PREDICTIVE VALUE OF QUANTITATIVE 18F‐FDG‐PET‐CT RADIOMICS ANALYSIS IN 174 PATIENTS WITH RELAPSED/REFRACTORY CLASSICAL HODGKIN LYMPHOMA

Abstract

Introduction: About 20% of patients with classical Hodgkin lymphoma (cHL) relapse or are primary refractory to first-line treatment and require second-line therapy followed by autologous stem cell transplant. There is no one standard second-line therapy and it is possible that not all patients require such an aggressive approach to achieve cure. Quantitative analysis of baseline 18F-FDG-PET-CT scans could provide a comprehensible risk-assessment complementary to clinical risk-factors. Methods: We analysed baseline 18F-FDG-PET-CT scans from r/r cHL patients treated within three clinical trials with ICE, ICE and brentuximab vedotin (BV) or DHAP and BV. For the clinical risk model we used the following parameters: primary refractory vs relapse, age, Ann Arbor stage and B-symptoms. Metabolic tumor volume (MTV) was calculated using a fixed threshold of standard uptake value (SUV) ≥4.0. Radiomics features were extracted in compliance with the Image Biomarker Standardization Initiative. We developed a predictive model for 3-year time to progression (TTP) using logistic regression with backward selection on robust radiomics features, e.g. SUVpeak (highest 1mL region FDG uptake) and several novel dispersity features, representing dissemination and differences in volume and SUV of lesions within a patient. Results were cross-validated (CV) and validated in an independent external cohort. High-risk groups were defined based on the prevalence of events in the training cohort (22/110; 20%). Results: We included 174 r/r cHL patients; n = 110 in the training set (BV-DHAP and BV-ICE cohort) and n = 64 in the validation set (ICE cohort). The clinical model resulted in an area under the curve (AUC) of 0.81 on the training set (tAUC), CV-AUC of 0.76 and AUC of 0.74 on the validation set (vAUC). Radiomics analysis resulted in a selection of 6 PET features: MTV and 5 dispersity features. The radiomics model showed a tAUC of 0.73, CV-AUC of 0.63 and vAUC of 0.70. Combining clinical and radiomics parameters yielded a tAUC of 0.90, CV-AUC of 0.79 and vAUC of 0.77. Using the combined model on the training set, patients in the high-risk group (n = 22) had a 3-year TTP of 38% vs 90% for patients in the low-risk group (n = 88; p < 0.0001; Fig1A). In the validation set, the 3-year TTP was 39% vs 80% for high- (n = 13) and low-risk patients (n = 51; p = 0.0011; Fig1B). In Fig1C we included an example of PET-CT scans of two patients with stage IV disease and a high and low prediction score. EA - previously submitted to EHA 2021. The research was funded by: SHOW foundation (Amsterdam UMC donation fund to support hematology/oncology scientific research) Keywords: Diagnostic and Prognostic Biomarkers, PET-CT, Hodgkin lymphoma No conflicts of interests pertinent to the abstract.