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Science to Practice |
Department of Radiology, Stanford University Medical Center,
300 Pasteur Dr, H-1307,
Stanford, CA 94305-5105,
gsommer@stanford.edu
SUMMARY
Daghini et al used a pig model to estimate single-kidney GFR with dynamic contrast-enhanced CT scanning. Three techniques were evaluated, two of which (the modified Patlak method and the gamma variate model) yielded GFR estimates that correlated significantly with determinations made by using standard inulin clearance techniques. The findings hold promise that noninvasive in vivo assessment of single-kidney renal function may be achieved in patients.
THE SETTING
Advances in computed tomographic (CT) technology have been used in renal imaging applications, which have proved excellent for the depiction of renal calculi, detection of renal colic, and overall imaging of the kidneys and genitourinary tract with CT urography and renal CT angiography. More recently, dynamic renal contrast material enhancement has been assessed (1–4) to determine if complementary renal functional information might also be determined with CT. Such studies have generally used specific models of dynamic renal enhancement to extract renal functional parameters, such as glomerular filtration rate (GFR). In this issue of Radiology, Daghini et al (1) report on the estimation of single-kidney GFR with dynamic contrast-enhanced CT.
THE SCIENCE
While there has been interest in dynamic renal CT contrast enhancement for years, more recent developments in CT technology—including spiral, multidetector, and electron-beam CT—have made the acquisition of high-temporal-resolution data more practical. In the study by Daghini et al (1), time-attenuation curve data for dynamic electron-beam CT were evaluated in a pig model. Estimates of single-kidney GFR and overall GFR for each animal were obtained with three modeling techniques for contrast enhancement in the kidney. The first two techniques (original Patlak and modified Patlak methods) used the Patlak method, which assumes that the rate of accumulation of an indicator, such as a CT contrast agent, is at least temporarily trapped in a tissue, such as renal tissue. The third technique (extended gamma variate modeling) required a somewhat longer time for acquisition of CT data than did the techniques that used the Patlak method. The modified Patlak method, in which regions of interest were measured only over the renal cortex, and the gamma variate model yielded overall GFR estimates that correlated significantly with GFR as determined with a standard inulin clearance technique.
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Clinical use:
It is easy to imagine the integration of CT image acquisition and analysis techniques that are capable of providing useful renal functional information into contrast-enhanced CT examinations of the kidney. Examples of such useful integration might involve the assessment of single-kidney renal function as part of a CT angiographic examination, since several authors (5) have suggested that kidneys that have only a moderate decrease in renal function are those that are most likely to benefit from revascularization. With renal obstruction or atrophy, residual function on the affected side of the body would be a useful clinical determination. Similarly, when partial or complete nephrectomy is being planned because of a tumor, knowledge of bilateral single-kidney renal function would be valuable when deciding on appropriate treatment. Dynamic techniques for the determination of functional information might likely be added to standard CT renal evaluation without much of an increase in acquisition time or radiation exposure, and the computations needed to extract functional parameters might be performed by skilled technologists who also reformat morphologic renal CT data.
Future opportunities and challenges:
While these techniques have the potential to provide clinically useful estimates of single-kidney GFR, to our knowledge, the most robust and accurate techniques for measurement of single-kidney function have not been clearly defined. The possibility of determining single-kidney renal function with contrast-enhanced CT is a subject of considerable research, and several models have been proposed as the basis for functional determinations. One limitation of renal function measurement with such techniques is that a particular model may be violated in some instances, thus leading to inaccuracy. For example, Hackstein et al (2,6) showed that the Patlak method functioned quite well in the estimation of single-kidney GFR in normal kidneys; however, when the interstitial space of kidneys was increased because of disease processes, the error in GFR estimate was substantially increased. Although it is likely that more research will be required to determine the best techniques for renal functional determination with CT, the findings of Daghini et al (1) hold promise that noninvasive estimation of human single-kidney GFR with CT is possible. The findings of recent studies have also indicated the possibility of estimating another fundamental parameter of single-kidney renal function, the renal extraction or filtration fraction, with contrast-enhanced CT (7). A single CT examination combining excellent morphologic and accurate functional information would provide a powerful noninvasive tool for renal diagnosis.
FOOTNOTES
See also the article by Daghini et al in this issue.
References
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