Characteristics of\dot V_A /\dot Q distributions recovered from inert gas elimination datadistributions recovered from inert gas elimination data

The resolving powers of the enforced smoothing and log-normal parametric estimation techniques in recovering ventilation/perfusion ratio distributions were evaluated using noisy inert gas elimination data simulated from hypothetical distribution functions representing various degrees of heterogeneity. The resolving powers were assessed in terms of the statistical recoverabilities of the shunt, dead space, modality, and modal moments characterizing the perfusion distribution. For all distributions tested, both modal mean and shunt were estimated by either technique with sufficient accuracies. Modal dispersions (σ) were consistently overestimated by up to 0.15 decade for narrow distributions, but the mean errors became negligible for σ greater than 0.2 decade. As compared with the shunt, the dead space estimates were more variable and biased, probably due to their indirect estimation from the perfusion distribution, which was imperfectly recovered. Both broad unimodal and widely separated bimodal or trimodal distributions (σ>0.6 decade) were recovered as bimodal distributions of similar forms, so that detection of modality was difficult. The recoveries by both techniques were comparable in most cases studied, except that parametric estimation generally tended to be more sensitive to measurement errors and was computationally less efficient. These results provide a useful basis for the interpretation of distributions obtained from empirical inert gas data.