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Various imaging modalities permit direct observation of the pulmonary arterial tree within the intact lung. We have been concerned with finding a means for efficient organization of the data such that they can reveal certain aspects of the hemodynamic function of the tree. Commonly, pulmonary arterial morphometric data have been summarized by grouping the individual vessel segments according to generation or order and then averaging the dimensions within each generation or order. The most effective criteria for grouping has been a question, and some criteria are not applicable to imaging methods having limited resolution. We have considered an alternative approach in which we begin with the concept that the bifurcating, volume filling characteristics of the tree put constraints of the structure such that the assignment of orders or generations may be superfluous. The scale independent, or fractal, appearance of the tree suggests that one might consider the three vessel segments joined at a bifurcation to be the fundamental repeating morphometric unit descriptive of the tree. The analysis is based on the information in the diameters of the three vessels at each bifurcation. These diameters, D1 the parent vessel diameter, and D2 and D3, the two daughter vessel diameters are used to calculate (beta) 1 which is the harmonic mean of (beta) 1 equals log2/[log2D1 - log(D1 + D2], where (beta) 1 is the quantitative descriptor of each bifurcation of the tree. Within the range of resolution of the imaging modality, a statistical sample of the values of (beta) 1 can provide an estimate of (beta) 1. To put the utility of (beta) 1 in perspective, we introduce the concept of cumulative vascular volume, which is the arterial volume upstream from all of the locations within the arterial tree that have the same intravascular pressure. The distribution of intravascular pressure from arterial inlet to capillary inlet as a function of cumulative vascular volume can be expressed in terms of (beta) 1. Thus, a sample containing a sufficiently large number of bifurcations can be used to relate the structural image data to pulmonary arterial tree hemodynamic function. Microfocal pulmonary angiographic data provide examples of the application of this concept.
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