Typically, indicator dilution theory is applied to time- density curves acquired from dynamic contrast images, including x-ray planar and fast CT, for determination of blood circulation parameters. The original theory developed by Zierler and now applied to image curves assumes that the time- density curves are flow-sampled, i.e. each particle of indicator is counted for a time proportional to its velocity so that particles traveling within streamlines with higher or lower flow contribute equally to the measured concentration. However, curves obtained from images are instead cross- sectionally sampled, i.e, each indicator particle is counted for a time proportional to its residence time within the ROI, (inversely proportional to its velocity), so that particles traveling within low flow streamlines contribute relatively more to the measured concentration than do particles within higher flow streamlines. We illustrate some of the potential pitfalls encountered when applying the conventional theory directly to image curves and propose a strategy for accounting for the cross-sectional error in the transit time estimate. The correction method was applied to a known simulated network system for verification and illustration of its usefulness. Finally, to illustrate its applicability, the method was implemented on experimental image curves obtained from a microfocal x-ray imaging system.
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