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Comparison of Mathematic Models for Assessment of Glomerular Filtration Rate with Electron-Beam CT in Pigs¹

¹ From the Division of Nephrology and Hypertension (E.D., J.D.K., L.O.L.) and Department of Physiology and Biomedical Engineering (L.J., J.A.H., J.C.R.), Mayo Clinic College of Medicine, 200 First St SW, Rochester, MN 55905. Received December 30, 2005; revision requested February 24, 2006; revision received March 24; accepted May 2; final version accepted July 6. Supported in part by National Institutes of Health grant nos. HL63282, DK73608, and HL77131, the Mayo Foundation, the Société de Néphrologie, Philippe Foundation and Hospices Civils de Lyon, and Università degli Studi di Pisa. Address correspondence to L.O.L. (e-mail: lerman.lilach{at}mayo.edu).

Purpose: To prospectively compare in pigs three mathematic models for assessment of glomerular filtration rate (GFR) on electron-beam (EB) computed tomographic (CT) images, with concurrent inulin clearance serving as the reference standard.

Materials and Methods: This study was approved by the institutional animal care and use committee. Inulin clearance was measured in nine pigs (18 kidneys) and compared with single-kidney GFR assessed from renal time-attenuation curves (TACs) obtained with EB CT before and after infusion of the vasodilator acetylcholine. CT-derived GFR was calculated with the original and modified Patlak methods and with previously validated extended gamma variate modeling of first-pass cortical TACs. Statistical analysis was performed to assess correlation between CT methods and inulin clearance for estimation of GFR with least-squares regression analysis and Bland-Altman graphical representation. Comparisons within groups were performed with a paired t test.

Results: GFR assessed with the original Patlak method indicated poor correlation with inulin clearance, whereas GFR assessed with the modified Patlak method (P < .001, r = 0.75) and with gamma variate modeling (P < .001, r = 0.79) correlated significantly with inulin clearance and indicated an increase in response to acetylcholine.

Conclusion: CT-derived estimates of GFR can be significantly improved by modifications in image analysis methods (eg, use of a cortical region of interest).

© RSNA, 2007

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