Medical School: Yale University School of Medicine
Residency: NewYork-Presbyterian Hospital
Fellowship in Nephrology: Brigham and Women’s Hospital, Harvard Medical School
Locations:
The Rogosin Institute Susan R. Knafel Polycystic Kidney Disease Center
505 East 70th Street
New York, NY 10021 212-746-7647 Get Directions+
Research:
Genetic basis of autosomal dominant polycystic kidney disease (ADPKD)
Pathogenesis of chronic kidney disease in autosomal dominant polycystic kidney disease (ADPKD)
Treatment strategies for autosomal dominant polycystic kidney disease (ADPKD)
Extrarenal manifestation of autosomal dominant polycystic kidney disease (ADPKD)
Publications
Natural history of simple and complex cysts in autosomal dominant polycystic kidney disease on MRI
Zhongxiu Hu, Caden Li, Jon D Blumenfeld, Martin R Prince
Commun Med (Lond). 2026 Jan 14. doi: 10.1038/s43856-025-01318-3. Online ahead of print.
ABSTRACT
BACKGROUND: Kidney volume, reflecting cumulative effects of many cysts, is an important prognostic biomarker for autosomal dominant polycystic kidney disease (ADPKD) but fails in many patients. Tracking individual cysts may more directly assess disease progression.
METHODS: Individual cysts (n = 299) from 37 subjects were evaluated retrospectively over ≥ 8 years by serial MRI (mean follow-up = 11 years). Cysts were labeled on every available MRI scan, totaling 1654 contours (median timepoints per cyst = 5). Effects of cyst location, morphology, and growth pattern on kidney function decline were evaluated by univariate and multivariate analyses.
RESULTS: Simple, T2-bright cysts follow logistic growth (median cyst growth rate = 11%/year). A subset (94/222, 42%) transitions over time to shrinking, to complex solid-fluid/fluid-fluid cysts, then to homogeneously T1-bright cysts and finally disappearing. By contrast, T1-bright complex cysts have no volume change (median cyst growth rate = 0%/year; p < 0.001). On multivariate analysis, faster kidney function decline is associated with simple cyst diameter > 2 cm on index scan (p = 0.007) and simple cyst transitions (p = 0.02). There is a trend towards faster kidney function decline with higher simple cyst growth rate (p = 0.16).
CONCLUSIONS: Profiling individual cysts on serial MRI to identify transitions as well as size and growth rate may improve predictions of ADPKD progression and treatment response.
Automatically Measuring Kidney, Liver, and Cyst Volumes in Autosomal Dominant Polycystic Kidney Disease
Qing Xiong, Xinzi He, Elisa Scalco, Siria Pasini, Chenglin Zhu, Mina C Moghadam, Usama Sattar, Vahid Davoudi, Vahid Bazojoo, Hreedi Dev, Mengjun Shen, Zhongxiu Hu, Sophie Shih, Serena J Prince, Jon D Blumenfeld, Robert J Min, James M Chevalier, Daniil Shimonov, Rebecca J Lepping, Alan S L Yu, Mert R Sabuncu, Anna Caroli, Martin R Prince...
J Am Soc Nephrol. 2025 Nov 4. doi: 10.1681/ASN.0000000904. Online ahead of print.
ABSTRACT
BACKGROUND: Kidney, liver and cyst volumes are important for diagnosis, classification and management of autosomal dominant polycystic kidney disease (ADPKD) but challenging to measure accurately and reproducibly. Here, we develop a web-based deep learning platform to automatically and robustly measure kidneys, liver and cyst volumes in ADPKD.
METHODS: MRI and CT scans from ADPKD patients (n=611) and participants without ADPKD (n=109) were used to train a 3D hybrid model combining U-Net and transformer elements for segmenting kidneys, liver and cysts. The model is implemented as a web-based calculator at www.traceorg.com, providing segmentation labels, volumes and Mayo Clinic Image Classification (MIC). Automatic browser anonymization of DICOM images ensures privacy. Internal validation was conducted on 70 MRIs for kidney and liver segmentations, 46 MRIs for cyst segmentations and performance was compared to 5 open access segmentation models (TotalSegmentator, MR Annotator, Kim, Woznicki and Gregory-Kline). External validation was performed on one single-center dataset (n=58), one multicenter dataset (n=73), CRISP2 (n=30) and PKD-RRC (n=115) MRIs with T2-weighted and T1-weighted images.
RESULTS: After training on 720 participants (mean age=48±15, eGFR=74±32 ml/min/1.73m2 and htTKV=826±772ml/m), TraceOrg internal validation performance achieved high mean Dice scores of 0.97 (kidneys), 0.97 (liver), 0.93 (kidney cysts) and 0.82 (liver cysts) outperforming existing models for ADPKD. External validation showed strong performance with Dice scores of 0.92-0.94 (kidney), 0.87-0.96 (liver), 0.85 (kidney cysts) and 0.76-0.90 (liver cysts) for the single-center and 0.95 (kidney), 0.81 (kidney cysts) for the multicenter dataset. Compared to CRISP volumes measured by stereology, mean absolute percent difference was 5.3% (kidneys, n=30), 11% (kidney cysts, n=30) and 5.5% (liver, n=22). Compared to PKD-RRC (n=115), mean absolute percent difference in TKV was 4.9%.
CONCLUSIONS: TraceOrg is a publicly available web-based tool that automatically measures kidney, liver and cyst volumes from abdominal MRI in ADPKD with high accuracy compared to manual segmentations.
Deep learning-based liver cyst segmentation in MRI for autosomal dominant polycystic kidney disease
Mina Chookhachizadeh Moghadam, Mohit Aspal, Xinzi He, Dominick J Romano, Arman Sharbatdaran, Zhongxiu Hu, Kurt Teichman, Hui Yi Ng He, Usama Sattar, Chenglin Zhu, Hreedi Dev, Daniil Shimonov, James M Chevalier, Akshay Goel, George Shih, Jon D Blumenfeld, Mert R Sabuncu, Martin R Prince...
Radiol Adv. 2024 May 23;1(2):umae014. doi: 10.1093/radadv/umae014. eCollection 2024 Jul.
ABSTRACT
BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) can lead to polycystic liver disease (PLD), characterized by liver cysts. Although majority of the patients are asymptomatic, massively enlarged liver secondary to PLD can cause discomfort, and compression on adjacent structures requiring cyst aspiration/fenestration, partial liver resection, or liver transplantation. Monitoring PLD by measuring liver volume fails to track the early stages when liver cyst volume is too small to affect liver volume.
PURPOSE: To improve PLD assessment in the early stages by automating detection and segmentation of liver cysts using deep learning (DL) models.
MATERIALS AND METHODS: A self-configured UNet-based platform (nnU-Net) was trained with 40 ADPKD subjects with liver cysts annotated by a radiologist. Internal (n = 7), External (n = 10), and test-retest reproducibility (n = 17) validations included macro- and micro-level performance metrics: patient-level Dice scores (PDice), along with voxel-level true positive rates (VTPR), as well as analysis of time saved in a model-assisted scenario. Additionally, we assessed human-level reliability in liver cyst segmentation and evaluated the model's test-retest reproducibility. We further compared liver volume vs cyst volume for tracking disease in a subject with 16+ years follow-up.
RESULTS: The model achieved an 82% ± 11% PDice and a 75% ± 15% VTPR on the internal test sets (n = 7 patients), and 80% ± 12% Dice score and a 91% ± 7% VTPR on the external test sets (n = 10 patients). It excelled particularly in detecting small liver cysts, a challenging task for manual annotation. This efficiency translated to a median of 91% (IQR: 14%) reduction in annotation time compared to manual labeling. Test-retest assessment demonstrated excellent reproducibility, with coefficients of variation of 94% for liver cyst fraction and 92% for cyst count.
CONCLUSION: DL automation of liver cyst segmentations demonstrates potential to improve tracking of liver cyst volume in polycystic liver disease.
Reporting ADPK Disease Phenotypes on Abdominal Scans
Zhongxiu Hu, Elizabeth G Lane, Grace C Lo, Jon D Blumenfeld, Daniil Shimonov, James M Chevalier, Emily A Schonfeld, Danielle Brandman, Martin R Prince...
INTRODUCTION: Kidney and liver volumes from abdominal magnetic resonance imaging (MRI) and computed tomography (CT) scans are critical biomarkers recommended by Kidney Disease: Improving Global Outcomes (KDIGO) for autosomal dominant polycystic kidney disease (ADPKD) progression and response to therapy. The purpose of this study was to determine how often these biomarkers are included in radiology reports as well as their reproducibility.
METHODS: Outside abdominal MRI (n = 102) and CT (n = 43) studies were reviewed retrospectively and independently by 2 observers for prevalence of reporting ADPKD-relevant findings with discrepancies resolved by 2 radiologists. These 2 radiologists independently reevaluated all examinations to assess interobserver reproducibility.
RESULTS: Outside reports (n = 145; males: 46%; median age: 47 [interquartile range: 35-61] years) by 122 radiologists from 88 institutions included kidney volumes in only 30 (21%) reports. Out of 140 imaging examinations that included the entire liver, 1 (1%) outside report provided liver volume. Comparison of outside and study radiologists' kidney volume measurements showed a median absolute difference of 15%, using the ellipsoidal method and 8% using model-assisted contouring. Additional positive findings not mentioned in 145 outside reports included umbilical hernia (n = 44), hepatic steatosis (n = 3), inguinal hernia (n = 4), pancreatic cyst (n = 6) and severe inferior vena cava (IVC) compression by cysts (n = 2).
CONCLUSION: Radiologists report reliably on complex cysts, calcifications, ascites, and abdominal aortic aneurysms in ADPKD. However, the clinical utility of these reports can be improved more reliably by including kidney volume and other important imaging features of ADPKD recommended by clinical guidelines.
Common bile duct dilatation on MRI in autosomal dominant polycystic kidney disease
Usama Sattar, Chenglin Zhu, Xiaorui Yin, Xianfu Luo, Vahid Bazojoo, Albert S Prince, Hanna Rennert, Danielle Brandman, Emily Schonfeld, Jon D Blumenfeld, Martin R Prince...
PURPOSE: Polycystic liver disease is the most prevalent extrarenal manifestation of autosomal dominant polycystic kidney disease (ADPKD). Non-obstructive asymptomatic common bile duct (CBD) dilatation has been observed anecdotally on CT scans, but CT is not optimal for biliary visualization. Here, we measured CBD diameter on T2-weighted MRI in ADPKD subjects to determine if CBD dilatation is associated with ADPKD.
METHODS: CBD diameter was measured retrospectively on ADPKD subjects (n = 254) and on age- and sex-matched controls without ADPKD (n = 254) who underwent abdominal MRI. CBD diameter in these groups was compared and correlated with clinical, laboratory and magnetic resonance imaging (MRI) features, including organ volumes and cyst burden.
RESULTS: CBD median diameter [interquartile range, IQR, 25%, 75%] was 22% larger in ADPKD compared to controls (5.6 [4.7, 6.9] mm vs. 4.6 [3.9, 5.4] mm, p < 0.001). CBD diameter measurements had excellent inter-observer agreement (Intraclass correlation coefficient = 0.92). Thirteen (5.1%) ADPKD subjects had a CBD diameter ≥ 10 mm compared to 1 (0.4%) control subject (p < 0.001). Multivariable analysis found the presence of PKD1 or PKD2 mutation (beta = 1.5, P < 0.001) and age (beta = 0.04, p < 0.001) to be associated with increased CBD diameter and serum albumin associated with decreased CBD diameter (beta=-0.39, p < 0.001).
CONCLUSION: ADPKD subjects had 22% larger CBD diameters than in non-ADPKD controls and were more likely to have CBD dilatation ≥ 10 mm without CBD obstruction. Awareness of this association of non-obstructive CBD dilatation with ADPKD may limit unnecessary diagnostic testing.
Effects of Pregnancy on Liver and Kidney Cyst Growth Rates in Autosomal Dominant Polycystic Kidney Disease: A Pilot Study
Vahid Bazojoo, Vahid Davoudi, Jon D Blumenfeld, Chenglin Zhu, Line Malha, Grace C Lo, James M Chevalier, Daniil Shimonov, Arman Sharbatdaran, Hreedi Dev, Syed I Raza, Zhongxiu Hu, Xinzi He, Arindam RoyChoudhury, Martin R Prince...
J Clin Med. 2025 May 24;14(11):3688. doi: 10.3390/jcm14113688.
ABSTRACT
Background/Objectives: Polycystic liver disease (PLD) is the most common extrarenal manifestation of autosomal dominant polycystic kidney disease (ADPKD). PLD is more prevalent in women, and women have larger liver cysts, possibly due to estrogen-related mechanisms. Maternal estrogen levels normally increase during pregnancy. Thus, we investigated the pregnancy-associated increase in liver volume, liver cyst volume, total kidney volume (TKV), and kidney cyst growth rates in ADPKD patients. Methods: Kidney, liver, and cyst volumes were measured in 16 ADPKD patients by magnetic resonance imaging (MRI) at multiple timepoints before and after pregnancy. The log-transformed TKV, liver volume, and cyst volume growth rates during a period with pregnancy were compared to a period without pregnancy. Results: In ADPKD patients, a higher annualized liver cyst growth rate was observed during a period with pregnancy compared to a period without pregnancy (34 ± 16%/yr vs. 23 ± 17%/yr; p-value = 0.005). Liver volume growth was also higher during a period with pregnancy, 6 [2, 7]%/yr vs. 0.3 [-0.4, 2]%/yr (p-value = 0.04). In addition, the mean kidney cyst growth rate was higher (12 ± 11%/yr vs. 4 ± 9%/yr; p-value = 0.05), and there was a trend toward a pregnancy-associated increase in the TKV growth rate (6 [4, 8]%/yr vs. 3 [0.8, 5]%/yr, (p-value = 0.14) during a period with pregnancy. Conclusions: In patients with ADPKD, the liver volume and cyst volume growth rates increased during pregnancy. This supports the hypothesis that the estrogen-mediated stimulation of liver cyst growth may contribute to the severe polycystic liver disease that is more prevalent in women than men with ADPKD. Further studies with larger populations are needed to explore the mechanisms and long-term implications of these findings.
The Role of Baseline Total Kidney Volume Growth Rate in Predicting Tolvaptan Efficacy for ADPKD Patients: A Feasibility Study
Hreedi Dev, Zhongxiu Hu, Jon D Blumenfeld, Arman Sharbatdaran, Yelynn Kim, Chenglin Zhu, Daniil Shimonov, James M Chevalier, Stephanie Donahue, Alan Wu, Arindam RoyChoudhury, Xinzi He, Martin R Prince...
J Clin Med. 2025 Feb 21;14(5):1449. doi: 10.3390/jcm14051449.
ABSTRACT
Background/Objectives: Although tolvaptan efficacy in ADPKD has been demonstrated in randomized clinical trials, there is no definitive method for assessing its efficacy in the individual patient in the clinical setting. In this exploratory feasibility study, we report a method to quantify the change in total kidney volume (TKV) growth rate to retrospectively evaluate tolvaptan efficacy for individual patients. Treatment-related changes in estimated glomerular filtration rate (eGFR) are also assessed. Methods: MRI scans covering at least 1 year prior to and during treatment with tolvaptan were performed, with deep learning facilitated kidney segmentation and fitting multiple imaging timepoints to exponential growth in 32 ADPKD patients. Clustering analysis differentiated tolvaptan treatment "responders" and "non-responders" based upon the magnitude of change in TKV growth rate. Differences in rate of eGFR decline, urine osmolality, and other parameters were compared between responders and non-responders. Results: Eighteen (56%) tolvaptan responders (mean age 42 ± 8 years) were identified by k-means clustering, with an absolute reduction in annual TKV growth rate of >2% (mean = -5.1% ± 2.5% per year). Thirteen (44%) non-responders were identified, with <1% absolute reduction in annual TKV growth rate (mean = +2.4% ± 2.7% per year) during tolvaptan treatment. Compared to non-responders, tolvaptan responders had significantly higher mean TKV growth rates prior to tolvaptan treatment (7.1% ± 3.6% per year vs. 3.7% ± 2.4% per year; p = 0.003) and higher median pretreatment spot urine osmolality (Uosm, 393 mOsm/kg vs. 194 mOsm/kg, p = 0.03), confirmed by multivariate analysis. Mean annual rate of eGFR decline was less in responders than in non-responders (-0.25 ± 0.04, CI: [-0.27, -0.23] mL/min/1.73 m2 per year vs. -0.40 ± 0.06, CI: [-0.43, -0.37] mL/min/1.73 m2 per year, p = 0.036). Conclusions: In this feasibility study designed to assess predictors of tolvaptan treatment efficacy in individual patients with ADPKD, we found that high pretreatment levels of annual TKV growth rate and higher pretreatment spot urine osmolality were associated with a responder phenotype.
Hypothesis: Reactive increases in plasma renin activity attenuate the fall in blood pressure caused by salt depletion and renin-angiotensin system inhibition
Jean E Sealey, Jon D Blumenfeld
J Hypertens. 2025 May 1;43(5):739-746. doi: 10.1097/HJH.0000000000003964. Epub 2025 Feb 7.
ABSTRACT
There are inconsistencies in the effect of raising or lowering body salt on blood pressure (BP). We hypothesize that they are caused in part by differences in plasma renin activity (PRA). PRA changes reciprocally with body salt. PRA is the rate limiting step in the formation of the vasoconstrictor peptide angiotensin II (Ang II) in the circulation where it cleaves Ang I from plasma angiotensinogen, and then Ang I is rapidly converted to Ang II by angiotensin-converting enzyme in plasma and vascular endothelial cells. We hypothesize that PRA levels above 0.65 ng/ml/h lead to sufficient Ang II production to cause vasoconstriction, whereas lower levels do not. PRA is usually more than 0.65 in normotensives who are not on a high-salt diet; in them, the increase in PRA/Ang II vasoconstriction caused by reduction in body salt (low-salt diet, diuretic use) is large enough to prevent BP from falling. By contrast, a similar reduction in body salt lowers BP in the 30% of hypertensive patients with low baseline PRA (<0.65 ng/ml/h), because vasoconstriction does not increase in that range. A similar reduction in body salt also lowers BP in the 60% of hypertensive patients with baseline PRA between 0.65 and 4.5 ng/ml/h, but for a different reason; the rise in PRA and the increase in vasoconstriction is too small to prevent BP from falling. However, after body salt has been reduced enough to raise PRA above 4.5 ng/ml/h, further salt depletion increases PRA to a greater extent, and BP does not fall. Renin-angiotensin system (RAS) inhibitors leave a small amount of renin unblocked. In salt-depleted hypertensive patients, they also raise PRA enough to prevent BP from falling significantly. We propose that this PRA/Ang II vasoconstrictor effect related to reactive increases in PRA can prevent or attenuate the decrease in BP caused by excessive salt depletion, even during concurrent RAS inhibition. This phenomenon, if confirmed, could inform new strategies to optimize the treatment of hypertension, cardiovascular disease (CVD) and chronic kidney disease (CKD).
Automatically Detecting Pancreatic Cysts in Autosomal Dominant Polycystic Kidney Disease on MRI Using Deep Learning
Sophie J Wang, Zhongxiu Hu, Collin Li, Xinzi He, Chenglin Zhu, Yin Wang, Usama Sattar, Vahid Bazojoo, Hui Yi Ng He, Jon D Blumenfeld, Martin R Prince...
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.
Prevalence of Spinal Meningeal Diverticula in Autosomal Dominant Polycystic Kidney Disease
Usama Sattar, Xiaorui Yin, Xianfu Luo, Chenglin Zhu, Zhongxiu Hu, Jon D Blumenfeld, Hanna Rennert, Alan Wu, Arindam RoyChoudhury, Gayle Salama, Martin R Prince...
AJNR Am J Neuroradiol. 2025 Jan 8;46(1):200-206. doi: 10.3174/ajnr.A8407.
ABSTRACT
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) mm3 in those with ADPKD compared with 250 (IQR, 180-440) mm3 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.
Improved predictions of total kidney volume growth rate in ADPKD using two-parameter least squares fitting
Zhongxiu Hu, Arman Sharbatdaran, Xinzi He, Chenglin Zhu, Jon D Blumenfeld, Hanna Rennert, Zhengmao Zhang, Andrew Ramnauth, Daniil Shimonov, James M Chevalier, Martin R Prince...
Sci Rep. 2024 Jun 14;14(1):13794. doi: 10.1038/s41598-024-62776-8.
ABSTRACT
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.
A Primer for Utilizing Deep Learning and Abdominal MRI Imaging Features to Monitor Autosomal Dominant Polycystic Kidney Disease Progression
Chenglin Zhu, Xinzi He, Jon D Blumenfeld, Zhongxiu Hu, Hreedi Dev, Usama Sattar, Vahid Bazojoo, Arman Sharbatdaran, Mohit Aspal, Dominick Romano, Kurt Teichman, Hui Yi Ng He, Yin Wang, Andrea Soto Figueroa, Erin Weiss, Anna G Prince, James M Chevalier, Daniil Shimonov, Mina C Moghadam, Mert Sabuncu, Martin R Prince...
Biomedicines. 2024 May 20;12(5):1133. doi: 10.3390/biomedicines12051133.
ABSTRACT
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.
Feasibility of Water Therapy for Slowing Autosomal Dominant Polycystic Kidney Disease Progression
Hreedi Dev, Chenglin Zhu, Irina Barash, Jon D Blumenfeld, Xinzi He, Arindam RoyChoudhury, Alan Wu, Martin R Prince...
Kidney360. 2024 May 1;5(5):698-706. doi: 10.34067/KID.0000000000000428. Epub 2024 Apr 1.
ABSTRACT
KEY POINTS:
Water therapy in autosomal dominant polycystic kidney disease (ADPKD) reduces urine osmolality and serum copeptin level, a marker of vasopressin activity.
Water therapy reduces the ADPKD kidney growth rate indicating it is slowing disease progression.
Patients with ADPKD are less likely to report pain on water therapy.
BACKGROUND: In animal models of autosomal dominant polycystic kidney disease (ADPKD), high water intake (HWI) decreases vasopressin secretion and slows disease progression, but the efficacy of HWI in human ADPKD is uncertain.
METHODS: This exploratory, prospective, cross-over study of patients with ADPKD (N=7) evaluated the hypothesis that HWI slows the rate of increase in height-adjusted total kidney volume (ht-TKV; a biomarker for ADPKD progression) and reduces pain. Patients at high risk of ADPKD progression (i.e., Mayo Imaging Classifications 1C/1D) were evaluated during 6 months of usual water intake (UWI), followed by 12 months of HWI calculated to reduce urine osmolality (Uosm) to <285 mOsm/kg. Measurements of Uosm, serum copeptin (secreted in equimolar amounts with vasopressin), magnetic resonance imaging measurements of ht-TKV, and pain survey responses were compared between HWI and UWI.
RESULTS: During HWI, mean 24-hour Uosm decreased compared with UWI (428 [398–432] mOsm/kg versus 209 [190–223] mOsm/kg; P = 0.01), indicating adherence to the protocol. Decreases during HWI also occurred in levels of serum copeptin (5.8±2.0 to 4.2±1.6 pmol/L; P = 0.03), annualized rate of increase in ht-TKV (6.8% [5.9–8.5] to 4.4% [3.0–5.0]; P < 0.02), and pain occurrence and pain interference during sleep (P < 0.01). HWI was well tolerated.
CONCLUSIONS: HWI in patients at risk of rapid progression of ADPKD slowed the rate of ht-TKV growth and reduced pain. This suggests that suppressing vasopressin levels by HWI provides an effective nonpharmacologic treatment of ADPKD.
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.
Test Retest Reproducibility of Organ Volume Measurements in ADPKD Using 3D Multimodality Deep Learning
Xinzi He, Zhongxiu Hu, Hreedi Dev, Dominick J Romano, Arman Sharbatdaran, Syed I Raza, Sophie J Wang, Kurt Teichman, George Shih, James M Chevalier, Daniil Shimonov, Jon D Blumenfeld, Akshay Goel, Mert R Sabuncu, Martin R Prince...
Acad Radiol. 2024 Mar;31(3):889-899. doi: 10.1016/j.acra.2023.09.009. Epub 2023 Oct 3.
ABSTRACT
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.
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