Blood volume analysis by radioisotopic dilution techniques: state of the art.

In the last years, there has been a growing recognition of the importance of blood volume abnormalities in the pathophysiology of several conditions and, consequently, a growing interest of accurate and rapid volume status assessment. Accordingly, there has been a surge of interest in blood volume analysis by radioisotopic dilution technique. However, there are still some controversies about this technique, such as the use of the f-cell ratio, the errors associated with the method and the reference values. This review aims to revise and discuss the theoretical and methodological aspects of this technique and also to discuss their controversies. Furthermore, it is questioned whether red cell volume or plasma volume can be accurately estimated once the other quantity has been measured or should red cell volume and plasma volume be directly measured. As a conclusion, blood volume analysis by radioisotopic dilution technique is still valid and very useful.

Empirical estimators of gamma fits to tracer-dilution curves and their technical basis and practical scope.

A gamma fit facilitates smoothing and extrapolation of distorted tracer-dilution curves in blood flow studies. Theoretically based empirical estimators were developed as simple alternatives to direct regression approaches from simulated gamma distributions with a wide range of shape asymmetry. Key curve features of peak height p, full width w at half peak height, rising and falling limb inflection tangents and asymmetry of the peak time with respect to the p/2 height occurrences were related to the parameters of the distribution by multiple linear regression after suitable transformations. The product pw was simply related to the total area A under the curve, pw/A being 0.93 +/- 0.01 in 70 cardiac output determinations from ten surgical patients. Shape and scale parameters were closely related to the standard deviation, inflection point properties and w for the curves. Mensuration devices suitable for cardiac output computers were developed that calculated total areas from incomplete portions under gamma curves and by-passed the need for parameter estimation. There was limited point in estimating the distribution parameters just to derive particle transit times, because of the ad hoc nature of the fitting form, which did not allow for the back-dispersion by Brownian motion of tracer molecules diluting in blood flow. Nonetheless, the accuracy of area prediction using a gamma fit was adequate for most clinical purposes and comparable to that via the random walk function, giving good insight to established results and computing procedures.

Estimation of cardiac output by first-pass transit of radiotracers.

To evaluate cardiac function with various tracers to be used for radionuclide scintigraphy, we examined the validity of a simplified method to measure cardiac output (CO) by modifying the equation of Stewart-Hamilton in the radionuclide study. After a bolus injection of I-123 or Tc-99m tracer, the total injection dose and count in the pulmonary artery during the first transit of the tracer were measured to calculate the CO Index. The CO Index was obtained from the integral of the first transit of radiotracers in the pulmonary artery divided by the total injected count. CO was estimated from the regression formula which was obtained by comparing the CO Index with CO measured by the Doppler echocardiographic method. There were close correlations between the CO Index and CO measured by Doppler echocardiography both in the study with I-123 (n = 13, r = 0.85, p < 0.001) and with Tc-99m (n = 17, r = 0.88, p < 0.001). The regression formula varied according to the radionuclide used for the study (CO = 2.29 x (CO Index)(0.634) for I-123 and CO = 3.18 x (CO Index)(0.518) for Tc-99m). CO measured by this method is useful for the assessment of cardiac function with various tracers in routine clinical studies, and this simple method may be utilized for assessment of organ blood flow on the basis of the microsphere model.