ArticleKidney international reports2024
An Artificial Intelligence Generated Automated Algorithm to Measure Total Kidney Volume in ADPKD.
Article in Kidney international reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
- A rapid automated segmentation method for total kidney volume measurement on unenhanced computed tomography in autosomal dominant polycystic kidney disease.Abdominal radiology (New York) · 2026Article
- The role of artificial intelligence in paediatric abdominal imaging.Pediatric radiology · 2026Review
- Automatically Measuring Kidney, Liver, and Cyst Volumes in Autosomal Dominant Polycystic Kidney Disease.Journal of the American Society of Nephrology : JASN · 2026Article
- Machine Learning Prediction of Progression to Dialysis in Patients With Polycystic Kidney Disease: Population-Based Retrospective Cohort Study.JMIR medical informatics · 2026Article
- Progress in fully automated abdominal CT interpretation-an update over the past decade.Abdominal radiology (New York) · 2026Review
- Are Image-Based Deep Learning Algorithms of Kidney Volume in Polycystic Kidney Disease Ready for Clinical Deployment? A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2025Review
- Deep Learning Pipeline for Automated Assessment of Distances Between Tonsillar Tumors and the Internal Carotid Artery.Head & neck · 2025Article
- Comparison Between the Human-Sourced Ellipsoid Method and Kidney Volumetry Using Artificial Intelligence in Polycystic Kidney Disease.Journal of personalized medicine · 2025Article
- Commentary: Tolvaptan for Autosomal Dominant Polycystic Kidney Disease (ADPKD) - an update.BMC nephrology · 2025Review
- Reactive Oxygen Species in Cystic Kidney Disease.Antioxidants (Basel, Switzerland) · 2024Review
- Improved predictions of total kidney volume growth rate in ADPKD using two-parameter least squares fitting.Scientific reports · 2024Article
- A Primer for Utilizing Deep Learning and Abdominal MRI Imaging Features to Monitor Autosomal Dominant Polycystic Kidney Disease Progression.Biomedicines · 2024Review
Corrections and comments
- Erratum issued
Authors and funding
18 authors at 10 institutions in 7 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Accurate tools to inform individual prognosis in patients with autosomal dominant polycystic kidney disease (ADPKD) are lacking. Here, we report an artificial intelligence (AI)-generated method for routinely measuring total kidney volume (TKV). Methods: An ensemble U-net algorithm was created using the nnUNet approach. The training and internal cross-validation cohort consisted of all 1.5T magnetic resonance imaging (MRI) data acquired using 5 different MRI scanners (454 kidneys, 227 scans) in the CYSTic consortium, which was first manually segmented by a single human operator. As an independent validation cohort, we utilized 48 sequential clinical MRI scans with reference results of manual segmentation acquired by 6 individual analysts at a single center. The tool was then implemented for clinical use and its performance analyzed. Results: The training or internal validation cohort was younger (mean age 44.0 vs. 51.5 years) and the female-to-male ratio higher (1.2 vs. 0.94) compared to the clinical validation cohort. The majority of CYSTic patients had Conclusion: Our AI-based algorithm demonstrates performance comparable to manual segmentation. Its rapidity and precision in real-world clinical cases demonstrate its suitability for clinical application.
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