Utility of new image-derived biomarkers for autosomal dominant polycystic kidney disease prognosis using automated instance cyst segmentation.

Autor:	Gregory AV; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA., Chebib FT; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA., Poudyal B; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA., Holmes HL; Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA., Yu ASL; Jared Grantham Kidney Institute, Kansas University Medical Center, Kansas City, Kansas, USA; Division of Nephrology and Hypertension, Kansas University Medical Center, Kansas City, Kansas, USA., Landsittel DP; Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA., Bae KT; Department of Diagnostic Radiology, University of Hong Kong, Hong Kong., Chapman AB; Division of Nephrology, University of Chicago School of Medicine, Chicago, Illinois, USA., Frederic RO; Division of Renal Medicine, Emory University School of Medicine, Atlanta, Georgia, USA., Mrug M; Division of Nephrology, University of Alabama and the Department of Veterans Affairs Medical Center, Birmingham, Alabama, USA., Bennett WM; Legacy Transplant Services, Legacy Good Samaritan Hospital, Portland, Oregon, USA., Harris PC; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA., Erickson BJ; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA., Torres VE; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA., Kline TL; Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA. Electronic address: kline.timothy@mayo.edu.
Jazyk:	angličtina
Zdroj:	Kidney international [Kidney Int] 2023 Aug; Vol. 104 (2), pp. 334-342. Date of Electronic Publication: 2023 Feb 01.
DOI:	10.1016/j.kint.2023.01.010
Abstrakt:	New image-derived biomarkers for patients affected by autosomal dominant polycystic kidney disease are needed to improve current clinical management. The measurement of total kidney volume (TKV) provides critical information for clinicians to drive care decisions. However, patients with similar TKV may present with very different phenotypes, often requiring subjective decisions based on other factors (e.g., appearance of healthy kidney parenchyma, a few cysts contributing significantly to overall TKV, etc.). In this study, we describe a new technique to individually segment cysts and quantify biometric parameters including cyst volume, cyst number, parenchyma volume, and cyst parenchyma surface area. Using data from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) study the utility of these new parameters was explored, both quantitatively as well as visually. Total cyst number and cyst parenchyma surface area showed superior prediction of the slope of estimated glomerular filtration rate decline, kidney failure and chronic kidney disease stages 3A, 3B, and 4, compared to TKV. In addition, presentations such as a few large cysts contributing significantly to overall kidney volume were shown to be much better stratified in terms of outcome predictions. Thus, these new image biomarkers, which can be obtained automatically, will have great utility in future studies and clinical care for patients affected by autosomal dominant polycystic kidney disease. (Copyright © 2023 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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