Automatic total kidney volume measurement on follow-up magnetic resonance images to facilitate monitoring of autosomal dominant polycystic kidney disease progression

Kline, Timothy L.; Korfiatis, Panagiotis; Edwards, Marie E.; Warner, Joshua D.; Irazabal, María V.; King, Bernard F.; Torres, Vicente E.; Erickson, Bradley J.

doi:10.1093/ndt/gfv314

Cited by 43 publications

(42 citation statements)

References 37 publications

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“…A steepest-descent approach was used to find the local minima, or steady state, as represented by the following equation:

C = [g (I) \cdot K - \nabla g (I) \cdot N] N,

where K is the Euclidean curvature of C and where N is the normal to the curve. Our GAC was run with σ = 3 and α = 1E5, which were found to be appropriate values on separate data [30]. …”

Section: Methodsmentioning

confidence: 99%

Semiautomated Segmentation of Polycystic Kidneys in T2-Weighted MR Images

Kline

Edwards

Korfiatis

et al. 2016

American Journal of Roentgenology

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OBJECTIVE The objective of the present study is to develop and validate a fast, accurate, and reproducible method that will increase and improve institutional measurement of total kidney volume and thereby avoid the higher costs, increased operator processing time, and inherent subjectivity associated with manual contour tracing. MATERIALS AND METHODS We developed a semiautomated segmentation approach, known as the minimal interaction rapid organ segmentation (MIROS) method, which results in human interaction during measurement of total kidney volume on MR images being reduced to a few minutes. This software tool automatically steps through slices and requires rough definition of kidney boundaries supplied by the user. The approach was verified on T2-weighted MR images of 40 patients with autosomal dominant polycystic kidney disease of varying degrees of severity. RESULTS The MIROS approach required less than 5 minutes of user interaction in all cases. When compared with the ground-truth reference standard, MIROS showed no significant bias and had low variability (mean ± 2 SD, 0.19% ± 6.96%). CONCLUSION The MIROS method will greatly facilitate future research studies in which accurate and reproducible measurements of cystic organ volumes are needed.

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“…A steepest-descent approach was used to find the local minima, or steady state, as represented by the following equation:

C = [g (I) \cdot K - \nabla g (I) \cdot N] N,

where K is the Euclidean curvature of C and where N is the normal to the curve. Our GAC was run with σ = 3 and α = 1E5, which were found to be appropriate values on separate data [30]. …”

Section: Methodsmentioning

confidence: 99%

Semiautomated Segmentation of Polycystic Kidneys in T2-Weighted MR Images

Kline

Edwards

Korfiatis

et al. 2016

American Journal of Roentgenology

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“…These matters justify several recent studies aimed at the computation of TKV in ADPKD patients from MRI [3,4,5,6,7,8]. A comprehensive review of the state-of-the-art MRI for the estimation of kidney volume in chronic kidney disease is presented in [9].…”

Section: Introductionmentioning

confidence: 99%

“…These methods have differences between them, since some rely on geometric approximations [3,6] limiting manual contouring to one mid-MRI slice; others are highly automated [4,5] requiring a single seed point selection in one mid-MR slice to obtain the 3D kidney surfaces. Very recently, two additional fully automated approaches were proposed; the first one [7] was exclusively proposed to monitor disease progression starting from patient kidney surfaces obtained by manual contouring during the first visit; the second one [8] was based on spatial probability density maps and regional mapping with total variation regularization and propagated shape constraints.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Total Kidney Volume Quantification Methods in Autosomal Dominant Polycystic Disease for a Comprehensive Disease Assessment

et al. 2017

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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.

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“…Fully automated techniques have therefore been developed to analyze MRI scans [50,51], which then need only a final quality check [51].…”

Section: Fully Automated Techniques For Mrimentioning

confidence: 99%

“…Another requires baseline segmentation initialization performed by manual tracing of MRI scans acquired during the first visit to allow future segmentation to occur automatically [51]. Both approaches correlate well with manual procedures, with comparable accuracy and reproducibility (spatial prior probability map, R 2 = 0.97; baseline segmentation initialization, mean ± SD Dice similarity coefficient = 0.88 ± 0.08) [50,51]. However, manual tracing of a vast set of images from different patients is required to build a reliable spatial probability map on which the accuracy of the automated TKV measurement depends.…”

Section: Fully Automated Techniques For Mrimentioning

confidence: 99%

A Review of the Imaging Techniques for Measuring Kidney and Cyst Volume in Establishing Autosomal Dominant Polycystic Kidney Disease Progression

et al. 2018

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Background: Autosomal dominant polycystic kidney disease (ADPKD) is the commonest inherited renal disorder; it is defined by progressive renal cyst formation and subsequent renal enlargement that leads to end-stage renal disease. Until recently, only symptomatic treatments for ADPKD existed. However, therapies that address the underlying pathophysiology of ADPKD are now available and accurate identification of the rate of disease progression is essential. Summary: Published data on the different imaging modalities for measuring kidney and cyst volumes in ADPKD are reviewed. The advantages and drawbacks of the different techniques for calculating kidney volume from renal imaging are also examined, including the use of manual planimetry, stereology, and the ellipsoid equation, as well as the prospect of semi- and fully automatic techniques. The translation of these approaches into clinical practice and their role in informing treatment decisions is discussed. Key Messages: These new therapies require the accurate monitoring of disease progression, which along with diagnosis and prognosis, relies on the effective use of renal imaging techniques. There is growing support for the use of total kidney volume as a measure of cyst burden and as a prognostic predictor of renal function in ADPKD, showing promise as a marker of disease progression.

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Automatic total kidney volume measurement on follow-up magnetic resonance images to facilitate monitoring of autosomal dominant polycystic kidney disease progression

Cited by 43 publications

References 37 publications

Semiautomated Segmentation of Polycystic Kidneys in T2-Weighted MR Images

Semiautomated Segmentation of Polycystic Kidneys in T2-Weighted MR Images

Comparison of Total Kidney Volume Quantification Methods in Autosomal Dominant Polycystic Disease for a Comprehensive Disease Assessment

A Review of the Imaging Techniques for Measuring Kidney and Cyst Volume in Establishing Autosomal Dominant Polycystic Kidney Disease Progression

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