Baseline 18F-FDG PET/CT radiomics for prognosis prediction in diffuse large B cell lymphoma with extranodal involvement

被引:2
作者
Jing, Fenglian [1 ]
Zhang, Xinchao [3 ]
Liu, Yunuan [1 ]
Chen, Xiaolin [1 ]
Zhao, Jianqiang [1 ]
Zhao, Xinming [1 ,2 ]
Chen, Xiaoshan [1 ]
Yuan, Huiqing [1 ]
Dai, Meng [1 ]
Wang, Na [1 ]
Zhang, Zhaoqi [1 ]
Zhang, Jingmian [1 ]
机构
[1] Hebei Med Univ, Dept Nucl Med, Hosp 4, 12 Jiankang Rd, Shijiazhuang 050011, Hebei, Peoples R China
[2] Hebei Prov Key Lab Tumor Microenvironm & Drug Resi, Shijiazhuang 050011, Hebei, Peoples R China
[3] Hebei Gen Hosp, Dept Nucl Med, Shijiazhuang 050000, Hebei, Peoples R China
关键词
Diffuse large B-cell lymphoma; Extranodal involvement; PET/CT; Radiomics; Prognosis; TUMOR BURDEN; IPI; IMPACT;
D O I
10.1007/s12094-024-03633-y
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Purpose The objective of this investigation is to explore the capability of baseline F-18-FDG PET/CT radiomics to predict the prognosis of diffuse large B-cell lymphoma (DLBCL) with extranodal involvement (ENI). Methods 126 patients diagnosed with DLBCL with ENI were included in the cohort. The least absolute shrinkage and selection operator (LASSO) Cox regression was utilized to refine the optimum subset from the 1328 features. Cox regression analyses were employed to discern significant clinical variables and conventional PET parameters, which were then employed with radiomics score to develop combined model for predicting both progression-free survival (PFS) and overall survival (OS). The fitness and the predictive capability of the models were assessed via the Akaike information criterion (AIC) and concordance index (C-index). Results 62 patients experienced disease recurrence or progression and 28 patients ultimately died. The combined model exhibited a lower AIC value compared to the radiomics model and SDmax/clinical variables for both PFS (507.101 vs. 510.658 vs. 525.506) and OS (215.667 vs. 230.556 vs. 219.313), respectively. The C-indices of the combined model, radiomics model, and SDmax/clinical variables were 0.724, 0.704, and 0.615 for PFS, and 0.842, 0.744, and 0.792 for OS, respectively. Kaplan--Meier curves showed significantly higher rates of relapse and mortality among patients classified as high-risk compared to those classified as low-risk (all P < 0.05). Conclusions The combined model of clinical variables, conventional PET parameters, and baseline PET/CT radiomics features demonstrates a higher accuracy in predicting the prognosis of DLBCL with ENI.
引用
收藏
页码:727 / 735
页数:9
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