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Abstract #3404

Quantification of Spatial Ventilation Defect Distribution in Hyperpolarized Gas MRI of Lungs Using A 3D Clustering Algorithm

Gabriela Maria Garcia Delgado1, Ummul Afia Shammi1, Talissa Ann Altes2, John P Mugler III3,4, and Robert Paul Thomen1,2
1Biomedical, Biological and Chemical Engineering, University of Missouri, Columbia, MO, United States, 2Radiology, School of Medicine, University of Missouri, 65201, MO, United States, 3Radiology and Medical Imaging, School of Medicine, University of Virginia, Charlottesville, VA, United States, 4Biomedical Engineering, University of Virginia, Charlottesville, VA, United States

Synopsis

Keywords: Quantitative Imaging, Hyperpolarized MR (Gas), Body, Lung, Contrast Mechanisms, Data AnalysisHyperpolarized gas (HPG) MR imaging allows for quantification of a patient’s lung function. The spatial distribution of ventilation defect patterns is often overlooked in quantitative analyses but may be important for further understanding the nature of lung disease. Here we present a method for quantifying the extent to which defect voxels tend to be sparsely distributed or clustered. This technique involves spherical region-growing for each defect voxel to assess the fraction of neighbors which are also part of a defect. A ‘clustering index’ is reported which quantifies the extent to which defect voxels are spatially congregated or scattered.

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