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Abstract #1473

Assessment of Compressed-Sensing Reconstruction Fidelity for Depicting Ventilation Defects in Hyperpolarized He3 MRI Using H1 Image-Masked Segmentation

Kun Qing1, Nicholas J. Tustison2, Talissa A. Altes2, Jaime F. Mata2, G. Wilson Miller2, Eduard E. De Lange2, William A. Tobias3, Gordon D. Cates Jr. 3, James R. Brookeman2, John P. Mugler, III, 12

1Biomedical Engineering, University of Virginia, Charlottesville, VA, United States; 2Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, United States; 3Physics, University of Virginia, Charlottesville, VA, United States

Previous studies have demonstrated the potential utility of the combined acquisition of helium-3 (He3) and proton (H1) 3D image sets within one breath-hold, accelerated using the compressed-sensing (CS) technique. The purpose of this study was to use an automated segmentation method to compare and quantify the ventilation defects found in fully-sampled versus CS-reconstructed undersampled He3 image sets acquired in the same subjects but during different breath-holds. Relatively high similarities were found between the segmentation results. Much of the difference appears to be due to real variation of ventilation defects between breath holds rather than artifacts related to the CS acquisition.