Related Experiment Video
Updated: Mar 6, 2026
Use of Ultra-high Field MRI in Small Rodent Models of Polycystic Kidney Disease for In Vivo Phenotyping and Drug Monitoring
Published on: June 23, 2015
Comparison of Total Kidney Volume Quantification Methods in Autosomal Dominant Polycystic Disease for a Comprehensive
Dario Turco1, Marco Busutti, Renzo Mignani
1Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi," University of Bologna, Cesena, Italy.
Background:
In recent times, the scientific community has been showing increasing interest in the treatments aimed at slowing the progression of the autosomal dominant polycystic kidney disease (ADPKD). Therefore, in this paper, we test and evaluate the performance of several available methods for total kidney volume (TKV) computation in ADPKD patients - from echography to MRI - in order to optimize patient classification.
Methods:
Two methods based on geometric assumptions (mid-slice [MS], ellipsoid [EL]) and a third one on true contour detection were tested on 40 ADPKD patients at different disease stage using MRI. The EL method was also tested using ultrasound images in a subset of 14 patients. Their performance was compared against TKVs derived from reference manual segmentation of MR images. Patient clinical classification was also performed based on computed volumes.
Results:
Kidney volumes derived from echography significantly underestimated reference volumes. Geometric-based methods applied to MR images had similar acceptable results. The highly automated method showed better performance. Volume assessment was accurate and reproducible. Importantly, classification resulted in 79, 13, 10, and 2.5% of misclassification using kidney volumes obtained from echo and MRI applying the EL, the MS and the highly automated method respectively.
Conclusion:
Considering the fact that the image-based technique is the only approach providing a 3D patient-specific kidney model and allowing further analysis including cyst volume computation and monitoring disease progression, we suggest that geometric assumption (e.g., EL method) should be avoided. The contour-detection approach should be used for a reproducible and precise morphologic classification of the renal volume of ADPKD patients.
Insights
Accurate total kidney volume (TKV) measurement in autosomal dominant polycystic kidney disease (ADPKD) is crucial for patient classification. A contour-detection method using MRI offers superior accuracy and reproducibility compared to geometric assumptions or ultrasound.
Area of Science:
- Nephrology
- Medical Imaging
- Biomedical Engineering
Background:
- Autosomal dominant polycystic kidney disease (ADPKD) management increasingly focuses on slowing disease progression.
- Accurate assessment of total kidney volume (TKV) is vital for classifying ADPKD patients and monitoring disease.
- Current methods for TKV computation vary in accuracy and reproducibility.
Purpose of the Study:
- To evaluate and compare the performance of different methods for TKV computation in ADPKD patients.
- To determine the optimal imaging modality and technique for accurate TKV assessment.
- To assess the impact of TKV computation methods on patient classification.
Main Methods:
- Tested geometric (mid-slice, ellipsoid) and contour-detection methods for TKV computation using MRI in 40 ADPKD patients.
- Evaluated the ellipsoid method using ultrasound in 14 patients.
- Compared computed TKVs against reference manual segmentation of MR images and assessed patient classification accuracy.
Main Results:
- Ultrasound-derived volumes significantly underestimated reference TKV.
- Geometric methods on MRI showed acceptable but less accurate results than contour detection.
- The highly automated contour-detection method demonstrated superior accuracy and reproducibility, significantly reducing misclassification rates.
Conclusions:
- Geometric assumption methods (e.g., ellipsoid) should be avoided for TKV computation in ADPKD.
- The contour-detection approach provides a precise, reproducible 3D kidney model for morphologic classification and disease monitoring.
- Image-based contour detection using MRI is recommended for accurate ADPKD patient stratification.
Related Concept Videos
01:08Renal Drug Clearance: Comparison Between Renal Excretion Methods
Renal clearance is often associated with the renal glomerular filtration rate (GFR), which represents the rate at which plasma is filtered through the glomeruli in the kidney. When drug reabsorption is minimal and there is no active secretion, renal clearance is closely related to the...
01:28Drug Dosing in Renal Diseases: Estimation of Glomerular Filtration Rate Based on Serum Creatinine Concentration
01:25Drug Dosing in Renal Diseases: Measurement of Glomerular Filtration Rate
01:07Determination of Renal Drug Clearance: Graphical and Midpoint Methods
The graphical method involves plotting the rate of drug excretion in urine against the plasma drug concentration. By analyzing the graph, the clearance can be calculated and obtained. Drugs rapidly excreted by the kidneys exhibit a...
01:28Imaging Studies I: Kidney, Ureter, and Bladder Studies