Estimation of Total Kidney Volume in Autosomal Dominant Polycystic Kidney Disease

Validation of the Mayo Imaging Classification System for Predicting Kidney Outcomes in ADPKD

BACKGROUND

The Mayo Imaging Classification was developed to predict the rate of disease progression in patients with autosomal dominant polycystic kidney disease. This study aimed to validate its ability to predict kidney outcomes in a large multicenter autosomal dominant polycystic kidney disease cohort.

METHODS

Included were patients with ≥1 height-adjusted total kidney volume (HtTKV) measurement and ≥3 eGFR values during ≥1-year follow-up. Mayo HtTKV class stability, kidney growth rates, and eGFR decline rates were calculated. The observed eGFR decline was compared with predictions from the Mayo Clinic future eGFR equation. The future eGFR prediction equation was also tested for nonlinear eGFR decline. Kaplan-Meier survival analysis and Cox regression models were used to assess time to kidney failure using Mayo HtTKV class as a predictor variable.

RESULTS

We analyzed 618 patients with a mean age of 47±11 years and mean eGFR of 64±25 ml/min per 1.73 m 2 at baseline. Most patients (82%) remained in their baseline Mayo HtTKV class. During a mean follow-up of 5.1±2.2 years, the mean total kidney volume growth rates and eGFR decline were 5.33%±3.90%/yr and -3.31±2.53 ml/min per 1.73 m 2 per year, respectively. Kidney growth and eGFR decline showed considerable overlap between the classes. The observed annual eGFR decline was not significantly different from the predicted values for classes 1A, 1B, 1C, and 1D but significantly slower for class 1E. This was also observed in patients aged younger than 40 years and older than 60 years and those with PKD2 mutations. A polynomial model allowing nonlinear eGFR decline provided more accurate slope predictions. Ninety-seven patients (16%) developed kidney failure during follow-up. The classification predicted the development of kidney failure, although the sensitivity and positive predictive values were limited.

CONCLUSIONS

The Mayo Imaging Classification demonstrated acceptable stability and generally predicted kidney failure and eGFR decline rate. However, there was marked interindividual variability in the rate of disease progression within each class.

Abdominal Imaging in ADPKD: Beyond Total Kidney Volume

In the context of autosomal dominant polycystic kidney disease (ADPKD), measurement of the total kidney volume (TKV) is crucial. It acts as a marker for tracking disease progression, and evaluating the effectiveness of treatment strategies. The TKV has also been recognized as an enrichment biomarker and a possible surrogate endpoint in clinical trials. Several imaging modalities and methods are available to calculate the TKV, and the choice depends on the purpose of use. Technological advancements have made it possible to accurately assess the cyst burden, which can be crucial to assessing the disease state and helping to identify rapid progressors. Moreover, the development of automated algorithms has increased the efficiency of total kidney and cyst volume measurements. Beyond these measurements, the quantification and characterization of non-cystic kidney tissue shows potential for stratifying ADPKD patients early on, monitoring disease progression, and possibly predicting renal function loss. A broad spectrum of radiological imaging techniques are available to characterize the kidney tissue, showing promise when it comes to non-invasively picking up the early signs of ADPKD progression. Radiomics have been used to extract textural features from ADPKD images, providing valuable information about the heterogeneity of the cystic and non-cystic components. This review provides an overview of ADPKD imaging biomarkers, focusing on the quantification methods, potential, and necessary steps toward a successful translation to clinical practice.

Clinical Quality Control of MRI Total Kidney Volume Measurements in Autosomal Dominant Polycystic Kidney Disease

Total kidney volume measured on MRI is an important biomarker for assessing the progression of autosomal dominant polycystic kidney disease and response to treatment. However, we have noticed that there can be substantial differences in the kidney volume measurements obtained from the various pulse sequences commonly included in an MRI exam. Here we examine kidney volume measurement variability among five commonly acquired MRI pulse sequences in abdominal MRI exams in 105 patients with ADPKD. Right and left kidney volumes were independently measured by three expert observers using model-assisted segmentation for axial T2, coronal T2, axial single-shot fast spin echo (SSFP), coronal SSFP, and axial 3D T1 images obtained on a single MRI from ADPKD patients. Outlier measurements were analyzed for data acquisition errors. Most of the outlier values (88%) were due to breathing during scanning causing slice misregistration with gaps or duplication of imaging slices (n = 35), slice misregistration from using multiple breath holds during acquisition (n = 25), composing of two overlapping acquisitions (n = 17), or kidneys not entirely within the field of view (n = 4). After excluding outlier measurements, the coefficient of variation among the five measurements decreased from 4.6% pre to 3.2%. Compared to the average of all sequences without errors, TKV measured on axial and coronal T2 weighted imaging were 1.2% and 1.8% greater, axial SSFP was 0.4% greater, coronal SSFP was 1.7% lower and axial T1 was 1.5% lower than the mean, indicating intrinsic measurement biases related to the different MRI contrast mechanisms. In conclusion, MRI data acquisition errors are common but can be identified using outlier analysis and excluded to improve organ volume measurement consistency. Bias toward larger volume measurements on T2 sequences and smaller volumes on axial T1 sequences can also be mitigated by averaging data from all error-free sequences acquired.

Automated Kidney and Liver Segmentation in MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease: A Multicenter Study

Background

Imaging-based total kidney volume (TKV) and total liver volume (TLV) are major prognostic factors in autosomal dominant polycystic kidney disease (ADPKD) and end points for clinical trials. However, volumetry is time consuming and reader dependent in clinical practice. Our aim was to develop a fully automated method for joint kidney and liver segmentation in magnetic resonance imaging (MRI) and to evaluate its performance in a multisequence, multicenter setting.

Methods

The convolutional neural network was trained on a large multicenter dataset consisting of 992 MRI scans of 327 patients. Manual segmentation delivered ground-truth labels. The model's performance was evaluated in a separate test dataset of 93 patients (350 MRI scans) as well as a heterogeneous external dataset of 831 MRI scans from 323 patients.

Results

The segmentation model yielded excellent performance, achieving a median per study Dice coefficient of 0.92-0.97 for the kidneys and 0.96 for the liver. Automatically computed TKV correlated highly with manual measurements (intraclass correlation coefficient [ICC]: 0.996-0.999) with low bias and high precision (-0.2%±4% for axial images and 0.5%±4% for coronal images). TLV estimation showed an ICC of 0.999 and bias/precision of -0.5%±3%. For the external dataset, the automated TKV demonstrated bias and precision of -1%±7%.

Conclusions

Our deep learning model enabled accurate segmentation of kidneys and liver and objective assessment of TKV and TLV. Importantly, this approach was validated with axial and coronal MRI scans from 40 different scanners, making implementation in clinical routine care feasible.Clinical Trial registry name and registration number: The German ADPKD Tolvaptan Treatment Registry (AD[H]PKD), NCT02497521.

A MRI-based radiomics nomogram for evaluation of renal function in ADPKD

OBJECTIVES

This study is aimed to establish a fusion model of radiomics-based nomogram to predict the renal function of autosomal dominant polycystic kidney disease (ADPKD).

METHODS

One hundred patients with ADPKD were randomly divided into training group (n = 69) and test group (n = 31). The radiomics features were extracted from T1-weighted fat suppression images (FS-T1WI) and T2-weighted fat suppression images (FS-T2WI). Decision tree algorithm was employed to build radiomics model to get radiomics signature. Then multivariate logistic regression analysis was used to establish the radiomics nomogram based on independent clinical factors, conventional MR imaging variables and radiomics signature. The receiver operating characteristic (ROC) analysis and Delong test were used to compare the performance of radiomics model and radiomics nomogram model, and the decision curve to evaluate the clinical application value of radiomics nomogram model in the evaluation of renal function in patients with ADPKD.

RESULTS

Fourteen radiomics features were selected to establish radiomics model. Based on FS-T1WI and FS-T2WI sequences, the radiomics model showed good discrimination ability in training group and test group [training group: (AUC) = 0.7542, test group (AUC) = 0.7417]. The performance of radiomics nomogram model was significantly better than that of radiomics model in all data sets [radiomics model (AUC) = 0.7505, radiomics nomogram model (AUC) = 0.8435, p value = 0.005]. The analysis of calibration curve and decision curve showed that radiomics nomogram model had more clinical application value.

CONCLUSION

radiomics analysis of MRI can be used for the preliminary evaluation and prediction of renal function in patients with ADPKD. The radiomics nomogram model shows better prediction effect in renal function evaluation, and can be used as a non-invasive renal function prediction tool to assist clinical decision-making. Trial registration ChiCTR, ChiCTR2100046739. Registered 27 May 2021-retrospectively registered, http://www.ChiCTR.org.cn/showproj.aspx?proj=125955.

Polycystic liver: automatic segmentation using deep learning on CT is faster and as accurate compared to manual segmentation

OBJECTIVE

This study aimed to develop and investigate the performance of a deep learning model based on a convolutional neural network (CNN) for the automatic segmentation of polycystic livers at CT imaging.

METHOD

This retrospective study used CT images of polycystic livers. To develop the CNN, supervised training and validation phases were performed using 190 CT series. To assess performance, the test phase was performed using 41 CT series. Manual segmentation by an expert radiologist (Rad1a) served as reference for all comparisons. Intra-observer variability was determined by the same reader after 12 weeks (Rad1b), and inter-observer variability by a second reader (Rad2). The Dice similarity coefficient (DSC) evaluated overlap between segmentations. CNN performance was assessed using the concordance correlation coefficient (CCC) and the two-by-two difference between the CCCs; their confidence interval was estimated with bootstrap and Bland-Altman analyses. Liver segmentation time was automatically recorded for each method.

RESULTS

A total of 231 series from 129 CT examinations on 88 consecutive patients were collected. For the CNN, the DSC was 0.95 ± 0.03 and volume analyses yielded a CCC of 0.995 compared with reference. No statistical difference was observed in the CCC between CNN automatic segmentation and manual segmentations performed to evaluate inter-observer and intra-observer variability. While manual segmentation required 22.4 ± 10.4 min, central and graphics processing units took an average of 5.0 ± 2.1 s and 2.0 ± 1.4 s, respectively.

CONCLUSION

Compared with manual segmentation, automated segmentation of polycystic livers using a deep learning method achieved much faster segmentation with similar performance.

KEY POINTS

• Automatic volumetry of polycystic livers using artificial intelligence method allows much faster segmentation than expert manual segmentation with similar performance. • No statistical difference was observed between automatic segmentation, inter-observer variability, or intra-observer variability.

Limited Performance of Estimated Total Kidney Volume for Follow-up of ADPKD

Introduction

Total kidney volume (TKV) is a qualified biomarker for disease progression in autosomal dominant polycystic kidney disease (ADPKD). Recent studies suggest that TKV estimated using ellipsoid formula correlates well with TKV measured by manual planimetry (gold standard). We investigated whether the ellipsoid formula could replace manual planimetry for follow-up of ADPKD patients.

Methods

Abdominal magnetic resonance images of patients with ADPKD performed between January 1, 2013, and June 31, 2019, in Saint-Luc Hospital, Brussels, were used. Two radiologists independently performed manual TKV (mTKV) measures and kidney axial measures necessary for estimating TKV (eTKV) using ellipsoid equation. Repeatability and reproducibility of axial measures, mTKV and eTKV, and agreement between mTKV and eTKV were assessed (Bland-Altman). Intraclass correlation coefficient (ICC) was used to assess agreement on Mayo Clinic Imaging Classification (MCIC) scores.

Results

140 patients were included with mean age 45±13 years, estimated glomerular filtration rate (eGFR) 71±31 ml/min per 1.73 m², and mTKV 1697±1538 ml. Repeatability and reproducibility were superior for mTKV versus eTKV (repeatability coefficient 2.4% vs. 14% in senior reader, and reproducibility coefficient 6.7% vs. 15%). Intertechnique reproducibility coefficient (95% confidence interval [CI]) was 19% (17%, 21%) in senior reader. Intertechnique agreement on derived MCIC scores was very good (ICC = 0.924 [0.884, 0.949]).

Conclusion

TKV estimated using ellipsoid equation demonstrates poor repeatability and reproducibility compared with that of mTKV. Intertechnique agreement is also limited, even when measurements are performed by an experienced radiologist. Estimated TKV, however, accurately determines MCIC score.

Automated renal segmentation in healthy and chronic kidney disease subjects using a convolutional neural network

PURPOSE

Total kidney volume (TKV) is an important measure in renal disease detection and monitoring. We developed a fully automated method to segment the kidneys from T₂ -weighted MRI to calculate TKV of healthy control (HC) and chronic kidney disease (CKD) patients.

METHODS

This automated method uses machine learning, specifically a 2D convolutional neural network (CNN), to accurately segment the left and right kidneys from T₂ -weighted MRI data. The data set consisted of 30 HC subjects and 30 CKD patients. The model was trained on 50 manually defined HC and CKD kidney segmentations. The model was subsequently evaluated on 50 test data sets, comprising data from 5 HCs and 5 CKD patients each scanned 5 times in a scan session to enable comparison of the precision of the CNN and manual segmentation of kidneys.

RESULTS

The unseen test data processed by the 2D CNN had a mean Dice score of 0.93 ± 0.01. The difference between manual and automatically computed TKV was 1.2 ± 16.2 mL with a mean surface distance of 0.65 ± 0.21 mm. The variance in TKV measurements from repeat acquisitions on the same subject was significantly lower using the automated method compared to manual segmentation of the kidneys.

CONCLUSION

The 2D CNN method provides fully automated segmentation of the left and right kidney and calculation of TKV in <10 s on a standard office computer, allowing high data throughput and is a freely available executable.

Influence of 3D-Calculated Parenchymal Volume Loss on Renal Function After Partial Nephrectomy

Background: Our study aims to evaluate the influence of potential determinants of glomerular filtration rate (GFR) decrease after partial nephrectomy (PN), including renal parenchymal loss and other clinical, tumoral, and surgical factors. Materials and Methods: Eighty-six patients who had undergone PN and for whom preoperative and postoperative computerized tomography scans were available were selected. We calculated the preoperative total kidney volumes, tumor volumes, and postoperative total kidney volumes 1 year after surgery using a three-dimensional (3D) volume segmentation method. Factors that may be potential determinants of percent GFR decrease were also evaluated, including patient age, type of procedure (laparoscopic vs. open), comorbidity index, preoperative GFR, tumor size and volume, RENAL nephrometry score, warm ischemia time, and 3D calculated renal parenchymal loss. Clinical, surgical, and tumor parameters potentially associated with renal parenchymal loss were evaluated. Results: The mean age of the patients was 58 years, the mean tumor diameter was 3.6 cm, and the mean tumor volume was 11.7 cc. The mean percent of renal parenchymal loss was 22.3%, and the mean percent of GFR loss was 17.3%. The renal parenchymal loss was strongly associated with age (r = 0.702, P = .02), Charlson comorbidities index (r = 0.768, P < .001), and RENAL nephrometry score (r = 0.812, P < .001). In multivariate logistic regression analysis, older age, higher Charlson comorbidities index, higher percent renal parenchymal loss, and higher RENAL nephrometry score were independently associated with higher percent of GFR loss. Conclusion: Of all the factors analyzed, RENAL score and Charlson comorbidities index were the most accurate predictors of postoperative parenchymal loss. Also, the percent decrease in GFR at late time points was associated with renal volume preservation and quality of the remnant parenchyma.

Serum uromodulin levels, MR imaging findings, and their relationship with eGFR-based CKD staging in ADPKD patients

PURPOSE

Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease that may progress to end-stage renal disease, characterized by increased kidney volume due to cystic formations. In this study, we aimed to investigate the relationship between serum uromodulin levels, total kidney volume and estimated glomerular filtration rate (eGFR) in patients with ADPKD.

METHODS

This study included a total of 54 ADPKD patients and 18 healthy volunteers (control group). Total kidney volumes were calculated through magnetic resonance images using ellipsoid method. Serum uromodulin measurements were measured using an ELISA method.

RESULTS

Serum uromodulin levels were lower in patients compared with the control group (2.47 ± 0.16 vs 2.6 ± 0.28, p = 0.021). There was no significant difference in uromodulin values among the patients in chronic kidney disease (CKD) stages 1-2, 3 and 4-5. TKV measurements of CKD stage 4-5 patients were significantly higher than the stage 1-2 patients (p = 0.015). A negative correlation was observed between TKV and eGFR (r = - 0.433, p = 0.001). A positive correlation was observed between uromodulin and eGFR (r = 0.274, p = 0.02). When the serum levels of uromodulin and the level of eGFR were evaluated using simple linear regression analysis, R² value was found to be 0.075, suggesting that 7.5% change in serum uromodulin values corresponds with the change in eGFR value.

CONCLUSION

These findings are consistent with previous studies that reported that serum uromodulin may be a good biomarker for demonstrating renal function in the early stages of CKD, before eGFR levels deteriorate. Serum uromodulin level may be useful in demonstrating renal functions in the follow-up of individuals with ADPKD.

European ADPKD Forum multidisciplinary position statement on autosomal dominant polycystic kidney disease care: European ADPKD Forum and Multispecialist Roundtable participants

Autosomal dominant polycystic kidney disease (ADPKD) is a chronic, progressive condition characterized by the development and growth of cysts in the kidneys and other organs and by additional systemic manifestations. Individuals with ADPKD should have access to lifelong, multidisciplinary, specialist and patient-centred care involving: (i) a holistic and comprehensive assessment of the manifestations, complications, prognosis and impact of the disease (in physical, psychological and social terms) on the patient and their family; (ii) access to treatment to relieve symptoms, manage complications, preserve kidney function, lower the risk of cardiovascular disease and maintain quality of life; and (iii) information and support to help patients and their families act as fully informed and active partners in care, i.e. to maintain self-management approaches, deal with the impact of the condition and participate in decision-making regarding healthcare policies, services and research. Building on discussions at an international roundtable of specialists and patient advocates involved in ADPKD care, this article sets out (i) the principles for a patient-centred, holistic approach to the organization and delivery of ADPKD care in practice, with a focus on multispecialist collaboration and shared-decision making, and (ii) the rationale and knowledge base for a route map for ADPKD care intended to help patients navigate the services available to them and to help stakeholders and decision-makers take practical steps to ensure that all patients with ADPKD can access the comprehensive multispecialist care to which they are entitled. Further multispecialty collaboration is encouraged to design and implement these services, and to work with patient organizations to promote awareness building, education and research.

MRI-derived markers for predicting a decline in renal function in patients with autosomal dominant polycystic kidney disease

Autosomal dominant polycystic kidney disease (ADPKD) constitutes the fourth cause of end-stage renal disease in Europe. The course of the disease varies widely among patients with ADPKD. Due to the emergence of new possibilities of pharmacotherapy, it has become crucial to identify the group of patients with the fastest rate and risk of disease progression. This particular group of patients will benefit most from the therapy and they are the best candidates for clinical trials. At the early stages of ADPKD typical markers of severity and progression of the disease remain unchanged in contrast to the kidney volume, which increases continuously in an exponential way. Therefore, the use of height-adjusted total kidney volume as a biomarker should become a mandatory diagnostic option. Also, quantitative MRI techniques are promising biomarkers for the evaluation of disease severity and could provide additional insights into its course.

Lanreotide Reduces Liver Growth In Patients With Autosomal Dominant Polycystic Liver and Kidney Disease

BACKGROUND & AIMS

Polycystic liver disease is the most common extrarenal manifestation of autosomal dominant polycystic kidney disease (ADPKD). There is need for robust long-term evidence for the volume-reducing effect of somatostatin analogues. We made use of data from an open-label, randomized trial to determine the effects of lanreotide on height-adjusted liver volume (hTLV) and combined height-adjusted liver and kidney volume (hTLKV) in patients with ADPKD.

METHODS

We performed a 120-week study comparing the reno-protective effects of lanreotide vs standard care in 305 patients with ADPKD (the DIPAK-1 study). For this analysis, we studied the 175 patients with polycystic liver disease with hepatic cysts identified by magnetic resonance imaging and liver volume ≥2000 mL. Of these, 93 patients were assigned to a group that received lanreotide (120 mg subcutaneously every 4 weeks) and 82 to a group that received standard care (blood pressure control, a sodium-restricted diet, and antihypertensive agents). The primary endpoint was percent change in hTLV between baseline and end of treatment (week 120). A secondary endpoint was change in hTLKV.

RESULTS

At 120 weeks, hTLV decreased by 1.99% in the lanreotide group (95% confidence interval [CI], -4.21 to 0.24) and increased by 3.92% in the control group (95% CI, 1.56-6.28). Compared with the control group, lanreotide reduced the growth of hTLV by 5.91% (95% CI, -9.18 to -2.63; P < .001). Growth of hTLV was still reduced by 3.87% at 4 months after the last injection of lanreotide compared with baseline (95% CI, -7.55 to -0.18; P = .04). Lanreotide reduced growth of hTLKV by 7.18% compared with the control group (95% CI, -10.25 to -4.12; P < .001).

CONCLUSIONS

In this subanalysis of a randomized trial of patients with polycystic liver disease due to ADPKD, lanreotide for 120 weeks reduced the growth of liver and combined liver and kidney volume. This effect was still present 4 months after the last injection of lanreotide. ClinicalTrials.gov, Number: NCT01616927.

A rapid high-performance semi-automated tool to measure total kidney volume from MRI in autosomal dominant polycystic kidney disease

OBJECTIVES

To develop a high-performance, rapid semi-automated method (Sheffield TKV Tool) for measuring total kidney volume (TKV) from magnetic resonance images (MRI) in patients with autosomal dominant polycystic kidney disease (ADPKD).

METHODS

TKV was initially measured in 61 patients with ADPKD using the Sheffield TKV Tool and its performance compared to manual segmentation and other published methods (ellipsoidal, mid-slice, MIROS). It was then validated using an external dataset of MRI scans from 65 patients with ADPKD.

RESULTS

Sixty-one patients (mean age 45 ± 14 years, baseline eGFR 76 ± 32 ml/min/1.73 m2) with ADPKD had a wide range of TKV (258-3680 ml) measured manually. The Sheffield TKV Tool was highly accurate (mean volume error 0.5 ± 5.3% for right kidney, - 0.7 ± 5.5% for left kidney), reproducible (intra-operator variability - 0.2 ± 1.3%; inter-operator variability 1.1 ± 2.9%) and outperformed published methods. It took less than 6 min to execute and performed consistently with high accuracy in an external MRI dataset of T2-weighted sequences with TKV acquired using three different scanners and measured using a different segmentation methodology (mean volume error was 3.45 ± 3.96%, n = 65).

CONCLUSIONS

The Sheffield TKV Tool is operator friendly, requiring minimal user interaction to rapidly, accurately and reproducibly measure TKV in this, the largest reported unselected European patient cohort with ADPKD. It is more accurate than estimating equations and its accuracy is maintained at larger kidney volumes than previously reported with other semi-automated methods. It is free to use, can run as an independent executable and will accelerate the application of TKV as a prognostic biomarker for ADPKD into clinical practice.

KEY POINTS

• This new semi-automated method (Sheffield TKV Tool) to measure total kidney volume (TKV) will facilitate the routine clinical assessment of patients with ADPKD. • Measuring TKV manually is time consuming and laborious. • TKV is a prognostic indicator in ADPKD and the only imaging biomarker approved by the FDA and EMA.

Prognostic Performance of Kidney Volume Measurement for Polycystic Kidney Disease: A Comparative Study of Ellipsoid vs. Manual Segmentation

Total kidney volume (TKV) is a validated prognostic biomarker for risk assessment in autosomal dominant polycystic kidney disease (ADPKD). TKV by manual segmentation (MS) is the “gold standard” but is time-consuming and requires expertise. The purpose of this study was to compare TKV-based prognostic performance by ellipsoid (EL) vs. MS in a large cohort of patients. Cross-sectional study of 308 patients seen at a tertiary referral center; all had a standardized MRI with typical imaging of ADPKD. An experienced radiologist blinded to patient clinical results performed all TKV measurements by EL and MS. We assessed the agreement of TKV measurements by intraclass correlation(ICC) and Bland-Altman plot and also how the disagreement of the two methods impact the prognostic performance of the Mayo Clinic Imaging Classification (MCIC). We found a high ICC of TKV measurements (0.991, p < 0.001) between EL vs. MS; however, 5.5% of the cases displayed disagreement of TKV measurements >20%. We also found a high degree of agreement of the individual MCIC risk classes (i.e. 1A to 1E) with a Cohen’s weighted-kappa of 0.89; but 42 cases (13.6%) were misclassified by EL with no misclassification spanning more than one risk class. The sensitivity and specificity of EL in distinguishing low-risk (1A-B) from high-risk (1C-E) MCIC prognostic grouping were 96.6% and 96.1%, respectively. Overall, we found an excellent agreement of TKV-based risk assessment between EL and MS. However, caution is warranted for patients with MCIC 1B and 1C, as misclassification can have therapeutic consequence.

Automatic Measurement of Kidney and Liver Volumes from MR Images of Patients Affected by Autosomal Dominant Polycystic Kidney Disease

BACKGROUND

The formation and growth of cysts in kidneys, and often liver, in autosomal dominant polycystic kidney disease (ADPKD) cause progressive increases in total kidney volume (TKV) and liver volume (TLV). Laborious and time-consuming manual tracing of kidneys and liver is the current gold standard. We developed a fully automated segmentation method for TKV and TLV measurement that uses a deep learning network optimized to perform semantic segmentation of kidneys and liver.

METHODS

We used 80% of a set of 440 abdominal magnetic resonance images (T2-weighted HASTE coronal sequences) from patients with ADPKD to train the network and the remaining 20% for validation. Both kidneys and liver were also segmented manually. To evaluate the method's performance, we used an additional test set of images from 100 patients, 45 of whom were also involved in longitudinal analyses.

RESULTS

TKV and TLV measured by the automated approach correlated highly with manually traced TKV and TLV (intraclass correlation coefficients, 0.998 and 0.996, respectively), with low bias and high precision (<0.1%±2.7% for TKV and -1.6%±3.1% for TLV); this was comparable with inter-reader variability of manual tracing (<0.1%±3.5% for TKV and -1.5%±4.8% for TLV). For longitudinal analysis, bias and precision were <0.1%±3.2% for TKV and 1.4%±2.9% for TLV growth.

CONCLUSIONS

These findings demonstrate a fully automated segmentation method that measures TKV, TLV, and changes in these parameters as accurately as manual tracing. This technique may facilitate future studies in which automated and reproducible TKV and TLV measurements are needed to assess disease severity, disease progression, and treatment response.

Plasma copeptin levels predict disease progression and tolvaptan efficacy in autosomal dominant polycystic kidney disease

In the TEMPO 3:4 Trial, treatment with tolvaptan, a vasopressin V2 receptor antagonist, slowed the increase in total kidney volume and decline in estimated glomerular filtration rate (eGFR) in autosomal dominant polycystic kidney disease (ADPKD). We investigated whether plasma copeptin levels, a marker of plasma vasopressin, are associated with disease progression, and whether pre-treatment copeptin and treatment-induced change in copeptin are associated with tolvaptan treatment efficacy. This post hoc analysis included 1,280 TEMPO 3:4 participants (aged 18-50 years, estimated creatinine clearance ≥60 ml/min and total kidney volume ≥750 mL) who had plasma samples available at baseline for measurement of copeptin using an automated immunofluorescence assay. In placebo-treated subjects, baseline copeptin predicted kidney growth and eGFR decline over 3 years. These associations were independent of sex, age, and baseline eGFR, but were no longer statistically significant after additional adjustment for baseline total kidney volume. In tolvaptan-treated subjects, copeptin increased from baseline to week 3 (6.3 pmol/L versus 21.9 pmol/L, respectively). In tolvaptan-treated subjects with higher baseline copeptin levels, a larger treatment effect was noted with respect to kidney growth rate and eGFR decline. Tolvaptan-treated subjects with a larger percentage increase in copeptin from baseline to week 3 had a better disease outcome, with less kidney growth and eGFR decline after three years. Copeptin holds promise as a biomarker to predict outcome and tolvaptan treatment efficacy in ADPKD.

Association of plasma somatostatin with disease severity and progression in patients with autosomal dominant polycystic kidney disease

Background

Somatostatin (SST) inhibits intracellular cyclic adenosine monophosphate (cAMP) production and thus may modify cyst formation in autosomal dominant polycystic kidney disease (ADPKD). We investigated whether endogenous plasma SST concentration is associated with disease severity and progression in patients with ADPKD, and whether plasma SST concentrations change during treatment with a vasopressin V2 receptor antagonist or SST analogue.

Methods

In this observational study, fasting concentrations of SST were measured in 127 ADPKD patients (diagnosed upon the revised Ravine criteria) by ELISA. cAMP was measured in 24 h urine by Radio Immuno Assay. Kidney function was measured (mGFR) as ¹²⁵I-iothalamate clearance, and total kidney volume was measured by MRI volumetry and adjusted for height (htTKV). Disease progression was expressed as annual change in mGFR and htTKV. Additionally, baseline versus follow-up SST concentrations were compared in ADPKD patients during vasopressin V2 receptor antagonist (tolvaptan) (n = 27) or SST analogue (lanreotide) treatment (n = 25).

Results

In 127 ADPKD patients, 41 ± 11 years, 44% female, eGFR 73 ± 32 ml/min/1.73m², mGFR 75 ± 32 ml/min/1.73m² and htTKV 826 (521–1297) ml/m, SST concentration was 48.5 (34.3–77.8) pg/ml. At baseline, SST was associated with urinary cAMP, mGFR and htTKV (p = 0.02, p = 0.004 and p = 0.02, respectively), but these associations lost significance after adjustment for age and sex or protein intake (p = 0.09, p = 0.06 and p = 0.15 respectively). Baseline SST was not associated with annual change in mGFR, or htTKV during follow-up (st. β = − 0.02, p = 0.87 and st. β = − 0.07, p = 0.54 respectively). During treatment with tolvaptan SST levels remained stable 38.2 (23.8–70.7) pg/mL vs. 39.8 (31.2–58.5) pg/mL, p = 0.85), whereas SST levels decreased significantly during treatment with lanreotide (42.5 (33.2–55.0) pg/ml vs. 29.3 (24.8–37.6), p = 0.008).

Conclusions

Fasting plasma SST concentration is not associated with disease severity or progression in patients with ADPKD. Treatment with lanreotide caused a decrease in SST concentration. These data suggest that plasma SST cannot be used as a biomarker to assess prognosis in ADPKD, but leave the possibility open that change in SST concentration during lanreotide treatment may reflect therapy efficacy.

Electronic supplementary material

The online version of this article (10.1186/s12882-018-1176-y) contains supplementary material, which is available to authorized users.

Effect of Lanreotide on Kidney Function in Patients With Autosomal Dominant Polycystic Kidney Disease: The DIPAK 1 Randomized Clinical Trial

Importance

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive cyst formation in both kidneys and loss of renal function, eventually leading to a need for kidney replacement therapy. There are limited therapeutic management options.

Objective

To examine the effect of the somatostatin analogue lanreotide on the rate of kidney function loss in patients with later-stage ADPKD.

Design, Setting, and Participants

An open-label randomized clinical trial with blinded end point assessment that included 309 patients with ADPKD from July 2012 to March 2015 at 4 nephrology outpatient clinics in the Netherlands. Eligible patients were 18 to 60 years of age and had an estimated glomerular filtration rate (eGFR) of 30 to 60 mL/min/1.73 m2. Follow-up of the 2.5-year trial ended in August 2017.

Interventions

Patients were randomized to receive either lanreotide (120 mg subcutaneously once every 4 weeks) in addition to standard care (n = 153) or standard care only (target blood pressure <140/90 mm Hg; n = 152).

Main Outcomes and Measures

Primary outcome was annual change in eGFR assessed as slope through eGFR values during the 2.5-year treatment phase. Secondary outcomes included change in eGFR before vs after treatment, incidence of worsening kidney function (start of dialysis or 30% decrease in eGFR), change in total kidney volume and change in quality of life (range: 1 [not bothered] to 5 [extremely bothered]).

Results

Among the 309 patients who were randomized (mean [SD] age, 48.4 [7.3] years; 53.4% women), 261 (85.6%) completed the trial. Annual rate of eGFR decline for the lanreotide vs the control group was -3.53 vs -3.46 mL/min/1.73 m2 per year (difference, -0.08 [95% CI, -0.71 to 0.56]; P = .81). There were no significant differences for incidence of worsening kidney function (hazard ratio, 0.87 [95% CI, 0.49 to 1.52]; P = .87), change in eGFR (-3.58 vs -3.45; difference, -0.13 mL/min/1.73 m2 per year [95% CI, -1.76 to 1.50]; P = .88), and change in quality of life (0.05 vs 0.07; difference, -0.03 units per year [95% CI, -0.13 to 0.08]; P = .67). The rate of growth in total kidney volume was lower in the lanreotide group than the control group (4.15% vs 5.56%; difference, -1.33% per year [95% CI, -2.41% to -0.24%]; P = .02). Adverse events in the lanreotide vs control group included injection site discomfort (32% vs 0.7%), injection site papule (5.9% vs 0%), loose stools (91% vs 6.6%), abdominal discomfort (79% vs 20%), and hepatic cyst infections (5.2% vs 0%).

Conclusions and Relevance

Among patients with later-stage autosomal dominant polycystic kidney disease, treatment with lanreotide compared with standard care did not slow the decline in kidney function over 2.5 years of follow-up. These findings do not support the use of lanreotide for treatment of later-stage autosomal dominant polycystic kidney disease.

Trial Registration

ClinicalTrials.gov Identifier: NCT01616927.

Updated Canadian Expert Consensus on Assessing Risk of Disease Progression and Pharmacological Management of Autosomal Dominant Polycystic Kidney Disease

PURPOSE

The purpose of this article is to update the previously published consensus recommendations from March 2017 discussing the optimal management of adult patients with autosomal dominant polycystic kidney disease (ADPKD). This document focuses on recent developments in genetic testing, renal imaging, assessment of risk regarding disease progression, and pharmacological treatment options for ADPKD.

SOURCES OF INFORMATION

Published literature was searched in PubMed, the Cochrane Library, and Google Scholar to identify the latest evidence related to the treatment and management of ADPKD.

METHODS

All pertinent articles were reviewed by the authors to determine if a new recommendation was required, or if the previous recommendation needed updating. The consensus recommendations were developed by the authors based on discussion and review of the evidence.

KEY FINDINGS

The genetics of ADPKD are becoming more complex with the identification of new and rarer genetic variants such as GANAB. Magnetic resonance imaging (MRI) and computed tomography (CT) continue to be the main imaging modalities used to evaluate ADPKD. Total kidney volume (TKV) continues to be the most validated and most used measure to assess disease progression. Since the publication of the previous consensus recommendations, the use of the Mayo Clinic Classification for prognostication purposes has been validated in patients with class 1 ADPKD. Recent evidence supports the benefits of a low-osmolar diet and dietary sodium restriction in patients with ADPKD. Evidence from the Replicating Evidence of Preserved Renal Function: an Investigation of Tolvaptan Safety and Efficacy in ADPKD (REPRISE) trial supports the use of ADH (antidiuretic hormone) receptor antagonism in patients with ADPKD 18 to 55 years of age with eGFR (estimated glomerular filtration rate) of 25 to 65 mL/min/1.73 m2 or 56 to 65 years of age with eGFR of 25 to 44 mL/min/1.73 m2 with historical evidence of a decline in eGFR >2.0 mL/min/1.73 m2/year.

LIMITATIONS

Available literature was limited to English language publications and to publications indexed in PubMed, the Cochrane Library, and Google Scholar.

IMPLICATIONS

Advances in the assessment of the risk of disease progression include the validation of the Mayo Clinic Classification for patients with class 1 ADPKD. Advances in the pharmacological management of ADPKD include the expansion of the use of ADH receptor antagonism in patients 18 to 55 years of age with eGFR of 25 to 65 mL/min/1.73 m2 or 56 to 65 years of age with eGFR of 25 to 44 mL/min/1.73 m2 with historical evidence of a decline in eGFR >2.0 mL/min/1.73 m2/year, as per the results of the REPRISE study.

In vivo three-dimensional photoacoustic imaging of the renal vasculature in preclinical rodent models

Noninvasive imaging of the kidney vasculature in preclinical murine models is important for the assessment of renal development, studying diseases and evaluating new therapies but is challenging to achieve using existing imaging modalities. Photoacoustic imaging is a promising new technique that is particularly well suited to visualizing the vasculature and could provide an alternative to existing preclinical imaging methods for studying renal vascular anatomy and function. To investigate this, an all-optical Fabry-Perot-based photoacoustic scanner was used to image the abdominal region of mice. High-resolution three-dimensional, noninvasive, label-free photoacoustic images of the mouse kidney and renal vasculature were acquired in vivo. The scanner was also used to visualize and quantify differences in the vascular architecture of the kidney in vivo due to polycystic kidney disease. This study suggests that photoacoustic imaging could be utilized as a novel preclinical imaging tool for studying the biology of renal disease.

3DUS as an alternative to MRI for measuring renal volume in children with autosomal dominant polycystic kidney disease

BACKGROUND

Total kidney volume, measured by magnetic resonance imaging (MRI), is a validated disease progression marker in adults with autosomal dominant polycystic kidney disease (ADPKD). However, in childhood, MRI is burdensome, explaining the need for alternatives.

METHODS

Kidney volume (KV) was evaluated in 30 children with ADPKD, using three-dimensional ultrasound (3DUS), applying the ellipsoid method and manual contouring (KV_{3DUS-ellipsoid,} KV_3DUS-contour respectively); manual contouring on MRI (KV_MRI), and the ellipsoid method on two-dimensional ultrasound (2DUS, KV_2DUS). Correlations and differences were evaluated using Pearson's r and Wilcoxon signed-rank tests, and variability using Bland-Altman plots.

RESULTS

All ultrasound volumetry methods showed significantly lower mean (± SD) KV (mL), compared with MRI-KV_2DUS: 159 (±101); K_{3DUS-ellipsoid}: 169 (±105); KV_3DUS-contour: 185 (±110); KV_MRI: 206 (±130); all p < 0.001. All had a strong correlation with KV_MRI: 2DUS: r = 0.96; 3DUS-ellipsoid: r = 0.89 and 3DUS-contour: r = 0.94. Both before and after correction factor application, Bland-Altman plots showed lower variability and absolute error for KV_3DUS-contour vs KV_2DUS and KV_{3DUS-ellipsoid}.

CONCLUSIONS

Compared with MRI, ultrasound volumetry was prone to underestimation. However, KV_3DUS-contour represents a valuable alternative for MRI in early ADPKD. Although more time-consuming, KV_3DUS-contour is recommended over KV_2DUS for estimation and follow-up of KV in ADPKD children, given its smaller error.

Novel semi-automated kidney volume measurements in autosomal dominant polycystic kidney disease

BACKGROUND

We assessed the effectiveness and convenience of a novel semi-automatic kidney volume (KV) measuring high-speed 3D-image analysis system SYNAPSE VINCENT^® (Fuji Medical Systems, Tokyo, Japan) for autosomal dominant polycystic kidney disease (ADPKD) patients.

METHODS

We developed a novel semi-automated KV measurement software for patients with ADPKD to be included in the imaging analysis software SYNAPSE VINCENT^®. The software extracts renal regions using image recognition software and measures KV (VINCENT KV). The algorithm was designed to work with the manual designation of a long axis of a kidney including cysts. After using the software to assess the predictive accuracy of the VINCENT method, we performed an external validation study and compared accurate KV and ellipsoid KV based on geometric modeling by linear regression analysis and Bland-Altman analysis.

RESULTS

Median eGFR was 46.9 ml/min/1.73 m². Median accurate KV, Vincent KV and ellipsoid KV were 627.7, 619.4 ml (IQR 431.5-947.0) and 694.0 ml (IQR 488.1-1107.4), respectively. Compared with ellipsoid KV (r = 0.9504), Vincent KV correlated strongly with accurate KV (r = 0.9968), without systematic underestimation or overestimation (ellipsoid KV; 14.2 ± 22.0%, Vincent KV; - 0.6 ± 6.0%). There were no significant slice thickness-specific differences (p = 0.2980).

CONCLUSIONS

The VINCENT method is an accurate and convenient semi-automatic method to measure KV in patients with ADPKD compared with the conventional ellipsoid method.

Temporal and geographical external validation study and extension of the Mayo Clinic prediction model to predict eGFR in the younger population of Swiss ADPKD patients

Background

Prediction models in autosomal dominant polycystic kidney disease (ADPKD) are useful in clinical settings to identify patients with greater risk of a rapid disease progression in whom a treatment may have more benefits than harms. Mayo Clinic investigators developed a risk prediction tool for ADPKD patients using a single kidney value. Our aim was to perform an independent geographical and temporal external validation as well as evaluate the potential for improving the predictive performance by including additional information on total kidney volume.

Methods

We used data from the on-going Swiss ADPKD study from 2006 to 2016. The main analysis included a sample size of 214 patients with Typical ADPKD (Class 1). We evaluated the Mayo Clinic model performance calibration and discrimination in our external sample and assessed whether predictive performance could be improved through the addition of subsequent kidney volume measurements beyond the baseline assessment.

Results

The calibration of both versions of the Mayo Clinic prediction model using continuous Height adjusted total kidney volume (HtTKV) and using risk subclasses was good, with R² of 78% and 70%, respectively. Accuracy was also good with 91.5% and 88.7% of the predicted within 30% of the observed, respectively. Additional information regarding kidney volume did not substantially improve the model performance.

Conclusion

The Mayo Clinic prediction models are generalizable to other clinical settings and provide an accurate tool based on available predictors to identify patients at high risk for rapid disease progression.

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

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.

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

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.

Total Kidney Volume as a Biomarker of Disease Progression in Autosomal Dominant Polycystic Kidney Disease

Purpose of review:

Autosomal dominant polycystic kidney disease (ADPKD) is an inherited disorder characterized by the formation of kidney cysts and kidney enlargement, which progresses to kidney failure by the fifth to seventh decade of life in a majority of patients. Disease progression is evaluated primarily through serum creatinine and estimated glomerular filtration rate (eGFR) measurements; however, it is known that serum creatinine and eGFR values typically do not change until the fourth or fifth decade of life. Until recently, therapy only existed to target complications of ADPKD. As therapeutic agents continue to be investigated for use in ADPKD, a suitable biomarker of disease progression in place of serum creatinine is needed.

Sources of information:

This review summarizes recent research regarding the use of total kidney volume as a biomarker in ADPKD, as presented at the Canadian Society of Nephrology symposium held in April 2015.

Findings:

Measurement of patients’ total kidney volume made using ultrasound (US) or magnetic resonance imaging (MRI) has been shown by the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) study to be directly correlated with both increases in cyst volume and change in glomerular filtration rate (GFR). Additional studies have shown total kidney volume to have an association with complications of ADPKD as well.

Limitations:

Areas for further study continue to exist in comparison of methods of measuring total kidney volume.

Implications:

We believe that the evidence suggests that total kidney volume may be an appropriate surrogate marker for ADPKD disease progression.

Assessing Risk of Disease Progression and Pharmacological Management of Autosomal Dominant Polycystic Kidney Disease: A Canadian Expert Consensus

Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited renal disorder worldwide. The disease is characterized by renal cysts and progressive renal failure due to progressive enlargement of cysts and renal fibrosis. An estimated 45% to 70% of patients with ADPKD progress to end-stage renal disease by age 65 years. Although both targeted and nontargeted therapies have been tested in patients with ADPKD, tolvaptan is currently the only pharmacological therapy approved in Canada for the treatment of ADPKD. The purpose of this consensus recommendation is to develop an evidence-informed recommendation for the optimal management of adult patients with ADPKD. This document focuses on the role of genetic testing, the role of renal imaging, predicting the risk of disease progression, and pharmacological treatment options for ADPKD. These areas of focus were derived from 2 national surveys that were disseminated to nephrologists and patients with ADPKD with the aim of identifying unmet needs in the management of ADPKD in Canada. Specific recommendations are provided for the treatment of ADPKD with tolvaptan.

Semiautomated Segmentation of Polycystic Kidneys in T2-Weighted MR Images

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.

Recommendations for the use of tolvaptan in autosomal dominant polycystic kidney disease: a position statement on behalf of the ERA-EDTA Working Groups on Inherited Kidney Disorders and European Renal Best Practice

Recently, the European Medicines Agency approved the use of the vasopressin V2 receptor antagonist tolvaptan to slow the progression of cyst development and renal insufficiency of autosomal dominant polycystic kidney disease (ADPKD) in adult patients with chronic kidney disease stages 1–3 at initiation of treatment with evidence of rapidly progressing disease. In this paper, on behalf of the ERA-EDTA Working Groups of Inherited Kidney Disorders and European Renal Best Practice, we aim to provide guidance for making the decision as to which ADPKD patients to treat with tolvaptan. The present position statement includes a series of recommendations resulting in a hierarchical decision algorithm that encompasses a sequence of risk-factor assessments in a descending order of reliability. By examining the best-validated markers first, we aim to identify ADPKD patients who have documented rapid disease progression or are likely to have rapid disease progression. We believe that this procedure offers the best opportunity to select patients who are most likely to benefit from tolvaptan, thus improving the benefit-to-risk ratio and cost-effectiveness of this treatment. It is important to emphasize that the decision to initiate treatment requires the consideration of many factors besides eligibility, such as contraindications, potential adverse events, as well as patient motivation and lifestyle factors, and requires shared decision-making with the patient.

Diagnostic Evaluation as a Biomarker in Patients with ADPKD

Recently, newer treatments have been introduced for autosomal dominant polycystic kidney disease (ADPKD) patients. Since cysts grow and renal function declines over a long period of time, the evaluation of treatment effects in ADPKD has been very difficult. Therefore, there has been a great interest to find out the "better" surrogate marker or biomarker which reflects disease progression. Biomarkers in ADPKD should have three clinical implications: (1) They should reflect disease severity, (2) they should distinguish patients with poor versus good prognosis to select those who will benefit better from the treatment, and (3) they should be easy to evaluate short-term outcome after treatment, which will demonstrate hard outcome. Herein, we will discuss currently available surrogate biomarkers including the volume of total kidney and urinary molecular markers.