Barbara Dymerska1, Korbinian Eckstein2, Beata Bachrata2,3, Bernard Siow4, Siegfried Trattnig2,3, Karin Shmueli1, Simon Daniel Robinson2,5,6. 1. Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom. 2. High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria. 3. Christian Doppler Laboratory for Clinical Molecular MR Imaging, Medical University of Vienna, Vienna, Austria. 4. Magnetic Resonance Imaging, The Francis Crick Institute, London, United Kingdom. 5. Centre for Advanced Imaging, University of Queensland, Australia. 6. Department of Neurology, Medical University of Graz, Graz, Austria.
Abstract
PURPOSE: To develop a rapid and accurate MRI phase-unwrapping technique for challenging phase topographies encountered at high magnetic fields, around metal implants, or postoperative cavities, which is sufficiently fast to be applied to large-group studies including Quantitative Susceptibility Mapping and functional MRI (with phase-based distortion correction). METHODS: The proposed path-following phase-unwrapping algorithm, ROMEO, estimates the coherence of the signal both in space-using MRI magnitude and phase information-and over time, assuming approximately linear temporal phase evolution. This information is combined to form a quality map that guides the unwrapping along a 3D path through the object using a computationally efficient minimum spanning tree algorithm. ROMEO was tested against the two most commonly used exact phase-unwrapping methods, PRELUDE and BEST PATH, in simulated topographies and at several field strengths: in 3T and 7T in vivo human head images and 9.4T ex vivo rat head images. RESULTS: ROMEO was more reliable than PRELUDE and BEST PATH, yielding unwrapping results with excellent temporal stability for multi-echo or multi-time-point data. It does not require image masking and delivers results within seconds, even in large, highly wrapped multi-echo data sets (eg, 9 seconds for a 7T head data set with 31 echoes and a 208 × 208 × 96 matrix size). CONCLUSION: Overall, ROMEO was both faster and more accurate than PRELUDE and BEST PATH, delivering exact results within seconds, which is well below typical image acquisition times, enabling potential on-console application.
PURPOSE: To develop a rapid and accurate MRI phase-unwrapping technique for challenging phase topographies encountered at high magnetic fields, around metal implants, or postoperative cavities, which is sufficiently fast to be applied to large-group studies including Quantitative Susceptibility Mapping and functional MRI (with phase-based distortion correction). METHODS: The proposed path-following phase-unwrapping algorithm, ROMEO, estimates the coherence of the signal both in space-using MRI magnitude and phase information-and over time, assuming approximately linear temporal phase evolution. This information is combined to form a quality map that guides the unwrapping along a 3D path through the object using a computationally efficient minimum spanning tree algorithm. ROMEO was tested against the two most commonly used exact phase-unwrapping methods, PRELUDE and BEST PATH, in simulated topographies and at several field strengths: in 3T and 7T in vivo human head images and 9.4T ex vivo rat head images. RESULTS: ROMEO was more reliable than PRELUDE and BEST PATH, yielding unwrapping results with excellent temporal stability for multi-echo or multi-time-point data. It does not require image masking and delivers results within seconds, even in large, highly wrapped multi-echo data sets (eg, 9 seconds for a 7T head data set with 31 echoes and a 208 × 208 × 96 matrix size). CONCLUSION: Overall, ROMEO was both faster and more accurate than PRELUDE and BEST PATH, delivering exact results within seconds, which is well below typical image acquisition times, enabling potential on-console application.
Authors: Barbara Dymerska; Benedikt A Poser; Markus Barth; Siegfried Trattnig; Simon D Robinson Journal: Neuroimage Date: 2016-07-07 Impact factor: 6.556
Authors: Dávid Z Balla; Rosa M Sanchez-Panchuelo; Samuel J Wharton; Gisela E Hagberg; Klaus Scheffler; Susan T Francis; Richard Bowtell Journal: Neuroimage Date: 2014-06-17 Impact factor: 6.556
Authors: Barbara Dymerska; Korbinian Eckstein; Beata Bachrata; Bernard Siow; Siegfried Trattnig; Karin Shmueli; Simon Daniel Robinson Journal: Magn Reson Med Date: 2020-10-26 Impact factor: 4.668
Authors: Korbinian Eckstein; Beata Bachrata; Gilbert Hangel; Georg Widhalm; Christian Enzinger; Markus Barth; Siegfried Trattnig; Simon Daniel Robinson Journal: Neuroimage Date: 2021-05-15 Impact factor: 7.400
Authors: Barbara Dymerska; Korbinian Eckstein; Beata Bachrata; Bernard Siow; Siegfried Trattnig; Karin Shmueli; Simon Daniel Robinson Journal: Magn Reson Med Date: 2020-10-26 Impact factor: 4.668