Automatic Computation of Vessel Cross-sectional Area and Its Application to the Analysis of White Matter Lesions and Vessels Relationship

D. Kozinska (Poland, USA), C. Holland, and C.R.G. Guttmann (USA)


Integrated Image Analysis, Morphometric Analysis, White Matter Lesions, Vessels


We have been studying geometrical relationship between brain white matter lesions imaged with dual-echo spin echo magnetic resonance imaging and brain vasculature imaged with magnetic resonance angiography. One of the features we are interested in is the relationship between lesion geometry and tissue perfusion, which is possibly related to the caliber of the closest vessel. This analysis requires computation of vessels' cross-sectional areas (CSA). We developed a technique that automatically computes CSAs of arbitrary shaped vessels using binary vessel volume segmented from 3D MRA data. For each point of the vessel boundary we determine a short tube like segment. For this segment we find orientations of its three principal axes by solving its inertia matrix. The orientation of the axis associated with the largest inertia moment determines vessel orientation for this tube-like segment. The cross-section is determined as the intersection of a plane orthogonal to this vessel's orientation with this vessel's boundary. Then its area is computed. The method was used to analyze 3 patients with multiple sclerosis lesions. The results of group analysis of all patients' lesions were in good agreement with our previous studies. Results based on individual patients were consistent with the group analysis only when using the new method.

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