Ability of ¹⁸F-FDG PET/CT Radiomic Features to Distinguish Breast Carcinoma from Breast Lymphoma

Purpose. To investigate the value of SUV metrics and radiomic features based on the ability of ¹⁸F-FDG PET/CT in differentiating between breast lymphoma and breast carcinoma. Methods. A total of 67 breast nodules from 44 patients who underwent ¹⁸F-FDG PET/CT pretreatment were retrospectively analyzed. Radiomic parameters and SUV metrics were extracted using the LIFEx package on PET and CT images. All texture parameters were divided into six groups: histogram (HISTO), SHAPE, gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), neighborhood gray-level different matrix (NGLDM), and gray-level zone-length matrix (GLZLM). Receiver operating characteristics (ROC) curves were generated to evaluate the discriminative ability of each parameter, and the optimal parameter in each group was selected to generate a new predictive variable by using binary logistic regression. PET predictive variable, CT predictive variable, the combination of PET and CT predictive variables, and SUV_max were compared in terms of areas under the curve (AUCs), sensitivity, specificity, and accuracy. Results. Except for SUVmin (p=0.971), the averages of FDG uptake metrics of lymphoma were significantly higher than those of carcinoma (p≤0.001), with the following median values: SUV_mean, 4.75 versus 2.38 g/ml (P<0.001); SUV_std, 2.04 versus 0.88 g/ml (P=0.001); SUV_max, 10.69 versus 4.76 g/ml (P=0.001); SUV_peak, 9.15 versus 2.78 g/ml (P<0.001); TLG, 42.24 versus 9.90 (P<0.001). In the ROC curves analysis based on radiomic features and SUV_max, the AUC for SUV_max was 0.747, for CT texture parameters was 0.729, for PET texture parameters was 0.751, and for the combination of CT and PET texture parameters was 0.771. Conclusion. The SUV metrics in ¹⁸FDG PET/CT images showed a potential ability in the differentiation between breast lymphoma and carcinoma. The combination of SUV_max and PET/CT texture analysis may be promising to provide an effectively discriminant modality for the differential diagnosis of breast lymphoma and carcinoma, even for the differentiation of subtypes of lymphoma.