ArticleAbdominal radiology (New York)2021
Automatic semantic segmentation of kidney cysts in MR images of patients affected by autosomal-dominant polycystic kidney disease.
Article in Abdominal radiology (New York), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06688981 (Artificial Intelligence-based Image Processing Methods to Advance the Characterization of Polycystic Kidney Disease), which is not on this map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Artificial Intelligence-based Image Processing Methods to Advance the Characterization of Polycystic Kidney Disease
Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Exploring alternative approaches to precision medicine through genomics and artificial intelligence - a systematic review.Frontiers in medicine · 2023Pooled it
- Automatically Measuring Kidney, Liver, and Cyst Volumes in Autosomal Dominant Polycystic Kidney Disease.Journal of the American Society of Nephrology : JASN · 2026Article
- Autosomal dominant polycystic kidney disease: an overview of recent genetic and clinical advances.Renal failure · 2025Review
- 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
- In-depth 3D exploration of autosomal dominant polycystic kidney disease through light sheet fluorescence microscopy.Scientific reports · 2025Article
- Foam sclerotherapy for symptomatic cysts in ADPKD, ADPLD and solitary cysts.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2025Observational
- Improvement of artificial intelligence-based computed tomography pulmonary angiography in identifying acute pulmonary embolism.Quantitative imaging in medicine and surgery · 2025Article
- Reliability of radiomic analysis on multiparametric MRI for patients affected by autosomal dominant polycystic kidney disease.Scientific reports · 2025Article
- Time-restricted eating and autosomal dominant polycystic kidney disease: a pilot, randomized clinical trial.Clinical kidney journal · 2025Article
- Segmentation of ADPKD Computed Tomography Images with Deep Learning Approach for Predicting Total Kidney Volume.Biomedicines · 2025Article
- Deep learning-based segmentation of kidneys and renal cysts on T2-weighted MRI from patients with autosomal dominant polycystic kidney disease.European radiology experimental · 2024Article
- Multiscale and multimodal evaluation of autosomal dominant polycystic kidney disease development.Communications biology · 2024Article
- Deep learning-based liver cyst segmentation in MRI for autosomal dominant polycystic kidney disease.Radiology advances · 2024Article
- AI models for automated segmentation of engineered polycystic kidney tubules.Scientific reports · 2024Article
- Total kidney volume in autosomal dominant polycystic kidney disease: intraobserver and interobserver agreement of two methods with MRI.Turkish journal of medical sciences · 2024Article
- Renal MRI: From Nephron to NMR Signal.Journal of magnetic resonance imaging : JMRI · 2023Review
- Evaluation of advanced imaging biomarkers at kidney failure in patients with ADPKD: a pilot study.Clinical kidney journal · 2023Article
- Diffusion magnetic resonance imaging for kidney cyst volume quantification and non-cystic tissue characterisation in ADPKD.European radiology · 2023Article
- Abdominal Imaging in ADPKD: Beyond Total Kidney Volume.Journal of clinical medicine · 2023Review
- Clinical Implementation of an Artificial Intelligence Algorithm for Magnetic Resonance-Derived Measurement of Total Kidney Volume.Mayo Clinic proceedings · 2023Article
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Authors and funding
7 authors.
Funding
Abstract
purposeFor patients affected by autosomal-dominant polycystic kidney disease (ADPKD), successful differentiation of cysts is useful for automatic classification of patient phenotypes, clinical decision-making, and disease progression. The objective was to develop and evaluate a fully automated semantic segmentation method to differentiate and analyze renal cysts in patients with ADPKD.
methodsAn automated deep learning approach using a convolutional neural network was trained, validated, and tested on a set of 60 MR T2-weighted images. A three-fold cross-validation approach was used to train three models on distinct training and validation sets (n = 40). An ensemble model was then built and tested on the hold out cases (n = 20), with each of the cases compared to manual segmentations performed by two readers. Segmentation agreement between readers and the automated method was assessed.
resultsThe automated approach was found to perform at the level of interobserver variability. The automated approach had a Dice coefficient (mean ± standard deviation) of 0.86 ± 0.10 vs Reader-1 and 0.84 ± 0.11 vs. Reader-2. Interobserver Dice was 0.86 ± 0.08. In terms of total cyst volume (TCV), the automated approach had a percent difference of 3.9 ± 19.1% vs Reader-1 and 8.0 ± 24.1% vs Reader-2, whereas interobserver variability was - 2.0 ± 16.4%.
conclusionThis study developed and validated a fully automated approach for performing semantic segmentation of kidney cysts in MR images of patients affected by ADPKD. This approach will be useful for exploring additional imaging biomarkers of ADPKD and automatically classifying phenotypes.
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