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      Kidney volume measurement methods for clinical studies on autosomal dominant polycystic kidney disease

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          Abstract

          Background

          In autosomal dominant polycystic kidney disease (ADPKD), total kidney volume (TKV) is regarded as an important biomarker of disease progression and different methods are available to assess kidney volume. The purpose of this study was to identify the most efficient kidney volume computation method to be used in clinical studies evaluating the effectiveness of treatments on ADPKD progression.

          Methods and findings

          We measured single kidney volume (SKV) on two series of MR and CT images from clinical studies on ADPKD (experimental dataset) by two independent operators (expert and beginner), twice, using all of the available methods: polyline manual tracing (reference method), free-hand manual tracing, semi-automatic tracing, Stereology, Mid-slice and Ellipsoid method. Additionally, the expert operator also measured the kidney length. We compared different methods for reproducibility, accuracy, precision, and time required. In addition, we performed a validation study to evaluate the sensitivity of these methods to detect the between-treatment group difference in TKV change over one year, using MR images from a previous clinical study. Reproducibility was higher on CT than MR for all methods, being highest for manual and semiautomatic contouring methods (planimetry). On MR, planimetry showed highest accuracy and precision, while on CT accuracy and precision of both planimetry and Stereology methods were comparable. Mid-slice and Ellipsoid method, as well as kidney length were fast but provided only a rough estimate of kidney volume. The results of the validation study indicated that planimetry and Stereology allow using an importantly lower number of patients to detect changes in kidney volume induced by drug treatment as compared to other methods.

          Conclusions

          Planimetry should be preferred over fast and simplified methods for accurately monitoring ADPKD progression and assessing drug treatment effects. Expert operators, especially on MR images, are required for performing reliable estimation of kidney volume. The use of efficient TKV quantification methods considerably reduces the number of patients to enrol in clinical investigations, making them more feasible and significant.

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          Most cited references38

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          Imaging classification of autosomal dominant polycystic kidney disease: a simple model for selecting patients for clinical trials.

          The rate of renal disease progression varies widely among patients with autosomal dominant polycystic kidney disease (ADPKD), necessitating optimal patient selection for enrollment into clinical trials. Patients from the Mayo Clinic Translational PKD Center with ADPKD (n=590) with computed tomography/magnetic resonance images and three or more eGFR measurements over ≥6 months were classified radiologically as typical (n=538) or atypical (n=52). Total kidney volume (TKV) was measured using stereology (TKVs) and ellipsoid equation (TKVe). Typical patients were randomly partitioned into development and internal validation sets and subclassified according to height-adjusted TKV (HtTKV) ranges for age (1A-1E, in increasing order). Consortium for Radiologic Imaging Study of PKD (CRISP) participants (n=173) were used for external validation. TKVe correlated strongly with TKVs, without systematic underestimation or overestimation. A longitudinal mixed regression model to predict eGFR decline showed that log2HtTKV and age significantly interacted with time in typical patients, but not in atypical patients. When 1A-1E classifications were used instead of log2HtTKV, eGFR slopes were significantly different among subclasses and, except for 1A, different from those in healthy kidney donors. The equation derived from the development set predicted eGFR in both validation sets. The frequency of ESRD at 10 years increased from subclass 1A (2.4%) to 1E (66.9%) in the Mayo cohort and from 1C (2.2%) to 1E (22.3%) in the younger CRISP cohort. Class and subclass designations were stable. An easily applied classification of ADPKD based on HtTKV and age should optimize patient selection for enrollment into clinical trials and for treatment when one becomes available.
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            Volume progression in polycystic kidney disease.

            Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive enlargement of cyst-filled kidneys. In a three-year study, we measured the rates of change in total kidney volume, total cyst volume, and iothalamate clearance in patients with ADPKD. Of a total of 241 patients, in 232 patients without azotemia who were 15 to 46 years old at baseline we used magnetic-resonance imaging to correlate the total kidney volume and total cyst volume with iothalamate clearance. Statistical methods included analysis of variance, Pearson correlation, and multivariate regression analysis. Total kidney volume and total cyst volume increased exponentially, a result consistent with an expansion process dependent on growth. The mean (+/-SD) total kidney volume was 1060+/-642 ml at baseline and increased by a mean of 204+/-246 ml (5.27+/-3.92 percent per year, P<0.001) over a three-year period among 214 patients. Total cyst volume increased by 218+/-263 ml (P<0.001) during the same period among 210 patients. The baseline total kidney volume predicted the subsequent rate of increase in volume, independently of age. A baseline total kidney volume above 1500 ml in 51 patients was associated with a declining glomerular filtration rate (by 4.33+/-8.07 ml per minute per year, P<0.001). Total kidney volume increased more in 135 patients with PKD1 mutations (by 245+/-268 ml) than in 28 patients with PKD2 mutations (by 136+/-100 ml, P=0.03). Kidney enlargement resulting from the expansion of cysts in patients with ADPKD is continuous and quantifiable and is associated with the decline of renal function. Higher rates of kidney enlargement are associated with a more rapid decrease in renal function. Copyright 2006 Massachusetts Medical Society.
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              Everolimus in patients with autosomal dominant polycystic kidney disease.

              Autosomal dominant polycystic kidney disease (ADPKD) is a slowly progressive hereditary disorder that usually leads to end-stage renal disease. Although the underlying gene mutations were identified several years ago, efficacious therapy to curtail cyst growth and prevent renal failure is not available. Experimental and observational studies suggest that the mammalian target of rapamycin (mTOR) pathway plays a critical role in cyst growth. In this 2-year, double-blind trial, we randomly assigned 433 patients with ADPKD to receive either placebo or the mTOR inhibitor everolimus. The primary outcome was the change in total kidney volume, as measured on magnetic resonance imaging, at 12 and 24 months. Total kidney volume increased between baseline and 1 year by 102 ml in the everolimus group, versus 157 ml in the placebo group (P=0.02) and between baseline and 2 years by 230 ml and 301 ml, respectively (P=0.06). Cyst volume increased by 76 ml in the everolimus group and 98 ml in the placebo group after 1 year (P=0.27) and by 181 ml and 215 ml, respectively, after 2 years (P=0.28). Parenchymal volume increased by 26 ml in the everolimus group and 62 ml in the placebo group after 1 year (P=0.003) and by 56 ml and 93 ml, respectively, after 2 years (P=0.11). The mean decrement in the estimated glomerular filtration rate after 24 months was 8.9 ml per minute per 1.73 m2 of body-surface area in the everolimus group versus 7.7 ml per minute in the placebo group (P=0.15). Drug-specific adverse events were more common in the everolimus group; the rate of infection was similar in the two groups. Within the 2-year study period,as compared with placebo, everolimus slowed the increase in total kidney volume of patients with ADPKD but did not slow the progression of renal impairment [corrected]. (Funded by Novartis; EudraCT number, 2006-001485-16; ClinicalTrials.gov number, NCT00414440.)
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                30 May 2017
                2017
                : 12
                : 5
                : e0178488
                Affiliations
                [1 ]Bioengineering Department, IRCCS Istituto di Ricerche Farmacologiche Mario Negri, Bergamo, Italy
                [2 ]Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
                [3 ]Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
                [4 ]Unit of Nephrology and Dialysis, ASST Papa Giovanni XXIII, Bergamo, Italy
                [5 ]Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
                [6 ]Department of Management, Information and Production Engineering, University of Bergamo, Bergamo, Italy
                UCL Institute of Child Health, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: KS AC ALS GR AR.

                • Data curation: KS AC ALS AR.

                • Formal analysis: KS AC.

                • Funding acquisition: KS ALS AR.

                • Investigation: KS AC LVQ KP MB.

                • Methodology: KS AC AR.

                • Software: KS MB.

                • Supervision: GR AR.

                • Validation: AC AR.

                • Visualization: KS AC AR MB.

                • Writing – original draft: KS AC AR.

                • Writing – review & editing: LVQ KP MB ALS GR.

                Article
                PONE-D-17-08189
                10.1371/journal.pone.0178488
                5448775
                28558028
                aa578a96-a4a0-444c-9cd2-35eea8da3370
                © 2017 Sharma et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 1 March 2017
                : 13 May 2017
                Page count
                Figures: 4, Tables: 5, Pages: 19
                Funding
                Funded by: FP7-PEOPLE-MCA-ITN-317246
                Award ID: TranCYST project
                This study was funded in part by ERA – EDTA (EuroCYST Initiative), and by PKD Foundation, Kansas City, MO, USA (grant number 01TRN07a). KS was supported by a Marie Curie fellowship from the European Community (FP7-PEOPLE-MCA-ITN-317246, TranCYST project). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Research and Analysis Methods
                Imaging Techniques
                Neuroimaging
                Computed Axial Tomography
                Biology and Life Sciences
                Neuroscience
                Neuroimaging
                Computed Axial Tomography
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Tomography
                Computed Axial Tomography
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Tomography
                Computed Axial Tomography
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Tomography
                Computed Axial Tomography
                Physical Sciences
                Mathematics
                Geometry
                Ellipsoids
                Research and Analysis Methods
                Imaging Techniques
                Medicine and Health Sciences
                Pharmaceutics
                Drug Therapy
                Biology and Life Sciences
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Medicine and Health Sciences
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Medicine and Health Sciences
                Clinical Medicine
                Clinical Trials
                Medicine and Health Sciences
                Pharmacology
                Drug Research and Development
                Clinical Trials
                Research and Analysis Methods
                Clinical Trials
                Custom metadata
                All data used and obtained during the investigation are within the paper and its Supporting Information files.

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