Supervised segmentation of polycystic kidneys: a new application for stereology data

Standardizing total kidney volume measurements for clinical trials of autosomal dominant polycystic kidney disease

Background

The ability of unstandardized methods to track kidney growth in clinical trials for autosomal dominant polycystic kidney disease (ADPKD) has not been critically evaluated.

Methods

The Tolvaptan Efficacy and Safety Management of ADPKD and its Outcomes (TEMPO) 3:4 study involved baseline and annual magnetic resonance follow-up imaging yearly for 3 years. Total kidney volume (TKV) measurements were performed on these four time points in addition to the baseline imaging in TEMPO 4:4, initially by Perceptive Informatics (Waltham, MA, USA) using planimetry (original dataset) and for this study by the Mayo Translational PKD Center using semiautomated and complementary automated methods (sequential dataset). In the original dataset, the same reader was assigned to all scans of individual patients in TEMPO 3:4, but readers were reassigned in TEMPO 4:4. Two placebo-treated cohorts were included. In the first (n = 158), intervals between the end of TEMPO 3:4 and the start of TEMPO 4:4 scan visits ranged from 12 to 403 days; in the second (n = 95), the same scan (measured twice) visit was used for both.

Results

Growth rates in TEMPO 3:4 were similar in the original and sequential datasets (5.5 and 5.9%/year). Growth rates during the TEMPO 3:4 to TEMPO 4:4 interval were higher in the original (13.7%/year) but were not different in the sequential dataset (4.0%/year). Comparing volumes from the same images, TKVs showed a bias of 2.2% [95% confidence interval (CI) −5.2–9.7] in the original and −0.16% (95% CI −1.91–1.58) in the sequential dataset.

Conclusions

Despite using the same software, TKV and growth rate changes were present, likely due to reader differences in the transition from TEMPO 3:4 to TEMPO 4:4 in the original but not in the sequential dataset. Robust, standardized methods are essential in ADPKD trials to minimize errors in serial TKV measurements.

Automatic Segmentation of Kidneys using Deep Learning for Total Kidney Volume Quantification in Autosomal Dominant Polycystic Kidney Disease

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is the most common inherited disorder of the kidneys. It is characterized by enlargement of the kidneys caused by progressive development of renal cysts, and thus assessment of total kidney volume (TKV) is crucial for studying disease progression in ADPKD. However, automatic segmentation of polycystic kidneys is a challenging task due to severe alteration in the morphology caused by non-uniform cyst formation and presence of adjacent liver cysts. In this study, an automated segmentation method based on deep learning has been proposed for TKV computation on computed tomography (CT) dataset of ADPKD patients exhibiting mild to moderate or severe renal insufficiency. The proposed method has been trained (n = 165) and tested (n = 79) on a wide range of TKV (321.2-14,670.7 mL) achieving an overall mean Dice Similarity Coefficient of 0.86 ± 0.07 (mean ± SD) between automated and manual segmentations from clinical experts and a mean correlation coefficient (ρ) of 0.98 (p < 0.001) for segmented kidney volume measurements in the entire test set. Our method facilitates fast and reproducible measurements of kidney volumes in agreement with manual segmentations from clinical experts.

Impact of liver volume on polycystic liver disease-related symptoms and quality of life

Background

Symptoms in polycystic liver disease (PLD) are thought to be caused by compression of organs and structures by the enlarged liver.

Aim

The aim of this article is to assess the impact of liver volume on symptoms and quality of life (QoL) in PLD.

Methods

We included PLD patients from two prospective studies that used the PLD-questionnaire (PLD-Q) for symptom assessment. QoL was assessed through SF-36, summarized in a physical (PCS) and mental (MCS) component score. Liver volume was correlated with PLD-Q total scores. Patients were classified based on height-corrected liver volume in mild (<1600 ml), moderate (1600–3200 ml), and severe (>3200 ml) disease. PLD-Q and QoL (PCS and MCS) scores were compared across disease stages.

Results

We included 82 of 131 patients from the original studies (disease stages; mild n = 26, moderate n = 33, and severe n = 23). Patients with larger liver volume reported higher symptom burden (r = 0.516, p < 0.001). Symptom scores increased with disease progression, except for abdominal pain (p = 0.088). PCS decreased with advancing disease (p < 0.001), in contrast to MCS (p = 0.055). Moderate (p = 0.007) and severe (p < 0.001) PLD patients had lower PCS scores than the general population.

Conclusion

PLD with larger liver volume is more likely to be symptomatic and is associated with lower QoL.

Development and Validation of a Disease-Specific Questionnaire to Assess Patient-Reported Symptoms in Polycystic Liver Disease

Treatment of polycystic liver disease (PLD) focuses on symptom improvement. Generic questionnaires lack sensitivity to capture PLD-related symptoms, a prerequisite to determine effectiveness of therapy. We developed and validated a disease-specific questionnaire that assesses symptoms in PLD (PLD-Q). We identified 16 PLD-related symptoms (total score 0-100 points) by literature review and interviews with patients and clinicians. The developed PLD-Q was validated in Dutch (n = 200) and United States (US; n = 203) PLD patients. We assessed the correlation of PLD-Q total score with European Organization for Research and Treatment of Cancer (EORTC) symptom scale, global health visual analogue scale (VAS) of EQ-5D, and liver volume. To test discriminative validity, we compared PLD-Q total scores of patients with different PLD severity stages (Gigot classification) and PLD-Q total scores of PLD patients with general controls and polycystic kidney disease patients without PLD. Reproducibility was tested by comparing original test scores with 2-week retest scores. In total, 167 Dutch and 124 US patients returned the questionnaire. Correlation between PLD-Q total score and EORTC symptom scale (The Netherlands [NL], r = 0.788; US, r = 0.811) and global health VAS (NL, r = -0.517; US, r = -0.593) was good. There was no correlation of PLD-Q total score with liver volume (NL, r = 0.138; P = 0.236; US, r = 0.254; P = 0.052). Gigot type III individuals scored numerically higher than type II patients (NL, 46 vs. 40; P = 0.089; US, 48 vs. 36; P = 0.055). PLD patients scored higher on the PLD-Q total score than general controls (NL, 42 vs. 17; US, 40 vs. 13 points) and polycystic kidney disease patients without PLD (22 points). Reproducibility of PLD-Q was excellent (NL, r = 0.94; US, 0.96).

CONCLUSION

PLD-Q is a valid, reproducible, and sensitive disease-specific questionnaire that can be used to assess PLD-related symptoms in clinical care and future research. (Hepatology 2016;64:151-160).

Semiautomated Segmentation of Polycystic Kidneys in T2-Weighted MR Images

OBJECTIVE

The objective of the present study is to develop and validate a fast, accurate, and reproducible method that will increase and improve institutional measurement of total kidney volume and thereby avoid the higher costs, increased operator processing time, and inherent subjectivity associated with manual contour tracing.

MATERIALS AND METHODS

We developed a semiautomated segmentation approach, known as the minimal interaction rapid organ segmentation (MIROS) method, which results in human interaction during measurement of total kidney volume on MR images being reduced to a few minutes. This software tool automatically steps through slices and requires rough definition of kidney boundaries supplied by the user. The approach was verified on T2-weighted MR images of 40 patients with autosomal dominant polycystic kidney disease of varying degrees of severity.

RESULTS

The MIROS approach required less than 5 minutes of user interaction in all cases. When compared with the ground-truth reference standard, MIROS showed no significant bias and had low variability (mean ± 2 SD, 0.19% ± 6.96%).

CONCLUSION

The MIROS method will greatly facilitate future research studies in which accurate and reproducible measurements of cystic organ volumes are needed.

Utilizing magnetization transfer imaging to investigate tissue remodeling in a murine model of autosomal dominant polycystic kidney disease

Purpose

Noninvasive imaging techniques that quantify renal tissue composition are needed to more accurately ascertain prognosis and monitor disease progression in polycystic kidney disease (PKD). Given the success of magnetization transfer (MT) imaging to characterize various tissue remodeling pathologies, it was tested on a murine model of autosomal dominant PKD.

Methods

C57Bl/6 Pkd1 R3277C mice at 9, 12, and 15 months were imaged with a 16.4T MR imaging system. Images were acquired without and with RF saturation in order to calculate MT ratio (MTR) maps. Following imaging, the mice were euthanized and kidney sections were analyzed for cystic and fibrotic indices, which were compared with statistical parameters of the MTR maps.

Results

The MTR‐derived mean, median, 25th percentile, skewness, and kurtosis were all closely related to indices of renal pathology, including kidney weight/body weight, cystic index, and percent of remaining parenchyma. The correlation between MTR and histology‐derived cystic and fibrotic changes was R² = 0.84 and R² = 0.70, respectively.

Conclusion

MT imaging provides a new, noninvasive means of measuring tissue remodeling PKD changes and may be better suited for characterizing renal impairment compared with conventional MR techniques. Magn Reson Med 75:1466–1473, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance.