Zhou Yeye, Li Jihui, Zhang Xiaoyi, Jia Tongtong, Zhang Bin, Dai Na, Sang Shibiao, Deng Shengming
Department of Nuclear Medicine, the First Affiliated Hospital of Soochow University, Suzhou, China.
Department of Nuclear Medicine, Changshu No. 2 People's Hospital, Changshu, China.
Front Oncol. 2022 Feb 7;12:834288. doi: 10.3389/fonc.2022.834288. eCollection 2022.
In the present study, we aimed to evaluate the prognostic value of PET/CT-derived radiomic features for patients with B-cell lymphoma (BCL), who were treated with CD19/CD22 dual-targeted chimeric antigen receptor (CAR) T cells. Moreover, we explored the relationship between baseline radiomic features and the occurrence probability of cytokine release syndrome (CRS).
A total of 24 BCL patients who received F-FDG PET/CT before CAR T-cell infusion were enrolled in the present study. Radiomic features from PET and CT images were extracted using LIFEx software, and the least absolute shrinkage and selection operator (LASSO) regression was used to select the most useful predictive features of progression-free survival (PFS) and overall survival (OS). Receiver operating characteristic curves, Cox proportional hazards model, and Kaplan-Meier curves were conducted to assess the potential prognostic value.
Contrast extracted from neighbourhood grey-level different matrix (NGLDM) was an independent predictor of PFS (HR = 15.16, p = 0.023). MYC and BCL2 double-expressor (DE) was of prognostic significance for PFS (HR = 7.02, p = 0.047) and OS (HR = 10.37, p = 0.041). The combination of NGLDM_Contrast and DE yielded three risk groups with zero (n = 7), one (n = 11), or two (n = 6) factors (p < 0.0001 and p = 0.0004, for PFS and OS), respectively. The PFS was 85.7%, 63.6%, and 0%, respectively, and the OS was 100%, 90.9%, and 16.7%, respectively. Moreover, there was no significant association between PET/CT variables and CRS.
In conclusion, radiomic features extracted from baseline F-FDG PET/CT images in combination with genomic factors could predict the survival outcomes of BCL patients receiving CAR T-cell therapy.
在本研究中,我们旨在评估PET/CT衍生的放射组学特征对接受CD19/CD22双靶点嵌合抗原受体(CAR)T细胞治疗的B细胞淋巴瘤(BCL)患者的预后价值。此外,我们还探讨了基线放射组学特征与细胞因子释放综合征(CRS)发生概率之间的关系。
本研究共纳入24例在CAR T细胞输注前接受F-FDG PET/CT检查的BCL患者。使用LIFEx软件从PET和CT图像中提取放射组学特征,并采用最小绝对收缩和选择算子(LASSO)回归来选择无进展生存期(PFS)和总生存期(OS)最有用的预测特征。通过绘制受试者工作特征曲线、Cox比例风险模型和Kaplan-Meier曲线来评估潜在的预后价值。
从邻域灰度级差异矩阵(NGLDM)中提取的对比度是PFS的独立预测因子(HR = 15.16,p = 0.023)。MYC和BCL2双表达(DE)对PFS(HR = 7.02,p = 0.047)和OS(HR = 10.37,p = 0.041)具有预后意义。NGLDM_对比度和DE的组合产生了三个风险组,分别有零个(n = 7)、一个(n = 11)或两个(n = 6)因素(PFS和OS的p分别为<0.0001和p = 0.0004)。PFS分别为85.7%、63.6%和0%,OS分别为100%、90.9%和16.7%。此外,PET/CT变量与CRS之间无显著关联。
总之,从基线F-FDG PET/CT图像中提取的放射组学特征与基因组因素相结合,可以预测接受CAR T细胞治疗的BCL患者的生存结果。