基于 PET 的影像组学特征可预测大 B 细胞淋巴瘤患者对 CAR-T 细胞治疗的持久缓解

Chimeric antigen receptor (CAR) T-cell therapy is a promising treatment option for relapsed or refractory (R/R) large B-cell lymphoma (LBCL).

However, only a subset of patients will present long-term benefit. In this study, we explored the potential of PET-based radiomics to predict treatment outcomes with the aim of improving patient selection for CAR T-cell therapy.

We conducted a single-center study including 93 consecutive R/R LBCL patients who received a CAR T-cell infusion from 2018 to 2021, split in training set (73 patients) and test set (20 patients). Radiomics features were extracted from baseline PET scans and clinical benefit was defined based on median progression-free survival (PFS). Cox regression models including the radiomics signature, conventional PET biomarkers and clinical variables were performed for most relevant outcomes.

A radiomics signature including 4 PET-based parameters achieved an AUC = 0. 73 for predicting clinical benefit in the test set, outperforming the predictive value of conventional PET biomarkers (total metabolic tumor volume [TMTV]: AUC = 0. 66 and maximum standardized uptake value [SUV max ]: AUC = 0. 59). A high radiomics score was also associated with longer PFS and OS in the multivariable analysis.

In conclusion, the PET-based radiomics signature predicted efficacy of CAR T-cell therapy and outperformed conventional PET biomarkers in our cohort of LBCL patients.