Assessment of Beat-To-Beat Variability in Left Atrial Hemodynamics Using Real Time Phase Contrast MRI in Patients With Atrial Fibrillation.

BACKGROUND: Hemodynamic assessment of left atrial (LA) flow using phase contrast MRI provides insight into thromboembolic risk in atrial fibrillation (AF). However, conventional flow imaging techniques are averaged over many heartbeats. PURPOSE: To evaluate beat-to-beat variability and LA hemodynamics in patients with AF using real time phase contrast (RTPC) MRI. STUDY TYPE: Prospective. SUBJECTS: Thirty-five patients with history of AF (68 ± 10 years, nine female), 10 healthy controls (57 ± 19 years, four female). FIELD STRENGTH/SEQUENCE: 5T, 2D RTPC with through-plane velocity-encoded gradient echo sequence and 4D flow MRI with three-directional velocity-encoded gradient echo sequence. ASSESSMENT: RTPC was continuously acquired for a mid-LA slice in all subjects. 4D flow data were interpolated at the RTPC location and normally projected for comparison with RTPC. RR intervals extracted from RTPC were used to calculate heart rate variability (HRV = interquartile range over median × 100%). Patients were classified into low (<9.7%) and high (>9.7%) HRV groups. LA peak/mean velocity and stasis (%velocities < 5.8 cm/sec) were calculated from segmented 2D images. Variability in RTPC flow metrics was quantified by coefficient of variation (CV) over all cycles. STATISTICAL TESTS: Pearson's correlation coefficient (r), Bland-Altman analysis, Kruskal-Wallis test. A P value < 0.05 was considered statistically significant. RESULTS: RTPC and 4D flow measurements were strongly/significantly correlated for all hemodynamic parameters (R2  = 0.75-0.83) in controls. Twenty-four patients had low HRV (mean = 4 ± 2%) and 11 patients had high HRV (27 ± 9%). In patients, increased HRV was significantly correlated with CV of peak velocity (r = 0.67), mean velocity (r = 0.51), and stasis (r = 0.41). A stepwise decrease in peak/mean velocity and increase in stasis was observed when comparing controls vs. low HRV vs. high HRV groups. Mean velocity and stasis differences were significant for control vs. high HRV groups. CONCLUSIONS: RTPC may be suitable for assessing the impact of HRV on hemodynamics and provide insight for AF management in highly arrhythmic patients. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Quantification of changes in myocardial T1 * values with exercise cardiac MRI using a free-breathing non-electrocardiograph radial imaging.

PURPOSE: To develop and evaluate a free breathing non-electrocardiograph (ECG) myocardial T1 * mapping sequence using radial imaging to quantify the changes in myocardial T1 * between rest and exercise (T1 *reactivity ) in exercise cardiac MRI (Ex-CMR). METHODS: A free-running T1 * sequence was developed using a saturation pulse followed by three Look-Locker inversion-recovery experiments. Each Look-Locker continuously acquired data as radial trajectory using a low flip-angle spoiled gradient-echo readout. Self-navigation was performed with a temporal resolution of ∼100 ms for retrospectively extracting respiratory motion. The mid-diastole phase for every cardiac cycle was retrospectively detected on the recorded electrocardiogram signal using an empirical model. Multiple measurements were performed to obtain mean value to reduce effects from the free-breathing acquisition. Finally, data acquired at both mid-diastole and end-expiration are picked and reconstructed by a low-rank plus sparsity constraint algorithm. The performance of this sequence was evaluated by simulations, phantoms, and in vivo studies at rest and after physiological exercise. RESULTS: Numerical simulation demonstrated that changes in T1 * are related to the changes in T1 ; however, other factors such as breathing motion could influence T1 * measurements. Phantom T1 * values measured using free-running T1 * mapping sequence had good correlation with spin-echo T1 values and was insensitive to heart rate. In the Ex-CMR study, the measured T1 * reactivity was 10% immediately after exercise and declined over time. CONCLUSION: The free-running T1 * mapping sequence allows free-breathing non-ECG quantification of changes in myocardial T1 * with physiological exercise. Although, absolute myocardial T1 * value is sensitive to various confounders such as B1 and B0 inhomogeneity, quantification of its change may be useful in revealing myocardial tissue properties with exercise.

An inline deep learning based free-breathing ECG-free cine for exercise cardiovascular magnetic resonance.

BACKGROUND: Exercise cardiovascular magnetic resonance (Ex-CMR) is a promising stress imaging test for coronary artery disease (CAD). However, Ex-CMR requires accelerated imaging techniques that result in significant aliasing artifacts. Our goal was to develop and evaluate a free-breathing and electrocardiogram (ECG)-free real-time cine with deep learning (DL)-based radial acceleration for Ex-CMR. METHODS: A 3D (2D + time) convolutional neural network was implemented to suppress artifacts from aliased radial cine images. The network was trained using synthetic real-time radial cine images simulated using breath-hold, ECG-gated segmented Cartesian k-space data acquired at 3 T from 503 patients at rest. A prototype real-time radial sequence with acceleration rate = 12 was used to collect images with inline DL reconstruction. Performance was evaluated in 8 healthy subjects in whom only rest images were collected. Subsequently, 14 subjects (6 healthy and 8 patients with suspected CAD) were prospectively recruited for an Ex-CMR to evaluate image quality. At rest (n = 22), standard breath-hold ECG-gated Cartesian segmented cine and free-breathing ECG-free real-time radial cine images were acquired. During post-exercise stress (n = 14), only real-time radial cine images were acquired. Three readers evaluated residual artifact level in all collected images on a 4-point Likert scale (1-non-diagnostic, 2-severe, 3-moderate, 4-minimal). RESULTS: The DL model substantially suppressed artifacts in real-time radial cine images acquired at rest and during post-exercise stress. In real-time images at rest, 89.4% of scores were moderate to minimal. The mean score was 3.3 ± 0.7, representing increased (P < 0.001) artifacts compared to standard cine (3.9 ± 0.3). In real-time images during post-exercise stress, 84.6% of scores were moderate to minimal, and the mean artifact level score was 3.1 ± 0.6. Comparison of left-ventricular (LV) measures derived from standard and real-time cine at rest showed differences in LV end-diastolic volume (3.0 mL [- 11.7, 17.8], P = 0.320) that were not significantly different from zero. Differences in measures of LV end-systolic volume (7.0 mL [- 1.3, 15.3], P < 0.001) and LV ejection fraction (- 5.0% [- 11.1, 1.0], P < 0.001) were significant. Total inline reconstruction time of real-time radial images was 16.6 ms per frame. CONCLUSIONS: Our proof-of-concept study demonstrated the feasibility of inline real-time cine with DL-based radial acceleration for Ex-CMR.

Artifact reduction in free-breathing, free-running myocardial perfusion imaging with interleaved non-selective RF excitations.

PURPOSE: To reduce inflow and motion artifacts in free-breathing, free-running, steady-state spoiled gradient echo T1 -weighted (SPGR) myocardial perfusion imaging. METHOD: Unsaturated spins from inflowing blood or out-of-plane motion cause flashing artifacts in free-running SPGR myocardial perfusion. During free-running SPGR, 1 non-selective RF excitation was added after every 3 slice-selective RF excitations to suppress inflow artifacts by forcing magnetization in neighboring regions to steady-state. Bloch simulations and phantom experiments were performed to evaluate the impact of the flip angle and non-selective RF frequency on inflowing spins and tissue contrast. Free-running perfusion with (n = 11) interleaved non-selective RF or without (n = 11) were studied in 22 subjects (age = 60.2 ± 14.3 years, 11 male). Perfusion images were graded on a 5-point Likert scale for conspicuity of wall enhancement, inflow/motion artifact, and streaking artifact and compared using Wilcoxon sum-rank testing. RESULT: Numeric simulation showed that 1 non-selective RF excitation applied after every 3 slice-selective RF excitations produced superior out-of-plane signal suppression compared to 1 non-selective RF excitation applied after every 6 or 9 slice-selective RF excitations. In vitro experiments showed that a 30° flip angle produced near-optimal myocardial contrast. In vivo experiments demonstrated that the addition of interleaved non-selective RF significantly (P < .01) improved conspicuity of wall enhancement (mean score = 4.4 vs. 3.2) and reduced inflow/motion (mean score = 4.5 vs. 2.5) and streaking (mean score = 3.9 vs. 2.4) artifacts. CONCLUSION: Non-selective RF excitations interleaved between slice-selective excitations can reduce image artifacts in free-breathing, ungated perfusion images. Further studies are warranted to assess the diagnostic accuracy of the proposed solution for evaluating myocardial ischemia.

Multi-domain convolutional neural network (MD-CNN) for radial reconstruction of dynamic cardiac MRI.

PURPOSE: Cardiac MR cine imaging allows accurate and reproducible assessment of cardiac function. However, its long scan time not only limits the spatial and temporal resolutions but is challenging in patients with breath-holding difficulty or non-sinus rhythms. To reduce scan time, we propose a multi-domain convolutional neural network (MD-CNN) for fast reconstruction of highly undersampled radial cine images. METHODS: MD-CNN is a complex-valued network that processes MR data in k-space and image domains via k-space interpolation and image-domain subnetworks for residual artifact suppression. MD-CNN exploits spatio-temporal correlations across timeframes and multi-coil redundancies to enable high acceleration. Radial cine data were prospectively collected in 108 subjects (50 ± 17 y, 72 males) using retrospective-gated acquisition with 80%:20% split for training/testing. Images were reconstructed by MD-CNN and k-t Radial Sparse-Sense(kt-RASPS) using an undersampled dataset (14 of 196 acquired views; relative acceleration rate = 14). MD-CNN images were evaluated quantitatively using mean-squared-error (MSE) and structural similarity index (SSIM) relative to reference images, and qualitatively by three independent readers for left ventricular (LV) border sharpness and temporal fidelity using 5-point Likert-scale (1-non-diagnostic, 2-poor, 3-fair, 4-good, and 5-excellent). RESULTS: MD-CNN showed improved MSE and SSIM compared to kt-RASPS (0.11 ± 0.10 vs. 0.61 ± 0.51, and 0.87 ± 0.07 vs. 0.72 ± 0.07, respectively; P < .01). Qualitatively, MD-CCN significantly outperformed kt-RASPS in LV border sharpness (3.87 ± 0.66 vs. 2.71 ± 0.58 at end-diastole, and 3.57 ± 0.6 vs. 2.56 ± 0.6 at end-systole, respectively; P < .01) and temporal fidelity (3.27 ± 0.65 vs. 2.59 ± 0.59; P < .01). CONCLUSION: MD-CNN reduces the scan time of cine imaging by a factor of 23.3 and provides superior image quality compared to kt-RASPS.

Highly accelerated free-breathing real-time phase contrast cardiovascular MRI via complex-difference deep learning.

PURPOSE: To develop and evaluate a real-time phase contrast (PC) MRI protocol via complex-difference deep learning (DL) framework. METHODS: DL used two 3D U-nets to separately filter aliasing artifact from radial real-time velocity-compensated and complex-difference images. U-nets were trained with synthetic real-time PC generated from electrocardiograph (ECG) -gated, breath-hold, segmented PC (ECG-gated segmented PC) acquired at the ascending aorta of 510 patients. In 21 patients, free-breathing, ungated real-time (acceleration rate = 28.8) and ECG-gated segmented (acceleration rate = 2) PC were prospectively acquired at the ascending aorta. Hemodynamic parameters (cardiac output [CO], stroke volume [SV], and mean velocity at peak systole [peak mean velocity]) were measured for ECG-gated segmented and DL-filtered synthetic real-time PC and compared using Bland-Altman and linear regression analyses. Additionally, hemodynamic parameters were quantified from DL-filtered, compressed-sensing (CS) -reconstructed, and gridding reconstructed prospective real-time PC and compared to ECG-gated segmented PC. RESULTS: Synthetic real-time PC with DL showed strong correlation (R > 0.98) and good agreement with ECG-gated segmented PC for quantified hemodynamic parameters (mean-difference: CO = -0.3 L/min, SV = -4.3 mL, peak mean velocity = -2.3 cm/s). On average, DL required 0.39 s/frame to filter prospective real-time PC, which was 4.6-fold faster than CS. Compared to CS, DL showed superior correlation, tighter limits of agreement (LOAs), better bias for peak mean velocity, and worse bias for CO and SV. Compared to gridding, DL showed similar correlation, tighter LOAs for CO and SV, similar bias for CO, and worse bias for SV and peak mean velocity. CONCLUSION: The complex-difference DL framework accelerated real-time PC-MRI by nearly 28-fold, enabling rapid free-running real-time assessment of flow hemodynamics.

Rapid reconstruction of highly undersampled, non-Cartesian real-time cine k-space data using a perceptual complex neural network (PCNN).

Highly accelerated real-time cine MRI using compressed sensing (CS) is a promising approach to achieve high spatio-temporal resolution and clinically acceptable image quality in patients with arrhythmia and/or dyspnea. However, its lengthy image reconstruction time may hinder its clinical translation. The purpose of this study was to develop a neural network for reconstruction of non-Cartesian real-time cine MRI k-space data faster (<1 min per slice with 80 frames) than graphics processing unit (GPU)-accelerated CS reconstruction, without significant loss in image quality or accuracy in left ventricular (LV) functional parameters. We introduce a perceptual complex neural network (PCNN) that trains on complex-valued MRI signal and incorporates a perceptual loss term to suppress incoherent image details. This PCNN was trained and tested with multi-slice, multi-phase, cine images from 40 patients (20 for training, 20 for testing), where the zero-filled images were used as input and the corresponding CS reconstructed images were used as practical ground truth. The resulting images were compared using quantitative metrics (structural similarity index (SSIM) and normalized root mean square error (NRMSE)) and visual scores (conspicuity, temporal fidelity, artifacts, and noise scores), individually graded on a five-point scale (1, worst; 3, acceptable; 5, best), and LV ejection fraction (LVEF). The mean processing time per slice with 80 frames for PCNN was 23.7 ± 1.9 s for pre-processing (Step 1, same as CS) and 0.822 ± 0.004 s for dealiasing (Step 2, 166 times faster than CS). Our PCNN produced higher data fidelity metrics (SSIM = 0.88 ± 0.02, NRMSE = 0.014 ± 0.004) compared with CS. While all the visual scores were significantly different (P < 0.05), the median scores were all 4.0 or higher for both CS and PCNN. LVEFs measured from CS and PCNN were strongly correlated (R2 = 0.92) and in good agreement (mean difference = -1.4% [2.3% of mean]; limit of agreement = 10.6% [17.6% of mean]). The proposed PCNN is capable of rapid reconstruction (25 s per slice with 80 frames) of non-Cartesian real-time cine MRI k-space data, without significant loss in image quality or accuracy in LV functional parameters.

Rapid dealiasing of undersampled, non-Cartesian cardiac perfusion images using U-net.

Compressed sensing (CS) is a promising method for accelerating cardiac perfusion MRI to achieve clinically acceptable image quality with high spatial resolution (1.6 × 1.6 × 8 mm3 ) and extensive myocardial coverage (6-8 slices per heartbeat). A major disadvantage of CS is its relatively lengthy processing time (~8 min per slice with 64 frames using a graphics processing unit), thereby making it impractical for clinical translation. The purpose of this study was to implement and test whether an image reconstruction pipeline including a neural network is capable of reconstructing 6.4-fold accelerated, non-Cartesian (radial) cardiac perfusion k-space data at least 10 times faster than CS, without significant loss in image quality. We implemented a 3D (2D + time) U-Net and trained it with 132 2D + time datasets (coil combined, zero filled as input; CS reconstruction as reference) with 64 time frames from 28 patients (8448 2D images in total). For testing, we used 56 2D + time coil-combined, zero-filled datasets (3584 2D images in total) from 12 different patients as input to our trained U-Net, and compared the resulting images with CS reconstructed images using quantitative metrics of image quality and visual scores (conspicuity of wall enhancement, noise, artifacts; each score ranging from 1 (worst) to 5 (best), with 3 defined as clinically acceptable) evaluated by readers. Including pre- and post-processing steps, compared with CS, U-Net significantly reduced the reconstruction time by 14.4-fold (32.1 ± 1.4 s for U-Net versus 461.3 ± 16.9 s for CS, p < 0.001), while maintaining high data fidelity (structural similarity index = 0.914 ± 0.023, normalized root mean square error = 1.7 ± 0.3%, identical mean edge sharpness of 1.2 mm). The median visual summed score was not significantly different (p = 0.053) between CS (14; interquartile range (IQR) = 0.5) and U-Net (12; IQR = 0.5). This study shows that the proposed pipeline with a U-Net is capable of reconstructing 6.4-fold accelerated, non-Cartesian cardiac perfusion k-space data 14.4 times faster than CS, without significant loss in data fidelity or image quality.

Highly accelerated, real-time phase-contrast MRI using radial k-space sampling and GROG-GRASP reconstruction: a feasibility study in pediatric patients with congenital heart disease.

Retrospective electrocardiogram-gated, 2D phase-contrast (PC) flow MRI is routinely used in clinical evaluation of valvular/vascular disease in pediatric patients with congenital heart disease (CHD). In patients not requiring general anesthesia, clinical standard PC is conducted with free breathing for several minutes per slice with averaging. In younger patients under general anesthesia, clinical standard PC is conducted with breath-holding. One approach to overcome this limitation is using either navigator gating or self-navigation of respiratory motion, at the expense of lengthening scan times. An alternative approach is using highly accelerated, free-breathing, real-time PC (rt-PC) MRI, which to date has not been evaluated in CHD patients. The purpose of this study was to develop a 38.4-fold accelerated 2D rt-PC pulse sequence using radial k-space sampling and compressed sensing with 1.5 × 1.5 × 6.0 mm3 nominal spatial resolution and 40 ms nominal temporal resolution, and evaluate whether it is capable of accurately measuring flow in 17 pediatric patients (aortic valve, pulmonary valve, right and left pulmonary arteries) compared with clinical standard 2D PC (either breath-hold or free breathing). For clinical translation, we implemented an integrated reconstruction pipeline capable of producing DICOMs of the order of 2 min per time series (46 frames). In terms of association, forward volume, backward volume, regurgitant fraction, and peak velocity at peak systole measured with standard PC and rt-PC were strongly correlated (R2 > 0.76; P < 0.001). Compared with clinical standard PC, in terms of agreement, forward volume (mean difference = 1.4% (3.0% of mean)) and regurgitant fraction (mean difference = -2.5%) were in good agreement, whereas backward volume (mean difference = -1.1 mL (28.2% of mean)) and peak-velocity at peak systole (mean difference = -21.3 cm/s (17.2% of mean)) were underestimated by rt-PC. This study demonstrates that the proposed rt-PC with the said spatial resolution and temporal resolution produces relatively accurate forward volumes and regurgitant fractions but underestimates backward volumes and peak velocities at peak systole in pediatric patients with CHD.

Accelerated, free-breathing, noncontrast, electrocardiograph-triggered, thoracic MR angiography with stack-of-stars k-space sampling and GRASP reconstruction.

PURPOSE: To develop an accelerated, free-breathing, noncontrast, electrocardiograph-triggered, thoracic MR angiography (NC-MRA) pulse sequence capable of achieving high spatial resolution at clinically acceptable scan time and test whether it produces clinically acceptable image quality in patients with suspected aortic disease. METHODS: We modified a "coronary" MRA pulse sequence to use a stack-of-stars k-space sampling pattern and combined it with golden-angle radial sparse parallel (GRASP reconstruction to enable self-navigation of respiratory motion and high data acceleration. The performance of the proposed NC-MRA was evaluated in 13 patients, where clinical standard contrast-enhanced MRA (CE-MRA) was used as control. For visual analysis, two readers graded the conspicuity of vessel lumen, artifacts, and noise level on a 5-point scale (overall score index = sum of three scores). The aortic diameters were measured at seven standardized locations. The mean visual scores, inter-observer variability, and vessel diameters were compared using appropriate statistical tests. RESULTS: The overall mean visual score index (12.1 ± 1.7 for CE-MRA versus 12.1 ± 1.0 for NC-MRA) scores were not significantly different (P > 0.16). The two readers' scores were significantly different for CE-MRA (P = 0.01) but not for NC-MRA (P = 0.21). The mean vessel diameters were not significantly different, except at the proximal aortic arch (P < 0.03). The mean diameters were strongly correlated (R2 ≥ 0.96) and in good agreement (absolute mean difference ≤ 0.01 cm and 95% confidence interval ≤ 0.62 cm). CONCLUSION: This study shows that the proposed NC-MRA produces clinically acceptable image quality in patients at high spatial resolution (1.5 mm × 1.5 mm × 1.5 mm) and clinically acceptable scan time (~6 min).

Accelerated, first-pass cardiac perfusion pulse sequence with radial k-space sampling, compressed sensing, and k-space weighted image contrast reconstruction tailored for visual analysis and quantification of myocardial blood flow.

PURPOSE: To develop an accelerated cardiac perfusion pulse sequence and test whether it is capable of increasing spatial coverage, generating high-quality images, and enabling quantification of myocardial blood flow (MBF). METHODS: We implemented an accelerated first-pass cardiac perfusion pulse sequence by combining radial k-space sampling, compressed sensing (CS), and k-space weighted image contrast (KWIC) filtering. The proposed and clinical standard pulse sequences were evaluated in a randomized order in 13 patients at rest. For visual analysis, 3 readers graded the conspicuity of wall enhancement, artifact, and noise level on a 5-point Likert scale (overall score index = sum of 3 individual scores). Resting MBF was calculated using a Fermi function model with and without KWIC filtering. Mean visual scores and MBF values were compared between sequences using appropriate statistical tests. RESULTS: The proposed pulse sequence produced greater spatial coverage (6-8 slices) with higher spatial resolution (1.6 × 1.6 × 8 mm3 ) and shorter readout duration (78 ms) compared to clinical standard (3-4 slices, 3 × 3 × 8 mm3 , 128 ms, respectively). The overall image score index between accelerated (11.1 ± 1.3) and clinical standard (11.2 ± 1.3) was not significantly different (P = 0.64). Mean resting MBF values with KWIC filtering (0.9-1.2 mL/g/min across different slices) were significantly lower (P < 0.0001) than those without KWIC filtering (3.1-4.3 mL/g/min) and agreed better with values reported in literature. CONCLUSION: An accelerated, first-pass cardiac perfusion pulse sequence with radial k-space sampling, CS, and KWIC filtering is capable of increasing spatial coverage, generating high-quality images, and enabling quantification of MBF.

Validation of highly accelerated real-time cardiac cine MRI with radial k-space sampling and compressed sensing in patients at 1.5T and 3T.

PURPOSE: To validate an optimal 12-fold accelerated real-time cine MRI pulse sequence with radial k-space sampling and compressed sensing (CS) in patients at 1.5T and 3T. METHODS: We used two strategies to reduce image artifacts arising from gradient delays and eddy currents in radial k-space sampling with balanced steady-state free precession readout. We validated this pulse sequence against a standard breath-hold cine sequence in two patient cohorts: a myocardial infarction (n = 16) group at 1.5T and chronic kidney disease group (n = 18) at 3T. Two readers independently performed visual analysis of 68 cine sets in four categories (myocardial definition, temporal fidelity, artifact, noise) on a 5-point Likert scale (1 = nondiagnostic, 2 = poor, 3 = adequate or moderate, 4 = good, 5 = excellent). Another reader calculated left ventricular (LV) functional parameters, including ejection fraction. RESULTS: Compared with standard cine, real-time cine produced nonsignificantly different visually assessed scores, except for the following categories: 1) temporal fidelity scores were significantly lower (P = 0.013) for real-time cine at both field strengths, 2) artifacts scores were significantly higher (P = 0.013) for real-time cine at both field strengths, and 3) noise scores were significantly (P = 0.013) higher for real-time cine at 1.5T. Standard and real-time cine pulse sequences produced LV functional parameters that were in good agreement (e.g., absolute mean difference in ejection fraction <4%). CONCLUSION: This study demonstrates that an optimal 12-fold, accelerated, real-time cine MRI pulse sequence using radial k-space sampling and CS produces good to excellent visual scores and relatively accurate LV functional parameters in patients at 1.5T and 3T. Magn Reson Med 79:2745-2751, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Single-Shot Coronary Quiescent-Interval Slice-Selective Magnetic Resonance Angiography Using Compressed Sensing: A Feasibility Study in Patients With Congenital Heart Disease.

OBJECTIVE: The aim of this study was to determine whether it is feasible to visualize the coronary origins in patients with congenital heart disease (CHD) using single-shot coronary quiescent-interval slice-selective (QISS) magnetic resonance angiography (MRA) with compressed sensing (CS). METHODS: This retrospective study leveraged a parent study, which aimed to compare breath-hold, 2.1-fold accelerated, 2-shot coronary QISS MRA and clinical standard contrast-enhanced (CE) MRA in 14 patients with CHD (mean age, 17.0 ± 8.6 years, 6 females and 8 males). We evaluated the feasibility of single-shot coronary QISS MRA by retrospectively undersampling the 2-shot data set by an additional factor of 2, performing CS reconstruction, and comparing the retrospectively derived single-shot QISS MRA to 2-shot coronary QISS MRA and clinical standard CE MRA. For quantitative analysis, structural similarity index and normalized root mean square error were calculated. For qualitative analysis, 2 experienced readers scored the conspicuity of coronary origins on a 5-point Likert scale (1 = nondiagnostic, 2 = poor, 3 = clinically acceptable, 4 = good, 5 = excellent). RESULTS: Compared with 2-shot QISS, single-shot QISS produced normalized root mean square error of 5.8% ± 0.8% and structural similarity index of 95.4% ± 1.6%, suggesting high data fidelity by CS reconstruction. Compared with the mean conspicuity scores for clinical CE MRA (4.2 ± 0.5 and 4.1 ± 0.6 for right and left coronary origins, respectively), the mean conspicuity scores were not significantly different (P > 0.3) for 2-shot QISS (4.4 ± 0.9 and 4.2 ± 1.1, respectively) and single-shot QISS with CS (4.3 ± 1.1 and 3.8 ± 1.3, respectively) and deemed clinically acceptable to good (scores ≥3.0). CONCLUSIONS: This study shows that it is feasible to visualize the coronary origins in patients with CHD with clinically acceptable to good image quality using single-shot coronary QISS MRA with CS.

Accelerating compressed sensing reconstruction of subsampled radial k-space data using geometrically-derived density compensation.

Objective.To accelerate compressed sensing (CS) reconstruction of subsampled radial k-space data using a geometrically-derived density compensation function (gDCF) without significant loss in image quality.Approach.We developed a theoretical framework to calculate a gDCF based on Nyquist distance along the radial and circumferential directions of a discrete polar coordinate system. Our gDCF was compared against standard DCF (e.g. ramp filter) and another commonly used DCF (modified Shepp-Logan (SL) filter). The resulting image quality produced by each DCF was quantified using normalized root-mean-square-error (NRMSE), blur metric (1 = blurriest; 0 = sharpest), and structural similarity index (SSIM; 1 = perfect match; 0 = no match) compared with the reference. For filtered backprojection (FBP) of phantom data obtained at the Nyquist sampling rate, Cartesian k-space sampling was used as the reference. For CS reconstruction of subsampled cardiac magnetic resonance imaging datasets (real-time cardiac cine data with 11 projections per frame,n = 20 patients; cardiac perfusion data with 30 projections per frame,n = 19 patients), CS reconstruction without DCF was used as the reference.Main results.The NRMSE, SSIM, and blur metrics of the phantom data were good for all DCFs, confirming that our gDCF produces uniform densities at the upper limit (Nyquist). For CS reconstruction of subsampled real-time cine and cardiac perfusion datasets, the image quality metrics (SSIM, NRMSE) were significantly (p < 0.05) higher for our gDCF than other DCFs, and the reconstruction time was significantly (p < 0.05) faster for our gDCF (reference) than no DCF (11.9%-52.9% slower), standard DCF (23.9%-57.6% slower), and modified SL filter (13.5%-34.8% slower).Significance.The proposed gDCF accelerates CS reconstruction of subsampled radial k-space data without significant loss in image quality compared with no DCF as the reference.

Rapid Reconstruction of Four-dimensional MR Angiography of the Thoracic Aorta Using a Convolutional Neural Network.

PURPOSE: To implement an integrated reconstruction pipeline including a graphics processing unit (GPU)-based convolutional neural network (CNN) architecture and test whether it reconstructs four-dimensional non-Cartesian, non-contrast material-enhanced MR angiographic k-space data faster than a central processing unit (CPU)-based compressed sensing (CS) reconstruction pipeline, without significant losses in data fidelity, summed visual score (SVS), or arterial vessel-diameter measurements. MATERIALS AND METHODS: Raw k-space data of 24 patients (18 men and six women; mean age, 56.8 years ± 11.8 [standard deviation]) suspected of having thoracic aortic disease were used to evaluate the proposed reconstruction pipeline derived from an open-source three-dimensional CNN. For training, 4800 zero-filled images and the corresponding CS-reconstructed images from 10 patients were used as input-output pairs. For testing, 6720 zero-filled images from 14 different patients were used as inputs to a trained CNN. Metrics for evaluating the agreement between the CNN and CS images included reconstruction times, structural similarity index (SSIM) and normalized root-mean-square error (NRMSE), SVS (3 = nondiagnostic, 9 = clinically acceptable, 15 = excellent), and vessel diameters. RESULTS: The mean reconstruction time was 65 times and 69 times shorter for the CPU-based and GPU-based CNN pipelines (216.6 seconds ± 40.5 and 204.9 seconds ± 40.5), respectively, than for CS (14 152.3 seconds ± 1708.6) (P < .001). Compared with CS as practical ground truth, CNNs produced high data fidelity (SSIM = 0.94 ± 0.02, NRMSE = 2.8% ± 0.4) and not significantly different (P = .25) SVS and aortic diameters, except at one out of seven locations, where the percentage difference was only 3% (ie, clinically irrelevant). CONCLUSION: The proposed integrated reconstruction pipeline including a CNN architecture is capable of rapidly reconstructing time-resolved volumetric cardiovascular MRI k-space data, without a significant loss in data quality, thereby supporting clinical translation of said non-contrast-enhanced MR angiograms. Supplemental material is available for this article. © RSNA, 2020.

Accelerated 3D Left Atrial Late Gadolinium Enhancement in Patients with Atrial Fibrillation at 1.5 T: Technical Development.

PURPOSE: To develop an accelerated three-dimensional (3D) late gadolinium enhancement (LGE) pulse sequence using balanced steady-state free precession readout with stack-of-stars k-space sampling and extra motion-state golden-angle radial sparse parallel (XD-GRASP) reconstruction and test the performance for detecting atrial scar and fibrosis in patients with atrial fibrillation (AF). MATERIALS AND METHODS: Twenty-five patients with AF (20 paroxysmal and five persistent; 65 years ± 7 [standard deviation]; 18 men) were imaged at 1.5 T using the proposed LGE sequence with 1.3 mm × 1.3 mm × 2-mm spatial resolution and predictable imaging time. The resulting images were compared with historic images of 25 patients with AF (18 paroxysmal and seven persistent; 67 years ± 10; 14 men) obtained using a reference 3D left atrial (LA) LGE sequence with 1.3 mm × 1.3 mm × 2.5-mm spatial resolution. Two readers visually graded the 3D LGE images (conspicuity, artifact, noise) on a five-point Likert scale (1 = worst, 3 = acceptable, 5 = best), in which the summed visual score (SVS) of 9 or greater was defined as clinically acceptable. Appropriate statistical analyses (Cohen κ coefficient, Mann-Whitney U test, t tests, and intraclass correlation) were performed, where a P value < .05 was considered significant. RESULTS: Mean imaging time was significantly shorter (P < .01) for the proposed pulse sequence (5.9 minutes ± 1.3) than for the reference pulse sequence (10.6 minutes ± 2). Median SVS was significantly higher (P < .01) for the proposed (SVS = 11) than reference (SVS = 9.5) 3D LA LGE images. Interrater reproducibility in visual scores was higher for the proposed (κ = 0.78-1) than reference 3D LA LGE (κ = 0.44-0.75). Intrareader repeatability in fibrosis quantification was higher for the reference cohort (intraclass correlation coefficient [ICC] = 0.94) than the prospective cohort (ICC = 0.79). CONCLUSION: The proposed 3D LA LGE method produced clinically acceptable image quality with 1.5 mm × 1.5 mm × 2-mm nominal spatial resolution and 6-minute predictable imaging time for quantification of LA scar and fibrosis in patients with AF. Supplemental material is available for this article. © RSNA, 2020.

A factor VIII-derived peptide enables von Willebrand factor (VWF)-binding of artificial platelet nanoconstructs without interfering with VWF-adhesion of natural platelets.

There is substantial clinical interest in synthetic platelet analogs for potential application in transfusion medicine. To this end, our research is focused on self-assembled peptide-lipid nanoconstructs that can undergo injury site-selective adhesion and subsequently promote site-directed active platelet aggregation, thus mimicking platelet's primary hemostatic actions. For injury site-selective adhesion, we have utilized a coagulation factor FVIII-derived VWF-binding peptide (VBP). FVIII binds to VWF's D'-D3 domain while natural platelet GPIbα binds to VWF's A1 domain. Therefore, we hypothesized that the VBP-decorated nanoconstructs will adhere to VWF without mutual competition with natural platelets. We further hypothesized that the adherent VBP-decorated constructs can enhance platelet aggregation when co-decorated with a fibrinogen-mimetic peptide (FMP). To test these hypotheses, we used glycocalicin to selectively block VWF's A1 domain and, using fluorescence microscopy, studied the binding of fluorescently labeled VBP-decorated nanoconstructs versus platelets to ristocetin-treated VWF. Subsequently, we co-decorated the nanoconstructs with VBP and FMP and incubated them with human platelets to study construct-mediated enhancement of platelet aggregation. Decoration with VBP resulted in substantial construct adhesion to ristocetin-treated VWF even if the A1-domain was blocked by glycocalicin. In comparison, such A1-blocking resulted in significant reduction of platelet adhesion. Without A1-blocking, the VBP-decorated constructs and natural platelets could adhere to VWF concomitantly. Furthermore, the constructs co-decorated with VBP and FMP enhanced active platelet aggregation. The results indicate significant promise in utilizing the FVIII-derived VBP in developing synthetic platelet analogs that do not interfere with VWF-binding of natural platelets but allow site-directed enhancement of platelet aggregation when combined with FMP.