Toward accurate and fast velocity quantification with 3D ultrashort TE phase-contrast imaging.

PURPOSE: Traditional phase-contrast MRI is affected by displacement artifacts caused by non-synchronized spatial- and velocity-encoding time points. The resulting inaccurate velocity maps can affect the accuracy of derived hemodynamic parameters. This study proposes and characterizes a 3D radial phase-contrast UTE (PC-UTE) sequence to reduce displacement artifacts. Furthermore, it investigates the displacement of a standard Cartesian flow sequence by utilizing a displacement-free synchronized-single-point-imaging MR sequence (SYNC-SPI) that requires clinically prohibitively long acquisition times. METHODS: 3D flow data was acquired at 3T at three different constant flow rates and varying spatial resolutions in a stenotic aorta phantom using the proposed PC-UTE, a Cartesian flow sequence, and a SYNC-SPI sequence as reference. Expected displacement artifacts were calculated from gradient timing waveforms and compared to displacement values measured in the in vitro flow experiments. RESULTS: The PC-UTE sequence reduces displacement and intravoxel dephasing, leading to decreased geometric distortions and signal cancellations in magnitude images, and more spatially accurate velocity quantification compared to the Cartesian flow acquisitions; errors increase with velocity and higher spatial resolution. CONCLUSION: PC-UTE MRI can measure velocity vector fields with greater accuracy than Cartesian acquisitions (although pulsatile fields were not studied) and shorter scan times than SYNC-SPI. As such, this approach is superior to traditional Cartesian 3D and 4D flow MRI when spatial misrepresentations cannot be tolerated, for example, when computational fluid dynamics simulations are compared to or combined with in vitro or in vivo measurements, or regional parameters such as wall shear stress are of interest.

Motion-corrected model-based reconstruction for 2D myocardial T1 mapping.

PURPOSE: To allow for T1 mapping of the myocardium within 2.3 s for a 2D slice utilizing cardiac motion-corrected, model-based image reconstruction. METHODS: Golden radial data acquisition is continuously carried out for 2.3 s after an inversion pulse. In a first step, dynamic images are reconstructed which show both contrast changes due to T1 recovery and anatomical changes due to the heartbeat. An image registration algorithm with a signal model for T1 recovery is applied to estimate non-rigid cardiac motion. In a second step, estimated motion fields are applied during an iterative model-based T1 reconstruction. The approach was evaluated in numerical simulations, phantom experiments and in in-vivo scans in healthy volunteers. RESULTS: The accuracy of cardiac motion estimation was shown in numerical simulations with an average motion field error of 0.7 ± 0.6 mm for a motion amplitude of 5.1 mm. The accuracy of T1 estimation was demonstrated in phantom experiments, with no significant difference (p = 0.13) in T1 estimated by the proposed approach compared to an inversion-recovery reference method. In vivo, the proposed approach yielded 1.3 × 1.3 mm T1 maps with no significant difference (p = 0.77) in T1 and SDs in comparison to a cardiac-gated approach requiring 16 s scan time (i.e., seven times longer than the proposed approach). Cardiac motion correction improved the precision of T1 maps, shown by a 40% reduced SD. CONCLUSION: We have presented an approach that provides T1 maps of the myocardium in 2.3 s by utilizing both cardiac motion correction and model-based T1 reconstruction.

Open-source magnetic resonance imaging: Improving access, science, and education through global collaboration.

Open-source practices and resources in magnetic resonance imaging (MRI) have increased substantially in recent years. This trend started with software and data being published open-source and, more recently, open-source hardware designs have become increasingly available. These developments towards a culture of sharing and establishing nonexclusive global collaborations have already improved the reproducibility and reusability of code and designs, while providing a more inclusive approach, especially for low-income settings. Community-driven standardization and documentation efforts are further strengthening and expanding these milestones. The future of open-source MRI is bright and we have just started to discover its full collaborative potential. In this review we will give an overview of open-source software and open-source hardware projects in human MRI research.

Pilot tone-based prospective correction of respiratory motion for free-breathing myocardial T1 mapping.

OBJECTIVE: To provide respiratory motion correction for free-breathing myocardial T1 mapping using a pilot tone (PT) and a continuous golden-angle radial acquisition. MATERIALS AND METHODS: During a 45 s prescan the PT is acquired together with a dynamic sagittal image covering multiple respiratory cycles. From these images, the respiratory heart motion in head-feet and anterior-posterior direction is estimated and two linear models are derived between the PT and heart motion. In the following scan through-plane motion is corrected prospectively with slice tracking based on the PT. In-plane motion is corrected for retrospectively. Our method was evaluated on a motion phantom and 11 healthy subjects. RESULTS: Non-motion corrected measurements using a moving phantom showed T1 errors of 14 ± 4% (p < 0.05) compared to a reference measurement. The proposed motion correction approach reduced this error to 3 ± 4% (p < 0.05). In vivo the respiratory motion led to an overestimation of T1 values by 26 ± 31% compared to breathhold T1 maps, which was successfully corrected to an average difference of 3 ± 2% (p < 0.05) between our free-breathing approach and breathhold data. DISCUSSION: Our proposed PT-based motion correction approach allows for T1 mapping during free-breathing with the same accuracy as a corresponding breathhold T1 mapping scan.

Cardio-respiratory motion-corrected 3D cardiac water-fat MRI using model-based image reconstruction.

PURPOSE: Myocardial fat infiltrations are associated with a range of cardiomyopathies. The purpose of this study was to perform cardio-respiratory motion-correction for model-based water-fat separation to image fatty infiltrations of the heart in a free-breathing, non-cardiac-triggered high-resolution 3D MRI acquisition. METHODS: Data were acquired in nine patients using a free-breathing, non-cardiac-triggered high-resolution 3D Dixon gradient-echo sequence and radial phase encoding trajectory. Motion correction was combined with a model-based water-fat reconstruction approach. Respiratory and cardiac motion models were estimated using a dual-mode registration algorithm incorporating both motion-resolved water and fat information. Qualitative comparisons of fat structures were made between 2D clinical routine reference scans and reformatted 3D motion-corrected images. To evaluate the effect of motion correction the local sharpness of epicardial fat structures was analyzed for motion-averaged and motion-corrected fat images. RESULTS: The reformatted 3D motion-corrected reconstructions yielded qualitatively comparable fat structures and fat structure sharpness in the heart as the standard 2D breath-hold. Respiratory motion correction improved the local sharpness on average by 32% ± 24% with maximum improvements of 81% and cardiac motion correction increased the sharpness further by another 15% ± 11% with maximum increases of 31%. One patient showed a fat infiltration in the myocardium and cardio-respiratory motion correction was able to improve its visualization in 3D. CONCLUSION: The 3D water-fat separated cardiac images were acquired during free-breathing and in a clinically feasible and predictable scan time. Compared to a motion-averaged reconstruction an increase in sharpness of fat structures by 51% ± 27% using the presented motion correction approach was observed for nine patients.

Motion-compensated fat-water imaging for 3D cardiac MRI at ultra-high fields.

PURPOSE: Respiratory motion-compensated (MC) 3D cardiac fat-water imaging at 7T. METHODS: Free-breathing bipolar 3D triple-echo gradient-recalled-echo (GRE) data with radial phase-encoding (RPE) trajectory were acquired in 11 healthy volunteers (7M\4F, 21-35 years, mean: 30 years) with a wide range of body mass index (BMI; 19.9-34.0 kg/m2 ) and volunteer tailored B1+ shimming. The bipolar-corrected triple-echo GRE-RPE data were binned into different respiratory phases (self-navigation) and were used for the estimation of non-rigid motion vector fields (MF) and respiratory resolved (RR) maps of the main magnetic field deviations (ΔB0 ). RR ΔB0 maps and MC ΔB0 maps were compared to a reference respiratory phase to assess respiration-induced changes. Subsequently, cardiac binned fat-water images were obtained using a model-based, respiratory motion-corrected image reconstruction. RESULTS: The 3D cardiac fat-water imaging at 7T was successfully demonstrated. Local respiration-induced frequency shifts in MC ΔB0 maps are small compared to the chemical shifts used in the multi-peak model. Compared to the reference exhale ΔB0 map these changes are in the order of 10 Hz on average. Cardiac binned MC fat-water reconstruction reduced respiration induced blurring in the fat-water images, and flow artifacts are reduced in the end-diastolic fat-water separated images. CONCLUSION: This work demonstrates the feasibility of 3D fat-water imaging at UHF for the entire human heart despite spatial and temporal B1+ and B0 variations, as well as respiratory and cardiac motion.

Pilot tone-based motion correction for prospective respiratory compensated cardiac cine MRI.

PURPOSE: To evaluate prospective motion correction using the pilot tone (PT) as a quantitative respiratory motion signal with high temporal resolution for cardiac cine images during free breathing. METHODS: Before cine data acquisition, a short prescan was performed, calibrating the PT to the respiratory-induced heart motion using respiratory-resolved real-time images. The calibrated PT was then applied for nearly real-time prospective motion correction of cine MRI through slice tracking (ie, updating the slice position before every readout). Additionally, in-plane motion correction was performed retrospectively also based on the calibrated PT data. The proposed method was evaluated in a moving phantom and 10 healthy volunteers. RESULTS: The PT showed very good correlation to the phantom motion. In volunteer studies using a long-term scan over 7.96 ± 1.40 min, the mean absolute error between registered and predicted motion from the PT was 1.44 ± 0.46 mm in head-feet and 0.46 ± 0.07 mm in anterior-posterior direction. Irregular breathing could also be corrected well with the PT. The PT motion correction leads to a significant improvement of contrast-to-noise ratio by 68% (P ≤ .01) between blood pool and myocardium and sharpness of endocardium by 24% (P = .04) in comparison to uncorrected data. The image score, which refers to the cine image quality, has improved with the utilization of the proposed PT motion correction. CONCLUSION: The proposed approach provides respiratory motion-corrected cine images of the heart with improved image quality and a high scan efficiency using the PT. The PT is independent of the MR acquisition, making this a very flexible motion-correction approach.

3D Free-breathing multichannel absolute B1+ Mapping in the human body at 7T.

PURPOSE: To introduce and investigate a method for free-breathing three-dimensional (3D) B1+ mapping of the human body at ultrahigh field (UHF), which can be used to generate homogenous flip angle (FA) distributions in the human body at UHF. METHODS: A 3D relative B1+ mapping sequence with a radial phase-encoding (RPE) k-space trajectory was developed and applied in 11 healthy subjects at 7T. An RPE-based actual flip angle mapping method was applied with a dedicated B1+ shim setting to calibrate the relative B1+ maps yielding absolute B1+ maps of the individual transmit channels. The method was evaluated in a motion phantom and by multidimensional in vivo measurements. Additionally, 3D gradient echo scans with and without static phase-only B1+ shims were used to qualitatively validate B1+ shim predictions. RESULTS: The phantom validation revealed good agreement for B1+ maps between dynamic measurement and static reference acquisition. The proposed 3D method was successfully validated in vivo by comparing magnitude and phase distributions with a 2D Cartesian reference. 3D B1+ maps free from visible motion artifacts were successfully acquired for 11 subjects with body mass indexes ranging from 19 kg/m2 to 34 kg/m2 . 3D respiration-resolved absolute B1+ maps indicated FA differences between inhalation and exhalation up to 15% for one channel and up to 24% for combined channels for shallow breathing. CONCLUSION: The proposed method provides respiration-resolved absolute 3D B1+ maps of the human body at UHF, which enables the investigation and development of 3D B1+ shimming and parallel transmission methods to further enhance body imaging at UHF.

Imaging coronary plaques using 3D motion-compensated [18F]NaF PET/MR.

BACKGROUND: Cardiac PET has recently found novel applications in coronary atherosclerosis imaging using [18F]NaF as a radiotracer, highlighting vulnerable plaques. However, the resulting uptakes are relatively small, and cardiac motion and respiration-induced movement of the heart can impair the reconstructed images due to motion blurring and attenuation correction mismatches. This study aimed to apply an MR-based motion compensation framework to [18F]NaF data yielding high-resolution motion-compensated PET and MR images. METHODS: Free-breathing 3-dimensional Dixon MR data were acquired, retrospectively binned into multiple respiratory and cardiac motion states, and split into fat and water fraction using a model-based reconstruction framework. From the dynamic MR reconstructions, both a non-rigid cardiorespiratory motion model and a motion-resolved attenuation map were generated and applied to the PET data to improve image quality. The approach was tested in 10 patients and focal tracer hotspots were evaluated concerning their target-to-background ratio, contrast-to-background ratio, and their diameter. RESULTS: MR-based motion models were successfully applied to compensate for physiological motion in both PET and MR. Target-to-background ratios of identified plaques improved by 7 ± 7%, contrast-to-background ratios by 26 ± 38%, and the plaque diameter decreased by -22 ± 18%. MR-based dynamic attenuation correction strongly reduced attenuation correction artefacts and was not affected by stent-related signal voids in the underlying MR reconstructions. CONCLUSIONS: The MR-based motion correction framework presented here can improve the target-to-background, contrast-to-background, and width of focal tracer hotspots in the coronary system. The dynamic attenuation correction could effectively mitigate the risk of attenuation correction artefacts in the coronaries at the lung-soft tissue boundary. In combination, this could enable a more reproducible and reliable plaque localisation.

Synergistic tomographic image reconstruction: part 2.

This special issue is the second part of a themed issue that focuses on synergistic tomographic image reconstruction and includes a range of contributions in multiple disciplines and application areas. The primary subject of study lies within inverse problems which are tackled with various methods including statistical and computational approaches. This volume covers algorithms and methods for a wide range of imaging techniques such as spectral X-ray computed tomography (CT), positron emission tomography combined with CT or magnetic resonance imaging, bioluminescence imaging and fluorescence-mediated imaging as well as diffuse optical tomography combined with ultrasound. Some of the articles demonstrate their utility on real-world challenges, either medical applications (e.g. motion compensation for imaging patients) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issues is to bring together different scientific communities which do not usually interact as they do not share the same platforms such as journals and conferences. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Synergistic tomographic image reconstruction: part 1.

This special issue focuses on synergistic tomographic image reconstruction in a range of contributions in multiple disciplines and various application areas. The topic of image reconstruction covers substantial inverse problems (Mathematics) which are tackled with various methods including statistical approaches (e.g. Bayesian methods, Monte Carlo) and computational approaches (e.g. machine learning, computational modelling, simulations). The issue is separated in two volumes. This volume focuses mainly on algorithms and methods. Some of the articles will demonstrate their utility on real-world challenges, either medical applications (e.g. cardiovascular diseases, proton therapy planning) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issue is to bring together different scientific communities which do not usually interact as they do not share the same platforms (such as journals and conferences). This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.

Evaluation of synergistic image registration for motion-corrected coronary NaF-PET-MR.

Coronary artery disease (CAD) is caused by the formation of plaques in the coronary arteries and is one of the most common cardiovascular diseases. NaF-PET can be used to assess plaque composition, which could be important for therapy planning. One of the main challenges of NaF-PET is cardiac and respiratory motion which can strongly impair diagnostic accuracy. In this study, we investigated the use of a synergistic image registration approach which combined motion-resolved MR and PET data to estimate cardiac and respiratory motion. This motion estimation could then be used to improve the NaF-PET image quality. The approach was evaluated with numerical simulations and in vivo scans of patients suffering from CAD. In numerical simulations, it was shown, that combining MR and PET information can improve the accuracy of motion estimation by more than 15%. For the in vivo scans, the synergistic image registration led to an improvement in uptake visualization. This is the first study to assess the benefit of combining MR and NaF-PET for cardiac and respiratory motion estimation. Further patient evaluation is required to fully evaluate the potential of this approach. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.

Motion estimation and correction for simultaneous PET/MR using SIRF and CIL.

SIRF is a powerful PET/MR image reconstruction research tool for processing data and developing new algorithms. In this research, new developments to SIRF are presented, with focus on motion estimation and correction. SIRF's recent inclusion of the adjoint of the resampling operator allows gradient propagation through resampling, enabling the MCIR technique. Another enhancement enabled registering and resampling of complex images, suitable for MRI. Furthermore, SIRF's integration with the optimization library CIL enables the use of novel algorithms. Finally, SPM is now supported, in addition to NiftyReg, for registration. Results of MR and PET MCIR reconstructions are presented, using FISTA and PDHG, respectively. These demonstrate the advantages of incorporating motion correction and variational and structural priors. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Respiratory motion corrected 4D flow using golden radial phase encoding.

PURPOSE: To minimize respiratory motion artifacts while achieving predictable scan times with 100% scan efficiency for thoracic 4D flow MRI. METHODS: A 4D flow sequence with golden radial phase encoding (GRPE) was acquired in 9 healthy volunteers covering the heart, aorta, and venae cavae. Scan time was 15 min, and data were acquired without motion gating during acquisition. Data were retrospectively re-binned into respiratory and cardiac phases based on respiratory self-navigation and the electrocardiograph signals, respectively. Nonrigid respiratory motion fields were extracted and corrected for during the k-t SENSE reconstruction. A respiratory-motion corrected (GRPE-MOCO) and a free-breathing (GRPE-UNCORR) 4D flow dataset was reconstructed using 100% of the acquired data. For comparison, a respiratory gated Cartesian 4D flow acquisition (CART-REF) covering the aorta was acquired. Stroke volumes and peak flows were compared. Additionally, an internal flow validation based on mass conservation was performed on the GRPE-MOCO and GRPE-UNCORR. Statistically significant differences were analyzed using a paired Wilcoxon test. RESULTS: Stroke volumes and peak flows in the aorta between GRPE-MOCO and the CART-REF showed a mean difference of -1.5 ± 10.3 mL (P > 0.05) and 25.2 ± 55.9 mL/s (P > 0.05), respectively. Peak flow in the GRPE-UNCORR data was significantly different compared with CART-REF (P < 0.05). GRPE-MOCO showed higher accuracy for internal consistency analysis than GRPE-UNCORR. CONCLUSION: The proposed 4D flow sequence allows a straight-forward planning by covering the entire thorax and ensures a predictable scan time independent of cardiac cycle variations and breathing patterns.

Fast myocardial T1 mapping using cardiac motion correction.

PURPOSE: To improve the efficiency of native and postcontrast high-resolution cardiac T1 mapping by utilizing cardiac motion correction. METHODS: Common cardiac T1 mapping techniques only acquire data in a small part of the cardiac cycle, leading to inefficient data sampling. Here, we present an approach in which 80% of each cardiac cycle is used for T1 mapping by integration of cardiac motion correction. Golden angle radial data was acquired continuously for 8 s with in-plane resolution of 1.3 × 1.3 mm2 . Cine images were reconstructed for nonrigid cardiac motion estimation. Images at different TIs were reconstructed from the same data, and motion correction was performed prior to T1 mapping. Native T1 mapping was evaluated in healthy subjects. Furthermore, the technique was applied for postcontrast T1 mapping in 5 patients with suspected fibrosis. RESULTS: Cine images with high contrast were obtained, leading to robust cardiac motion estimation. Motion-corrected T1 maps showed myocardial T1 times similar to cardiac-triggered T1 maps obtained from the same data (1288 ± 49 ms and 1259 ± 55 ms, respectively) but with a 34% improved precision (spatial variation: 57.0 ± 12.5 ms and 94.8 ± 15.4 ms, respectively, P < 0.0001) due to the increased amount of data. In postcontrast T1 maps, focal fibrosis could be confirmed with late contrast-enhancement images. CONCLUSION: The proposed approach provides high-resolution T1 maps within 8 s. Data acquisition efficiency for T1 mapping was improved by a factor of 5 by integration of cardiac motion correction, resulting in precise T1 maps.

Simultaneous high-resolution cardiac T1 mapping and cine imaging using model-based iterative image reconstruction.

PURPOSE: To provide high-resolution cardiac T1 mapping of various cardiac phases and cine imaging within a single breath-hold using continuous golden ratio-based radial acquisition and model-based iterative image reconstruction. METHODS: Data acquisition was performed continuously using golden ratio-based radial sampling and multiple inversion pulses were applied independent of the heart rate. Native T1 maps of diastole and systole were reconstructed with in-plane resolution of 1.3 × 1.3 mm2 using model-based iterative image reconstruction. Cine images with 30 cardiac phases were reconstructed from the same data using kt-SENSE. The method was evaluated in a commercially available T1 phantom and 10 healthy subjects. In vivo T1 assessment was carried out segment-wise. RESULTS: Evaluation in the phantom demonstrated accurate T1 times (R2 > 0.99) and insensitivity to the heart rate. In vivo T1 values did not differ between systole and diastole, and T1 times assessed by the proposed approach were longer than measured with a modified Look-Locker inversion recovery (MOLLI) sequence, except for lateral segments. Cine images had a consistent dark-blood contrast and functional assessment was in agreement with assessment based on Cartesian cine scans (difference in ejection fraction: 0.26 ± 2.65%, P = 0.65). CONCLUSION: The proposed approach provides native T1 maps of diastole and systole with high spatial resolution and cine images simultaneously within 16 s, which could strongly improve the scan efficiency.

3D nonrigid motion correction for quantitative assessment of hepatic lesions in DCE-MRI.

PURPOSE: To provide nonrigid respiratory motion-corrected DCE-MRI images with isotropic resolution of 1.5 mm, full coverage of abdomen, and covering the entire uptake curve with a temporal resolution of 6 seconds, for the quantitative assessment of hepatic lesions. METHODS: 3D DCE-MRI data were acquired at 3 T during free breathing for 5 minutes using a 3D T1 -weighted golden-angle radial phase-encoding sequence. Nonrigid respiratory motion information was extracted and used in motion-corrected image reconstruction to obtain high-quality DCE-MRI images with temporal resolution of 6 seconds and isotropic resolution of 1.5 mm. An extended Tofts model was fitted to the dynamic data sets, yielding quantitative parametric maps of endothelial permeability using the hepatic artery as input function. The proposed approach was evaluated in 11 patients (52 ± 17 years, 5 men) with and without known hepatic lesions, undergoing DCE-MRI. RESULTS: Respiratory motion produced artifacts and misalignment between dynamic volumes (lesion average motion amplitude of 3.82 ± 1.11 mm). Motion correction minimized artifacts and improved average contrast-to-noise ratio of hepatic lesions in late phase by 47% (p < .01). Quantitative endothelial permeability maps of motion-corrected data demonstrated enhanced visibility of different pathologies (e.g., metastases, hemangiomas, cysts, necrotic tumor substructure) and showed improved contrast-to-noise ratio by 62% (p < .01) compared with uncorrected data. CONCLUSION: 3D nonrigid motion correction in DCE-MRI improves both visual and quantitative assessment of hepatic lesions by ensuring accurate alignment between 3D DCE images and reducing motion blurring. This approach does not require breath-holds and minimizes scan planning by using a large FOV with isotropic resolution.

Fully integrated 3D high-resolution multicontrast abdominal PET-MR with high scan efficiency.

PURPOSE: To provide 3D multicontrast anatomical MR with high isotropic resolution and metabolic positron emission tomography (PET) images using a respiratory motion-compensated simultaneous PET-MR examination with high scan efficiency. THEORY AND METHODS: Standard abdominal PET-MR examinations combine MR data obtained during multiple breath-holds with free-breathing PET acquisitions, limiting the achievable image resolution and potentially causing misalignment errors between breath-hold and free-breathing data. Here, a 3D free-breathing PET-MR acquisition is presented, yielding T1 and T2 -weighted MR images with an isotropic resolution of 1.5 mm3 . In addition, nonrigid respiratory motion information and respiratory-resolved attenuation-correction maps are obtained without an increase in scan time. Motion information is used in motion-compensated image reconstructions to improve MR and PET image quality while shortening scan times. RESULTS: The proposed approach was evaluated in 11 oncology patients and provided respiratory motion information with an accuracy of 1.3 ± 0.1 mm. Sharpness of anatomical features was increased by 19 ± 13% compared with the uncorrected MR images in a 54 ± 26% shorter scan time than a gated MR acquisition. The MR-based motion information improved uptake values (75 ± 94%) and resolution (16 ± 27%) of simultaneously acquired PET images. CONCLUSIONS: The proposed method provides motion-compensated 3D high-quality MR and PET images in a comprehensive and highly efficient examination. Magn Reson Med 79:900-911, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Manifold learning based ECG-free free-breathing cardiac CINE MRI.

PURPOSE: To present and validate a manifold learning (ML)-based method that can estimate both cardiac and respiratory navigator signals from electrocardiogram (ECG)-free free-breathing cardiac magnetic resonance imaging (MRI) data to achieve self-gated retrospective CINE reconstruction. MATERIALS AND METHODS: In this work the use of the ML method is demonstrated for 2D cardiac CINE to achieve both cardiac and respiratory self-gating without the need of an external navigator or ECG signal. This is achieved by sequentially applying ML to two sets of retrospectively reconstructed real-time images with differing temporal resolutions. A 1D cardiac signal is estimated by applying ML to high temporal resolution real-time images reconstructed from the acquired data. Using the estimated cardiac signal, a 1D respiratory signal was obtained by applying the ML method to low temporal resolution images reconstructed from the same acquired data for each cardiac cycle. Data were acquired in five volunteers with a 2D golden angle radial trajectory in a balanced steady-state free precession (b-SSFP) acquisition. The accuracy of the estimated cardiac signal was calculated as the standard deviation of the temporal difference between the estimated signal and the recorded ECG. The correlation between the estimated respiratory signal and standard pencil beam navigator signal was evaluated. Gated CINE reconstructions (20 cardiac phases per cycle, temporal resolution ∼30 msec) using the estimated cardiac and respiratory signals were qualitatively compared against conventional ECG-gated breath-hold CINE acquisitions. RESULTS: Accurate cardiac signals were estimated with the proposed method, with an error standard deviation in comparison to ECG lower than 20 msec. Respiratory signals estimated with the proposed method achieved a mean cross-correlation of 94% with respect to standard pencil beam navigator signals. Good quality visual scores of 2.80 ± 0.45 (scores from 0, bad, to 4, excellent quality) were observed for the proposed approach in comparison with the conventional ECG-gated breath-hold images (visual score: 3.00 ± 0.71). CONCLUSION: Accurate respiratory and cardiac navigator signals can be estimated using the proposed framework from the acquired data itself, resulting in retrospective self-gated CINE reconstruction with high spatial and temporal quality.

Comparison of image-based and reconstruction-based respiratory motion correction for golden radial phase encoding coronary MR angiography.

PURPOSE: To evaluate two commonly used respiratory motion correction techniques for coronary magnetic resonance angiography (MRA) regarding their dependency on motion estimation accuracy and final image quality and to compare both methods to the respiratory gating approach used in clinical practice. MATERIALS AND METHODS: Ten healthy volunteers were scanned using a non-Cartesian radial phase encoding acquisition. Respiratory motion was corrected for coronary MRA according to two motion correction techniques, image-based (IMC) and reconstruction-based (RMC) respiratory motion correction. Both motion correction approaches were compared quantitatively and qualitatively against a reference standard navigator-based respiratory gating (RG) approach. Quantitative comparisons were performed regarding visible vessel length, vessel sharpness, and total acquisition time. Two experts carried out a visual scoring of image quality. Additionally, numerical simulations were performed to evaluate the effect of motion estimation inaccuracy on RMC and IMC. RESULTS: RMC led to significantly better image quality than IMC (P's paired Student's t-test were smaller than 0.001 for vessel sharpness and visual scoring). RMC did not show a statistically significant difference compared to reference standard RG (vessel length [99% confidence interval]: 86.913 [83.097-95.015], P = 0.107; vessel sharpness: 0.640 [0.605-0.802], P = 0.012; visual scoring: 2.583 [2.410-3.424], P = 0.018) in terms of vessel visualization and image quality while reducing scan times by 56%. Simulations showed higher dependencies for RMC than for IMC on motion estimation inaccuracies. CONCLUSION: RMC provides a similar image quality as the clinically used RG approach but almost halves the scan time and is independent of subjects' breathing patterns. Clinical validation of RMC is now desirable.