Repeatability of prostate MRI-based radiomics features: The influence of lesion segmentation volume

MRI radiomics is an effective tool for assessing prostate cancer. The volume of the region of interest (ROI) in prostate cancer lesions varies among patients, which may affect the intra-observer repeatability of radiomics features. The aim of this study was to evaluate the impact of varying prostate lesion ROI volumes on the intra-observer repeatability of radiomics features in prostate MRI. This study involved 337 men from the ProstateX dataset, all with a PI-RADS score of 3 or higher who underwent MRI-guided targeted biopsy. Imaging was performed using a 3 T MRI with T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and ADC maps. Prostate lesions were manually segmented by three qualified observers, and the Sørensen-Dice coefficient assessed the similarity of the segmentations. Lesions were categorized into five groups based on average ROI volume: A (0–500 mm³), B (500–1000 mm³), C (1000–1500 mm³), D (1500–2000 mm³), and E (> 2000 mm³). Intra-class correlation coefficients (ICC) evaluated intra-observer repeatability, while Kendall correlation analysis explored the relationship between repeatability and ROI volume. After preprocessing, radiomics features were extracted from T2WI and ADC maps for further analysis, with P < 0.05 considered statistically significant. Group E had the highest repeatability of radiomics features on T2WI (83.1 % with ICC ≥ 0.75) and ADC map (81.3 % with ICC ≥ 0.75). In contrast, Group A had the lowest repeatability on T2WI (46.6 % with ICC ≥ 0.75) and ADC map (28.3 % with ICC ≥ 0.75). Furthermore, ROI volume showed a significant positive correlation with repeatability (p < 0.01). The intra-observer repeatability of radiomics features is significantly positively correlated with the volume of the prostate lesion ROI, highlighting the importance of considering ROI volume as a potential confounding factor in study design to enhance the reliability of radiomics analyses. • Intra-observer repeatability improves with larger lesion volumes. • ADC-derived features are more affected by lesion volume than T2-weighted imaging features. • First-order features show stable repeatability across different volumes, unlike shape and texture features. • Consider lesion volume impact in future radiomics research.