Automatic semantic segmentation of kidney cysts in MR images of patients affected by autosomal-dominant polycystic kidney disease.

PURPOSE: For patients affected by autosomal-dominant polycystic kidney disease (ADPKD), successful differentiation of cysts is useful for automatic classification of patient phenotypes, clinical decision-making, and disease progression. The objective was to develop and evaluate a fully automated semantic segmentation method to differentiate and analyze renal cysts in patients with ADPKD. METHODS: An automated deep learning approach using a convolutional neural network was trained, validated, and tested on a set of 60 MR T2-weighted images. A three-fold cross-validation approach was used to train three models on distinct training and validation sets (n = 40). An ensemble model was then built and tested on the hold out cases (n = 20), with each of the cases compared to manual segmentations performed by two readers. Segmentation agreement between readers and the automated method was assessed. RESULTS: The automated approach was found to perform at the level of interobserver variability. The automated approach had a Dice coefficient (mean ± standard deviation) of 0.86 ± 0.10 vs Reader-1 and 0.84 ± 0.11 vs. Reader-2. Interobserver Dice was 0.86 ± 0.08. In terms of total cyst volume (TCV), the automated approach had a percent difference of 3.9 ± 19.1% vs Reader-1 and 8.0 ± 24.1% vs Reader-2, whereas interobserver variability was - 2.0 ± 16.4%. CONCLUSION: This study developed and validated a fully automated approach for performing semantic segmentation of kidney cysts in MR images of patients affected by ADPKD. This approach will be useful for exploring additional imaging biomarkers of ADPKD and automatically classifying phenotypes.

Long-Term Administration of Tolvaptan in Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND AND OBJECTIVES: In the 3-year Tolvaptan Efficacy and Safety in Management of ADPKD and Its Outcomes (TEMPO) 3:4 and 1-year Replicating Evidence of Preserved Renal Function: an Investigation of Tolvaptan Safety and Efficacy in ADPKD (REPRISE) trials, tolvaptan slowed the decline of eGFR in patients with autosomal dominant polycystic kidney disease at early and later stages of CKD, respectively. Our objective was to ascertain whether the reduction associated with the administration of tolvaptan is sustained, cumulative, and likely to delay the need for kidney replacement therapy. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: One hundred and twenty-eight patients with autosomal dominant polycystic kidney disease participated in clinical trials of tolvaptan at the Mayo Clinic. All had the opportunity to enroll into open-label extension studies. Twenty participated in short-term studies or received placebo only. The remaining 108 were analyzed for safety. Ninety seven patients treated with tolvaptan for ≥1 year (mean±SD, 4.6±2.8; range, 1.1-11.2) were analyzed for efficacy using three approaches: (1) comparison of eGFR slopes and outcome (33% reduction from baseline eGFR) to controls matched by sex, age, and baseline eGFR; (2) Stability of eGFR slopes with duration of follow-up; and (3) comparison of observed and predicted eGFRs at last follow-up. RESULTS: Patients treated with tolvaptan had lower eGFR slopes from baseline (mean±SD, -2.20±2.18 ml/min per 1.73 m2 per year) and from month 1 (mean±SD, -1.97±2.44 ml/min per 1.73 m2 per year) compared with controls (mean±SD, -3.50±2.09 ml/min per 1.73 m2 per year; P<0.001), and lower risk of a 33% reduction in eGFR (risk ratio, 0.63; 95% confidence interval, 0.38 to 0.98 from baseline; risk ratio, 0.53; 95% confidence interval, 0.31 to 0.85 from month 1). Annualized eGFR slopes of patients treated with tolvaptan did not change during follow-up and differences between observed and predicted eGFRs at last follow-up increased with duration of treatment. CONCLUSIONS: Follow-up for up to 11.2 years (average 4.6 years) showed a sustained reduction in the annual rate of eGFR decline in patients treated with tolvaptan compared with controls and an increasing separation of eGFR values over time between the two groups.

Getting what you want: How fit between desired and received leader sensitivity influences emotion and counterproductive work behavior.

We challenge the intuitive belief that greater leader sensitivity is always associated with desirable outcomes for employees and organizations. Specifically, we argue that followers' idiosyncratic desires for, and perceptions of, leader sensitivity behaviors play a key role in how followers react to their leader's sensitivity. Moreover, these resulting affective experiences are likely to have important consequences for organizations, specifically as they relate to employee counterproductive work behavior (CWB). Drawing from supplies-values (S-V) fit theory and the stressor-emotion model of CWB, the current study focuses on the affective and behavioral consequences of fit between subordinates' ideal leader sensitivity behavior preferences and subordinates' perceptions of their actual leader's sensitivity behaviors. Polynomial regression analyses reveal that congruence between ideal and actual leader sensitivity influences employee negative affect and, consequently, engagement in counterproductive work behavior. (PsycINFO Database Record