ArticleJournal of the American Society of Nephrology : JASN2026
Automatically Measuring Kidney, Liver, and Cyst Volumes in Autosomal Dominant Polycystic Kidney Disease.
Article in Journal of the American Society of Nephrology : JASN, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Prospective Study of Multiparametric Renal MRI for CKD Progression (AFiRM).Kidney international reports · 2026Article
- Advanced MRI methods for children and young adults with autosomal recessive polycystic kidney disease (ARPKD) to support future multi-center clinical trials.Pediatric radiology · 2026Review
- Improving Early Risk Prediction for Autosomal Dominant Polycystic Kidney Disease.Journal of the American Society of Nephrology : JASN · 2026Article
- Halting cyst progression in ADPKD using long-term ketogenic metabolic therapy and supplementation with exogenous ketones and alkaline citrate-a case series.Frontiers in nutrition · 2026Article
- Prognostic Performance of Ellipsoid Kidney Volume Measurement in a Computed Tomography-Heavy ADPKD Cohort: A Retrospective Observational Cohort Study.Canadian journal of kidney health and disease · 2026Article
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23 authors.
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Abstract
key pointsTraceOrg is a web-based tool that automatically labels kidney, liver, and cysts, reporting volumes and Mayo Imaging Classification. External validation showed high performance and good generalizability on Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease, Polycystic Kidney Disease-Research Resource Consortium, and other external datasets. Training on multiple pulse sequences enables TraceOrg to process images from a wide variety of protocols.
backgroundKidney, liver, and cyst volumes are important for diagnosis, classification, and management of autosomal dominant polycystic kidney disease (ADPKD) but challenging to measure accurately and reproducibly. Here, we develop a web-based deep learning platform to automatically and robustly measure kidneys, liver, and cyst volumes in ADPKD.
methodsMagnetic resonance imaging (MRI) and computed tomography scans from patients with ADPKD ( n =611) and participants without ADPKD ( n =109) were used to train a 3D hybrid model combining U-Net and transformer elements for segmenting kidneys, liver, and cysts. The model is implemented as a web-based calculator at www.traceorg.com , providing segmentation labels, volumes, and Mayo Clinic Image Classification. Automatic browser anonymization of digital imaging and communications in medicine images ensures privacy. Internal validation was conducted on 70 MRIs for kidney and liver segmentations and 46 MRIs for cyst segmentations, and performance was compared with five open access segmentation models (TotalSegmentator, MRAnnotator, Kim, Woznicki, and Gregory-Kline). External validation was performed on one single-center dataset ( n =58), one multicenter dataset ( n =73), Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease 2 (CRISP, n =30), and Polycystic Kidney Disease-Research Resource Consortium (PKD-RRC, n =115) MRIs with T2-weighted and T1-weighted images.
resultsAfter training on 720 participants (mean age=48±15, eGFR=74±32 ml/min per 1.73 m 2 and height-adjusted total kidney volume=826±772 ml/m), TraceOrg internal validation performance achieved high mean Dice scores of 0.97 (kidneys), 0.97 (liver), 0.93 (kidney cysts), and 0.82 (liver cysts) outperforming existing models for ADPKD. External validation showed strong performance with Dice scores of 0.92-0.94 (kidney), 0.87-0.96 (liver), 0.85 (kidney cysts), and 0.76-0.90 (liver cysts) for the single-center dataset and 0.95 (kidney) and 0.81 (kidney cysts) for the multicenter dataset. Compared with CRISP volumes measured by stereology, the mean absolute percent difference was 5.3% (kidneys, n =30), 11% (kidney cysts, n =30), and 5.5% (liver, n =22). Compared with PKD-RRC ( n =115), the mean absolute percent difference in total kidney volume was 4.9%.
conclusionsTraceOrg, a publicly available web-based tool, automatically measured kidney, liver, and cyst volumes from abdominal MRI in ADPKD with high accuracy compared with manual segmentations. PODCAST: This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/JASN/2026_02_03_ASN0000000904.mp3.
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