Multiethnic growth standards for fetal body composition and organ volumes derived from 3D ultrasonography.

BACKGROUND: A major goal of contemporary obstetrical practice is to optimize fetal growth and development throughout pregnancy. To date, fetal growth during prenatal care is assessed by performing ultrasonographic measurement of 2-dimensional fetal biometry to calculate an estimated fetal weight. Our group previously established 2-dimensional fetal growth standards using sonographic data from a large cohort with multiple sonograms. A separate objective of that investigation involved the collection of fetal volumes from the same cohort. OBJECTIVE: The Fetal 3D Study was designed to establish standards for fetal soft tissue and organ volume measurements by 3-dimensional ultrasonography and compare growth trajectories with conventional 2-dimensional measures where applicable. STUDY DESIGN: The National Institute of Child Health and Human Development Fetal 3D Study included research-quality images of singletons collected in a prospective, racially and ethnically diverse, low-risk cohort of pregnant individuals at 12 U.S. sites, with up to 5 scans per fetus (N=1730 fetuses). Abdominal subcutaneous tissue thickness was measured from 2-dimensional images and fetal limb soft tissue parameters extracted from 3-dimensional multiplanar views. Cerebellar, lung, liver, and kidney volumes were measured using virtual organ computer aided analysis. Fractional arm and thigh total volumes, and fractional lean limb volumes were measured, with fractional limb fat volume calculated by subtracting lean from total. For each measure, weighted curves (fifth, 50th, 95th percentiles) were derived from 15 to 41 weeks' using linear mixed models for repeated measures with cubic splines. RESULTS: Subcutaneous thickness of the abdomen, arm, and thigh increased linearly, with slight acceleration around 27 to 29 weeks. Fractional volumes of the arm, thigh, and lean limb volumes increased along a quadratic curvature, with acceleration around 29 to 30 weeks. In contrast, growth patterns for 2-dimensional humerus and femur lengths demonstrated a logarithmic shape, with fastest growth in the second trimester. The mid-arm area curve was similar in shape to fractional arm volume, with an acceleration around 30 weeks, whereas the curve for the lean arm area was more gradual. The abdominal area curve was similar to the mid-arm area curve with an acceleration around 29 weeks. The mid-thigh and lean area curves differed from the arm areas by exhibiting a deceleration at 39 weeks. The growth curves for the mid-arm and thigh circumferences were more linear. Cerebellar 2-dimensional diameter increased linearly, whereas cerebellar 3-dimensional volume growth gradually accelerated until 32 weeks followed by a more linear growth. Lung, kidney, and liver volumes all demonstrated gradual early growth followed by a linear acceleration beginning at 25 weeks for lungs, 26 to 27 weeks for kidneys, and 29 weeks for liver. CONCLUSION: Growth patterns and timing of maximal growth for 3-dimensional lean and fat measures, limb and organ volumes differed from patterns revealed by traditional 2-dimensional growth measures, suggesting these parameters reflect unique facets of fetal growth. Growth in these three-dimensional measures may be altered by genetic, nutritional, metabolic, or environmental influences and pregnancy complications, in ways not identifiable using corresponding 2-dimensional measures. Further investigation into the relationships of these 3-dimensional standards to abnormal fetal growth, adverse perinatal outcomes, and health status in postnatal life is warranted.

Estimating baseline creatinine levels based on the kidney parenchymal volume.

BACKGROUND: Acute kidney injury (AKI) diagnosis often lacks a baseline serum creatinine (Cr) value. Our study aimed to create a regression equation linking kidney morphology to function in kidney donors and chronic kidney disease patients. We also sought to estimate baseline Cr in minimal change disease (MCD) patients, a common AKI-predisposing condition. METHODS: We analyzed 119 participants (mean age 60 years, 50% male, 40% donors) with CT scans, dividing them into derivation and validation groups. An equation based on kidney parenchymal volume (PV) was developed in the derivation group and validated in the validation group. We estimated baseline Cr in 43 MCD patients (mean age 45 years, 61% male) using the PV-based equation and compared with their 6 month post-MCD onset Cr values. RESULTS: In the derivation group, the equation for the estimated glomerular filtration rate (eGFR) was: eGFR (mL/min/1.73m2) = 0.375 × PV (cm3) + (- 0.395) × age (years) + (- 2.93) × male sex + (- 13.3) × hypertension + (- 14.0) × diabetes + (- 0.210) × height (cm) + 82.0 (intercept). In the validation group, the eGFR and estimated Cr values correlated well with the measured values (r = 0.46, p = 0.01; r = 0.51, p = 0.004, respectively). In the MCD group, the baseline Cr values were significantly correlated with the estimated baseline Cr values (r = 0.52, p < 0.001), effectively diagnosing AKI (kappa = 0.76, p < 0.001). CONCLUSIONS: The PV-based regression equation established in this study holds promise for estimating baseline Cr values and diagnosing AKI in patients with MCD. Further validation in diverse AKI populations is warranted.

Deep Learning-Based Automated Imaging Classification of ADPKD.

Introduction: The Mayo imaging classification model (MICM) requires a prestep qualitative assessment to determine whether a patient is in class 1 (typical) or class 2 (atypical), where patients assigned to class 2 are excluded from the MICM application. Methods: We developed a deep learning-based method to automatically classify class 1 and 2 from magnetic resonance (MR) images and provide classification confidence utilizing abdominal T 2 -weighted MR images from 486 subjects, where transfer learning was applied. In addition, the explainable artificial intelligence (XAI) method was illustrated to enhance the explainability of the automated classification results. For performance evaluations, confusion matrices were generated, and receiver operating characteristic curves were drawn to measure the area under the curve. Results: The proposed method showed excellent performance for the classification of class 1 (97.7%) and 2 (100%), where the combined test accuracy was 98.01%. The precision and recall for predicting class 1 were 1.00 and 0.98, respectively, with F 1 -score of 0.99; whereas those for predicting class 2 were 0.87 and 1.00, respectively, with F 1 -score of 0.93. The weighted averages of precision and recall were 0.98 and 0.98, respectively, showing the classification confidence scores whereas the XAI method well-highlighted contributing regions for the classification. Conclusion: The proposed automated method can classify class 1 and 2 cases as accurately as the level of a human expert. This method may be a useful tool to facilitate clinical trials investigating different types of kidney morphology and for clinical management of patients with autosomal dominant polycystic kidney disease (ADPKD).

Late Changes in Renal Volume and Function after Proton Beam Therapy in Pediatric and Adult Patients: Children Show Significant Renal Atrophy but Deterioration of Renal Function Is Minimal in the Long-Term in Both Groups.

To compare late renal effects in pediatric and adult patients with malignancies after PBT involving part of the kidney. A retrospective study was conducted to assess changes in renal volume and function in 24 patients, including 12 children (1-14 years old) and 12 adults (51-80 years old). Kidney volumes were measured from CT or MRI images during follow-up. Dose-volume histograms were calculated using a treatment planning system. In children, the median volume changes for the irradiated and control kidneys were -5.58 (-94.95 to +4.79) and +14.92 (-19.45 to +53.89) mL, respectively, with a relative volume change of -28.38 (-119.45 to -3.87) mL for the irradiated kidneys. For adults, these volume changes were -22.43 (-68.7 to -3.48) and -21.56 (-57.26 to -0.16) mL, respectively, with a relative volume change of -5.83 (-28.85 to +30.92) mL. Control kidneys in children exhibited a marked increase in size, while those in adults showed slight volumetric loss. The percentage of irradiated volume receiving 10 Gy (RBE) (V10) and 20 Gy (RBE) (V20) were significantly negatively associated with the relative volume change per year, especially in children. The CKD stage based on eGFR for all patients ranged from 1 to 3 and no cases with severe renal dysfunction were found before or after PBT. Late effects on the kidneys after PBT vary among age groups. Children are more susceptible than adults to significant renal atrophy after PBT. V10 and V20 might serve as predictors of the degree of renal atrophy after PBT, especially in children. PBT has a minimal impact on deterioration of renal function in both children and adults.

Magnetic resonance imaging based kidney volume assessment for risk stratification in pediatric autosomal dominant polycystic kidney disease.

Introduction: In the pediatric context, most children with autosomal dominant polycystic kidney disease (ADPKD) maintain a normal glomerular filtration rate (GFR) despite underlying structural kidney damage, highlighting the critical need for early intervention and predictive markers. Due to the inverse relationship between kidney volume and kidney function, risk assessments have been presented on the basis of kidney volume. The aim of this study was to use magnetic resonance imaging (MRI)-based kidney volume assessment for risk stratification in pediatric ADPKD and to investigate clinical and genetic differences among risk groups. Methods: This multicenter, cross-sectional, and case-control study included 75 genetically confirmed pediatric ADPKD patients (5-18 years) and 27 controls. Kidney function was assessed by eGFR calculated from serum creatinine and cystatin C using the CKiD-U25 equation. Blood pressure was assessed by both office and 24-hour ambulatory measurements. Kidney volume was calculated from MRI using the stereological method. Total kidney volume was adjusted for the height (htTKV). Patients were stratified from A to E classes according to the Leuven Imaging Classification (LIC) using MRI-derived htTKV. Results: Median (Q1-Q3) age of the patients was 6.0 (2.0-10.0) years, 56% were male. There were no differences in sex, age, height-SDS, or GFR between the patient and control groups. Of the patients, 89% had PKD1 and 11% had PKD2 mutations. Non-missense mutations were 73% in PKD1 and 75% in PKD2. Twenty patients (27%) had hypertension based on ABPM. Median htTKV of the patients was significantly higher than controls (141 vs. 117 ml/m, p = 0.0003). LIC stratification revealed Classes A (38.7%), B (28%), C (24%), and D + E (9.3%). All children in class D + E and 94% in class C had PKD1 variants. Class D + E patients had significantly higher blood pressure values and hypertension compared to other classes (p > 0.05 for all). Discussion: This study distinguishes itself by using MRI-based measurements of kidney volume to stratify pediatric ADPKD patients into specific risk groups. It is important to note that PKD1 mutation and elevated blood pressure were higher in the high-risk groups stratified by age and kidney volume. Our results need to be confirmed in further studies.

The screening, diagnosis, and management of patients with autosomal dominant polycystic kidney disease: A national consensus statement from Taiwan.

Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited cause of end-stage kidney disease (ESKD) worldwide. Guidelines for the diagnosis and management of ADPKD in Taiwan remains unavailable. In this consensus statement, we summarize updated information on clinical features of international and domestic patients with ADPKD, followed by suggestions for optimal diagnosis and care in Taiwan. Specifically, counselling for at-risk minors and reproductive issues can be important, including ethical dilemmas surrounding prenatal diagnosis and pre-implantation genetic diagnosis. Studies reveal that ADPKD typically remains asymptomatic until the fourth decade of life, with symptoms resulting from cystic expansion with visceral compression, or rupture. The diagnosis can be made based on a detailed family history, followed by imaging studies (ultrasound, computed tomography, or magnetic resonance imaging). Genetic testing is reserved for atypical cases mostly. Common tools for prognosis prediction include total kidney volume, Mayo classification and PROPKD/genetic score. Screening and management of complications such as hypertension, proteinuria, urological infections, intracranial aneurysms, are also crucial for improving outcome. We suggest that the optimal management strategies of patients with ADPKD include general medical care, dietary recommendations and ADPKD-specific treatments. Key points include rigorous blood pressure control, dietary sodium restriction and Tolvaptan use, whereas the evidence for somatostatin analogues and mammalian target of rapamycin (mTOR) inhibitors remains limited. In summary, we outline an individualized care plan emphasizing careful monitoring of disease progression and highlight the need for shared decision-making among these patients.

Kidney volume normative values in Central European children aged 0-19 years: a multicenter study.

BACKGROUND AND OBJECITVES: The currently available kidney volume normative values in children are restricted to small populations from single-centre studies not assessing kidney function and including none or only a small number of adolescents. This study aimed to obtain ultrasound-based kidney volume normative values derived from a large European White/Caucasian paediatric population with normal kidney function. METHODS: After recruitment of 1427 children aged 0-19 years, 1396 individuals with no history of kidney disease and normal estimated glomerular filtration rate were selected for the sonographic evaluation of kidney volume. Kidney volume was correlated with age, height, weight, body surface area and body mass index. Kidney volume curves and tables related to anthropometric parameters were generated using the LMS method. Kidney volume predictors were evaluated using multivariate regression analysis with collinearity checks. RESULTS: No clinically significant differences in kidney volume in relation to height were found between males and females, between supine and prone position and between left and right kidneys. Males had, however, larger age-related kidney volumes than females in most age categories. For the prediction of kidney volume, the highest coefficient correlation was observed for body surface area (r = 0.94), followed by weight (r = 0.92), height (r = 0.91), age (r = 0.91), and body mass index (r = 0.67; p < 0.001 for all). CONCLUSIONS: This study presents LMS-percentile curves and tables for kidney volume which can be used as reference values for children aged 0-19 years.

nnUNet for Automatic Kidney and Cyst Segmentation in Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND: Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a genetic disorder that causes uncontrolled kidney cyst growth, leading to kidney volume enlargement and renal function loss over time. Total kidney volume (TKV) and cyst burdens have been used as prognostic imaging biomarkers for ADPKD. OBJECTIVE: This study aimed to evaluate nnUNet for automatic kidney and cyst segmentation in T2-weighted (T2W) MRI images of ADPKD patients. METHODS: 756 kidney images were retrieved from 95 patients in the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) cohort (95 patients × 2 kidneys × 4 follow-up scans). The nnUNet model was trained, validated, and tested on 604, 76, and 76 images, respectively. In contrast, all images of each patient were exclusively assigned to either the training, validation, or test sets to minimize evaluation bias. The kidney and cyst regions defined using a semi-automatic method were employed as ground truth. The model performance was assessed using the Dice Similarity Coefficient (DSC), the intersection over union (IoU) score, and the Hausdorff distance (HD). RESULTS: The test DSC values were 0.96±0.01 (mean±SD) and 0.90±0.05 for kidney and cysts, respectively. Similarly, the IoU scores were 0.91± 0.09 and 0.81±0.06, and the HD values were 12.49±8.71 mm and 12.04±10.41 mm, respectively, for kidney and cyst segmentation. CONCLUSION: The nnUNet model is a reliable tool to automatically determine kidney and cyst volumes in T2W MRI images for ADPKD prognosis and therapy monitoring.

An Artificial Intelligence Generated Automated Algorithm to Measure Total Kidney Volume in ADPKD.

Introduction: Accurate tools to inform individual prognosis in patients with autosomal dominant polycystic kidney disease (ADPKD) are lacking. Here, we report an artificial intelligence (AI)-generated method for routinely measuring total kidney volume (TKV). Methods: An ensemble U-net algorithm was created using the nnUNet approach. The training and internal cross-validation cohort consisted of all 1.5T magnetic resonance imaging (MRI) data acquired using 5 different MRI scanners (454 kidneys, 227 scans) in the CYSTic consortium, which was first manually segmented by a single human operator. As an independent validation cohort, we utilized 48 sequential clinical MRI scans with reference results of manual segmentation acquired by 6 individual analysts at a single center. The tool was then implemented for clinical use and its performance analyzed. Results: The training or internal validation cohort was younger (mean age 44.0 vs. 51.5 years) and the female-to-male ratio higher (1.2 vs. 0.94) compared to the clinical validation cohort. The majority of CYSTic patients had PKD1 mutations (79%) and typical disease (Mayo Imaging class 1, 86%). The median DICE score on the clinical validation data set between the algorithm and human analysts was 0.96 for left and right kidneys with a median TKV error of -1.8%. The time taken to manually segment kidneys in the CYSTic data set was 56 (±28) minutes, whereas manual corrections of the algorithm output took 8.5 (±9.2) minutes per scan. Conclusion: Our AI-based algorithm demonstrates performance comparable to manual segmentation. Its rapidity and precision in real-world clinical cases demonstrate its suitability for clinical application.

Combining genotype with height-adjusted kidney length predicts rapid progression of ADPKD.

INTRODUCTION: Our main objective was to identify baseline prognostic factors predictive of rapid disease progression in a large unselected clinical autosomal dominant polycystic kidney disease (ADPKD) cohort. METHODS: A cross-sectional analysis was performed in 618 consecutive ADPKD patients assessed and followed-up for over a decade. A total of 123 patients (19.9%) had reached kidney failure by the study date. Data were available for the following: baseline eGFR (n = 501), genotype (n = 549), baseline ultrasound mean kidney length (MKL, n = 424) and height-adjusted baseline MKL (HtMKL, n = 377). Rapid disease progression was defined as an annualized eGFR decline (∆eGFR) of >2.5 mL/min/year by linear regression over 5 years (n = 158). Patients were further divided into slow, rapid and very rapid ∆eGFR classes for analysis. Genotyped patients were classified into several categories: PKD1 (T, truncating; or NT, non-truncating), PKD2, other genes (non-PKD1 or -PKD2), no mutation detected or variants of uncertain significance. RESULTS: A PKD1-T genotype had the strongest influence on the probability of reduced baseline kidney function by age. A multivariate logistic regression model identified PKD1-T genotype and HtMKL (>9.5 cm/m) as independent predictors for rapid disease progression. The combination of both factors increased the positive predictive value for rapid disease progression over age 40 years and of reaching kidney failure by age 60 years to 100%. Exploratory analysis in a subgroup with available total kidney volumes showed higher positive predictive value (100% vs 80%) and negative predictive value (42% vs 33%) in predicting rapid disease progression compared with the Mayo Imaging Classification (1C-E). CONCLUSION: Real-world longitudinal data confirm the importance of genotype and kidney length as independent variables determining ∆eGFR. Individuals with the highest risk of rapid disease progression can be positively selected for treatment based on this combination.

Choosing the larger kidney on CT volumetry: a study on the early post-donation kidney function of living donors.

BACKGROUND: Selecting the smaller kidney for donation has been advocated if there is a size difference of > 10% between the 2 kidneys but has never been prospectively evaluated. With increase in donor nephrectomies, it is important to evaluate this to minimize loss of renal function to donors. METHODS: 75 consecutive donor nephrectomy patients were included in our longitudinal study. The Split Renal Volume (SRV) of bilateral kidneys were measured using contrasted computer tomography scans and patients segregated into 2 groups depending on donated kidney having more (Group 1) or less than (Group 2) 52.5% of SRV. RESULTS: Patients in Group 1 (n = 19) and 2 (n = 56) were of similar age (43.8 vs. 48.3), BMI (22.4 vs. 25.2), sex (57.9 vs. 55.4% women), respectively. Although total kidney volumes were similar in both groups, Group 1 had significantly smaller right kidney volumes (120.4 ± 24.9 vs. 142.7 ± 28.4 mls, p = 0.003). EGFR pre-operatively (116.3 ± 20.8 vs. 106.3 ± 23.8 mL/min/1.73 m2) and at 6-months (65.7 ± 13.3 vs. 66.9 ± 15.5 mL/min/1.73 m2) were not different between groups. However, patients in Group 1 had significantly greater absolute (50.6 ± 14.9 vs. 39.5 ± 14.7 mL/min/1.73 m2) and relative decline (43.0 ± 8.6 vs. 36.3 ± 10.6%) in eGFR at 6 months (p = 0.06, 0.009). CONCLUSION: With a SRV difference of 5% between the 2 sides, removal of the larger kidney for living kidney donation resulted in greater early decline of renal function than kidney donors whose larger or equivalent kidney is preserved.

Estimating risk of rapid disease progression in pediatric patients with autosomal dominant polycystic kidney disease: a randomized trial of tolvaptan.

BACKGROUND: Tolvaptan preserves kidney function in adults with autosomal dominant polycystic kidney disease (ADPKD) at elevated risk of rapid progression. A trial (NCT02964273) evaluated tolvaptan safety and pharmacodynamics in children (5-17 years). However, progression risk was not part of study eligibility criteria due to lack of validated criteria for risk assessment in children. As risk estimation is important to guide clinical management, baseline characteristics of the study participants were retrospectively evaluated to determine whether risk of rapid disease progression in pediatric ADPKD can be assessed and to identify parameters relevant for risk estimation. METHODS: Four academic pediatric nephrologists reviewed baseline data and rated participant risk from 1 (lowest) to 5 (highest) based on clinical judgement and the literature. Three primary reviewers independently scored all cases, with each case reviewed by two primary reviewers. For cases with discordant ratings (≥ 2-point difference), the fourth reviewer provided a secondary rating blinded to the primary evaluations. Study participants with discordant ratings and/or for whom data were lacking were later discussed to clarify parameters relevant to risk estimation. RESULTS: Of 90 evaluable subjects, primary reviews of 69 (77%) were concordant. The proportion considered at risk of rapid progression (final mean rating ≥ 3.5) by age group was: 15-17 years, 27/34 (79%); 12- < 15, 9/32 (28%); 4- < 12, 8/24 (33%). The panelists agreed on characteristics important for risk determination: age, kidney imaging, kidney function, blood pressure, urine protein, and genetics. CONCLUSIONS: High ratings concordance and agreement among reviewers on relevant clinical characteristics support the feasibility of pediatric risk assessment.

Statin therapy in patients with early-stage autosomal dominant polycystic kidney disease: Design and baseline characteristics.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is characterized by the development and continued growth of multiple cysts in the kidneys leading to ultimate loss of kidney function in most patients. Currently, tolvaptan is the only agency approved therapy to slow kidney disease advancement in patients with faster progressing disease underscoring the need for additional ADPKD therapies suitable for all patients. We previously showed that pravastatin slowed kidney disease progression in children and young adults with ADPKD. However, the intervention has not been tested in an adult cohort. AIMS: The aim of the study is to conduct a single center, randomized, placebo-controlled double-blinded clinical trial to determine the efficacy of pravastatin on slowing kidney disease progression in adult patients with early stage ADPKD. METHODS: One hundred and fifty adult patients with ADPKD and eGFR ≥60 ml/min/1.73m2 will be enrolled in the study and randomized to receive 40 mg/day pravastatin or placebo for a period of 2-years. OUTCOMES: The primary outcome of the trial is change in total kidney volume assessed by magnetic resonance imaging (MRI). Secondary outcomes include change in kidney function by iothalamate GFR and renal blood flow and markers of inflammation and oxidative stress. CONCLUSION: This study will assess the kidney therapeutic benefits of pravastatin in adult patients with ADPKD. The recruitment goal of 150 subjects was attained and the study is ongoing. REGISTRATION: This study is registered on Clinicaltrials.gov # NCT03273413.

Trunk muscle quality and quantity are associated with renal volume in nondiabetic people.

Background: Renal disease is a major problem in terms of community health and the economy. Skeletal muscle is involved in crosstalk with the kidney. We therefore investigated the relationship between muscle quality and quantity, and renal parenchymal volume (RPV). Methods: The association between the parameters of skeletal muscle and RPV/body surface area (BSA) was analyzed by computed tomography in 728 middle-aged participants without kidney disease or diabetes mellitus in a cross-sectional study. A retrospective cohort study of 68 participants was undertaken to analyze the association between changes in RPV/BSA and muscle parameters. Parameter change was calculated as follows: parameter at the follow-up examination/parameter at the baseline examination. The normal attenuation muscle (NAM) and low attenuation muscle (LAM) were identified by Hounsfield Unit thresholds of +30 to +150, and -29 to +29, respectively. Results: Positive correlations were found between estimated glomerular filtration rate and RPV/BSA (r = 0.451, P < .0001). Multiple regression analyses revealed that the NAM index was positively related to RPV/BSA (ß = 0.458, P < .0001), whereas the LAM index was negatively related to RPV/BSA (ß = -0.237, P < .0001). In this cohort study, a change in the LAM index was independently associated with a change in RPV/BSA (ß = -0.349, P = .0032). Conclusion: Both trunk muscle quantity and quality were associated with renal volume related to renal function in nondiabetic people. An increase in low quality muscle volume might be related to a decrease in renal volume.

Kidney shape statistical analysis: associations with disease and anthropometric factors.

BACKGROUND: Organ measurements derived from magnetic resonance imaging (MRI) have the potential to enhance our understanding of the precise phenotypic variations underlying many clinical conditions. METHODS: We applied morphometric methods to study the kidneys by constructing surface meshes from kidney segmentations from abdominal MRI data in 38,868 participants in the UK Biobank. Using mesh-based analysis techniques based on statistical parametric maps (SPMs), we were able to detect variations in specific regions of the kidney and associate those with anthropometric traits as well as disease states including chronic kidney disease (CKD), type-2 diabetes (T2D), and hypertension. Statistical shape analysis (SSA) based on principal component analysis was also used within the disease population and the principal component scores were used to assess the risk of disease events. RESULTS: We show that CKD, T2D and hypertension were associated with kidney shape. Age was associated with kidney shape consistently across disease groups. Body mass index (BMI) and waist-to-hip ratio (WHR) were also associated with kidney shape for the participants with T2D. Using SSA, we were able to capture kidney shape variations, relative to size, angle, straightness, width, length, and thickness of the kidneys, within disease populations. We identified significant associations between both left and right kidney length and width and incidence of CKD (hazard ratio (HR): 0.74, 95% CI: 0.61-0.90, p < 0.05, in the left kidney; HR: 0.76, 95% CI: 0.63-0.92, p < 0.05, in the right kidney) and hypertension (HR: 1.16, 95% CI: 1.03-1.29, p < 0.05, in the left kidney; HR: 0.87, 95% CI: 0.79-0.96, p < 0.05, in the right kidney). CONCLUSIONS: The results suggest that shape-based analysis of the kidneys can augment studies aiming at the better categorisation of pathologies associated with chronic kidney conditions.

Dapagliflozin administration for 1 year promoted kidney enlargement in patient with ADPKD.

To date, there is insufficient evidence regarding use of sodium-glucose cotransporter-2 (SGLT2) inhibitors for patients with autosomal-dominant polycystic kidney disease (ADPKD), as such cases have been excluded from previous clinical trials exploring the kidney protection effects of such medications. Here, findings of an ADPKD patient who received dapagliflozin, a selective SGLT2 inhibitor, for 1 year are presented. A 38-year-old woman with a family history of ADPKD wished for treatment with dapagliflozin. After starting administration at 10 mg/day, total kidney volume (TKV) continued to increase, from 1641 to 1764 mL after 84 days and then to 2297 mL after 340 days. The estimated glomerular filtration rate (eGFR) was also decreased from 67.3 to 56.2 mL/min/1.73 m2, and then to 51.4 mL/min/1.73 m2 at those times. Immediately after discontinuation of dapagliflozin, TKV and eGFR were slightly improved to 2263 mL and 55.1 mL/min/1.73 m2, respectively. Following a review of basic research studies, we consider that increased intratubular urinary osmotic pressure, compensatory glucose reabsorption by sodium-glucose cotransporter-1 in the late proximal tubule, and hypertrophy shown in collected cells caused by increased vasopressin may be associated with ADPKD disease progression. Caution may be needed when administering dapagliflozin to patients with ADPKD.

Higher beta-hydroxybutyrate ketone levels associated with a slower kidney function decline in ADPKD.

BACKGROUND AND HYPOTHESIS: Dysregulated energy metabolism is a recently discovered key feature of Autosomal Dominant Polycystic Kidney Disease (ADPKD). Cystic cells depend on glucose and are poorly able to use other energy sources such as ketone bodies. Raising ketone body concentration reduced disease progression in animal models of polycystic kidney diseases. Therefore, we hypothesized that higher endogenous plasma beta-hydroxybutyrate concentrations are associated with reduced disease progression in patients with ADPKD. METHODS: We analyzed data from 670 patients with ADPKD participating in the DIPAK cohort, a multi-center prospective observational cohort study. Beta-hydroxybutyrate was measured at baseline using nuclear magnetic resonance spectroscopy. Participants were excluded if they had type 2 diabetes, were using disease-modifying drugs (e.g. tolvaptan, somatostatin analogs), were not fasting, or had missing beta-hydroxybutyrate levels, leaving 521 participants for the analyses. Linear regression analyses were used to study cross-sectional associations and linear mixed-effect modeling for longitudinal associations. RESULTS: Of the participants, 61% were female, with an age of 47.3 ± 11.8 years, a height-adjusted total kidney volume (htTKV) of 834 (IQR 495-1327) ml/m, and an estimated glomerular filtration rate (eGFR) of 63.3 ± 28.9 mL/min/1.73m2. The median concentration of beta-hydroxybutyrate was 94 (IQR 68-147) µmol/L. Cross-sectionally, beta-hydroxybutyrate was neither associated with eGFR nor with htTKV. Longitudinally, beta-hydroxybutyrate was positively associated with eGFR slope (B = 0.35 ml/min/1.73m2 (95% CI 0.09 to 0.61), p = 0.007), but not with kidney growth. After adjustment for potential confounders, every doubling in beta-hydroxybutyrate concentration was associated with an improvement in the annual rate of eGFR by 0.33 ml/min/1.73m2 (95% CI 0.09 to 0.57, p = 0.008). CONCLUSION: These observational analyses support the hypothesis that interventions that raise beta-hydroxybutyrate concentration could reduce the rate of kidney function decline in patients with ADPKD.

Convolutional neural network-based kidney volume estimation from low-dose unenhanced computed tomography scans.

PURPOSE: Kidney volume is important in the management of renal diseases. Unfortunately, the currently available, semi-automated kidney volume determination is time-consuming and prone to errors. Recent advances in its automation are promising but mostly require contrast-enhanced computed tomography (CT) scans. This study aimed at establishing an automated estimation of kidney volume in non-contrast, low-dose CT scans of patients with suspected urolithiasis. METHODS: The kidney segmentation process was automated with 2D Convolutional Neural Network (CNN) models trained on manually segmented 2D transverse images extracted from low-dose, unenhanced CT scans of 210 patients. The models' segmentation accuracy was assessed using Dice Similarity Coefficient (DSC), for the overlap with manually-generated masks on a set of images not used in the training. Next, the models were applied to 22 previously unseen cases to segment kidney regions. The volume of each kidney was calculated from the product of voxel number and their volume in each segmented mask. Kidney volume results were then validated against results semi-automatically obtained by radiologists. RESULTS: The CNN-enabled kidney volume estimation took a mean of 32 s for both kidneys in a CT scan with an average of 1026 slices. The DSC was 0.91 and 0.86 and for left and right kidneys, respectively. Inter-rater variability had consistencies of ICC = 0.89 (right), 0.92 (left), and absolute agreements of ICC = 0.89 (right), 0.93 (left) between the CNN-enabled and semi-automated volume estimations. CONCLUSION: In our work, we demonstrated that CNN-enabled kidney volume estimation is feasible and highly reproducible in low-dose, non-enhanced CT scans. Automatic segmentation can thereby quantitatively enhance radiological reports.

Development of a multimodal kidney age prediction based on automatic segmentation CT image in patients with normal renal function.

Background: For decades, description of renal function has been of interest to clinicians and researchers. Serum creatinine (Scr) and estimated glomerular filtration rate (eGFR) are familiar but also limited in many circumstances. Meanwhile, the physiological volumes of the kidney cortex and medulla are presumed to change with age and have been proven to change with decreasing kidney function. Methods: We recruited 182 patients with normal Scr levels between October 2021 and February 2022 in Peking Union Medical College Hospital (PUMCH) with demographic and clinical data. A 3D U-Net architecture is used for both cortex and medullary separation, and volume calculation. In addition, we included patients with the same inclusion criteria but with diabetes (PUMCH-DM test set) and diabetic nephropathy (PUMCH-DN test set) for internal comparison to verify the possible clinical value of "kidney age" (K-AGE). Results: The PUMCH training set included 146 participants with a mean age of 47.5 ± 7.4 years and mean Scr 63.5 ± 12.3 µmol/L. The PUMCH test set included 36 participants with a mean age of 47.1 ± 7.9 years and mean Scr 66.9 ± 13.0 µmol/L. The multimodal method predicted K-AGE approximately close to the patient's actual physiological age, with 92% prediction within the 95% confidential interval. The mean absolute error increases with disease progression (PUMCH 5.00, PUMCH-DM 6.99, PUMCH-DN 9.32). Conclusion: We established a machine learning model for predicting the K-AGE, which offered the possibility of evaluating the whole kidney health in normal kidney aging and in disease conditions.

[Effect of a simple kidney cyst on renal function].

INTRODUCTION: Renal cysts are a common disease that occurs at a rate of 7-10%. Currently there are no clinical recommendations for the treatment of patients with simple renal cysts. In the current literature there is some evidence that a simple renal cyst has negative effects on renal function. Decreased renal function occurs due to partial atrophy and loss of the renal parenchyma (in the "crater" area at the base of the cyst) caused by compression. Therefore, the efforts to analyze the effect of simple kidney cysts on kidney function and identify the characteristics of the cyst that affect renal function to determine the indications for surgical treatment remains a substantial task. The aim of the study was to analyze the effect of simple renal cysts on renal function, to investigate the relationship between cyst size, atrophied parenchyma volume, and renal function, and to determine indications for surgical treatment of simple renal cysts. MATERIALS AND METHODS: We conducted a prospective cohort study. The study included 109 patients with simple renal cysts. Patients with a solitary cyst of the right or left renal kidney, grade I-II according to Bosniak classification, were included in the study. The estimated glomerular filtration rate (eGFR) of the patients was calculated using various formulas. A contrast CT scan of the urinary tract was also performed to determine the maximum size of the cyst, calculate the volume of the renal parenchyma, and the volume of the lost (atrophied) parenchyma. Patients underwent renal scintigraphy with calculation of total GFR and split renal function. We analyzed the symmetry of the function of both kidneys by comparing the GFR of the affected and healthy kidneys, analyzed the relationship between the presence of a kidney cyst and a decrease in GFR, between the maximum size of a renal cyst and a decrease in its function compared with that of a healthy kidney. We also analyzed the correspondence of total GFR values obtained in renal scintigraphy and GFR values calculated according to the formulas. RESULTS: Data from 109 patients were available for analysis; the mean blood creatinine was 87.4 mol/L. The median maximum cyst size was 80 mm. The median baseline volume of the affected kidney parenchyma was 174 ml, the median volume of the lost parenchyma was 49 ml, and the median proportion of the lost parenchyma was 28%. The median total GFR was 77.07 ml/min. The median GFR of the healthy kidney was 45.49 mL/min, and the median GFR of the kidney affected by the cyst was 34.46 mL/min. The median difference in GFR of the healthy and affected kidney units was 11 mL/min and was statistically significant. Comparison of the eGFR values obtained by the formulas with the reference values of GFR obtained by scintigraphy showed that the Cockcroft-Gault formula with standardization on the body surface area calculated closest eGFR values to the reference ones. Correlation analysis revealed a statistically significant association between the proportion of lost parenchyma volume and the maximum cyst size: =0.37 with 95% CI [0.20; 0.52] (p-value = 0). A multivariate logistic regression model revealed that a statistically significant factor influencing the probability of a significant decrease in GFR was the percent of lost renal parenchyma volume (OR=1,13; =0). CONCLUSIONS: Our study showed that growth of renal cysts associated with renal parenchyma atrophy and decrease of GFR of the affected kidney. An increase in the volume of atrophied parenchyma leads to the decrease in GFR of the affected kidney. The obtained data suggest that performing dynamic renal scintigraphy to assess the decrease in affected renal function and determine the indications for surgical treatment of renal cysts is a reasonable recommendation. According to the results of the study, the loss of 20% of the renal parenchyma can be considered an indication for renal scintigraphy. The Cockcroft-Gault formula with standardization on the body surface area allows to calculate closest GFR values to those obtained by scintigraphy and, therefore, can be recommended as the optimal formula for calculating eGFR in daily clinical practice.