Dahan Kim1,2, Myriam Edjlali3, Patrick Turski4, Kevin M Johnson2,4. 1. Department of Physics, University of Wisconsin, Madison, Wisconsin. 2. Department of Medical Physics, University of Wisconsin, Madison, Wisconsin. 3. Department of Neuroradiology, Université Paris-Descartes-Sorbonne-Paris-Cité, IMABRAIN-INSERM-UMR1266, DHU-Neurovasc, Centre Hospitalier Sainte-Anne, Paris, France. 4. Department of Radiology, University of Wisconsin, Madison, Wisconsin.
Abstract
PURPOSE: To develop a method to use information from multiple MRI contrasts to produce a composite angiogram with reduced sequence-specific artifacts and improved vessel depiction. METHODS: Bayesian posterior vessel probability was determined as a function of black blood (BB), contrast enhanced angiography (CE-MRA), and phase-contrast MRA (PC-MRA) intensities from training subjects (N = 4). To generate composite angiogram in evaluation subjects (N = 12), the voxel-wise vessel probabilities were weighted with a confidence measure and combined as a weighted product to yield angiogram intensity. For 23 internal carotid artery (ICA) segments (N = 23) from evaluation subjects, segmentation accuracy of composite MRA was evaluated and compared against CE-MRA using dice similarity coefficient (DSC). RESULTS: The composite MRA suppressed venous contaminations in CE-MRA, reduced flow artifacts, and velocity aliasing seen in PC-MRA and removed signal ambiguities in BB images. For ICA segmentations, the composite MRA improved segmentation over CE-MRA per DSC (0.908 ± 0.037 vs. 0.765 ± 0.079). Compared with CE-MRA, the composite MRA showed conservative changes in vessel appearance to small threshold changes. However, small vessels that are sensitive to registration errors or visible only weakly in CE-MRA were susceptible to poor depiction in composite MRA. CONCLUSION: By dynamically weighting vessel information from multiple contrasts and extracting their complementary information, the composite MRA produces reduced sequence-specific artifacts and improved vessel contrast. It is a promising technique for semi-automatic segmentation of vessels that are hard to segment because of artifacts.
PURPOSE: To develop a method to use information from multiple MRI contrasts to produce a composite angiogram with reduced sequence-specific artifacts and improved vessel depiction. METHODS: Bayesian posterior vessel probability was determined as a function of black blood (BB), contrast enhanced angiography (CE-MRA), and phase-contrast MRA (PC-MRA) intensities from training subjects (N = 4). To generate composite angiogram in evaluation subjects (N = 12), the voxel-wise vessel probabilities were weighted with a confidence measure and combined as a weighted product to yield angiogram intensity. For 23 internal carotid artery (ICA) segments (N = 23) from evaluation subjects, segmentation accuracy of composite MRA was evaluated and compared against CE-MRA using dice similarity coefficient (DSC). RESULTS: The composite MRA suppressed venous contaminations in CE-MRA, reduced flow artifacts, and velocity aliasing seen in PC-MRA and removed signal ambiguities in BB images. For ICA segmentations, the composite MRA improved segmentation over CE-MRA per DSC (0.908 ± 0.037 vs. 0.765 ± 0.079). Compared with CE-MRA, the composite MRA showed conservative changes in vessel appearance to small threshold changes. However, small vessels that are sensitive to registration errors or visible only weakly in CE-MRA were susceptible to poor depiction in composite MRA. CONCLUSION: By dynamically weighting vessel information from multiple contrasts and extracting their complementary information, the composite MRA produces reduced sequence-specific artifacts and improved vessel contrast. It is a promising technique for semi-automatic segmentation of vessels that are hard to segment because of artifacts.
Authors: Brian B Avants; Nicholas J Tustison; Gang Song; Philip A Cook; Arno Klein; James C Gee Journal: Neuroimage Date: 2010-09-17 Impact factor: 6.556
Authors: Kevin M Johnson; Darren P Lum; Patrick A Turski; Walter F Block; Charles A Mistretta; Oliver Wieben Journal: Magn Reson Med Date: 2008-12 Impact factor: 4.668