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Evaluation of advanced imaging biomarkers at kidney failure in patients with ADPKD: a pilot study.

AbstractBackground:
Autosomal dominant polycystic kidney disease (ADPKD) presents with variable disease severity and progression. Advanced imaging biomarkers may provide insights into cystic and non-cystic processes leading to kidney failure in different age groups.
Methods:
This pilot study included 39 ADPKD patients with kidney failure, stratified into three age groups (<46, 46-56, >56 years old). Advanced imaging biomarkers were assessed using an automated instance cyst segmentation tool. The biomarkers were compared with an age- and sex-matched ADPKD cohort in early chronic kidney disease (CKD).
Results:
Ht-total parenchymal volume correlated negatively with age at kidney failure. The median Ht-total parenchymal volume was significantly lower in patients older than 56 years. Cystic burden was significantly higher at time of kidney failure, especially in patients who reached it before age 46 years. The cyst index at kidney failure was comparable across age groups and Mayo Imaging Classes. Advanced imaging biomarkers showed higher correlation with Ht-total kidney volume in early CKD than at kidney failure. Cyst index and parenchymal index were relatively stable over 5 years prior to kidney failure, whereas Ht-total cyst volume and cyst parenchymal surface area increased significantly.
Conclusion:
Age-related differences in advanced imaging biomarkers suggest variable pathophysiological mechanisms in ADPKD patients with kidney failure. Further studies are needed to validate the utility of these biomarkers in predicting disease progression and guiding treatment strategies.
AuthorsStijn Wigerinck, Adriana V Gregory, Byron H Smith, Ioan-Andrei Iliuta, Christian Hanna, Maroun Chedid, Hasan-Daniel N Kaidbay, Sarah R Senum, Shebaz Shukoor, Peter C Harris, Vicente E Torres, Timothy L Kline, Fouad T Chebib
JournalClinical kidney journal (Clin Kidney J) Vol. 16 Issue 10 Pg. 1691-1700 (Oct 2023) ISSN: 2048-8505 [Print] England
PMID37779848 (Publication Type: Journal Article)
Copyright© The Author(s) 2023. Published by Oxford University Press on behalf of the ERA.

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