Predicting survival, neurotoxicity and response in B-Cell lymphoma patients treated with CAR-T therapy using an imaging features-based model

Abstract Background: This study aims to develop imaging-based prognostic and predictive models for relapsed/refractory (R/R) B-cell lymphoma patients undergoing CAR-T therapy by integrating clinical data and imaging features. Specifically, our aim was to predict 3- and 6-month treatment response, overall survival (OS), progression-free survival (PFS), and the occurrence of the immune effector cell-associated neurotoxicity syndrome (ICANS). Methods: This multicentre retrospective observational study includes 65 patients of R/R B-cell lymphoma treated with CAR-T cells in two centres. Pre-infusion 18F-FDG PET/CT scans and clinical data were systematically collected. Imaging features were extracted using the Quibim platform. Logistic regression was employed for predicting ICANS and CAR-T response, while univariate and multivariate analyses Cox proportional-hazards models were performed for survival prediction. Models with best overall fit based on Akaike information criterion and with 10-fold repeated cross-validation were selected. Results: Sixty-five patients with a median age of 62 (range 21–76) years were evaluated. The median follow-up for survivors was 10.47 (range 0.20–45.80) months. A logistic regression model accurately predicted neurotoxicity (AUC: 0.830), and models for CAR-T response at 3 and 6 months demonstrated high accuracy (AUC: 0.928 and 0.940, respectively). Median OS after CAR-T therapy was 4.73 months for high total metabolic tumour volume (MTVtotal) and 37.55 months for low MTVtotal. Predicted PFS was 2.73 months for high MTVtotal and 11.83 months for low MTVtotal. For all outcomes, predictive models, combining imaging features and clinical variables, showed improved accuracy compared to models using only clinical variables or imaging features alone. Conclusion: This study successfully integrates imaging features and clinical variables to predict outcomes in R/R B-cell lymphoma patients undergoing CAR-T. Notably, the identified MTVtotal cut-off effectively stratifies patients, as evidenced by significant differences in OS and PFS. Additionally, the predictive models for neurotoxicity and CAR-T response show promising accuracy. This comprehensive approach holds promise for risk stratification and personalized treatment strategies which may become a helpful tool for optimizing CAR-T outcomes in R/R lymphoma patients.