使用基于影像特征的模型预测接受 CAR-T 治疗的 B 细胞淋巴瘤患者的生存、神经毒性与缓解情况

This multicentre retrospective observational 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).

Sixty-five patients of R/R B-cell lymphoma treated with CAR-T cells in two centres were included. Pre-infusion [ 18 F]FDG PET/CT scans and clinical data were systematically collected, and imaging features, including kurtosis, entropy, maximum diameter, standardized uptake value (SUV) related features (SUV max , SUV mean , SUV std , SUV median , SUV p25 , SUV p75 ), total metabolic tumour volume (MTV total ), and total lesion glycolysis (TLG total ), were extracted using the Quibim platform. The median age was 62 (range 21-76) years and 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 Cox proportional-hazards models for CAR-T response at 3 and 6 months demonstrated high accuracy (AUC: 0.754 and 0.818, respectively). Median predicted OS after CAR-T therapy was 4.73 months for high MTV total and 37.55 months for low MTV total . Median predicted PFS was 2.73 months for high MTV total and 11.83 months for low MTV total . 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.

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 MTV total 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.