High-resolution 3D whole-heart coronary MRA: a study on the combination of data acquisition in multiple breath-holds and 1D residual respiratory motion compensation

Highly accelerated free-breathing real-time 2D flow imaging using compressed sensing and shared velocity encoding

OBJECTIVES

2D real-time (RT) phase-contrast (PC) MRI is a promising alternative to conventional PC MRI, which overcomes problems due to irregular heartbeats or poor respiratory control. This study aims to evaluate a prototype compressed sensing (CS)-accelerated 2D RT-PC MRI technique with shared velocity encoding (SVE) for accurate beat-to-beat flow measurements.

METHODS

The CS RT-PC technique was implemented using a single-shot fast RF-spoiled gradient echo with SVE by symmetric velocity encoding, and acquired with a temporal resolution of 51-56.5 ms in 1-5 heartbeats. Both aortic dissection phantom (n = 8) and volunteer (n = 7) studies were conducted using the prototype CS RT (CS, R = 8), the conventional (GRAPPA, R = 2), and the fully sampled PC sequences on a 3T clinical system. Flow parameters including peak velocity, peak flow rate, net flow rate, and maximum velocity were calculated to compare the performance between different methods using linear regression, intraclass correlation (ICC), and Bland-Altman analyses.

RESULTS

Comparisons of the flow measurements at all locations in the phantoms demonstrated an excellent correlation (all R2 ≥ 0.93) and agreement (all ICC ≥ 0.97) with negligible means of differences. In healthy volunteers, a similarly good correlation (all R2 ≥ 0.80) and agreement (all ICC ≥ 0.90) were observed; however, CS RT slightly underestimated the maximum velocities and flow rates (~ 12%).

CONCLUSION

The highly accelerated CS RT-PC technique is feasible for the evaluation of flow patterns without requiring breath-holding, and it allows for rapid flow assessment in patients with arrhythmia or poor breath-hold capacity.

CLINICAL RELEVANCE STATEMENT

The free-breathing real-time flow MRI technique offers improved spatial and temporal resolutions, as well as the ability to image individual cardiac cycles, resulting in superior image quality compared to the conventional PC technique when imaging patients with arrhythmias, especially those with atrial fibrillation.

KEY POINTS

• The highly accelerated prototype CS RT-PC MRI technique with improved temporal resolution by the concept of SVE is feasible for beat-to-beat flow evaluation without requiring breath-holding. • The results of the phantom and in vivo quantitative flow evaluation show the ability of the prototype CS RT-PC technique to obtain reliable flow measurements similarly to the conventional PC MRI. • With less than 12% underestimation, excellent agreements between the two techniques were shown for the measurements of peak velocities and flow rates.

Simultaneous Optimization of MP2RAGE T1 -weighted (UNI) and FLuid And White matter Suppression (FLAWS) brain images at 7T using Extended Phase Graph (EPG) Simulations

PURPOSE

The MP2RAGE sequence is typically optimized for either T1 -weighted uniform image (UNI) or gray matter-dominant fluid and white matter suppression (FLAWS) contrast images. Here, the purpose was to optimize an MP2RAGE protocol at 7 Tesla to provide UNI and FLAWS images simultaneously in a clinically applicable acquisition time at <0.7 mm isotropic resolution.

METHODS

Using the extended phase graph formalism, the signal evolution of the MP2RAGE sequence was simulated incorporating T2 relaxation, diffusion, RF spoiling, and B1 + variability. Flip angles and TI were optimized at different TRs (TRMP2RAGE ) to produce an optimal contrast-to-noise ratio for UNI and FLAWS images. Simulation results were validated by comparison to MP2RAGE brain scans of 5 healthy subjects, and a final protocol at TRMP2RAGE  = 4000 ms was applied in 19 subjects aged 8-62 years with and without epilepsy.

RESULTS

FLAWS contrast images could be obtained while maintaining >85% of the optimal UNI contrast-to-noise ratio. Using TI1 /TI2 /TRMP2RAGE of 650/2280/4000 ms, 6/8 partial Fourier in the inner phase-encoding direction, and GRAPPA factor = 4 in the other, images with 0.65 mm isotropic resolution were produced in <7.5 min. The contrast-to-noise ratio was around 20% smaller at TRMP2RAGE  = 4000 ms compared to that at TRMP2RAGE  = 5000 ms; however, the 20% shorter duration makes TRMP2RAGE  = 4000 ms a good candidate for clinical applications example, pediatrics.

CONCLUSION

FLAWS and UNI images could be obtained in a single scan with 0.65 mm isotropic resolution, providing a set of high-contrast images and full brain coverage in a clinically applicable scan time. Images with excellent anatomical detail were demonstrated over a wide age range using the optimized parameter set.

A Low-Cost Flexible Perforated Respiratory Sensor Based on Platinum for Continuous Respiratory Monitoring

Monitoring sleep conditions is of importance for sleep quality evaluation and sleep disease diagnosis. Accurate respiration detection provides key information about sleep conditions. Here, we propose a perforated temperature sensor that can be worn below the nasal cavity to monitor breath. The sensing system consists of two perforated temperature sensors, signal conditioning circuits, a transmission module, and a supporting analysis algorithm. The perforated structure effectively enhances the sensitivity of the system and shortens the response time. The sensor's response time is 0.07 s in air and sensitivity is 1.4‱°C^-1. The device can achieve a monitoring respiratory temperature range between normal room temperature and 40 °C. The simple and standard micromachining process ensures low cost and high reproducibility. We achieved the monitoring of different breathing patterns, such as normal breathing, panting, and apnea, which can be applied to sleep breath monitoring and exercise information recording.

Simultaneous multi-parametric acquisition and reconstruction techniques in cardiac magnetic resonance imaging: Basic concepts and status of clinical development

Simultaneous multi-parametric acquisition and reconstruction techniques (SMART) are gaining attention for their potential to overcome some of cardiovascular magnetic resonance imaging's (CMR) clinical limitations. The major advantages of SMART lie within their ability to simultaneously capture multiple "features" such as cardiac motion, respiratory motion, T1/T2 relaxation. This review aims to summarize the overarching theory of SMART, describing key concepts that many of these techniques share to produce co-registered, high quality CMR images in less time and with less requirements for specialized personnel. Further, this review provides an overview of the recent developments in the field of SMART by describing how they work, the parameters they can acquire, their status of clinical testing and validation, and by providing examples for how their use can improve the current state of clinical CMR workflows. Many of the SMART are in early phases of development and testing, thus larger scale, controlled trials are needed to evaluate their use in clinical setting and with different cardiac pathologies.

Isotropic 3D compressed sensing (CS) based sequence is comparable to 2D-LGE in left ventricular scar quantification in different disease entities

The goal of this study was to evaluate a three-dimensional compressed sensing (3D-CS) LGE prototype sequence for the detection and quantification of myocardial fibrosis in patients with chronic myocardial infarction (CMI) and myocarditis (MYC) compared with a 2D-LGE standard. Patients with left-ventricular LGE due to CMI (n = 33) or MYC (n = 20) were prospectively recruited. 2D-LGE and 3D-CS images were acquired in random order at 1.5 Tesla. 3D-CS short axis (SAX) images were reconstructed corresponding to 2D SAX images. LGE was quantitatively assessed on patient and segment level using semi-automated threshold methods. Image quality (4-point scoring system), Contrast-ratio (CR) and acquisition times were compared. There was no significant difference between 2D and 3D sequences regarding global LGE (%) (CMI [2D-LGE: 11.4 ± 7.5; 3D-LGE: 11.5 ± 8.5; p = 0.99]; MYC [2D-LGE: 27.0 ± 15.7; 3D-LGE: 26.2 ± 13.1; p = 0.70]) and segmental LGE-extent (p = 0.63). 3D-CS identified papillary infarction in 5 cases which was not present in 2D images. 2D-LGE acquisition time was shorter (2D: median: 06:59 min [IQR: 05:51-08:18]; 3D: 14:48 min [12:45-16:57]). 3D-CS obtained better quality scores (2D: 2.06 ± 0.56 vs. 3D: 2.29 ± 0.61). CR did not differ (p = 0.63) between basal and apical regions in 3D-CS images but decreased significantly in 2D apical images (CR basal: 2D: 0.77 ± 0.11, 3D: 0.59 ± 0.10; CR apical: 2D: 0.64 ± 0.17, 3D: 0.53 ± 0.11). 3D-LGE shows high congruency with standard LGE and allows better identification of small lesions. However, the current 3D-CS LGE sequence did not provide PSIR reconstruction and acquisition time was longer.

The Applications of Artificial Intelligence in Cardiovascular Magnetic Resonance-A Comprehensive Review

Cardiovascular disease remains an integral field on which new research in both the biomedical and technological fields is based, as it remains the leading cause of mortality and morbidity worldwide. However, despite the progress of cardiac imaging techniques, the heart remains a challenging organ to study. Artificial intelligence (AI) has emerged as one of the major innovations in the field of diagnostic imaging, with a dramatic impact on cardiovascular magnetic resonance imaging (CMR). AI will be increasingly present in the medical world, with strong potential for greater diagnostic efficiency and accuracy. Regarding the use of AI in image acquisition and reconstruction, the main role was to reduce the time of image acquisition and analysis, one of the biggest challenges concerning magnetic resonance; moreover, it has been seen to play a role in the automatic correction of artifacts. The use of these techniques in image segmentation has allowed automatic and accurate quantification of the volumes and masses of the left and right ventricles, with occasional need for manual correction. Furthermore, AI can be a useful tool to directly help the clinician in the diagnosis and derivation of prognostic information of cardiovascular diseases. This review addresses the applications and future prospects of AI in CMR imaging, from image acquisition and reconstruction to image segmentation, tissue characterization, diagnostic evaluation, and prognostication.

3D Dixon water-fat LGE imaging with image navigator and compressed sensing in cardiac MRI

Objectives

To evaluate an image-navigated isotropic high-resolution 3D late gadolinium enhancement (LGE) prototype sequence with compressed sensing and Dixon water-fat separation in a clinical routine setting.

Material and methods

Forty consecutive patients scheduled for cardiac MRI were enrolled prospectively and examined with 1.5 T MRI. Overall subjective image quality, LGE pattern and extent, diagnostic confidence for detection of LGE, and scan time were evaluated and compared to standard 2D LGE imaging. Robustness of Dixon fat suppression was evaluated for 3D Dixon LGE imaging. For statistical analysis, the non-parametric Wilcoxon rank sum test was performed.

Results

LGE was rated as ischemic in 9 patients and non-ischemic in 11 patients while it was absent in 20 patients. Image quality and diagnostic confidence were comparable between both techniques (p = 0.67 and p = 0.66, respectively). LGE extent with respect to segmental or transmural myocardial enhancement was identical between 2D and 3D (water-only and in-phase). LGE size was comparable (3D 8.4 ± 7.2 g, 2D 8.7 ± 7.3 g, p = 0.19). Good or excellent fat suppression was achieved in 93% of the 3D LGE datasets. In 6 patients with pericarditis, the 3D sequence with Dixon fat suppression allowed for a better detection of pericardial LGE. Scan duration was significantly longer for 3D imaging (2D median 9:32 min vs. 3D median 10:46 min, p = 0.001).

Conclusion

The 3D LGE sequence provides comparable LGE detection compared to 2D imaging and seems to be superior in evaluating the extent of pericardial involvement in patients suspected with pericarditis due to the robust Dixon fat suppression.

Key Points

• Three-dimensional LGE imaging provides high-resolution detection of myocardial scarring.

• Robust Dixon water-fat separation aids in the assessment of pericardial disease.

• The 2D image navigator technique enables 100% respiratory scan efficacy and permits predictable scan times.

Highly accelerated aortic 4D flow MRI using compressed sensing: Performance at different acceleration factors in patients with aortic disease

PURPOSE

To systematically assess the feasibility and performance of a highly accelerated compressed sensing (CS) 4D flow MRI framework at three different acceleration factors (R) for the quantification of aortic flow dynamics and wall shear stress (WSS) in patients with aortic disease.

METHODS

Twenty patients with aortic disease (58 ± 15 y old; 19 M) underwent four 4D flow scans: one conventional (GRAPPA, R = 2) and three CS 4D flows with R = 5.7, 7.7, and 10.2. All scans were acquired with otherwise equivalent imaging parameters on a 1.5T scanner. Peak-systolic velocity (V_max ), peak flow (Q_max ), and net flow (Q_net ) were quantified at the ascending aorta (AAo), arch, and descending aorta (DAo). WSS was calculated at six regions within the AAo and arch.

RESULTS

Mean scan times for the conventional and CS 4D flows with R = 5.7, 7.7, and 10.2 were 9:58 ± 2:58 min, 3:40 ± 1:19 min, 2:50 ± 0:56 min, and 2:05 ± 0:42 min, respectively. V_max , Q_max , and Q_net were significantly underestimated by all CS protocols (underestimation ≤ -7%, -9%, and -10% by CS, R = 5.7, 7.7, and 10.2, respectively). WSS measurements showed the highest underestimation by all CS protocols (underestimation ≤ -9%, -12%, and -14% by CS, R = 5.7, 7.7, and 10.2).

CONCLUSIONS

Highly accelerated aortic CS 4D flow at R = 5.7, 7.7, and 10.2 showed moderate agreement with the conventional 4D flow, despite systematically underestimating various hemodynamic parameters. The shortened scan time may enable the clinical translation of CS 4D flow, although potential hemodynamic underestimation should be considered when interpreting the results.

Comparison of compressed sensing and conventional coronary magnetic resonance angiography for detection of coronary artery stenosis

PURPOSE

This study aimed to compare the efficacy of compressed sensing (CS) and conventional coronary magnetic resonance angiography (CMRA) in detecting coronary artery stenosis.

METHOD

Twenty-eight patients underwent 3 T contrast-enhanced CS and conventional CMRA; for late gadolinium enhancement (LGE) imaging, 0.1 mmol/kg gadolinium medium was infused. CS CMRA was scanned within the LGE waiting time. After the LGE image acquisition, conventional CMRA was performed. The diagnostic performance of both CMRA for the detection of significant stenosis was evaluated using coronary angiography as a reference. The analysis was conducted to examine the three main coronary artery vessels: left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA). These arteries were subdivided into 8 segments (LAD; main, proximal, and middle, LCX; proximal and distal, RCA; proximal, middle, and distal). Of these, hypoplastic segments and vessels after coronary stent implantation were excluded. The acquisition time of CS CMRA was compared with that of conventional CMRA.

RESULTS

The coronary arteries were evaluated in 197 segments. The sensitivity, specificity, and accuracy of CS CMRA in detecting significant stenosis were 85.2 %, 82.5 %, and 83.2 %, respectively, on a per-segment basis. Those of conventional CMRA were 85.2 %, 86.7 %, and 86.3 %, respectively. The acquisition time was 207 s (range, 144-258 s) for CS and 975 s (range, 787-1226s) for conventional CMRA (p < 0.001).

CONCLUSIONS

Similar to conventional CMRA, CS CMRA has shown potential for the detection of significant coronary artery stenosis.

From Compressed-Sensing to Artificial Intelligence-Based Cardiac MRI Reconstruction

Cardiac magnetic resonance (CMR) imaging is an important tool for the non-invasive assessment of cardiovascular disease. However, CMR suffers from long acquisition times due to the need of obtaining images with high temporal and spatial resolution, different contrasts, and/or whole-heart coverage. In addition, both cardiac and respiratory-induced motion of the heart during the acquisition need to be accounted for, further increasing the scan time. Several undersampling reconstruction techniques have been proposed during the last decades to speed up CMR acquisition. These techniques rely on acquiring less data than needed and estimating the non-acquired data exploiting some sort of prior information. Parallel imaging and compressed sensing undersampling reconstruction techniques have revolutionized the field, enabling 2- to 3-fold scan time accelerations to become standard in clinical practice. Recent scientific advances in CMR reconstruction hinge on the thriving field of artificial intelligence. Machine learning reconstruction approaches have been recently proposed to learn the non-linear optimization process employed in CMR reconstruction. Unlike analytical methods for which the reconstruction problem is explicitly defined into the optimization process, machine learning techniques make use of large data sets to learn the key reconstruction parameters and priors. In particular, deep learning techniques promise to use deep neural networks (DNN) to learn the reconstruction process from existing datasets in advance, providing a fast and efficient reconstruction that can be applied to all newly acquired data. However, before machine learning and DNN can realize their full potentials and enter widespread clinical routine for CMR image reconstruction, there are several technical hurdles that need to be addressed. In this article, we provide an overview of the recent developments in the area of artificial intelligence for CMR image reconstruction. The underlying assumptions of established techniques such as compressed sensing and low-rank reconstruction are briefly summarized, while a greater focus is given to recent advances in dictionary learning and deep learning based CMR reconstruction. In particular, approaches that exploit neural networks as implicit or explicit priors are discussed for 2D dynamic cardiac imaging and 3D whole-heart CMR imaging. Current limitations, challenges, and potential future directions of these techniques are also discussed.

Accelerated coronary MRI with sRAKI: A database-free self-consistent neural network k-space reconstruction for arbitrary undersampling

Purpose

To accelerate coronary MRI acquisitions with arbitrary undersampling patterns by using a novel reconstruction algorithm that applies coil self-consistency using subject-specific neural networks.

Methods

Self-consistent robust artificial-neural-networks for k-space interpolation (sRAKI) performs iterative parallel imaging reconstruction by enforcing self-consistency among coils. The approach bears similarity to SPIRiT, but extends the linear convolutions in SPIRiT to nonlinear interpolation using convolutional neural networks (CNNs). These CNNs are trained individually for each scan using the scan-specific autocalibrating signal (ACS) data. Reconstruction is performed by imposing the learned self-consistency and data-consistency, which enables sRAKI to support random undersampling patterns. Fully-sampled targeted right coronary artery MRI was acquired in six healthy subjects. The data were retrospectively undersampled, and reconstructed using SPIRiT, l₁-SPIRiT and sRAKI for acceleration rates of 2 to 5. Additionally, prospectively undersampled whole-heart coronary MRI was acquired to further evaluate reconstruction performance.

Results

sRAKI reduces noise amplification and blurring artifacts compared with SPIRiT and l₁-SPIRiT, especially at high acceleration rates in targeted coronary MRI. Quantitative analysis shows that sRAKI outperforms these techniques in terms of normalized mean-squared-error (~44% and ~21% over SPIRiT and l1-SPIRiT at rate 5) and vessel sharpness (~10% and ~20% over SPIRiT and l₁-SPIRiT at rate 5). Whole-heart data shows the sharpest coronary arteries when resolved using sRAKI, with 11% and 15% improvement in vessel sharpness over SPIRiT and l₁-SPIRiT, respectively.

Conclusion

sRAKI is a database-free neural network-based reconstruction technique that may further accelerate coronary MRI with arbitrary undersampling patterns, while improving noise resilience over linear parallel imaging and image sharpness over l₁ regularization techniques.

Feasibility of contrast-enhanced coronary artery magnetic resonance angiography using compressed sensing

BACKGROUND

Coronary magnetic resonance angiography (CMRA) is a promising technique for assessing the coronary arteries. However, a disadvantage of CMRA is the comparatively long acquisition time. Compressed sensing (CS) can considerably reduce the scan time. The aim of this study was to verify the feasibility of CS CMRA scanning during the waiting time between contrast injection and late gadolinium enhancement (LGE) scan in a clinical protocol.

METHODS

Fifty clinical patients underwent contrast-enhanced CS CMRA and conventional CMRA on a 3 T CMR scanner. After contrast injection, CS CMRA was scanned during the waiting time for LGE CMR. A conventional CMRA scan was performed after LGE CMR. We assessed acquisition times and coronary artery image quality for each segment on a 4-point scale. Visible vessel length, sharpness and diameter of right (RCA), left anterior descending (LAD), and left circumflex (LCX) coronary arteries were also quantitatively compared among the scans.

RESULTS

All CS CMRA scans were successfully performed within the LGE waiting time. The median total scan time was 207 s (163, 259 s) for CS and 785 s (698, 975 s) for conventional CMRA (p < 0.001). No significant differences were observed in image quality scores, vessel length measurements, sharpness, and diameter between CS and conventional CMRA.

CONCLUSIONS

We could achieve all CS CMRA scans within the LGE waiting time. Contrast-enhanced CS CMRA could considerably shorten the scan time while maintaining image quality compared with conventional CMRA.

Aortic 4D flow MRI in 2 minutes using compressed sensing, respiratory controlled adaptive k-space reordering, and inline reconstruction

PURPOSE

To evaluate the accuracy and feasibility of a free-breathing 4D flow technique using compressed sensing (CS), where 4D flow imaging of the thoracic aorta is performed in 2 min with inline image reconstruction on the MRI scanner in less than 5 min.

METHODS

The 10 in vitro 4D flow MRI scans were performed with different acceleration rates on a pulsatile flow phantom (9 CS acceleration factors [R = 5.4-14.1], 1 generalized autocalibrating partially parallel acquisition [GRAPPA] R = 2). Based on in vitro results, CS-accelerated 4D flow of the thoracic aorta was acquired in 20 healthy volunteers (38.3 ± 15.2 years old) and 11 patients with aortic disease (61.3 ± 15.1 years) with R = 7.7. A conventional 4D flow scan was acquired with matched spatial coverage and temporal resolution.

RESULTS

CS depicted similar hemodynamics to conventional 4D flow in vitro, and in vivo, with >70% reduction in scan time (volunteers: 1:52 ± 0:25 versus 7:25 ± 2:35 min). Net flow values were within 3.5% in healthy volunteers, and voxel-by-voxel comparison demonstrated good agreement. CS significantly underestimated peak velocities (v_max ) and peak flow (Q_max ) in both volunteers and patients (volunteers: v_max , -16.2% to -9.4%, Q_max : -11.6% to -2.9%, patients: v_max , -11.2% to -4.0%; Q_max , -10.2% to -5.8%).

CONCLUSION

Aortic 4D flow with CS is feasible in a two minute scan with less than 5 min for inline reconstruction. While net flow agreement was excellent, CS with R = 7.7 produced underestimation of Q_max and v_max ; however, these were generally within 13% of conventional 4D flow-derived values. This approach allows 4D flow to be feasible in clinical practice for comprehensive assessment of hemodynamics.

Accelerated Time-of-Flight Magnetic Resonance Angiography with Sparse Undersampling and Iterative Reconstruction for the Evaluation of Intracranial Arteries

OBJECTIVE

To compare the image quality of three-dimensional time-of-flight (TOF) magnetic resonance angiography (MRA) with sparse undersampling and iterative reconstruction (sparse TOF) with that of conventional TOF MRA.

MATERIALS AND METHODS

This study included 56 patients who had undergone sparse TOF MRA for intracranial artery evaluation on a 3T MR scanner. Conventional TOF MRA scans were also acquired from 29 patients with matched acquisition times and another 27 patients with matched scanning parameters. The image quality was scored using a five-point scale based on the delineation of arterial vessel segments, artifacts, overall vessel visualization, and overall image quality by two radiologists independently, and the data were analyzed using the non-parametric Wilcoxon signed-rank test. Contrast ratios (CRs) of vessels were compared using the paired t test. Interobserver agreement was calculated using the kappa test.

RESULTS

Compared with conventional TOF at the same spatial resolution, sparse TOF with an acceleration factor of 3.5 could reduce acquisition time by 40% and showed comparable image quality. In addition, when compared with conventional TOF with the same acquisition time, sparse TOF with an acceleration factor of 5 could also achieve higher spatial resolution, better delineation of vessel segments, fewer artifacts, higher image quality, and a higher CR (p < 0.05). Good-to-excellent interobserver agreement (κ: 0.65-1.00) was obtained between the two radiologists.

CONCLUSION

Compared with conventional TOF, sparse TOF can achieve equivalent image quality in a reduced duration. Furthermore, using the same acquisition time, sparse TOF could improve the delineation of vessels and decrease image artifacts.

Shearlet-based compressed sensing for fast 3D cardiac MR imaging using iterative reweighting

High-resolution three-dimensional (3D) cardiovascular magnetic resonance (CMR) is a valuable medical imaging technique, but its widespread application in clinical practice is hampered by long acquisition times. Here we present a novel compressed sensing (CS) reconstruction approach using shearlets as a sparsifying transform allowing for fast 3D CMR (3DShearCS) using 3D radial phase encoding (RPE). An iterative reweighting scheme was applied during image reconstruction to ensure fast convergence and high image quality. Shearlets are mathematically optimal for a simplified model of natural images and have been proven to be more efficient than classical systems such as wavelets. 3DShearCS was compared to three other commonly used reconstruction approaches. Image quality was assessed quantitatively using general image quality metrics and using clinical diagnostic scores from expert reviewers. The proposed technique had lower relative errors, higher structural similarity and higher diagnostic scores compared to the other reconstruction techniques especially for high undersampling factors, i.e. short scan times. 3DShearCS provided ensured accurate depiction of cardiac anatomy for fast imaging and could help to promote 3D high-resolution CMR in clinical practice.

Automated Curved and Multiplanar Reformation for Screening of the Proximal Coronary Arteries in MR Angiography

Congenital anomalies of the coronary ostia can lead to sudden death. A screening solution would be useful to prevent adverse outcomes for the affected individuals. To be considered for integration into clinical routine, such a procedure must meet strict constraints in terms of invasiveness, time and user interaction. Imaging must be fast and seamlessly integrable into the clinical process. Non-contrast enhanced coronary magnetic resonance angiography (MRA) is well suited for this. Furthermore, planar reformations proved effective to reduce the acquired volumetric datasets to 2D images. These usually require time consuming user interaction, though. To fulfill the aforementioned challenges, we present a fully automated solution for imaging and reformatting of the proximal coronary arteries which enables rapid screening of these. The proposed pipeline consists of: (I) highly accelerated single breath-hold MRA data acquisition, (II) coronary ostia detection and vessel centerline extraction, and (III) curved planar reformation of the proximal coronary arteries, as well as multiplanar reformation of the coronary ostia. The procedure proved robust and effective in ten volunteer data sets. Imaging of the proximal coronary arteries took 24 ± 5 s and was successful within one breath-hold for all patients. The extracted centerlines achieve an overlap of 0.76 ± 0.18 compared to the reference standard and the average distance of the centerline points from the spherical surface for reformation was 1.1 ± 0.51 mm. The promising results encourage further experiments on patient data, particularly in coronary ostia anomaly screening.

Non-contrast compressed sensing whole-heart coronary magnetic resonance angiography at 3T: A comparison with conventional imaging

OBJECTIVES

Whole-heart coronary magnetic resonance angiography (MRA) is a promising non-contrast, radiation-free technique for assessing the coronary artery. Yet, a disadvantage of coronary MRA is the relatively long acquisition time. The purpose of this study was to evaluate the scan time and image quality of compressed sensing (CS) coronary MRA compared with conventional coronary MRA.

MATERIALS AND METHODS

Twenty healthy volunteers underwent navigator-gated coronary MRA with a CS prototype sequence and conventional navigator-gated coronary MRA on a clinical 3T MRI scanner without contrast medium. The spatial resolutions were 1.33 × 1.33 × 1.20 mm³ for CS and 1.33 × 1.33 × 1.48 mm³ interpolated to 0.70 × 0.70 × 1.20 mm³ for conventional, respectively. We compared acquisition times, rated image quality on a 4-point scale (RCA; proximal, middle, and distal, LAD; main, proximal, middle, and distal, LCX; proximal and distal), and measured the visualized vessel lengths of three vessels.

RESULTS

The mean acceptance rates were 44.9% for CS coronary MRA and 48.7% for conventional coronary MRA (p = .39). The mean effective scan time was 3 min 45 s for CS coronary MRA and 15 min 6 s for conventional coronary MRA (p < 0.001). Image quality scores were significantly lower for CS coronary MRA than for conventional coronary MRA (3.4 ± 0.7 for CS vs. 3.8 ± 0.4 for conventional; p < 0.0001). Conventional coronary MRA images were scored >3.4 in all segments on average, while CS coronary MRA images were scored >3.2 (good quality for diagnosis) in almost all segments, with only the distal RCA segment graded 2.9 on average. The average visible vessel lengths for CS and conventional coronary MRA were as follows: 11.5 ± 4.4 cm and 12.5 ± 4.8 cm for the RCA, respectively (p < 0.05, 95% limits of agreement [LOA]; -3.6 to 1.6 cm); 10.6 ± 3.0 cm and 11.1 ± 2.9 cm for the LAD, respectively (p = .15, 95% LOA -4.0 to 2.8 cm); and 7.1 ± 2.2 cm and 8.2 ± 2.5 cm for the LCX, respectively (p < 0.05, 95% LOA -4.0 to 1.7 cm).

CONCLUSIONS

Non-contrast coronary MRA using CS could largely shorten acquisition time, compared with conventional navigator-gated coronary MRA, while maintaining acceptable visualization at 3T.

Free breathing whole-heart 3D CINE MRI with self-gated Cartesian trajectory

Purpose

To present a method that uses a novel free-running self-gated acquisition to achieve isotropic resolution in whole heart 3D Cartesian cardiac CINE MRI.

Material and methods

3D cardiac CINE MRI using navigator gating results in long acquisition times. Recently, several frameworks based on self-gated non-Cartesian trajectories have been proposed to accelerate this acquisition. However, non-Cartesian reconstructions are computationally expensive due to gridding, particularly in 3D. In this work, we propose a novel highly efficient self-gated Cartesian approach for 3D cardiac CINE MRI. Acquisition is performed using CArtesian trajectory with Spiral PRofile ordering and Tiny golden angle step for eddy current reduction (so called here CASPR-Tiger). Data is acquired continuously under free breathing (retrospective ECG gating, no preparation pulses interruption) for 4–5 min and 4D whole-heart volumes (3D + cardiac phases) with isotropic spatial resolution are reconstructed from all available data using a soft gating technique combined with temporal total variation (TV) constrained iterative SENSE reconstruction.

Results

For data acquired on eight healthy subjects and three patients, the reconstructed images using the proposed method had good contrast and spatio-temporal variations, correctly recovering diastolic and systolic cardiac phases. Non-significant differences (P > 0.05) were observed in cardiac functional measurements obtained with proposed 3D approach and gold standard 2D multi-slice breath-hold acquisition.

Conclusion

The proposed approach enables isotropic 3D whole heart Cartesian cardiac CINE MRI in 4 to 5 min free breathing acquisition.

•

A novel self-gated 3D Cartesian acquisition is proposed for free breathing whole-heart cardiac MRI

•

The proposed framework has efficient k-space sampling, better eddy current performance and high computational efficiency

•

The Proposed method is able to achieve high spatio-temporal resolution 3D cardiac CINE

•

The proposed method only requires four to five minute free breathing scan

Self-gated 4D multiphase, steady-state imaging with contrast enhancement (MUSIC) using rotating cartesian K-space (ROCK): Validation in children with congenital heart disease

PURPOSE

To develop and validate a cardiac-respiratory self-gating strategy for the recently proposed multiphase steady-state imaging with contrast enhancement (MUSIC) technique.

METHODS

The proposed SG strategy uses the ROtating Cartesian K-space (ROCK) sampling, which allows for retrospective k-space binning based on motion surrogates derived from k-space center line. The k-space bins are reconstructed using a compressed sensing algorithm. Ten pediatric patients underwent cardiac MRI for clinical reasons. The original MUSIC and 2D-CINE images were acquired as a part of the clinical protocol, followed by the ROCK-MUSIC acquisition, all under steady-state intravascular distribution of ferumoxytol. Subjective scores and image sharpness were used to compare the images of ROCK-MUSIC and original MUSIC.

RESULTS

All scans were completed successfully without complications. The ROCK-MUSIC acquisition took 5 ± 1 min, compared to 8 ± 2 min for the original MUSIC. Image scores of ROCK-MUSIC were significantly better than original MUSIC at the ventricular outflow tracts (3.9 ± 0.3 vs. 3.3 ± 0.6, P < 0.05). There was a strong trend toward superior image scores for ROCK-MUSIC in the other anatomic locations.

CONCLUSION

ROCK-MUSIC provided images of equal or superior image quality compared to original MUSIC, and this was achievable with 40% savings in scan time and without the need for physiologic signal. Magn Reson Med 78:472-483, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Four-dimensional respiratory motion-resolved whole heart coronary MR angiography

PURPOSE

Free-breathing whole-heart coronary MR angiography (MRA) commonly uses navigators to gate respiratory motion, resulting in lengthy and unpredictable acquisition times. Conversely, self-navigation has 100% scan efficiency, but requires motion correction over a broad range of respiratory displacements, which may introduce image artifacts. We propose replacing navigators and self-navigation with a respiratory motion-resolved reconstruction approach.

METHODS

Using a respiratory signal extracted directly from the imaging data, individual signal-readouts are binned according to their respiratory states. The resultant series of undersampled images are reconstructed using an extradimensional golden-angle radial sparse parallel imaging (XD-GRASP) algorithm, which exploits sparsity along the respiratory dimension. Whole-heart coronary MRA was performed in 11 volunteers and four patients with the proposed methodology. Image quality was compared with that obtained with one-dimensional respiratory self-navigation.

RESULTS

Respiratory-resolved reconstruction effectively suppressed respiratory motion artifacts. The quality score for XD-GRASP reconstructions was greater than or equal to self-navigation in 80/88 coronary segments, reaching diagnostic quality in 61/88 segments versus 41/88. Coronary sharpness and length were always superior for the respiratory-resolved datasets, reaching statistical significance (P < 0.05) in most cases.

CONCLUSION

XD-GRASP represents an attractive alternative for handling respiratory motion in free-breathing whole heart MRI and provides an effective alternative to self-navigation. Magn Reson Med 77:1473-1484, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Is there an optimal respiratory reference position for self-navigated whole-heart coronary MR angiography?

PURPOSE

To test the direct influence of the reference respiratory position on image quality for self-navigated whole-heart coronary MRI.

METHODS

Self-navigated whole-heart coronary MRI was performed in 11 healthy adult subjects. Respiratory motion was compensated for by using three different respiratory reference positions of the heart: end-inspiratory, end-expiratory, and the mean of the entire respiratory excursion. All datasets were reconstructed without motion compensation for comparison. Image quality was assessed in all reconstructions using signal-to-noise ratio (SNR) and contrst-to-noise ratio (CNR) measurements, as well as percentage vessel sharpness and visible length of the coronary arteries.

RESULTS

While SNR and CNR remained close to constant in all reconstructions, a clear and significant improvement in vessel sharpness was identified in all motion corrected datasets with respect to their uncorrected counterpart (e.g., percentage sharpness of the proximal right coronary artery (RCA): 61.6 ± 8.2% for end-inspiration, 64.1 ± 10.7% for end-expiration, and 63.3 ± 7.0% for the mean respiratory position versus 55.0 ± 10.4 for the uncorrected datasets; P < 0.05). Among all motion corrected reconstructions, the use of an end-expiratory reference position most consistently provided the highest image quality. In particular, some of the improvements in vessel sharpness and length measured for end-expiration were statistically significant with respect to the reconstructions performed at end-inspiration (e.g., percentage sharpness of the proximal left anterior descending coronary: 58.2 ± 7.4% versus 55.8 ± 8.4%; P < 0.05; and visible length of the RCA: 125.7 ± 25.9 mm versus 114.4 ± 27.4 mm; P < 0.05).

CONCLUSION

The use of end-expiration as a reference position for respiratory motion correction in free-breathing self-navigated whole heart coronary MRA significantly improves image quality. J

Highly undersampled contrast-enhanced MRA with iterative reconstruction: Integration in a clinical setting

PURPOSE

To integrate, optimize, and evaluate a three-dimensional (3D) contrast-enhanced sparse MRA technique with iterative reconstruction on a standard clinical MR system.

METHODS

Data were acquired using a highly undersampled Cartesian spiral phyllotaxis sampling pattern and reconstructed directly on the MR system with an iterative SENSE technique. Undersampling, regularization, and number of iterations of the reconstruction were optimized and validated based on phantom experiments and patient data. Sparse MRA of the whole head (field of view: 265 × 232 × 179 mm(3) ) was investigated in 10 patient examinations.

RESULTS

High-quality images with 30-fold undersampling, resulting in 0.7 mm isotropic resolution within 10 s acquisition, were obtained. After optimization of the regularization factor and of the number of iterations of the reconstruction, it was possible to reconstruct images with excellent quality within six minutes per 3D volume. Initial results of sparse contrast-enhanced MRA (CEMRA) in 10 patients demonstrated high-quality whole-head first-pass MRA for both the arterial and venous contrast phases.

CONCLUSION

While sparse MRI techniques have not yet reached clinical routine, this study demonstrates the technical feasibility of high-quality sparse CEMRA of the whole head in a clinical setting. Sparse CEMRA has the potential to become a viable alternative where conventional CEMRA is too slow or does not provide sufficient spatial resolution.

Self-navigation with compressed sensing for 2D translational motion correction in free-breathing coronary MRI: a feasibility study

Purpose

Respiratory motion correction remains a challenge in coronary magnetic resonance imaging (MRI) and current techniques, such as navigator gating, suffer from sub-optimal scan efficiency and ease-of-use. To overcome these limitations, an image-based self-navigation technique is proposed that uses “sub-images” and compressed sensing (CS) to obtain translational motion correction in 2D. The method was preliminarily implemented as a 2D technique and tested for feasibility for targeted coronary imaging.

Methods

During a 2D segmented radial k-space data acquisition, heavily undersampled sub-images were reconstructed from the readouts collected during each cardiac cycle. These sub-images may then be used for respiratory self-navigation. Alternatively, a CS reconstruction may be used to create these sub-images, so as to partially compensate for the heavy undersampling. Both approaches were quantitatively assessed using simulations and in vivo studies, and the resulting self-navigation strategies were then compared to conventional navigator gating.

Results

Sub-images reconstructed using CS showed a lower artifact level than sub-images reconstructed without CS. As a result, the final image quality was significantly better when using CS-assisted self-navigation as opposed to the non-CS approach. Moreover, while both self-navigation techniques led to a 69% scan time reduction (as compared to navigator gating), there was no significant difference in image quality between the CS-assisted self-navigation technique and conventional navigator gating, despite the significant decrease in scan time.

Conclusions

CS-assisted self-navigation using 2D translational motion correction demonstrated feasibility of producing coronary MRA data with image quality comparable to that obtained with conventional navigator gating, and does so without the use of additional acquisitions or motion modeling, while still allowing for 100% scan efficiency and an improved ease-of-use. In conclusion, compressed sensing may become a critical adjunct for 2D translational motion correction in free-breathing cardiac imaging with high spatial resolution. An expansion to modern 3D approaches is now warranted.