Michael A Bush1, Yue Pan2, Ning Jin3, Yingmin Liu2, Juliet Varghese2, Rizwan Ahmad1,2,4, Orlando P Simonetti1,2,5,6. 1. Biomedical Engineering, The Ohio State University, Columbus, Ohio, USA. 2. Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, Ohio, USA. 3. Cardiovascular MR R&D, Siemens Medical Solutions USA Inc, Columbus, Ohio, USA. 4. Electrical and Computer Engineering, The Ohio State University, Columbus, Ohio, USA. 5. Internal Medicine, The Ohio State University, Columbus, Ohio, USA. 6. Radiology, The Ohio State University, Columbus, Ohio, USA.
Abstract
PURPOSE: Respiratory motion in cardiovascular MRI presents a challenging problem with many potential solutions. Current approaches require breath-holds, apply retrospective image registration, or significantly increase scan time by respiratory gating. Myocardial T1 and T2 mapping techniques are particularly sensitive to motion as they require multiple source images to be accurately aligned prior to the estimation of tissue relaxation. We propose a patient-specific prospective motion correction (PROCO) strategy that corrects respiratory motion on the fly with the goal of reducing the spatial variation of myocardial parametric mapping techniques. METHODS: A rapid, patient-specific training scan was performed to characterize respiration-induced motion of the heart relative to a diaphragmatic navigator, and a parametric mapping pulse sequence utilized the resulting motion model to prospectively update the scan plane in real-time. Midventricular short-axis T1 and T2 maps were acquired under breath-hold or free-breathing conditions with and without PROCO in 7 healthy volunteers and 3 patients. T1 and T2 were measured in 6 segments and compared to reference standard breath-hold measurements using Bland-Altman analysis. RESULTS: PROCO significantly reduced the spatial variation of parametric maps acquired during free-breathing, producing limits of agreement of -47.16 to 30.98 ms (T1 ) and -1.35 to 4.02 ms (T2 ), compared to -67.77 to 74.34 ms (T1 ) and -2.21 to 5.62 ms (T2 ) for free-breathing acquisition without PROCO. CONCLUSION: Patient-specific respiratory PROCO method significantly reduced the spatial variation of myocardial T1 and T2 mapping, while allowing for 100% efficient free-breathing acquisitions.
PURPOSE: Respiratory motion in cardiovascular MRI presents a challenging problem with many potential solutions. Current approaches require breath-holds, apply retrospective image registration, or significantly increase scan time by respiratory gating. Myocardial T1 and T2 mapping techniques are particularly sensitive to motion as they require multiple source images to be accurately aligned prior to the estimation of tissue relaxation. We propose a patient-specific prospective motion correction (PROCO) strategy that corrects respiratory motion on the fly with the goal of reducing the spatial variation of myocardial parametric mapping techniques. METHODS: A rapid, patient-specific training scan was performed to characterize respiration-induced motion of the heart relative to a diaphragmatic navigator, and a parametric mapping pulse sequence utilized the resulting motion model to prospectively update the scan plane in real-time. Midventricular short-axis T1 and T2 maps were acquired under breath-hold or free-breathing conditions with and without PROCO in 7 healthy volunteers and 3 patients. T1 and T2 were measured in 6 segments and compared to reference standard breath-hold measurements using Bland-Altman analysis. RESULTS: PROCO significantly reduced the spatial variation of parametric maps acquired during free-breathing, producing limits of agreement of -47.16 to 30.98 ms (T1 ) and -1.35 to 4.02 ms (T2 ), compared to -67.77 to 74.34 ms (T1 ) and -2.21 to 5.62 ms (T2 ) for free-breathing acquisition without PROCO. CONCLUSION: Patient-specific respiratory PROCO method significantly reduced the spatial variation of myocardial T1 and T2 mapping, while allowing for 100% efficient free-breathing acquisitions.
Authors: Ulf K Radunski; Gunnar K Lund; Christian Stehning; Bernhard Schnackenburg; Sebastian Bohnen; Gerhard Adam; Stefan Blankenberg; Kai Muellerleile Journal: JACC Cardiovasc Imaging Date: 2014-06-18
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