Utility of new image-derived biomarkers for autosomal dominant polycystic kidney disease prognosis using automated instance cyst segmentation.

New image-derived biomarkers for patients affected by autosomal dominant polycystic kidney disease are needed to improve current clinical management. The measurement of total kidney volume (TKV) provides critical information for clinicians to drive care decisions. However, patients with similar TKV may present with very different phenotypes, often requiring subjective decisions based on other factors (e.g., appearance of healthy kidney parenchyma, a few cysts contributing significantly to overall TKV, etc.). In this study, we describe a new technique to individually segment cysts and quantify biometric parameters including cyst volume, cyst number, parenchyma volume, and cyst parenchyma surface area. Using data from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) study the utility of these new parameters was explored, both quantitatively as well as visually. Total cyst number and cyst parenchyma surface area showed superior prediction of the slope of estimated glomerular filtration rate decline, kidney failure and chronic kidney disease stages 3A, 3B, and 4, compared to TKV. In addition, presentations such as a few large cysts contributing significantly to overall kidney volume were shown to be much better stratified in terms of outcome predictions. Thus, these new image biomarkers, which can be obtained automatically, will have great utility in future studies and clinical care for patients affected by autosomal dominant polycystic kidney disease.

Volume Progression and Imaging Classification of Polycystic Liver in Early Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND AND OBJECTIVES: The progression of polycystic liver disease is not well understood. The purpose of the study is to evaluate the associations of polycystic liver progression with other disease progression variables and classify liver progression on the basis of patient's age, height-adjusted liver cystic volume, and height-adjusted liver volume. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Prospective longitudinal magnetic resonance images from 670 patients with early autosomal dominant polycystic kidney disease for up to 14 years of follow-up were evaluated to measure height-adjusted liver cystic volume and height-adjusted liver volume. Among them, 245 patients with liver cyst volume >50 ml at baseline were included in the longitudinal analysis. Linear mixed models on log-transformed height-adjusted liver cystic volume and height-adjusted liver volume were fitted to approximate mean annual rate of change for each outcome. The association of sex, body mass index, genotype, baseline height-adjusted total kidney volume, and Mayo imaging class was assessed. We calculated height-adjusted liver cystic volume ranges for each specific age and divided them into five classes on the basis of annual percentage increase in height-adjusted liver cystic volume. RESULTS: The mean annual growth rate of height-adjusted liver cystic volume was 12% (95% confidence interval, 11.1% to 13.1%; P<0.001), whereas that for height-adjusted liver volume was 2% (95% confidence interval, 1.9% to 2.6%; P<0.001). Women had higher baseline height-adjusted liver cystic volume than men, but men had higher height-adjusted liver cystic volume growth rate than women by 2% (95% confidence interval, 0.4% to 4.5%; P=0.02). Whereas the height-adjusted liver cystic volume growth rate decreased in women after menopause, no decrease was observed in men at any age. Body mass index, genotype, and baseline height-adjusted total kidney volume were not associated with the growth rate of height-adjusted liver cystic volume or height-adjusted liver volume. According to the height-adjusted liver cystic volume growth rate, patients were classified into five classes (number of women, men in each class): A (24, six); B (44, 13); C (43, 48); D (28, 17); and E (13, nine). CONCLUSIONS: Compared with height-adjusted liver volume, the use of height-adjusted liver cystic volume showed greater separations in volumetric progression of polycystic liver disease. Similar to the Mayo imaging classification for the kidney, the progression of polycystic liver disease may be categorized on the basis of patient's age and height-adjusted liver cystic volume.

Prognostic Value of Fibroblast Growth Factor 23 in Autosomal Dominant Polycystic Kidney Disease.

INTRODUCTION: Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive cyst growth and a loss of functioning renal mass, but a decline in glomerular filtration rate (GFR) and onset of end-stage renal disease (ESRD) occur late in the disease course. There is therefore a great need for early prognostic biomarkers in this disorder. METHODS: We measured baseline serum fibroblast growth factor 23 (FGF23) levels in 192 patients with ADPKD from the Consortium for Radiologic Imaging Studies of PKD (CRISP) cohort that were followed for a median of 13 years and tested the association between FGF23 levels and change over time in height-adjusted total kidney volume (htTKV), GFR, and time to the composite endpoints of ESRD, death, and doubling of serum creatinine. RESULTS: Patients in the highest quartile for baseline FGF23 level had a higher rate of increase in htTKV (0.95% per year, P = 0.0016), and faster rate of decline in GFR (difference of -1.03 ml/min/1.73 m2 per year, P = 0.005) compared with the lowest quartile, after adjusting for other covariates, including htTKV and genotype. The highest quartile of FGF23 was also associated with a substantial increase in risk for the composite endpoint of ESRD, death, or doubling of serum creatinine (hazard ratio [HR] of 2.45 in the fully adjusted model, P = 0.03). CONCLUSION: FGF23 is a prognostic biomarker for disease progression and clinically important outcomes in ADPKD, and has additive value to established imaging and genetic biomarkers.

Growth Pattern of Kidney Cyst Number and Volume in Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND AND OBJECTIVES: To evaluate the growth pattern of kidney cyst number and cyst volume in association with kidney size, demographics, and genotypes in autosomal dominant polycystic kidney disease. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Kidney cyst number and cyst volume were measured from serial magnetic resonance images, giving a maximum follow-up of 14.23 years, from 241 patients with autosomal dominant polycystic kidney disease (15-46 years old at baseline). The growth pattern was analyzed, in association with sex, age, height-adjusted total kidney volume, and genotype, using linear mixed models of repeated measurements and tests of interactions with age (as a time-dependent covariate) to assess rates of change over time. Models were also fit using Irazabal class. Genotypic groups were characterized as either (1) PKD1 truncating, PKD1 nontruncating, and PKD2 plus patients with no mutation detected; or (2) in combination with PKD1 mutation strength groups. RESULTS: Imaging and genetic data were collected (at least one visit) for 236 participants. The mean height-adjusted total cyst number increased exponentially over time from a baseline value of 762 to 1715 at the last clinic visit, while the mean height-adjusted total cyst volume increased exponentially from 305 to 770 ml. Height-adjusted total kidney volume, height-adjusted total cyst number, and height-adjusted total cyst volume were all highly correlated over time. Female participants and participants with larger height-adjusted total kidney volume at baseline showed smaller rates of change in the log of height-adjusted total cyst number and cyst volume. PKD1 was associated with significant increases in both cyst number and volume at a given age, but genotype did not significantly affect the rate of growth. CONCLUSIONS: Both height-adjusted total cyst number and height-adjusted total cyst volume increased exponentially and more than doubled over 14.23 years of follow-up. Compared with PKD2 plus no mutation detected, PKD1 was associated with a greater cyst number and volume at a given age, but no significant difference in the rate of growth.

Long-term trajectory of kidney function in autosomal-dominant polycystic kidney disease.

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by cyst and kidney growth, which is hypothesized to cause loss of functioning renal mass and eventually end-stage kidney disease. However, the time course of decline in glomerular filtration rate (GFR) is poorly defined. The Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease study is a 14-year observational cohort study of 241 adults with ADPKD. As an estimate of the rate of kidney growth, participants were stratified into 5 subclasses based on baseline age and magnetic resonance imaging measurements of total kidney volume (TKV) according to the method of Irazabal. GFR trajectories spanning over four decades of life were reconstructed and fitted using mixed polynomial models, which were validated using data from the HALT-PKD study. GFR trajectories were nonlinear, with a period of relative stability in most participants, followed by accelerating decline. The shape and slope of these trajectories were strongly associated with baseline Irazabal class. Patients with PKD1 mutations had a steeper GFR decline than patients with PKD2 mutations or with no detected mutation, largely mediated by the effect of genotype on Irazabal class. Thus, GFR decline in ADPKD is nonlinear, and its trajectory throughout adulthood can be predicted from a single measurement of kidney volume. These models can be used for clinical prognostication, clinical trial design, and patient selection for clinical interventions. Our findings support a causal link between growth in kidney volume and GFR decline, adding support for the use of TKV as a surrogate endpoint in clinical trials.

Relationship between caffeine intake and autosomal dominant polycystic kidney disease progression: a retrospective analysis using the CRISP cohort.

BACKGROUND: Caffeine has been proposed, based on in vitro cultured cell studies, to accelerate progression of autosomal dominant polycystic kidney disease (ADPKD) by increasing kidney size. Since ADPKD patients are advised to minimize caffeine intake, we investigated the effect of caffeine on disease progression in the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP), a prospective, observational cohort study. METHODS: Our study included 239 patients (mean age = 32.3 ± 8.9 ys; 188 caffeine consumers) with a median follow-up time of 12.5 years. Caffeine intake reported at baseline was dichotomized (any vs. none). Linear mixed models, unadjusted and adjusted for age, race, sex, BMI, smoking, hypertension, genetics and time, were used to model height-adjusted total kidney volume (htTKV) and iothalamate clearance (mGFR). Cox proportional hazards models and Kaplan-Meier plots examined the effect of caffeine on time to ESRD or death. RESULTS: Caffeine-by-time was statistically significant when modeling ln(htTKV) in unadjusted and adjusted models (p <  0.01) indicating that caffeine consumers had slightly faster kidney growth (by 0.6% per year), but htTKV remained smaller from baseline throughout the study. Caffeine consumption was not associated with a difference in mGFR, or in the time to ESRD or death (p > 0.05). Moreover the results were similar when outcomes were modeled as a function of caffeine dose. CONCLUSION: We conclude that caffeine does not have a significant detrimental effect on disease progression in ADPKD.

Baseline total kidney volume and the rate of kidney growth are associated with chronic kidney disease progression in Autosomal Dominant Polycystic Kidney Disease.

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive enlargement of kidney cysts leading to chronic kidney disease (CKD) and end-stage renal disease (ESRD). Identification of an early biomarker that can predict progression of CKD is urgently needed. In an earlier Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) study (a prospective, multicenter, observational analysis of 241 patients with ADPKD initiated in 2000), baseline height-adjusted total kidney volume (htTKV) was shown to be associated with development of CKD stage 3 after eight years of follow-up. Here we conducted an extended study and found that in a multivariable logistic regression model, baseline htTKV was shown to be a strong, independent predictor for the development of CKD after a median follow-up of 13 years. The odds ratio of reaching each CKD stage per 100 mL/m increment in htTKV was 1.38 (95% confidence interval 1.19-1.60) for stage 3, 1.42 (1.23-1.64) for stage 4, and 1.35 (1.18-1.55) for stage 5 or ESRD. Baseline htTKV was also associated with relative decreases in the glomerular filtration rate of 30%, and 57% or more. Moreover, the rate of change in htTKV was negatively correlated with the slope of the glomerular filtration rate. While ADPKD genotype was also associated with CKD outcomes, it was not an independent prognostic factor after adjusting for htTKV. Thus, baseline total kidney volume and the rate of kidney growth are strongly associated with the development of advanced stages of CKD. These findings support the use of total kidney volume as a prognostic and potentially monitoring biomarker in ADPKD.

Image texture features predict renal function decline in patients with autosomal dominant polycystic kidney disease.

Magnetic resonance imaging (MRI) examinations provide high-resolution information about the anatomic structure of the kidneys and are used to measure total kidney volume (TKV) in patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD). Height-adjusted TKV (HtTKV) has become the gold-standard imaging biomarker for ADPKD progression at early stages of the disease when estimated glomerular filtration rate (eGFR) is still normal. However, HtTKV does not take advantage of the wealth of information provided by MRI. Here we tested whether image texture features provide additional insights into the ADPKD kidney that may be used as complementary information to existing biomarkers. A retrospective cohort of 122 patients from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) study was identified who had T2-weighted MRIs and eGFR values over 70 mL/min/1.73m2 at the time of their baseline scan. We computed nine distinct image texture features for each patient. The ability of each feature to predict subsequent progression to CKD stage 3A, 3B, and 30% reduction in eGFR at eight-year follow-up was assessed. A multiple linear regression model was developed incorporating age, baseline eGFR, HtTKV, and three image texture features identified by stability feature selection (Entropy, Correlation, and Energy). Including texture in a multiple linear regression model (predicting percent change in eGFR) improved Pearson correlation coefficient from -0.51 (using age, eGFR, and HtTKV) to -0.70 (adding texture). Thus, texture analysis offers an approach to refine ADPKD prognosis and should be further explored for its utility in individualized clinical decision making and outcome prediction.

Automated segmentation of liver and liver cysts from bounded abdominal MR images in patients with autosomal dominant polycystic kidney disease.

Liver and liver cyst volume measurements are important quantitative imaging biomarkers for assessment of disease progression in autosomal dominant polycystic kidney disease (ADPKD) and polycystic liver disease (PLD). To date, no study has presented automated segmentation and volumetric computation of liver and liver cysts in these populations. In this paper, we proposed an automated segmentation framework for liver and liver cysts from bounded abdominal MR images in patients with ADPKD. To model the shape and variations in ADPKD livers, the spatial prior probability map (SPPM) of liver location and the tissue prior probability maps (TPPMs) of liver parenchymal tissue intensity and cyst morphology were generated. Formulated within a three-dimensional level set framework, the TPPMs successfully captured liver parenchymal tissues and cysts, while the SPPM globally constrained the initial surfaces of the liver into the desired boundary. Liver cysts were extracted by combined operations of the TPPMs, thresholding, and false positive reduction based on spatial prior knowledge of kidney cysts and distance map. With cross-validation for the liver segmentation, the agreement between the radiology expert and the proposed method was 84% for shape congruence and 91% for volume measurement assessed by the intra-class correlation coefficient (ICC). For the liver cyst segmentation, the agreement between the reference method and the proposed method was ICC = 0.91 for cyst volumes and ICC = 0.94 for % cyst-to-liver volume.

Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND AND OBJECTIVES: Our study developed a fully automated method for segmentation and volumetric measurements of kidneys from magnetic resonance images in patients with autosomal dominant polycystic kidney disease and assessed the performance of the automated method with the reference manual segmentation method. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Study patients were selected from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease. At the enrollment of the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease Study in 2000, patients with autosomal dominant polycystic kidney disease were between 15 and 46 years of age with relatively preserved GFRs. Our fully automated segmentation method was on the basis of a spatial prior probability map of the location of kidneys in abdominal magnetic resonance images and regional mapping with total variation regularization and propagated shape constraints that were formulated into a level set framework. T2-weighted magnetic resonance image sets of 120 kidneys were selected from 60 patients with autosomal dominant polycystic kidney disease and divided into the training and test datasets. The performance of the automated method in reference to the manual method was assessed by means of two metrics: Dice similarity coefficient and intraclass correlation coefficient of segmented kidney volume. The training and test sets were swapped for crossvalidation and reanalyzed. RESULTS: Successful segmentation of kidneys was performed with the automated method in all test patients. The segmented kidney volumes ranged from 177.2 to 2634 ml (mean, 885.4±569.7 ml). The mean Dice similarity coefficient ±SD between the automated and manual methods was 0.88±0.08. The mean correlation coefficient between the two segmentation methods for the segmented volume measurements was 0.97 (P<0.001 for each crossvalidation set). The results from the crossvalidation sets were highly comparable. CONCLUSIONS: We have developed a fully automated method for segmentation of kidneys from abdominal magnetic resonance images in patients with autosomal dominant polycystic kidney disease with varying kidney volumes. The performance of the automated method was in good agreement with that of manual method.

Predicted Mutation Strength of Nontruncating PKD1 Mutations Aids Genotype-Phenotype Correlations in Autosomal Dominant Polycystic Kidney Disease.

Autosomal dominant polycystic kidney disease (ADPKD) often results in ESRD but with a highly variable course. Mutations to PKD1 or PKD2 cause ADPKD; both loci have high levels of allelic heterogeneity. We evaluated genotype-phenotype correlations in 1119 patients (945 families) from the HALT Progression of PKD Study and the Consortium of Radiologic Imaging Study of PKD Study. The population was defined as: 77.7% PKD1, 14.7% PKD2, and 7.6% with no mutation detected (NMD). Phenotypic end points were sex, eGFR, height-adjusted total kidney volume (htTKV), and liver cyst volume. Analysis of the eGFR and htTKV measures showed that the PKD1 group had more severe disease than the PKD2 group, whereas the NMD group had a PKD2-like phenotype. In both the PKD1 and PKD2 populations, men had more severe renal disease, but women had larger liver cyst volumes. Compared with nontruncating PKD1 mutations, truncating PKD1 mutations associated with lower eGFR, but the mutation groups were not differentiated by htTKV. PKD1 nontruncating mutations were evaluated for conservation and chemical change and subdivided into strong (mutation strength group 2 [MSG2]) and weak (MSG3) mutation groups. Analysis of eGFR and htTKV measures showed that patients with MSG3 but not MSG2 mutations had significantly milder disease than patients with truncating cases (MSG1), an association especially evident in extreme decile populations. Overall, we have quantified the contribution of genic and PKD1 allelic effects and sex to the ADPKD phenotype. Intrafamilial correlation analysis showed that other factors shared by families influence htTKV, with these additional genetic/environmental factors significantly affecting the ADPKD phenotype.

Glomerular endothelial vesicles in a renal allograft: an unusual pattern of immunoglobulin deposition in a patient with biclonal gammopathy of unknown significance.

Paraproteins have varied effects on the kidney on the basis of molecular structure, concentration, and renal function. Prototypical patterns include myeloma cast nephropathy, monoclonal immunoglobulin deposition disease, and amyloid, among others. We report a 69-year-old man with end-stage diabetic nephropathy and biclonal gammopathy of unknown significance. Serum monoclonal immunoglobulin G (IgG)-κ and urine monoclonal free λ light chains were identified during workup for nephrotic syndrome. A native renal biopsy demonstrated diabetic nephropathy, without indication of paraprotein-related pathology. After transplantation, a surveillance biopsy showed endothelialitis (type 2 rejection) and abundant eosinophilic droplets, nearly occluding glomerular capillary loops. Electron microscopy localized tightly packed electron-dense vesicles in glomerular endothelial cells. Immunofluorescence studies revealed IgG-κ-dominant endothelial staining, along with λ monotypic protein resorption droplets in tubules. Two additional biopsies within the following year showed this same paraprotein distribution, with some increase in mesangial sclerosis. Two years after transplant the patient remains asymptomatic with normal creatinine levels. Literature review yields rare cases of immunoglobulin crystalline deposits in multiple glomerular cell types, rarely including endothelial cells; however, this appears to be the first report of monoclonal immunoglobulin vesicles localized solely to endothelial cells. As these vesicles were not seen in the native kidney biopsy, we hypothesize an interaction of alloimmune-mediated endothelial injury and the physiochemical properties of the IgG-κ paraprotein. In addition, this case illustrates simultaneous different patterns of accumulation of monoclonal immunoglobulin and light chain components in this unique patient with biclonal gammopathy of unknown significance.

Novel methodology to evaluate renal cysts in polycystic kidney disease.

AIM: To develop and assess a semiautomated method for segmenting and counting individual renal cysts from mid-slice MR images in patients with autosomal dominant polycystic kidney disease (ADPKD). METHODS: A semiautomated method was developed to segment and count individual renal cysts from mid-slice MR images in 241 subjects with ADPKD from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease. For each subject, a mid-slice MR image was selected from each set of coronal T2-weighted MR images covering the entire kidney. The selected mid-slice image was processed with the semiautomated method to segment and count individual renal cysts. The number of cysts from the mid-slice image of each kidney was also measured by manual counting. The level of agreement between the semiautomated and manual cyst counts was compared using intraclass correlation (ICC) and a Bland-Altman plot. RESULTS: Individual renal cysts were successfully segmented using the semiautomated method in all 241 cases. The number of cysts in each kidney measured with the semiautomated and manual counting methods correlated well (ICC = 0.96 for the right or left kidney), with a small average difference (-0.52, with higher semiautomated counts, for the right kidney, and 0.13, with higher manual counts, for the left kidney) in the semiautomated method. However, there was substantial variation in a small number of subjects; 6 of 241 participants (2.5%) had a difference in the total cyst count of more than 15. CONCLUSION: We have developed a semiautomated method to segment individual renal cysts from mid-slice MR images in ADPKD kidneys as a quantitative indicator of characterization and disease progression of ADPKD.

Novel approach to estimate kidney and cyst volumes using mid-slice magnetic resonance images in polycystic kidney disease.

OBJECTIVE: To evaluate whether kidney and cyst volumes can be accurately estimated based on limited area measurements from magnetic resonance (MR) images of patients with autosomal dominant polycystic kidney disease (ADPKD). MATERIALS AND METHODS: MR coronal images of 178 ADPKD participants from the Consortium for Radiologic Imaging Studies of ADPKD (CRISP) were analyzed. For each MR image slice, we measured kidney and renal cyst areas using stereology and region-based thresholding methods, respectively. The kidney and cyst 'observed' volumes were calculated by summing up the area measurements of all the slices covering the kidney. To estimate the volume, we selected a coronal mid-slice in each kidney and multiplied its area by the total number of slices ('PANK2' for kidney and 'PANC2' for cyst). We then compared the kidney and cyst volumes predicted from PANK2 and PANC2, respectively, to the corresponding observed volumes, using a linear regression analysis. RESULTS: The kidney volume predicted from PANK2 correlated extremely well with the observed kidney volume (R(2) = 0.994 for the right kidney and 0.991 for the left kidney). The linear regression coefficient multiplier to PANK2 that best fit the kidney volume was 0.637 (95% CI: 0.629-0.644) for the right kidney and 0.624 (95% CI: 0.616-0.633) for the left kidney. The correlation between the cyst volume predicted from PANC2 and the observed cyst volume was also very high (R(2) = 0.984 for the right kidney and 0.967 for the left kidney). The least squares linear regression coefficient for PANC2 was 0.637 (95% CI: 0.624-0.649) for the right kidney and 0.608 (95% CI: 0.591-0.625) for the left kidney. CONCLUSION: Kidney and cyst volumes can be closely approximated by multiplying the product of the mid-slice area measurement and the total number of slices in the coronal MR images of ADPKD kidneys by 0.61-0.64. This information will help save processing time needed to estimate total kidney and cyst volumes of ADPKD kidneys.

Drug dosing in elderly patients with chronic kidney disease.

As the elderly population in the United States increases, health care professionals need to be aware of potential age-related changes that affect medication prescribing. Increased emphasis on careful patient assessment and safety can reduce the incidence of adverse events related to medications.