Combination of FDG PET/CT Radiomics and Clinical Parameters for Outcome Prediction in Patients with Hodgkin’s Lymphoma

SIMPLE SUMMARY: Hodgkin lymphoma is the most common malignancy of the lymphatic system, usually affecting young people and with favorable response to treatment. Tailored treatment is important in this patient population to achieve good therapy response while not exposing them to higher treatment related toxicity. These patients undergone PET/CT studies at baseline for staging as part of their workup. PET/CT is an hybrid modality including morphological and molecular images and most of the Hodgkin lymphomas are radiotracer avid. Radiomics is a new field analyzing features within the images itself which are not visible to the naked eye. Our hypothesis was that some radiomics features in the PET or CT modality when combined with clinical variables (laboratory, type of tumor, etc.) may help in prediction of how patients would respond to therapy, risk of relapse and if they might need to have additional therapies. ABSTRACT: Purpose: The aim of the study is to evaluate the prognostic value of a joint evaluation of PET and CT radiomics combined with standard clinical parameters in patients with HL. Methods: Overall, 88 patients (42 female and 46 male) with a median age of 43.3 (range 21–85 years) were included. Textural analysis of the PET/CT images was performed using freely available software (LIFE X). 65 radiomic features (RF) were evaluated. Univariate and multivariate models were used to determine the value of clinical characteristics and FDG PET/CT radiomics in outcome prediction. In addition, a binary logistic regression model was used to determine potential predictors for radiotherapy treatment and odds ratios (OR), with 95% confidence intervals (CI) reported. Features relevant to survival outcomes were assessed using Cox proportional hazards to calculate hazard ratios with 95% CI. Results: albumin (p = 0.034) + ALP (p = 0.028) + CT radiomic feature GLRLM GLNU mean (p = 0.012) (Area under the curve (AUC): 95% CI (86.9; 100.0)—Brier score: 3.9, 95% CI (0.1; 7.8) remained significant independent predictors for PFS outcome. PET-SHAPE Sphericity (p = 0.033); CT grey-level zone length matrix with high gray-level zone emphasis (GLZLM SZHGE mean (p = 0.028)); PARAMS XSpatial Resampling (p = 0.0091) as well as hemoglobin results (p = 0.016) remained as independent factors in the final model for a binary outcome as predictors of the need for radiotherapy (AUC = 0.79). Conclusion: We evaluated the value of baseline clinical parameters as well as combined PET and CT radiomics in HL patients for survival and the prediction of the need for radiotherapy treatment. We found that different combinations of all three factors/features were independently predictive of the here evaluated endpoints.