Assessment of Kidney Volumes From MRI: Acquisition and Segmentation Techniques

Zöllner, Frank G.; Svarstad, Einar; Munthe-Kaas, Antonella Zanna; Schad, Lothar R.; Lundervold, Arvid; Rørvik, Jarle

doi:10.2214/ajr.12.8657

Cited by 52 publications

(39 citation statements)

References 70 publications

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“…A comprehensive review of the state-of-the-art MRI for the estimation of kidney volume in chronic kidney disease is presented in [9]. 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.…”

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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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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“…2) Segmentation: The task of segmenting the kidney in DCE-MRI recordings has taken several approaches [57]. Manual delineation performed by an expert is potentially accurate, but also highly subjective and time consuming in contrast to automated methods [41].…”

Section: ) Registrationmentioning

confidence: 99%

Segmentation-Driven Image Registration-Application to 4D DCE-MRI Recordings of the Moving Kidneys

Hodneland

Hanson

Lundervold

et al. 2014

IEEE Trans. on Image Process.

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Abstract-Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of the kidneys requires proper motion correction and segmentation to enable an estimation of glomerular filtration rate through pharmacokinetic modeling. Traditionally, co-registration, segmentation, and pharmacokinetic modeling have been applied sequentially as separate processing steps. In this paper, a combined 4D model for simultaneous registration and segmentation of the whole kidney is presented. To demonstrate the model in numerical experiments, we used normalized gradients as data term in the registration and a Mahalanobis distance from the time courses of the segmented regions to a training set for supervised segmentation. By applying this framework to an input consisting of 4D image time series, we conduct simultaneous motion correction and two-region segmentation into kidney and background. The potential of the new approach is demonstrated on real DCE-MRI data from ten healthy volunteers.

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“…The algorithms focus on the kidney segmentation without giving particular attention to the PCS. A comprehensive review of the algorithms proposed for kidney volume assessment on MRI provided in [4] presents different acquisition techniques and tailored segmentation methods. Will et al [5] proposed a renal cortex, medulla and renal pelvis segmentation from MRI by simple thresholding.…”

Section: Introductionmentioning

confidence: 99%

Automatic Extraction of the Pelvicalyceal System for Preoperative Planning of Minimally Invasive Procedures

Heryan

Skalski

Jakubowski³

et al. 2017

Metrology and Measurement Systems

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Minimally invasive procedures for the kidney tumour removal require a 3D visualization of topological relations between kidney, cancer, the pelvicalyceal system and the renal vascular tree. In this paper, a novel methodology of the pelvicalyceal system segmentation is presented. It consists of four following steps: ROI designation, automatic threshold calculation for binarization (approximation of the histogram image data with three exponential functions), automatic extraction of the pelvicalyceal system parts and segmentation by the Locally Adaptive Region Growing algorithm. The proposed method was applied successfully on the Computed Tomography database consisting of 48 kidneys both healthy and cancer affected. The quantitative evaluation (comparison to manual segmentation) and visual assessment proved its effectiveness. The Dice Coefficient of Similarity is equal to 0.871 ± 0.060 and the average Hausdorff distance 0.46 ± 0.36 mm. Additionally, to provide a reliable assessment of the proposed method, it was compared with three other methods. The proposed method is robust regardless of the image acquisition mode, spatial resolution and range of image values. The same framework may be applied to further medical applications beyond preoperative planning for partial nephrectomy enabling to visually assess and to measure the pelvicalyceal system by medical doctors.

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Assessment of Kidney Volumes From MRI: Acquisition and Segmentation Techniques

Abstract: We review state-of-the-art MRI acquisition techniques for CKD, with a special focus on image segmentation methods used for the estimation of kidney volume.

Cited by 52 publications

References 70 publications

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

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

Segmentation-Driven Image Registration-Application to 4D DCE-MRI Recordings of the Moving Kidneys

Automatic Extraction of the Pelvicalyceal System for Preoperative Planning of Minimally Invasive Procedures

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