Anderson, Dennis U.

Indicator dilution techniques used for the estimation of flow (F), mean transit time (t), dispersion (σ), and mean transit time volume (V) in the circulation are subject to error when (1) flow is not steady and (2) concentrations are obtained by sampling at a constant rate (time averaging) rather than at rates proportional to the instantaneous flow past the sampling site (volume averaging). Using a simple descriptive model for indicator transport, the effects of simulated aortic flow or of sinusoidal flow of widely variable frequency were assessed. Errors in estimates of F, t, σ, and V are greater with bolus injections than with constant-rate injections. Errors are roughly proportional to the amplitude of variation in flow. They are maximal when the period of flow fluctuation is similar to the passage time of the dilution curve, which, for the human central circulation, is about the time for one respiratory cycle. With sinusoidal flow between 50% and 150% of the mean flow, errors were at worst up to 60% in F, 30% in t, 50% in σ, and 70% in V, with a bimodal distribution. Errors are minimal at cardiac frequencies. The troublesome lower frequencies can be avoided. Preliminary tests of a method for converting time- to volume-averaged concentrations gave encouraging results.

The fitting of mathematical models to physiological sys tems can be tedious and difficult, whether one uses analog or digital computer methods. Both methods have their pros and cons depending on the available hardware and software and on the type of modeling. In recent years many digital simulation languages have been written com bining analog-like and digital features to facilitate model ing, but, for a variety of reasons, none of these was suit able for our applications. We, therefore, designed a new digital simulation control system, SIMCON, which is de scribed in this paper. The primary objectives were to provide: (1) Maximum man-machine interaction at run-time, in cluding visual displays, digital control, and both con tinuous analog and digital parameter adjustment (2) The ability to generate solutions and to fit them to experimental data or other theoretical curves with a minimum of computer memory (3) The option to use a mathematically oriented language, FORTRAN, and block operators with variable input/ output. The result is a relatively general and simple simulation system which is easy to use and has wide versatility.