Matrix (Glrlm)). AUC of the Radiologists versus Reference Standard was 0.64 (95 % CI: (0.49-0.78) pâ¯=â¯0.20. AUC of the best 4 features (MajorAxisLength, Median, SizeZoneNonUniformity, ZoneEntropy) were: 0.73 (95 % CI: 0.58-0.88); 0.71 (95 % CI: 0.54-0.88); 0.79 (95 % CI: 0.66-0.92); 0.68 (95 % CI: 0.53-0.83) respectively. CONCLUSION: A Radiomics approach improves radiological evaluation of focal and diffuse pattern of MM on CT.