PURPOSE: To develop an efficient 3D affine respiratory motion compensation framework for Cartesian whole-heart coronary magnetic resonance angiography (MRA). MATERIALS AND METHODS: The proposed method achieves 100% scan efficiency by estimating the affine respiratory motion from the data itself and correcting the acquired data in the reconstruction process. For this, a golden-step Cartesian sampling with spiral profile ordering was performed to enable reconstruction of respiratory resolved images at any breathing position and with different respiratory window size. Affine motion parameters were estimated from image-based registration of 3D undersampled respiratory resolved images reconstructed with iterative SENSE and motion correction was performed directly in the reconstruction using a multiple-coils generalized matrix formulation method. This approach was tested on healthy volunteers and compared against a conventional diaphragmatic navigator-gated acquisition using quantitative and qualitative image quality assessment. RESULTS: The proposed approach achieved 47 ± 12% and 59 ± 6% vessel sharpness for the right (RCA) and left (LAD) coronary arteries, respectively. Also, good quality visual scores of 2.4 ± 0.74 and 2.44 ± 0.86 were observed for the RCA and LAD (scores from 0, no to 4, excellent coronary vessel delineation). A not statically significant difference (P = 0.05) was found between the proposed method and an 8-mm navigator-gated and tracked scan, although scan efficiency increased from 61 ± 10% to 100%. CONCLUSION: We demonstrate the feasibility of a new 3D affine respiratory motion correction technique for Cartesian whole-heart CMRA that achieves 100% scan efficiency and therefore a predictable acquisition time. This approach yields image quality comparable to that of an 8-mm navigator-gated acquisition with lower scan efficiency. Further evaluation of this technique in patients is now warranted to determine its clinical use.
PURPOSE: To develop an efficient 3D affine respiratory motion compensation framework for Cartesian whole-heart coronary magnetic resonance angiography (MRA). MATERIALS AND METHODS: The proposed method achieves 100% scan efficiency by estimating the affine respiratory motion from the data itself and correcting the acquired data in the reconstruction process. For this, a golden-step Cartesian sampling with spiral profile ordering was performed to enable reconstruction of respiratory resolved images at any breathing position and with different respiratory window size. Affine motion parameters were estimated from image-based registration of 3D undersampled respiratory resolved images reconstructed with iterative SENSE and motion correction was performed directly in the reconstruction using a multiple-coils generalized matrix formulation method. This approach was tested on healthy volunteers and compared against a conventional diaphragmatic navigator-gated acquisition using quantitative and qualitative image quality assessment. RESULTS: The proposed approach achieved 47 ± 12% and 59 ± 6% vessel sharpness for the right (RCA) and left (LAD) coronary arteries, respectively. Also, good quality visual scores of 2.4 ± 0.74 and 2.44 ± 0.86 were observed for the RCA and LAD (scores from 0, no to 4, excellent coronary vessel delineation). A not statically significant difference (P = 0.05) was found between the proposed method and an 8-mm navigator-gated and tracked scan, although scan efficiency increased from 61 ± 10% to 100%. CONCLUSION: We demonstrate the feasibility of a new 3D affine respiratory motion correction technique for Cartesian whole-heart CMRA that achieves 100% scan efficiency and therefore a predictable acquisition time. This approach yields image quality comparable to that of an 8-mm navigator-gated acquisition with lower scan efficiency. Further evaluation of this technique in patients is now warranted to determine its clinical use.
Authors: Joshua S Greer; Xinzeng Wang; Yiming Wang; Marco C Pinho; Joseph A Maldjian; Ivan Pedrosa; Ananth J Madhuranthakam Journal: Magn Reson Med Date: 2019-06-23 Impact factor: 4.668
Authors: David Y Zeng; Corey A Baron; Mario O Malavé; Adam B Kerr; Phillip C Yang; Bob S Hu; Dwight G Nishimura Journal: Magn Reson Med Date: 2019-11-05 Impact factor: 4.668
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Authors: Li Feng; Thomas Benkert; Kai Tobias Block; Daniel K Sodickson; Ricardo Otazo; Hersh Chandarana Journal: J Magn Reson Imaging Date: 2016-12-16 Impact factor: 4.813
Authors: Jieying Luo; Nii Okai Addy; R Reeve Ingle; Corey A Baron; Joseph Y Cheng; Bob S Hu; Dwight G Nishimura Journal: Magn Reson Med Date: 2016-05-13 Impact factor: 4.668