A Prognostic Model Incorporating Tumor Lesion Morphology And Texture Features Identifies High-Risk Patient Subpopulations In De Novo Dlbcl And Fl

Background: Despite effective first-line (1L) treatment options for patients with NHL almost 40% of patients with diffuse large B cell lymphoma (DLBCL) will have a poor response or disease progression after 1L treatment. In follicular lymphoma (FL) 15-20% of patients experience early relapse, and almost 8% may develop transformation to more aggressive forms of the disease (such as DLBCL) after 1L treatment. More accurate identification of patients at high-risk for a poor prognosis with the standard of care could lead to improved outcomes. Although the International Prognostic Index (IPI) and its FL extension (FLIPI) are often used to stratify patients by prognosis, they have relatively modest sensitivity and specificity for predicting individualized risk. Radiomics is a promising approach to improve upon existing prognostic models because it provides a comprehensive quantification of tumor lesion morphology and texture derived from FDG-PET scans and may provide new and important information about disease biology and progression risk on an individual level.