Parameter estimation and confidence intervals for Xe-CT ventilation studies: a Monte Carlo approach

Abstract

Simon, Brett A., Catherine Marcucci, Mansheung Fung, and Subhash R. Lele. Parameter estimation and confidence intervals for Xe-CT ventilation studies: a Monte Carlo approach. J. Appl. Physiol. 84(2): 709–716, 1998.—Xenon-enhanced computed tomography (Xe-CT) is a technique for the noninvasive measurement of regional pulmonary ventilation from the washin and/or washout time constants of radiodense stable xenon gas, determined from serial computed tomography scans. Although the measurement itself is straightforward, there is a need for methods for the estimation of variability and confidence intervals so that the statistical significance of the information obtained may be evaluated, particularly since obtaining repeated measurements is often not practical. We present a Monte Carlo (MC) approach to determine the 95% confidence interval (CI) for any given measurement. This MC method was characterized in terms of its unbiasedness and coverage of the CI. In addition, 10 identical Xe-CT ventilation runs were performed in an anesthetized dog, and the time constant was determined for several regions of varying size in each run. The 95% CI, estimated from these repeated measurements as the mean ± 2 × SE, compared favorably with the CI obtained by the MC approach. Finally, a simulation was performed to compare the performance of three imaging protocols in estimating model parameters.