GFR model aids kidney donor assessment

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Although measured glomerular filtration rate (GFR) is the best overall index of renal function, determining this measurement can be both costly and time consuming. A technique employing advanced visualization technology holds promise for both a quicker and lower-cost method of estimating GFR, according to research published this month in Radiology.

“Inulin clearance is the reference standard for measured GFR, but urinary clearance of a radiotracer-labeled compound is a commonly used alternative,” wrote the authors of a study conducted at Ohio’s Cleveland Clinic. “However, these tests are costly, time consuming, and not widely available and, thus, are less than ideal for routine clinical care.”

Automated segmentation algorithm includes entire kidney on basis of Hounsfield unit attenuation, including the central sinus fat but excluding perinephric fat. Volume is demarcated by a thin line (short arrow) and volume measurement is shown on image (long arrow).Image and caption courtesy of the Radiological Society of North America.

Researchers from the departments of quantitative health sciences and the Glickman Urological and Kidney Institute at the facility created a model to estimate GFR in healthy individuals, such as renal transplant donors, by using renal volume measurements derived from CT scans, serum creatinine level, height, weight, race, and age. This performance of this kidney volume-based model was then compared with the modification of diet in renal disease (MDRD) equation.

Age, sex, height, weight, race, serum creatinine level, and measured GFR were recorded from 244 individuals who underwent renal donor evaluation over a two-year period. An automated segmentation algorithm was used to measure renal parenchymal volume from CT images.

Donor renal volumes were measured by using preoperative CT scans obtained with 16- or 64-section helical CT scanners (Sensation 16 and 64, Siemens Healthcare). GFR was measured by using urinary clearance of iodine 125 (I125) iothalamate.

“Estimates of renal parenchymal volume can now be ascertained easily from cross-sectional imaging studies, either by using a simple calculation with the prolate ellipse formula or, more precisely, by using area tracings from axial sections and calculating volume according to section thickness,” the authors noted.

The researchers utilized an automated segmentation algorithm (Oncology, Siemens) to measure the renal parenchymal volume from unenhanced 1-mm images reconstructed
at 0.8-mm intervals.

“To develop a new model to estimate GFR, we used analysis of covariance to model GFR as a function of both continuous (age, serum creatinine level, height, weight, and renal volume) and categorical (race and sex) predictors and multiple linear regression analysis to model GFR as a function of continuous predictors only,” the authors wrote.

The multiple linear regression equation was fit by using their sample of 244 patients, modeling the unadjusted GFR as the reference standard. The model was externally validated and compared with the performance of the MDRD equation as well as I125-iothalamate exams.

“Correlation between renal volume-based GFR and GFR measured by using 125I-iothalamate clearance was +0.42,” the authors reported. “The model outperformed the MDRD equation in six of six measurements.”

The results are encouraging and show promise for application in clinical practice, according to the researchers.

Our renal volume-based model can be used to estimate renal donor GFR by using image data from CT scans that are obtained routinely as part of the anatomic evaluation of renal donors at no additional risk to the patient,” they wrote. “This renal volume-based model outperformed the MDRD equation in estimating renal donor GFR and could replace measurement of GFR by using 125I-iothalamate clearance or limit the need to measure GFR in this group of individuals.”