Radiomic Features of (18)F-FDG PET in Hodgkin Lymphoma Are Predictive of Outcomes

PURPOSE: In the present study, we aimed to investigate whether the radiomic features of baseline (18)F-FDG PET can predict the prognosis of Hodgkin lymphoma (HL). METHODS: A total 65 HL patients (training cohort: n = 49; validation cohort: n = 16) were retrospectively enrolled in the present study. A total of 47 radiomic features were extracted from pretreatment PET images. The least absolute shrinkage and selection operator (LASSO) regression was used to select the most useful prognostic features in the training cohort. The distance between the two lesions that were the furthest apart (D(max)) was recorded. The receiver operating characteristic (ROC) curve, Kaplan–Meier method, and Cox proportional hazards model were used to assess the prognostic factors. RESULTS: Long-zone high gray-level emphasis extracted from a gray-level zone-length matrix (LZHGE(GLZLM)) (HR = 9.007; p=0.044) and Dmax (HR = 3.641; p=0.048) were independently correlated with 2-year progression-free survival (PFS). A prognostic stratification model was established based on both risk predictors, which could distinguish three risk categories for PFS (p=0.0002). The 2-year PFS was 100.0%, 64.7%, and 33.3%, respectively. CONCLUSIONS: LZHGE(GLZLM) and Dmax were independent prognostic factors for survival outcomes. Besides, we proposed a prognostic stratification model that could further improve the risk stratification of HL patients.