Balagurunathan Yoganand, Wei Zhouping, Qi Jin, Thompson Zachary, Dean Erin, Lu Hong, Vardhanabhuti Saran, Corallo Salvatore, Choi Jung W, Kim Jenny J, Mattie Mike, Jain Michael, Locke Frederick L
Department of Machine Learning, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
Department of Cancer Physiology, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
Front Oncol. 2024 Nov 25;14:1485039. doi: 10.3389/fonc.2024.1485039. eCollection 2024.
Relapsed and refractory Diffuse large B cell lymphoma (DLBCL) can be successfully treated with axicabtagene ciloleucel (axi-cel), a CD19-directed autologous chimeric antigen receptor T cell (CAR-T) therapy. Diagnostic image-based features could help identify the patients who would clinically respond to this advanced immunotherapy.
The aim of this study was to establish a radiomic image feature-based signature derived from positron emission tomography/computed tomography (PET/CT), including metabolic tumor burden, which can predict a durable response to CAR-T therapy in refractory/relapsed DLBCL.
We conducted a retrospective review of 155 patients with relapsed/refractory DLBCL treated with axi-cel CAR-T therapy. The patients' disease involvement was evaluated based on nodal or extranodal sites. A sub-cohort of these patients with at least one nodal lesion (n=124) was assessed, while an overlapping sub-cohort (n=94) had at least one extranodal lesion. The lesion regions were characterized using 306 quantitative imaging metrics for PET images and CT images independently. Principal component (PC) analysis was performed to reduce the dimensionality in feature-based functional categories: size (n=38), shape (n=9), and texture (n=259). The selected features were used to build prediction models for survival at 1 year and tested for prognosis to overall/progression-free survival (OS/PFS) using a Kaplan-Meier (KM) plot.
The Shape-based PC features of the largest extranodal lesion on PET were predictive of 1-year survival (AUC 0.68 [0.43,0.94]) and prognostic of OS/PFS (p<0.018). Metabolic tumor volume (MTV) was an independent predictor with an area under the curve (AUC) of 0.74 [0.58, 0.87]. Combining these features improved the predictor performance (AUC of 0.78 [0.7, 0.87]). Additionally, the Shape-based PC features were unrelated to total MTV (Spearman's ρ of 0.359, p≤ 0.001).
Our study found that shape-based radiomic features on PET imaging were predictive of treatment outcome (1-year survival) and prognostic of overall survival. We also found non-size-based radiomic predictors that had comparable performance to MTV and provided complementary information to improve the predictability of treatment outcomes.
复发难治性弥漫性大B细胞淋巴瘤（DLBCL）可通过靶向CD19的自体嵌合抗原受体T细胞（CAR-T）疗法axi-cel成功治疗。基于诊断图像的特征有助于识别对这种先进免疫疗法有临床反应的患者。
本研究的目的是建立一种基于正电子发射断层扫描/计算机断层扫描（PET/CT）的影像组学图像特征标志物，包括代谢肿瘤负荷，以预测难治性/复发性DLBCL患者对CAR-T疗法的持久反应。
我们对155例接受axi-cel CAR-T疗法治疗的复发/难治性DLBCL患者进行了回顾性研究。根据淋巴结或结外部位评估患者的疾病累及情况。对这些患者中至少有一个淋巴结病变的亚组（n = 124）进行了评估，而一个重叠亚组（n = 94）至少有一个结外病变。分别使用306个PET图像和CT图像的定量成像指标对病变区域进行特征描述。进行主成分（PC）分析以降低基于特征的功能类别中的维度：大小（n = 38）、形状（n = 9）和纹理（n = 259）。所选特征用于构建1年生存率的预测模型，并使用Kaplan-Meier（KM）图对总生存/无进展生存（OS/PFS）的预后进行测试。
PET上最大结外病变的基于形状的PC特征可预测1年生存率（AUC 0.68 [0.43, 0.94]），并对OS/PFS具有预后价值（p < 0.018）。代谢肿瘤体积（MTV）是一个独立预测因子，曲线下面积（AUC）为0.74 [0.58, 0.87]。结合这些特征可提高预测性能（AUC为0.78 [0.7, 0.87]）。此外，基于形状的PC特征与总MTV无关（Spearman's ρ为0.359，p≤0.001）。
我们的研究发现，PET成像上基于形状的影像组学特征可预测治疗结果（1年生存率）并对总生存具有预后价值。我们还发现了与MTV性能相当的非基于大小的影像组学预测因子，并提供了补充信息以提高治疗结果的可预测性。
