9806883 Paschal The goal of this proposed research is to devise computational techniques that will allow the successful application of fractal analysis and other signal characterization methods to the assessment of pulmonary perfusion as measured by magnetic resonance angiography (MRA). Fractal analysis quantifies the self-similarity of a signal over a range of observational scales to determine if the patterns in a small volume scale up to match the patterns in a large volume. Lungs have already been demonstrated to have a fractal nature in both their tree structure and flow distribution. The application of fractal analysis to three-dimensional pulmonary perfusion information obtained with modern MRA techniques should provide a unique quantitative descriptor of flow patterns in normal and pathologic conditions, Issues to be researched include how to perform fractal analysis on an irregularly shaped three dimensional volume, the effect of flow distribution on fractal dimension, appropriate metrics to characterize regional flow, and effect of MR imaging technique on fractal analysis. An irregularly shaped volume presents a problem in that the typical fractal analysis involves division of the volume into parallelepiped elements@ depending on element size, some voxels containing lung tissue may be omitted from the analysis and some voxels outside the lungs may be included. Both cases will result in errors that diminish the accuracy of the computation of fractal dimension. To address this issue, tests will be done comparing fractal dimension computed from: (a) a parallelepiped volume that fits completely within a lung volume, (b) a parallelepiped volume that completely encompasses the lungs, and (c) the entire volume treated as a sequential list of data points. The effect of flow distribution on fractal dimension will be tested by comparing the results for healthy volunteers and patients with lung pathologies and also by applying the analysis techniques to a normal date set altered, for example, by removing a large sector of flow as might result from a large pulmonary embolus or by removing many small sectors of flow as might result from many small emboli. ***

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Vanderbilt University Medical Center
United States
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