Evaluating the Impact of Partial Volume Correction on FDG PET Radiomics Reproducibility in Lymphoma Lesions

Abstract

To evaluate how partial volume correction (PVC) affects the reproducibility of 18F-FDG PET radiomic features in lymphoma lesions, with respect to lesion volume and tissue type. This single-center retrospective study included 131 newly diagnosed lymphoma patients who underwent baseline 18F-FDG PET/CT. In total, 1,603 lesions (1,302 lymph nodes, 117 spleen/liver, 150 bone, and 34 bone/soft-tissue) were semi-automatically segmented and grouped by volume (<3, 3-10, 10-30, >30 mL) and tissue type. 93 radiomic features were extracted from non-PVC and PVC images processed with the Richardson-Lucy (RL) and Reblurred Van Cittert (RVC) algorithms following IBSI guidelines. Reproducibility was quantified using the coefficient of variation (CoV) and the intraclass correlation coefficient (ICC2, absolute agreement), with statistical comparisons performed via Mann-Whitney U tests and false-discovery-rate (FDR) correction. PVC significantly improved feature reproducibility, particularly for large lesions (>30 mL), with median ICC2>0.90 across most feature categories. Small lesions (<3 mL) showed lower stability (ICC2=0.84-0.94) and higher CoV (0.09-0.21). First-Order and GLCM features were the most robust overall (ICC2=0.92-0.99; CoV=0.07-0.11). Bone and spleen lesions exhibited the highest reproducibility (median ICC2 approx 0.95), whereas lymph-node and liver features were more variable. All volume- and tissue-dependent differences remained significant after FDR correction (p<0.05). PVC using RL and RVC markedly enhances FDG-PET radiomic reproducibility in lymphoma, particularly for larger and structurally uniform lesions. Robust features such as First-Order and GLCM can support standardized radiomics workflows and the development of reliable biomarkers for prognosis and personalized therapy. Multicenter validation is warranted to confirm generalizability beyond a single-center setting.