AI and Rare Diseases ── Kidney, liver and gut ── 2026-11-04
Rare kidney, liver and gastrointestinal diseases: treatment, trials and AI
- Abstract
RATIONALE AND OBJECTIVES: To assess a noninvasive ultrasound habitat radiomics approach with automatic kidney segmentation for distinguishing pediatric Henoch-Schonlein purpura nephritis (HSPN) from immunoglobulin A nephropathy (IgAN). MATERIALS AND METHODS: This retrospective multicenter study included 592 biopsy-confirmed pediatric patients from three centers (HSPN, n = 338; IgAN, n = 254). The development cohort (n = 453) was split into training (n = 362) and internal validation (n = 91) cohorts, and an independent external validation cohort (n = 139) was used for final testing. Kidney regions of interest were automatically segmented using nnU-Net. K-means clustering defined three echogenic habitat subregions, and 408 radiomics features were extracted from the whole-kidney region and habitat subregions. Feature selection was performed in the training cohort, and three machine-learning classifiers were evaluated. The selected radiomics model was compared with clinical and combined models. RESULTS: nnU-Net achieved high kidney segmentation performance, with a mean Dice similarity coefficient of 0.957 and a mean intersection over union of 0.918 in the independent healthy-child test set. Fifteen radiomics features were retained, including six whole-kidney features and nine habitat-derived features. Logistic regression showed stable performance, with areas under the receiver operating characteristic curve (AUCs) of 0.806 (95% confidence interval [CI], 0.715-0.897) internally and 0.825 (95% CI, 0.758-0.892) externally. The combined model outperformed the clinical model in AUC in both cohorts (0.846 vs 0.717; 0.805 vs 0.733). CONCLUSION: This deep-learning-assisted ultrasound habitat radiomics approach enabled automatic kidney delineation and showed encouraging performance as a reproducible imaging adjunct for differentiating pediatric HSPN from IgAN.
Journal IF-equivalent: 3.4 (OpenAlex 2-year mean citedness, value as of 2026-11-03, retrieved 2026-11-04; not the official Clarivate IF)Reference: Gong S, Zhang W, Xu T, Zhang XF, Zhang MJ, Gao P, et al. Automatic Ultrasound Habitat Radiomics for Differentiating Henoch–Schonlein Purpura Nephritis from IgA Nephropathy in Children: A Multicenter Study. Acad Radiol. 2026 Nov [Epub ahead of print]. doi:10.1016/j.acra.2026.10.015. PMID: 42971817.Checked: Abstract only