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Background and Purpose: Patients with autosomal dominant polycystic kidney disease (ADPKD) develop cysts in the kidneys, liver, spleen, pancreas, prostate, and arachnoid spaces. In addition, spinal meningeal diverticula have been reported. To determine whether spinal meningeal diverticula are associated with ADPKD, we compared their prevalence in subjects with ADPKD with a control cohort without ADPKD., Materials and Methods: Subjects with ADPKD and age- and sex-matched controls without ADPKD undergoing abdominal MRI from the midthorax to the pelvis from 2003 to 2023 were retrospectively evaluated for spinal meningeal diverticula by 4 blinded observers. The prevalence of spinal meningeal diverticula in ADPKD was compared with that in control subjects, using t tests and correlated with clinical and laboratory data and MR imaging features, including cyst volumes and cyst counts., Results: Identification of spinal meningeal diverticula in ADPKD ( n  = 285, median age, 47; interquartile range [IQR], 37-56 years; 54% female) and control ( n  = 285, median age, 47; IQR, 37-57 years; 54% female) subjects had high interobserver agreement (pairwise Cohen κ = 0.74). Spinal meningeal diverticula were observed in 145 of 285 (51%) subjects with ADPKD compared with 66 of 285 (23%) control subjects without ADPKD ( P < .001). Spinal meningeal diverticula in ADPKD were more prevalent in women (98 of 153 [64%]) than men (47 of 132 [36%], P < .001). The mean number of spinal meningeal diverticula per affected subject with ADPKD was 3.6 ± 2.9 compared with 2.4 ± 1.9 in controls with cysts ( P < .001). The median volume (IQR, 25%-75%) of spinal meningeal diverticula was 400 (IQR, 210-740) mm 3 in those with ADPKD compared with 250 (IQR, 180-440) mm 3 in controls ( P < .001). The mean spinal meningeal diverticulum diameter was greater in the sacrum (7.3 [SD, 4.1] mm) compared with thoracic (5.4 [SD, 1.8] mm) and lumbar spine (5.8 [SD, 2.0] mm), ( P < .001), suggesting that hydrostatic pressure contributed to enlargement., Conclusions: ADPKD has a high prevalence of spinal meningeal diverticula, particularly in women., (© 2025 by American Journal of Neuroradiology.)

Background: Pancreatic cysts in autosomal dominant polycystic kidney disease (ADPKD) correlate with PKD2 mutations, which have a different phenotype than PKD1 mutations. However, pancreatic cysts are commonly overlooked by radiologists. Here, we automate the detection of pancreatic cysts on abdominal MRI in ADPKD., Methods: Eight nnU-Net-based segmentation models with 2D or 3D configuration and various loss functions were trained on positive-only or positive-and-negative datasets, comprising axial and coronal T2-weighted MR images from 254 scans on 146 ADPKD patients with pancreatic cysts labeled independently by two radiologists. Model performance was evaluated on test subjects unseen in training, comprising 40 internal, 40 external, and 23 test-retest reproducibility ADPKD patients., Results: Two radiologists agreed on 52% of cysts labeled on training data, and 33%/25% on internal/external test datasets. The 2D model with a loss of combined dice similarity coefficient and cross-entropy trained with the dataset with both positive and negative cases produced an optimal dice score of 0.7 ± 0.5/0.8 ± 0.4 at the voxel level on internal/external validation and was thus used as the best-performing model. In the test-retest, the optimal model showed superior reproducibility (83% agreement between scan A and B) in segmenting pancreatic cysts compared to six expert observers (77% agreement). In the internal/external validation, the optimal model showed high specificity of 94%/100% but limited sensitivity of 20%/24%., Conclusions: Labeling pancreatic cysts on T2 images of the abdomen in patients with ADPKD is challenging, deep learning can help the automated detection of pancreatic cysts, and further image quality improvement is warranted.

Background and Purpose: The objective is to demonstrate feasibility of quantitative susceptibility mapping (QSM) in autosomal dominant polycystic kidney disease (ADPKD) patients and to compare imaging findings with traditional T1/T2w magnetic resonance imaging (MRI)., Methods: Thirty-three consecutive patients (11 male, 22 female) diagnosed with ADPKD were initially selected. QSM images were reconstructed from the multiecho gradient echo data and compared to co-registered T2w, T1w, and CT images. Complex cysts were identified and classified into distinct subclasses based on their imaging features. Prevalence of each subclass was estimated., Results: QSM visualized two renal calcifications measuring 9 and 10 mm and three pelvic phleboliths measuring 2 mm but missed 24 calcifications measuring 1 mm or less and 1 larger calcification at the edge of the field of view. A total of 121 complex T1 hyperintense/T2 hypointense renal cysts were detected. 52 (43%) Cysts appeared hyperintense on QSM consistent with hemorrhage; 60 (49%) cysts were isointense with respect to simple cysts and normal kidney parenchyma, while the remaining 9 (7%) were hypointense. The presentation of the latter two complex cyst subtypes is likely indicative of proteinaceous composition without hemorrhage., Conclusion: Our results indicate that QSM of ADPKD kidneys is possible and uniquely suited to detect large renal calculi without ionizing radiation and able to identify properties of complex cysts unattainable with traditional approaches., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Mayo Imaging Classification (MIC) for predicting future kidney growth in autosomal dominant polycystic kidney disease (ADPKD) patients is calculated from a single MRI/CT scan assuming exponential kidney volume growth and height-adjusted total kidney volume at birth to be 150 mL/m. However, when multiple scans are available, how this information should be combined to improve prediction accuracy is unclear. Herein, we studied ADPKD subjects ( n = 36 ) with 8+ years imaging follow-up (mean = 11 years) to establish ground truth kidney growth trajectory. MIC annual kidney growth rate predictions were compared to ground truth as well as 1- and 2-parameter least squares fitting. The annualized mean absolute error in MIC for predicting total kidney volume growth rate was 2.1 % ± 2 % compared to 1.1 % ± 1 % ( p = 0.002 ) for a 2-parameter fit to the same exponential growth curve used for MIC when 4 measurements were available or 1.4 % ± 1 % ( p = 0.01 ) with 3 measurements averaging together with MIC. On univariate analysis, male sex ( p = 0.05 ) and PKD2 mutation ( p = 0.04 ) were associated with poorer MIC performance. In ADPKD patients with 3 or more CT/MRI scans, 2-parameter least squares fitting predicted kidney volume growth rate better than MIC, especially in males and with PKD2 mutations where MIC was less accurate., (© 2024. The Author(s).)

Abdominal imaging of autosomal dominant polycystic kidney disease (ADPKD) has historically focused on detecting complications such as cyst rupture, cyst infection, obstructing renal calculi, and pyelonephritis; discriminating complex cysts from renal cell carcinoma; and identifying sources of abdominal pain. Many imaging features of ADPKD are incompletely evaluated or not deemed to be clinically significant, and because of this, treatment options are limited. However, total kidney volume (TKV) measurement has become important for assessing the risk of disease progression (i.e., Mayo Imaging Classification) and predicting tolvaptan treatment's efficacy. Deep learning for segmenting the kidneys has improved these measurements' speed, accuracy, and reproducibility. Deep learning models can also segment other organs and tissues, extracting additional biomarkers to characterize the extent to which extrarenal manifestations complicate ADPKD. In this concept paper, we demonstrate how deep learning may be applied to measure the TKV and how it can be extended to measure additional features of this disease.

Rationale and Objectives: Following autosomal dominant polycystic kidney disease (ADPKD) progression by measuring organ volumes requires low measurement variability. The objective of this study is to reduce organ volume measurement variability on MRI of ADPKD patients by utilizing all pulse sequences to obtain multiple measurements which allows outlier analysis to find errors and averaging to reduce variability., Materials and Methods: In order to make measurements on multiple pulse sequences practical, a 3D multi-modality multi-class segmentation model based on nnU-net was trained/validated using T1, T2, SSFP, DWI and CT from 413 subjects. Reproducibility was assessed with test-re-test methodology on ADPKD subjects (n = 19) scanned twice within a 3-week interval correcting outliers and averaging the measurements across all sequences. Absolute percent differences in organ volumes were compared to paired students t-test., Results: Dice similarlity coefficient > 97%, Jaccard Index > 0.94, mean surface distance < 1 mm and mean Hausdorff Distance < 2 cm for all three organs and all five sequences were found on internal (n = 25), external (n = 37) and test-re-test reproducibility assessment (38 scans in 19 subjects). When averaging volumes measured from five MRI sequences, the model automatically segmented kidneys with test-re-test reproducibility (percent absolute difference between exam 1 and exam 2) of 1.3% which was better than all five expert observers. It reliably stratified ADPKD into Mayo Imaging Classification (area under the curve=100%) compared to radiologist., Conclusion: 3D deep learning measures organ volumes on five MRI sequences leveraging the power of outlier analysis and averaging to achieve 1.3% total kidney test-re-test reproducibility., Competing Interests: Declaration of Competing Interest Study “Polycystic Kidney Disease Data Repository” is registered on ClinicalTrials.gov (NCT00792155). George Shih discloses co-chairman of the Society of Abdominal radiology Artificial Intelligence committee and the Society of Imaging Informatics machine learning committee. Daniil Shimonov discloses consulting for Accordant/CVS on chronic kidney disease education. None of the other authors have anything to disclose., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Background: Total kidney volume (TKV) is an important biomarker for assessing kidney function, especially for autosomal dominant polycystic kidney disease (ADPKD). However, TKV measurements from a single MRI pulse sequence have limited reproducibility, ± ~5%, similar to ADPKD annual kidney growth rates., Purpose: To improve TKV measurement reproducibility on MRI by extending artificial intelligence algorithms to automatically segment kidneys on T1-weighted, T2-weighted, and steady state free precession (SSFP) sequences in axial and coronal planes and averaging measurements., Study Type: Retrospective training, prospective testing., Subjects: Three hundred ninety-seven patients (356 with ADPKD, 41 without), 75% for training and 25% for validation, 40 ADPKD patients for testing and 17 ADPKD patients for assessing reproducibility., Field Strength/sequence: T2-weighted single-shot fast spin echo (T2), SSFP, and T1-weighted 3D spoiled gradient echo (T1) at 1.5 and 3T., Assessment: 2D U-net segmentation algorithm was trained on images from all sequences. Five observers independently measured each kidney volume manually on axial T2 and using model-assisted segmentations on all sequences and image plane orientations for two MRI exams in two sessions separated by 1-3 weeks to assess reproducibility. Manual and model-assisted segmentation times were recorded., Statistical Tests: Bland-Altman, Schapiro-Wilk (normality assessment), Pearson's chi-squared (categorical variables); Dice similarity coefficient, interclass correlation coefficient, and concordance correlation coefficient for analyzing TKV reproducibility. P-value < 0.05 was considered statistically significant., Results: In 17 ADPKD subjects, model-assisted segmentations of axial T2 images were significantly faster than manual segmentations (2:49 minute vs. 11:34 minute), with no significant absolute percent difference in TKV (5.9% vs. 5.3%, P = 0.88) between scans 1 and 2. Absolute percent differences between the two scans for model-assisted segmentations on other sequences were 5.5% (axial T1), 4.5% (axial SSFP), 4.1% (coronal SSFP), and 3.2% (coronal T2). Averaging measurements from all five model-assisted segmentations significantly reduced absolute percent difference to 2.5%, further improving to 2.1% after excluding an outlier., Data Conclusion: Measuring TKV on multiple MRI pulse sequences in coronal and axial planes is practical with deep learning model-assisted segmentations and can improve TKV measurement reproducibility more than 2-fold in ADPKD., Evidence Level: 2 TECHNICAL EFFICACY: Stage 1., (© 2023 International Society for Magnetic Resonance in Medicine.)

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.

Autosomal dominant polycystic kidney disease (ADPKD) has cystic fluid accumulations in the kidneys, liver, pancreas, arachnoid spaces as well as non-cystic fluid accumulations including pericardial effusions, dural ectasia and free fluid in the male pelvis. Here, we investigate the possible association of ADPKD with pleural effusion. ADPKD subjects (n = 268) and age-gender matched controls without ADPKD (n = 268) undergoing body magnetic resonance imaging from mid-thorax down into the pelvis were independently evaluated for pleural effusion by 3 blinded expert observers. Subjects with conditions associated with pleural effusion were excluded from both populations. Clinical and laboratory data as well as kidney, liver and spleen volume, pleural fluid volume, free pelvic fluid and polycystic kidney disease genotype were evaluated. Pleural effusions were observed in 56 of 268 (21%) ADPKD subjects compared with 21 of 268 (8%) in controls (p < 0.0001). In a subpopulation controlling for renal function by matching estimated glomerular filtration rate (eGFR), 28 of 110 (25%) ADPKD subjects had pleural effusions compared to 5 of 110 (5%) controls (p < 0.001). Pleural effusions in ADPKD subjects were more prevalent in females (37/141; 26%) than males (19/127,15%; p = 0.02) and in males were weakly correlated with the presence of free pelvic fluid (r = 0.24, p = 0.02). ADPKD subjects with pleural effusions were younger (48 ± 14 years old vs. 43 ± 14 years old) and weighed less (77 vs. 70 kg; p ≤ 0.02) than those without pleural effusions. For ADPKD subjects with pleural effusions, the mean volume of fluid layering dependently in the posterior−inferior thorax was 19 mL and was not considered to be clinically significant. Pleural effusion is associated with ADPKD, but its role in the pathogenesis of ADPKD requires further evaluation.

Organ volume measurements are a key metric for managing ADPKD (the most common inherited renal disease). However, measuring organ volumes is tedious and involves manually contouring organ outlines on multiple cross-sectional MRI or CT images. The automation of kidney contouring using deep learning has been proposed, as it has small errors compared to manual contouring. Here, a deployed open-source deep learning ADPKD kidney segmentation pipeline is extended to also measure liver and spleen volumes, which are also important. This 2D U-net deep learning approach was developed with radiologist labeled T2-weighted images from 215 ADPKD subjects (70% training = 151, 30% validation = 64). Additional ADPKD subjects were utilized for prospective (n = 30) and external (n = 30) validations for a total of 275 subjects. Image cropping previously optimized for kidneys was included in training but removed for the validation and inference to accommodate the liver which is closer to the image border. An effective algorithm was developed to adjudicate overlap voxels that are labeled as more than one organ. Left kidney, right kidney, liver and spleen labels had average errors of 3%, 7%, 3%, and 1%, respectively, on external validation and 5%, 6%, 5%, and 1% on prospective validation. Dice scores also showed that the deep learning model was close to the radiologist contouring, measuring 0.98, 0.96, 0.97 and 0.96 on external validation and 0.96, 0.96, 0.96 and 0.95 on prospective validation for left kidney, right kidney, liver and spleen, respectively. The time required for manual correction of deep learning segmentation errors was only 19:17 min compared to 33:04 min for manual segmentations, a 42% time saving ( p = 0.004). Standard deviation of model assisted segmentations was reduced to 7, 5, 11, 5 mL for right kidney, left kidney, liver and spleen respectively from 14, 10, 55 and 14 mL for manual segmentations. Thus, deep learning reduces the radiologist time required to perform multiorgan segmentations in ADPKD and reduces measurement variability.

This study develops, validates, and deploys deep learning for automated total kidney volume (TKV) measurement (a marker of disease severity) on T2-weighted MRI studies of autosomal dominant polycystic kidney disease (ADPKD). The model was based on the U-Net architecture with an EfficientNet encoder, developed using 213 abdominal MRI studies in 129 patients with ADPKD. Patients were randomly divided into 70% training, 15% validation, and 15% test sets for model development. Model performance was assessed using Dice similarity coefficient (DSC) and Bland-Altman analysis. External validation in 20 patients from outside institutions demonstrated a DSC of 0.98 (IQR, 0.97-0.99) and a Bland-Altman difference of 2.6% (95% CI: 1.0%, 4.1%). Prospective validation in 53 patients demonstrated a DSC of 0.97 (IQR, 0.94-0.98) and a Bland-Altman difference of 3.6% (95% CI: 2.0%, 5.2%). Last, the efficiency of model-assisted annotation was evaluated on the first 50% of prospective cases ( n = 28), with a 51% mean reduction in contouring time ( P < .001), from 1724 seconds (95% CI: 1373, 2075) to 723 seconds (95% CI: 555, 892). In conclusion, our deployed artificial intelligence pipeline accurately performs automated segmentation for TKV estimation of polycystic kidneys and reduces expert contouring time. Keywords: Convolutional Neural Network (CNN), Segmentation, Kidney ClinicalTrials.gov identification no.: NCT00792155 Supplemental material is available for this article. © RSNA, 2022., Competing Interests: Disclosures of Conflicts of Interest: A.G. No relevant relationships. G.S. Leadership roles as co-chair of Society for Imaging Informatics in Medicine machine learning committee, co-chair for Society of Abdominal Radiology AI committee, co-director of Radiological Society of North America AI certificate course; assistant editor of Radiology: Artificial Intelligence. S.R. No relevant relationships. S.J. No relevant relationships. H.D. No relevant relationships. R.H. No relevant relationships. D.R. No relevant relationships. K.T. No relevant relationships. J.D.B. Grants or contracts from Vertex Pharmaceuticals; secretary of American Journal of Hypertension. I.B. No relevant relationships. I.C. No relevant relationships. H.R. No relevant relationships. M.R.P. No relevant relationships., (2022 by the Radiological Society of North America, Inc.)

Background: Screening for rapidly progressing autosomal dominant polycystic kidney disease (ADPKD) is necessary for assigning and monitoring therapies. Height-adjusted total kidney volume (ht-TKV) is an accepted biomarker for clinical prognostication, but represents only a small fraction of information on abdominal MRI., Purpose: To investigate the utility of other MR features of ADPKD to predict progression., Study Type: Single-center retrospective., Population: Longitudinal data from 186 ADPKD subjects with baseline serum creatinine, PKD gene testing, abdominal MRI measurements, and ≥2 follow-up serum creatinine were reviewed., Field Strength/sequence: 1.5T, T 2 -weighted single-shot fast spin echo, T 1 -weighted 3D spoiled gradient echo (liver accelerated volume acquisition) and 2D cine velocity encoded gradient echo (phase contrast MRA)., Assessment: Ht-TKV, renal blood flow (RBF), number and fraction of renal and hepatic cysts, bright T 1 hemorrhagic renal cysts, and liver and spleen volumes were independently assessed by three observers blinded to estimated glomerular filtration rate (eGFR) data., Statistical Tests: Linear mixed-effect models were applied to predict eGFR over time using MRI features at baseline adjusted for confounders. Validation was performed in 158 patients who had follow-up MRI using receiver operator characteristic, sensitivity, and specificity., Results: Hemorrhagic cysts, fraction of renal and hepatic cysts, height-adjusted liver and spleen volumes were significant independent predictors of future eGFR (final prediction model R 2 = 0.88 P < 0.05). The number of hemorrhagic cysts significantly improved the prediction compared to ht-TKV in predicting future eGFR (area under the curve [AUC] = 0.94, 95% confidence interval [CI]: 0.9-0.94 vs. R 2 = 0.9, 95% CI: 0.85-0.9, P = 0.045). For baseline eGFR ≥60 ml/min/1.73m 2 , sensitivity for predicting eGFR<45 ml/min/1.73m 2 by ht-TKV alone was 29%. Sensitivity increased to 72% with all MRI variables in the model (P < 0.05 = 0.019), whereas specificity was unchanged, 100% vs. 99%., Data Conclusion: Combining multiple MR features including hemorrhagic renal cysts, renal cyst fraction, liver and spleen volume, hepatic cyst fraction, and renal blood flow enhanced sensitivity for predicting eGFR decline in ADPKD compared to the standard model including only ht-TKV. Level of Evidence 2 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2021;53:564-576., (© 2020 International Society for Magnetic Resonance in Medicine.)

Introduction: Kidney and liver cysts in autosomal dominant polycystic kidney disease (ADPKD) can compress the inferior vena cava (IVC), but IVC compression prevalence and its risk factors are unknown., Methods: Patients who have ADPKD (n = 216) with abdominal magnetic resonance imaging (MRI) studies and age-/sex-matched controls (n = 216) were evaluated for IVC compression as well as azygous vein diameter (a marker of collateral blood flow) and IVC aspect ratio (left-to-right dimension divided by anterior-to-posterior dimension with a value of 1 corresponding to a circular (high pressure) IVC caudal to compression., Results: Severe IVC compression (≥70%) was observed in 33 (15%) ADPKD subjects and mild compression (≥50% to <70%) was observed in 33 (15%) subjects; whereas controls had no IVC compression ( P  < 0.001). Severe IVC compression was associated with larger azygous vein (4.0 ± 1.3 mm versus 2.3 ± 0.8 mm without IVC compression; P  < 0.001) and a more circular IVC cross-section upstream (mean IVC aspect ratio: 1.16 ± 0.27 vs. 1.69 ± 0.67, P  < 0.001), suggesting higher pressure upstream from the compression. IVC compression was associated with older age, lower estimated glomerular filtration rate (eGFR), greater height-adjusted total kidney volumes, greater height-adjusted liver volume (ht-LV), and greater liver and renal cyst fractions ( P  < 0.001). No subject younger than 30 years had IVC compression, but ADPKD subjects ≥40 years old had 12-fold higher risk of IVC compression (95% confidence interval [CI]: 4.2-42.4), with highest predicted probability for Mayo Clinic classes 1D (59%; 95% CI: 39%-76%) and 1E (74%; 95% CI: 49%-90%) after adjustment ( P  < 0.001). Women with ht-LV ≥ 2000 ml/m had 83% (95% CI: 59%-95%) prevalence of IVC compression. Complications of IVC compression included deep vein thrombosis (DVT) and symptomatic hypotension., Conclusions: IVC compression is common in ADPKD patients >40 years old, with Mayo Clinic class 1D/E, and in females with ht-LV > 2000 ml/m., (© 2020 International Society of Nephrology. Published by Elsevier Inc.)

: The hypertension paradigm has contributed to a dramatic reduction in CVD mortality. This has been achieved by applying average results of population studies to identify a target population and design a common intervention to achieve a BP goal. Progressive lowering of the BP threshold has expanded the fraction of persons at risk who have access to treatment. Meanwhile, falling risk reduces potential benefit, while treatment-induced adverse events increase - making further expansion of the treatment pool no longer tenable. Still, CVD remains the leading cause of death. Fortunately, new science reveals opportunities to enhance CVD prevention when BP management is based upon individual characteristics. Treatment can be directed at those most likely to benefit, while sparing others the hazards of unnecessary therapy. Treatment can be designed to achieve a variety of physiological objectives that influence cardiovascular outcomes. This new strategy should improve both the efficacy and efficiency of BP-related CVD prevention.

Magnetic resonance imaging (MRI) is increasingly used in autosomal dominant polycystic kidney disease (ADPKD) for diagnosis, classification, assessment of disease progression and treatment response, and for identifying complications. Herein we review the role of MRI in the management of patients with ADPKD. We show how MRI-derived total kidney volume is a biomarker for assessing ADPKD severity and predicting decline in renal function. We also demonstrate the MR appearances of common complications. Level of Evidence: 3 Technical Efficacy Stage: 5 J. Magn. Reson. Imaging 2019;50:41-51., (© 2019 International Society for Magnetic Resonance in Medicine.)

Background: Autosomal dominant polycystic kidney disease (ADPKD) can involve prostate and seminal vesicles but the potential interrelationship of these findings and associations with PKD gene mutation locus and type is unknown., Purpose: To determine the interrelationship of seminal megavesicles (seminal vesicles with lumen diameter > 10mm) and prostatic cysts in ADPKD and to determine whether there are associations with PKD gene mutations., Study Type: Retrospective, case control., Population: Male ADPKD subjects (n = 92) with mutations in PKD1 (n = 71; 77%) or PKD2 (n = 21; 23%), and age/gender-matched controls without ADPKD (n = 92)., Field Strength/sequence: 1.5T, axial/coronal T 2 -weighted MR images., Assessment: Reviewers blinded to genotype independently measured seminal vesicle lumen diameter and prevalence of cysts in prostate, kidney, and liver., Statistical Tests: Nonparametric tests for group comparisons and univariate and multivariable logistic regression analyses to identify associations of megavesicles and prostate median cysts with mutations and renal/hepatic cyst burden., Results: Seminal megavesicles were found in 23 of 92 ADPKD (25%) subjects with PKD1 (22/71, 31%) or PKD2 (n = 1/21, 5%) mutations, but in only two control subjects (P < 0.0001). Prostate median cysts were found in 17/92 (18%) ADPKD subjects, compared with only 6/92 (7%) controls (P = 0.01), and were correlated with seminal vesicle diameters (ρ = 0.24, P = 0.02). Nonmedian prostate cyst prevalence was identical between ADPKD and controls (7/92, 8%). After adjusting for age, estimated glomerular filtration rate, and height-adjusted total kidney volume, ADPKD subjects with megavesicles were 10 times more likely to have a PKD1 than a PKD2 mutation. Among PKD1 subjects, seminal megavesicles occurred more frequently with nontruncating mutations with less severe kidney involvement., Data Conclusion: ADPKD is associated with prostate median cysts near ejaculatory ducts. These cysts correlate with seminal megavesicles (dilated to >10 mm) which predict a 10-fold greater likelihood of PKD1 vs. PKD2 mutation. Cysts elsewhere in the prostate are not related to ADPKD., Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:894-903., (© 2018 International Society for Magnetic Resonance in Medicine.)

Purpose: To compare MRI segmentation methods for measuring liver cyst volumes in autosomal dominant polycystic kidney disease (ADPKD)., Methods: Liver cyst volumes in 42 ADPKD patients were measured using region growing, thresholding and cyst diameter techniques. Manual segmentation was the reference standard., Results: Root mean square deviation was 113, 155, and 500 for cyst diameter, thresholding and region growing respectively. Thresholding error for cyst volumes below 500ml was 550% vs 17% for cyst volumes above 500ml (p<0.001)., Conclusion: For measuring volume of a small number of cysts, cyst diameter and manual segmentation methods are recommended. For severe disease with numerous, large hepatic cysts, thresholding is an acceptable alternative., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Purpose: To determine prevalence of complex liver cysts in Autosomal Dominant Polycystic Kidney Disease (ADPKD)., Methods: Abdominal MRI in 186 ADPKD subjects were evaluated by two independent observers to determine prevalence of complex liver cysts., Results: 23 (12%) of subjects, had at least 1 complex cyst. Only 8 (4%) were reported to have a complex cyst prospectively, representing an under-reporting rate of 65%. Median total cyst volume was 66-times greater for subjects with complex cysts compared to subjects without (p<0.0001)., Conclusion: Complex hepatic cysts were observed in 12% of ADPKD cases, occurring more frequently in livers with extensive cystic involvement., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background: About one-half of all hypertensive adults do not have their blood pressure controlled. They are often prescribed medications that conform to national guidelines but they continue to have elevated blood pressure. This public health problem might be improved by applying plasma renin guided therapy., Results: A contributor to the public health problem of unsuccessfully treated hypertension is that the circulating renin-angiotensin system (RAS) is not recognized in treatment guidelines as clinically relevant for the treatment of hypertension or as important as the body salt status for determining blood pressure levels. Another contributor to the problem is the lack of specificity in the package inserts for antihypertensive drugs. They do not specifically state under the heading "Indications" that RAS blockers are primarily most effective in hypertensive subjects with medium and high plasma renin levels; by contrast, natriuretic drugs are most effective in those with low plasma renin levels., Methods: Literature review., Conclusions: To address the problem of unsuccessfully treated hypertension, we recommend that the "Indications" section of package inserts for antihypertensive drugs be more specific. The primary indication for RAS blockers ought to be hypertension with medium and high plasma renin levels, and natriuretic agents for those with low plasma renin levels. Similar language ought to be added to treatment guidelines. Additionally, 3 other reasons for lack of blood pressure control also need to be addressed-failure to prescribe antihypertensive drugs to hypertensive subjects, failure of patients to fill prescriptions, and low drug adherence., (© American Journal of Hypertension, Ltd 2017. All rights reserved. For Permissions, please email: journals.permissions@oup.com)

Purpose To define the magnetic resonance (MR) imaging prevalence of pancreatic cysts in a cohort of patients with autosomal dominant polycystic kidney disease (ADPKD) compared with a control group without ADPKD that was matched for age, sex, and renal function. Materials and Methods In this HIPAA-compliant, institutional review board-approved study, all patients with ADPKD provided informed consent; for control subjects, informed consent was waived. Patients with ADPKD (n = 110) with mutations identified in PKD1 or PKD2 and control subjects without ADPKD or known pancreatic disease (n = 110) who were matched for age, sex, estimated glomerular filtration rate, and date of MR imaging examination were evaluated for pancreatic cysts by using axial and coronal single-shot fast spin-echo T2-weighted images obtained at 1.5 T. Total kidney volume and liver volume were measured. Univariate and multivariable logistic regression analyses were conducted to evaluate potential associations between collected variables and presence of pancreatic cysts among patients with ADPKD. The number, size, location, and imaging characteristics of the cysts were recorded. Results Patients with ADPKD were significantly more likely than control subjects to have at least one pancreatic cyst (40 of 110 patients [36%] vs 25 of 110 control subjects [23%]; P = .027). In a univariate analysis, pancreatic cysts were more prevalent in patients with ADPKD with mutations in PKD2 than in PKD1 (21 of 34 patients [62%] vs 19 of 76 patients [25%]; P = .0002). In a multivariable logistic regression model, PKD2 mutation locus was significantly associated with the presence of pancreatic cysts (P = .0004) and with liver volume (P = .038). Patients with ADPKD and a pancreatic cyst were 5.9 times more likely to have a PKD2 mutation than a PKD1 mutation after adjusting for age, race, sex, estimated glomerular filtration rate, liver volume, and total kidney volume. Conclusion Pancreatic cysts were more prevalent in patients with ADPKD with PKD2 mutation than in control subjects or patients with PKD1 mutation. (©) RSNA, 2016 Online supplemental material is available for this article.

Purpose: After observing prominent cisterna chyli in several patients with autosomal dominant polycystic kidney disease (ADPKD), we investigated the potential association of cistern chyli enlargement with ADPKD., Materials and Methods: Retrospective, cross-sectional analysis of abdominal and pelvic MRI at 1.5 Tesla (T) in 70 ADPKD patients (male 44.3%, 20-83 years, median = 53 years) were compared with 70 age and gender matched control subjects without ADPKD, cirrhosis, or cholestasis. Cisterna chyli diameter was measured on axial single shot fast spin echo (SSFSE) images at the level of T12-L2 and evaluated by multivariable regression models with covariates including estimated glomerular filtration rate (eGFR), total kidney volume (TKV), renal cyst fraction (cyst volume/kidney volume), and liver volume., Results: Subjects with ADPKD had larger median cisterna chyli diameter compared with those without ADPKD (6.1 mm versus 3.4 mm, P < 0.0001). The prevalence of cisterna chyli enlargement more than the median (3.4 mm), was greater in ADPKD than in controls (99% versus 51%, P < 0.0001). On univariate analysis, cisterna chyli diameter was inversely correlated with eGFR (r = -0.41; P < 0.0001) and directly correlated with TKV (r = 0.57; P < 0.0001), total renal cyst fraction (r = 0.61; P < 0.001), and liver volume (r = 0.17; P = 0.040). Multivariable linear regression modeling found a significant association of cisterna chyli diameter with ADPKD diagnosis (B = 2.14; 95% confidence interval [CI]: 0.05-4.23; P = 0.04). Logistic regression analysis confirmed the association of ADPKD with an enlarged cisterna chyli diameter (odds ratio = 68.4; 95%CI: 8.9-524, P < 0.0001)., Conclusion: Enlarged cisterna chyli is highly prevalent in ADPKD patients but not in age and gender-matched controls., (© 2014 Wiley Periodicals, Inc.)

Background: Autosomal dominant polycystic kidney disease (ADPKD) is clinically heterogenic. Biomarkers are needed to predict prognosis and guide management. We aimed to profile microRNA (miRNA) in ADPKD to gain molecular insight and evaluate biomarker potential., Methods: Small-RNA libraries were generated from urine specimens of ADPKD patients (N = 20) and patients with chronic kidney disease of other etiologies (CKD, N = 20). In this report, we describe the miRNA profiles and baseline characteristics. For reference, we also examined the miRNA transcriptome in primary cultures of ADPKD cyst epithelia (N = 10), normal adult tubule (N = 8) and fetal tubule (N = 7) epithelia., Results: In primary cultures of ADPKD kidney cells, miRNA cistrons mir-143(2) (9.2-fold), let-7i(1) (2.3-fold) and mir-3619(1) (12.1-fold) were significantly elevated compared to normal tubule epithelia, whereas mir-1(4) members (19.7-fold), mir-133b(2) (21.1-fold) and mir-205(1) (3.0-fold) were downregulated (P<0.01). Expression of the dysregulated miRNA in fetal tubule epithelia resembled ADPKD better than normal adult cells, except let-7i, which was lower in fetal cells. In patient biofluid specimens, mir-143(2) members were 2.9-fold higher in urine cells from ADPKD compared to other CKD patients, while expression levels of mir-133b(2) (4.9-fold) and mir-1(4) (4.4-fold) were lower in ADPKD. We also noted increased abundance mir-223(1) (5.6-fold), mir-199a(3) (1.4-fold) and mir-199b(1) (1.8-fold) (P<0.01) in ADPKD urine cells. In ADPKD urine microvesicles, miR-1(2) (7.2-fold) and miR-133a(2) (11.8-fold) were less abundant compared to other CKD patients (P<0.01)., Conclusions: We found that in ADPKD urine specimens, miRNA previously implicated as kidney tumor suppressors (miR-1 and miR-133), as well as miRNA of presumed inflammatory and fibroblast cell origin (miR-223/miR-199), are dysregulated when compared to other CKD patients. Concordant with findings in the primary tubule epithelial cell model, this suggests roles for dysregulated miRNA in ADPKD pathogenesis and potential use as biomarkers. We intend to assess prognostic potential of miRNA in a followup analysis.

Background: The occurrence of unilateral autosomal dominant polycystic kidney disease (ADPKD) with absence of the contralateral kidney has been described only rarely in the literature. Whether unilateral ADPKD is associated with faster disease progression is not known., Study Design: Case series., Setting & Participants: In a prospective cohort of 182 patients with ADPKD, we identified 3 patients with ADPKD and unilateral renal agenesis (2 patients) or severe hypoplasia (1 patient)., Measurements & Outcomes: Genetic analysis of the PKD1 and PKD2 genes was performed for all 3 patients. Serum creatinine levels and kidney volumes based on magnetic resonance imaging were determined twice, with a 6-month interval between measurements. Characteristics of the 3 patients were compared with age- and sex-matched controls from the full cohort., Results: Genotyping of the 3 patients indicated that each had a different [corrected] mutation in the PKD1 gene that is predicted to cause frameshift and/or truncation of the protein product. [corrected] All 3 patients with unilateral ADPKD had renal volumes and progression rates greater than the mean values of their matched control groups. However, their glomerular filtration rates were well preserved, with estimated single-kidney creatinine clearances much greater than their controls., Limitations: The number of cases in this study is small and time of follow-up was limited., Conclusions: Unilateral renal agenesis or hypoplasia in patients with ADPKD might not be as rare as previously thought. Glomerular filtration rate was preserved despite unilateral renal absence, suggesting that renal compensatory mechanisms are well conserved in patients with ADPKD.

Genetic testing of PKD1 and PKD2 is useful for diagnosis and prognosis of autosomal dominant polycystic kidney disease (ADPKD), particularly in asymptomatic individuals or those without a family history. PKD1 testing is complicated by the large transcript size, complexity of the gene region, and the extent of gene variations. A molecular assay was developed using Transgenomic's SURVEYOR Nuclease and WAVE Nucleic Acid High Sensitivity Fragment Analysis System to screen for PKD1 and PKD2 variants, followed by sequencing of variant gene segments, thereby reducing the sequencing reactions by 80%. This method was compared to complete DNA sequencing performed by a reference laboratory for 25 ADPKD patients from 22 families. The pathogenic potential of gene variations of unknown significance was examined by evolutionary comparison, effects of amino acid substitutions on protein structure, and effects of splice-site alterations. A total of 90 variations were identified, including all 82 reported by the reference laboratory (100% sensitivity). A total of 76 variations (84.4%) were in PKD1 and 14 (15.6%) in PKD2. Definite pathogenic mutations (seven nonsense, four truncation, and three splicing defects) were detected in 64% (14/22) of families. The remaining 76 variants included 26 missense, 33 silent, and 17 intronic changes. Two heterozygous nonsense mutations were incorrectly determined by the reference laboratory as homozygous. "Probably pathogenic" mutations were identified in an additional five families (overall detection rate 86%). In conclusion, the SURVEYOR nuclease method was comparable to direct sequencing for detecting ADPKD mutations, achieving high sensitivity with lower cost, providing an important tool for genetic analysis of complex genes., ((c) 2008 Wiley-Liss, Inc.)