The significant clinical heterogeneity of Multiple Myeloma (MM) patients implies that a set of
consolidated biomarkers is currently missing. Radiomics is an advanced, quantitative
feature-based methodology for image analysis. We assess the feasibility of an AI-based
approach for the automatic stratification of MM patients from CT data, and for the automatic
identification of radiological biomarkers with a possible prognostic value. A retrospective
analysis of n= 33 transplanted MM with focal lesion were performed via an open-source …

Multiple myeloma is a plasma cell dyscrasia characterized by focal and non-focal bone
lesions. Radiomic techniques extract morphological information from computerized
tomography images and exploit them for stratification and risk prediction purposes.
However, few papers so far have applied radiomics to multiple myeloma. A retrospective
study approved by the institutional review board: n= 51 transplanted patients and n= 33
(64%) with focal lesion analyzed via an open-source toolbox that extracted 109 radiomics …