Symptomatic urinary stone disease affects approximately 900,000 persons in the United States each year, resulting in an estimated annual medical cost of $4.5 billion. Computed tomography (CT) is the established method for imaging urinary calculi and can provide accurate sub-millimeter details of the size and location of renal stones. However, a complete characterization of renal stones, which includes stone composition and fragility, is critically needed for safe and cost effective management of stone disease, as well as for phenotyping of research subjects. Our long term goal is to use advanced CT methodologies to fully characterize urinary calculi, and to use evolving technology to reliably detect stone precursor lesions. Our objectives in this application are to develop a comprehensive, low-dose, stone-characterization exam using commercially-available dual-energy CT technology, and to detect stone precursor lesions using a prototype CT system equipped with energy resolving detectors. Based on our extensive preliminary results, we know that dual-energy CT can discriminate between several types of renal stones and provide accurate quantification of stone morphology. Our central hypothesis is that this quantitative information can be acquired at reduced dose levels and used to predict stone fragility, which we define as the likelihood of a stone to be broken by SWL or endoscopic methods. We further hypothesize that use of pre-clinical, 225-micron, energy-resolving CT detectors will allow detection of stone precursor lesions such as Randall's plaques, as well as the presence of trace elements having a suspected role in stone formation, such as zinc. We will accomplish these objectives through two specific aims: 1) Aim 1: Develop and validate a comprehensive low-dose stone-characterization exam using clinical dual-energy CT techniques. 2) Aim 2: Develop a pre-clinical spectral CT imaging technique that can detect precursor lesions and trace elements related to the formation of kidney stones.

Public Health Relevance

This proposal will develop imaging techniques that can determine urinary stone type and fragility in patients. The significance of this is that these advanced CT imaging techniques will allow physicians to more efficiently direct patient therapy and perform clinical research, potentially avoiding procedures associated with higher risk or cost.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54DK100227-02
Application #
8734909
Study Section
Special Emphasis Panel (ZDK1-GRB-9)
Project Start
Project End
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
2
Fiscal Year
2014
Total Cost
$157,523
Indirect Cost
$46,069
Name
Mayo Clinic, Rochester
Department
Type
DUNS #
006471700
City
Rochester
State
MN
Country
United States
Zip Code
55905
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Perinpam, Majuran; Enders, Felicity T; Mara, Kristin C et al. (2017) Plasma oxalate in relation to eGFR in patients with primary hyperoxaluria, enteric hyperoxaluria and urinary stone disease. Clin Biochem 50:1014-1019
Rossano, Adam J; Romero, Michael F (2017) Optical Quantification of Intracellular pH in Drosophila melanogaster Malpighian Tubule Epithelia with a Fluorescent Genetically-encoded pH Indicator. J Vis Exp :
Lieske, John C (2017) Probiotics for prevention of urinary stones. Ann Transl Med 5:29
Ferrero, Andrea; Chen, Baiyu; Li, Zhoubo et al. (2017) Technical Note: Insertion of digital lesions in the projection domain for dual-source, dual-energy CT. Med Phys 44:1655-1660
Pottel, Hans; Dubourg, Laurence; Schaeffner, Elke et al. (2017) Data on the relation between renal biomarkers and measured glomerular filtration rate. Data Brief 14:763-772
Kittanamongkolchai, Wonngarm; Mara, Kristin C; Mehta, Ramila A et al. (2017) Risk of Hypertension among First-Time Symptomatic Kidney Stone Formers. Clin J Am Soc Nephrol 12:476-482
Gutjahr, R; Polster, C; Henning, A et al. (2017) Dual Energy CT Kidney Stone Differentiation in Photon Counting Computed Tomography. Proc SPIE Int Soc Opt Eng 10132:
Canales, Benjamin K; Smith, Jennifer A; Weiner, I David et al. (2017) Polymorphisms in Renal Ammonia Metabolism Genes Correlate With 24-Hour Urine pH. Kidney Int Rep 2:1111-1121

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