Anne-Ségolène Cottereau1,2, Christophe Nioche2, Anne-Sophie Dirand2, Jérôme Clerc3, Franck Morschhauser4, Olivier Casasnovas5, Michel Meignan6, Irène Buvat2. 1. Department of Nuclear Medicine, Cochin Hospital, Assistance Publique Hôpitaux de Paris and Paris Descartes University, Paris, France annesegolene.cottereau@aphp.fr. 2. Imagerie Moléculaire In Vivo, CEA, INSERM, Université Paris Sud, CNRS, Université Paris Saclay, Orsay, France. 3. Department of Nuclear Medicine, Cochin Hospital, Assistance Publique Hôpitaux de Paris and Paris Descartes University, Paris, France. 4. Groupe de Recherche sur les formes Injectables et les Technologies Associées, Université Lille, CHU Lille, Lille, France. 5. Hematology Department, Dijon Hospital, and INSERM 1231, Bourgogne Franche Comte University, Dijon, France; and. 6. LYSA Imaging, Creteil, France.
Abstract
We assessed the predictive value of new radiomic features characterizing lesion dissemination in baseline 18F-FDG PET and tested whether combining them with baseline metabolic tumor volume (MTV) could improve prediction of progression-free survival (PFS) and overall survival (OS) in diffuse large B-cell lymphoma (DLBCL) patients. Methods: From the LNH073B trial (NCT00498043), patients with advanced-stage DLCBL and 18F-FDG PET/CT images available for review were selected. MTV and several radiomic features, including the distance between the 2 lesions that were farthest apart (Dmaxpatient), were calculated. Receiver-operating-characteristic analysis was used to determine the optimal cutoff for quantitative variables, and Kaplan-Meier survival analyses were performed. Results: With a median age of 46 y, 95 patients were enrolled, half of them treated with R-CHOP biweekly (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) and the other half with R-ACVBP (rituximab, doxorubicin, cyclophosphamide, vindesine, bleomycin, and prednisone), with no significant impact on outcome. Median MTV and Dmaxpatient were 375 cm3 and 45 cm, respectively. The median follow-up was 44 mo. High MTV and Dmaxpatient were adverse factors for PFS (P = 0.027 and P = 0.0003, respectively) and for OS (P = 0.0007 and P = 0.0095, respectively). In multivariate analysis, only Dmaxpatient was significantly associated with PFS (P = 0.0014) whereas both factors remained significant for OS (P = 0.037 and P = 0.0029, respectively). Combining MTV (>384 cm3) and Dmaxpatient (>58 cm) yielded 3 risk groups for PFS (P = 0.0003) and OS (P = 0.0011): high with 2 adverse factors (4-y PFS and OS of 50% and 53%, respectively, n = 18), low with no adverse factor (94% and 97%, n = 36), and an intermediate category with 1 adverse factor (73% and 88%, n = 41). Conclusion: Combining MTV with a parameter reflecting the tumor burden dissemination further improves DLBCL patient risk stratification at staging.
We assessed the predictive value of new radiomic features characterizing lesion dissemination in baseline 18F-FDG PET and tested whether combining them with baseline metabolic tumor volume (MTV) could improve prediction of progression-free survival (PFS) and overall survival (OS) in diffuse large B-cell lymphoma (DLBCL) patients. Methods: From the LNH073B trial (NCT00498043), patients with advanced-stage DLCBL and 18F-FDG PET/CT images available for review were selected. MTV and several radiomic features, including the distance between the 2 lesions that were farthest apart (Dmaxpatient), were calculated. Receiver-operating-characteristic analysis was used to determine the optimal cutoff for quantitative variables, and Kaplan-Meier survival analyses were performed. Results: With a median age of 46 y, 95 patients were enrolled, half of them treated with R-CHOP biweekly (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) and the other half with R-ACVBP (rituximab, doxorubicin, cyclophosphamide, vindesine, bleomycin, and prednisone), with no significant impact on outcome. Median MTV and Dmaxpatient were 375 cm3 and 45 cm, respectively. The median follow-up was 44 mo. High MTV and Dmaxpatient were adverse factors for PFS (P = 0.027 and P = 0.0003, respectively) and for OS (P = 0.0007 and P = 0.0095, respectively). In multivariate analysis, only Dmaxpatient was significantly associated with PFS (P = 0.0014) whereas both factors remained significant for OS (P = 0.037 and P = 0.0029, respectively). Combining MTV (>384 cm3) and Dmaxpatient (>58 cm) yielded 3 risk groups for PFS (P = 0.0003) and OS (P = 0.0011): high with 2 adverse factors (4-y PFS and OS of 50% and 53%, respectively, n = 18), low with no adverse factor (94% and 97%, n = 36), and an intermediate category with 1 adverse factor (73% and 88%, n = 41). Conclusion: Combining MTV with a parameter reflecting the tumor burden dissemination further improves DLBCL patient risk stratification at staging.
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