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Register a new userNoncontrast free-breathing respiratory self-navigated coronary artery cardiovascular magnetic resonance angiography at 3 T using lipid insensitive binomial off-resonant excitation (LIBRE)
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Added by
Jessica A.M. Bastiaansen
Publication date
2019
fields
Physics
and research's language is
English
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Robust and homogeneous lipid suppression is mandatory for coronary magnetic resonance angiography (MRA) since coronary arteries are commonly embedded in fat. However, effective large volume lipid suppression becomes challenging when performing radial whole-heart coronary MRA and the problem may even be exacerbated at increasing magnetic field strengths. Incomplete fat suppression also generates artifacts, and may affect advanced motion correction methods. The aim was to evaluate a recently reported lipid insensitive MRI method for self-navigated coronary MRA at 3T. Lipid insensitive binomial off resonant excitation (LIBRE) radiofrequency (RF) excitation pulses were included into a self-navigated 3D radial GRE coronary MRA sequence at 3T. LIBRE was compared against conventional fat saturation (FS) and binomial 1-180{deg}-1 water excitation (WE). First, fat suppression of all techniques was numerically characterized using Matlab and experimentally validated in phantoms and in legs of human volunteers. Subsequently, free-breathing self-navigated coronary MRA was performed using the LIBRE pulse as well as FS and WE in ten volunteers. Results obtained in the simulations were confirmed by the experimental validations as LIBRE enabled near complete fat suppression for 3D radial imaging in vitro and in vivo. For self-navigated whole-heart coronary MRA at 3T, fat SNR was significantly attenuated using LIBRE compared with conventional FS. LIBRE increased the RCA vessel sharpness significantly (37 +/- 9% (LIBRE) vs. 29 +/- 8% (FS) and 30 +/- 8% (WE), both p<0.05) and led to a significant increase in the measured RCA vessel length to (83 +/- 31 mm (LIBRE) vs. 56 +/- 12 mm (FS) and 59 +/- 27 (WE) p<0.05). LIBRE enables robust large volume fat suppression and significantly improves coronary artery image quality at 3T compared to the use of conventional fat suppression and water excitation.
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Purpose: To develop a robust and flexible low power water excitation pulse that enables effective fat suppression at high magnetic field strength. Methods: A water excitation method that uses spatially non-selective pulses was optimized in numerical simulations, and implemented and tested in phantoms and healthy volunteers at 3T. The lipid insensitive binomial off-resonant excitation (LIBRE) pulse comprises two low power rectangular sub-pulses that have a variable frequency offset, phase offset and duration. The capability and extent of LIBRE fat suppression was quantitatively compared with conventional fat saturation (FS) and water excitation (WE) techniques. Results: LIBRE enables simultaneous water excitation and near complete fat suppression in large volumes at 3T as demonstrated by numerical simulations, and experiments. In phantoms and in human subjects, the frequency responses matched well with those from the numerical simulation. Comparing FS and WE, LIBRE demonstrated an improved robustness to magnetic field inhomogeneities, and a much more effectively suppressed fat signal. This applied for a range of pulse durations and pulses as short as 1.4 ms. Conclusion: A flexible water excitation method was developed that shows robust, near complete fat suppression at 3T.
Background: RSN whole-heart CMRA is a technique that estimates and corrects for respiratory motion. However, RSN has been limited to a 1D rigid correction which is often insufficient for patients with complex respiratory patterns. The goal of this work is therefore to improve the robustness and quality of 3D radial CMRA by incorporating both 3D motion information and nonrigid intra-acquisition correction of the data into a framework called focused navigation (fNAV). Methods: We applied fNAV to 500 data sets from a numerical simulation, 22 healthy volunteers, and 549 cardiac patients. We compared fNAV to RSN and respiratory resolved XD-GRASP reconstructions of the same data and recorded reconstruction times. Motion accuracy was measured as the correlation between fNAV and ground truth for simulations, and fNAV and image registration for in vivo data. Vessel sharpness was measured using Soap-Bubble. Finally, image quality analysis was performed by a blinded expert reviewer who chose the best image for each data set. Results The reconstruction time for fNAV images was significantly higher than RSN (6.1 +/- 2.1 minutes vs 1.4 +/- 0.3, minutes, p<0.025) but significantly lower than XD-GRASP (25.6 +/- 7.1, minutes, p<0.025). There is high correlation between the fNAV, and reference displacement estimates across all data sets (0.73 +/- 0.29). For all data, fNAV lead to significantly sharper vessels than all other reconstructions (p < 0.01). Finally, a blinded reviewer chose fNAV as the best image in 239 out of 571 cases (p = 10-5). Conclusion: fNAV is a promising technique for improving free-breathing 3D radial whole-heart CMRA. This novel approach to respiratory self-navigation can derive 3D nonrigid motion estimations from an acquired 1D signal yielding statistically significant improvement in image sharpness relative to 1D translational correction as well as XD-GRASP reconstructions.
Vessel stenosis is a major risk factor in cardiovascular diseases (CVD). To analyze the degree of vessel stenosis for supporting the treatment management, extraction of coronary artery area from Computed Tomographic Angiography (CTA) is regarded as a key procedure. However, manual segmentation by cardiologists may be a time-consuming task, and present a significant inter-observer variation. Although various computer-aided approaches have been developed to support segmentation of coronary arteries in CTA, the results remain unreliable due to complex attenuation appearance of plaques, which are the cause of the stenosis. To overcome the difficulties caused by attenuation ambiguity, in this paper, a 3D multi-channel U-Net architecture is proposed for fully automatic 3D coronary artery reconstruction from CTA. Other than using the original CTA image, the main idea of the proposed approach is to incorporate the vesselness map into the input of the U-Net, which serves as the reinforcing information to highlight the tubular structure of coronary arteries. The experimental results show that the proposed approach could achieve a Dice Similarity Coefficient (DSC) of 0.8 in comparison to around 0.6 attained by previous CNN approaches.
Purpose: To study the accuracy of motion information extracted from beat-to-beat 3D image-based navigators (3D iNAVs) collected using a variable-density cones trajectory with different combinations of spatial resolutions and scan acceleration factors. Methods: Fully sampled, breath-held 4.4 mm 3D iNAV datasets for six respiratory phases are acquired in a volunteer. Ground truth translational and nonrigid motion information is derived from these datasets. Subsequently, the motion estimates from synthesized undersampled 3D iNAVs with isotropic spatial resolutions of 4.4 mm (acceleration factor = 10.9), 5.4 mm (acceleration factor = 7.2), 6.4 mm (acceleration factor = 4.2), and 7.8 mm (acceleration factor = 2.9) are assessed against the ground truth information. The undersampled 3D iNAV configuration with the highest accuracy motion estimates in simulation is then compared with the originally proposed 4.4 mm undersampled 3D iNAV in six volunteer studies. Results: The simulations indicate that for navigators beyond certain scan acceleration factors, the accuracy of motion estimates is compromised due to errors from residual aliasing and blurring/smoothening effects following compressed sensing reconstruction. The 6.4 mm 3D iNAV achieves an acceptable spatial resolution with a small acceleration factor, resulting in the highest accuracy motion information among all assessed undersampled 3D iNAVs. Reader scores for six volunteer studies demonstrate superior coronary vessel sharpness when applying an autofocusing nonrigid correction technique using the 6.4 mm 3D iNAVs in place of 4.4 mm 3D iNAVs. Conclusion: Undersampled 6.4 mm 3D iNAVs enable motion tracking with improved accuracy relative to previously proposed undersampled 4.4 mm 3D iNAVs.
Purpose: To develop a respiratory-resolved motion-compensation method for free-breathing, high-resolution coronary magnetic resonance angiography using a 3D cones trajectory. Methods: To achieve respiratory-resolved 0.98 mm resolution images in a clinically relevant scan time, we undersample the imaging data with a variable-density 3D cones trajectory. For retrospective motion compensation, translational estimates from 3D image-based navigators (3D iNAVs) are used to bin the imaging data into four phases from end-expiration to end-inspiration. To ensure pseudo-random undersampling within each respiratory phase, we devise a phyllotaxis readout ordering scheme mindful of eddy current artifacts in steady state free precession imaging. Following binning, residual 3D translational motion within each phase is computed using the 3D iNAVs and corrected for in the imaging data. The noise-like aliasing characteristic of the combined phyllotaxis and cones sampling pattern is leveraged in a compressed sensing reconstruction with spatial and temporal regularization to reduce aliasing in each of the respiratory phases. Results: In a volunteer and 5 patients, respiratory motion compensation using the proposed method yields improved image quality compared to non-respiratory-resolved approaches with no motion correction and with 3D translational correction. Qualitative assessment by two cardiologists indicates the superior sharpness of coronary segments reconstructed with the proposed method (P < 0.01). Conclusion: The proposed method better mitigates motion artifacts in free-breathing, high-resolution coronary angiography exams compared to translational correction.
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