Novel methodology to evaluate renal cysts in polycystic kidney disease

Abdominal Imaging in ADPKD: Beyond Total Kidney Volume

In the context of autosomal dominant polycystic kidney disease (ADPKD), measurement of the total kidney volume (TKV) is crucial. It acts as a marker for tracking disease progression, and evaluating the effectiveness of treatment strategies. The TKV has also been recognized as an enrichment biomarker and a possible surrogate endpoint in clinical trials. Several imaging modalities and methods are available to calculate the TKV, and the choice depends on the purpose of use. Technological advancements have made it possible to accurately assess the cyst burden, which can be crucial to assessing the disease state and helping to identify rapid progressors. Moreover, the development of automated algorithms has increased the efficiency of total kidney and cyst volume measurements. Beyond these measurements, the quantification and characterization of non-cystic kidney tissue shows potential for stratifying ADPKD patients early on, monitoring disease progression, and possibly predicting renal function loss. A broad spectrum of radiological imaging techniques are available to characterize the kidney tissue, showing promise when it comes to non-invasively picking up the early signs of ADPKD progression. Radiomics have been used to extract textural features from ADPKD images, providing valuable information about the heterogeneity of the cystic and non-cystic components. This review provides an overview of ADPKD imaging biomarkers, focusing on the quantification methods, potential, and necessary steps toward a successful translation to clinical practice.

Consensus document on autosomal dominant polycystic kindey disease from the Spanish Working Group on Inherited Kindey Diseases. Review 2020

Autosomal dominant polycystic kidney disease (ADPKD) is the most frequent cause of genetic renal disease and accounts for 6-10% of patients on kidney replacement therapy (KRT). Very few prospective, randomized trials or clinical studies address the diagnosis and management of this relatively frequent disorder. No clinical guidelines are available to date. This is a revised consensus statement from the previous 2014 version, presenting the recommendations of the Spanish Working Group on Inherited Kidney Diseases, which were agreed to following a literature search and discussions. Levels of evidence mostly are C and D according to the Centre for Evidence-Based Medicine (University of Oxford). The recommendations relate to, among other topics, the use of imaging and genetic diagnosis, management of hypertension, pain, cyst infections and bleeding, extra-renal involvement including polycystic liver disease and cranial aneurysms, management of chronic kidney disease (CKD) and KRT and management of children with ADPKD. Recommendations on specific ADPKD therapies are provided as well as the recommendation to assess rapid progression.

Retarding Progression of Chronic Kidney Disease in Autosomal Dominant Polycystic Kidney Disease with Metformin and Other Therapies: An Update of New Insights

Autosomal dominant polycystic kidney disease (ADPKD) is the most frequent single-gene disorder leading to renal failure. Current therapies are aimed to treat renal and extrarenal complications of ADPKD, but improved knowledge of the pathophysiological mechanisms leading to the generation and growth of cysts has permitted the identification of new drug candidates for clinical trials. Among these, in this review, we will examine above all the role of metformin, hypothesized to be able to activate the AMP-activated protein kinase (AMPK) pathway and potentially modulate some mechanisms implicated in the onset and the growth of the cysts.

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.

Comparison of MRI segmentation techniques for measuring liver cyst volumes in autosomal dominant polycystic kidney disease

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.

Autosomal dominant polycystic kidney disease: recent advances in clinical management

The first clinical descriptions of autosomal dominant polycystic kidney disease (ADPKD) go back at least 500 years to the late 16 (th) century. Advances in understanding disease presentation and pathophysiology have mirrored the progress of clinical medicine in anatomy, pathology, physiology, cell biology, and genetics. The identification of PKD1 and PKD2, the major genes mutated in ADPKD, has stimulated major advances, which in turn have led to the first approved drug for this disorder and a fresh reassessment of patient management in the 21 (st) century. In this commentary, we consider how clinical management is likely to change in the coming decade.

Risk factors for progression in ADPKD

PURPOSE OF REVIEW

Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease. This article will describe the factors associated with both functional and structural evidence of disease progression. It will also review the results of recent clinical trials that have shown an impact on markers of disease progression.

RECENT FINDINGS

A variety of prognostic factors have been described that relate to a decline in glomerular filtration rate or an increase in total cyst or kidney volumes. We now have clinical trials that show that glomerular filtration rate decline and kidney volume growth can be slowed in those with ADPKD.

SUMMARY

With the emergence of potential disease-modifying therapies, factors that can accurately identify those who are most at risk for renal progression or ADPKD-related complications need to be identified and validated.