Self-Supervised Learning for Improved Calibrationless Radial MRI with NLINV-Net.

PURPOSE: To develop a neural network architecture for improved calibrationless reconstruction of radial data when no ground truth is available for training. METHODS: NLINV-Net is a model-based neural network architecture that directly estimates images and coil sensitivities from (radial) k-space data via non-linear inversion (NLINV). Combined with a training strategy using self-supervision via data undersampling (SSDU), it can be used for imaging problems where no ground truth reconstructions are available. We validated the method for (1) real-time cardiac imaging and (2) single-shot subspace-based quantitative T1 mapping. Furthermore, region-optimized virtual (ROVir) coils were used to suppress artifacts stemming from outside the FoV and to focus the k-space based SSDU loss on the region of interest. NLINV-Net based reconstructions were compared with conventional NLINV and PI-CS (parallel imaging + compressed sensing) reconstruction and the effect of the region-optimized virtual coils and the type of training loss was evaluated qualitatively. RESULTS: NLINV-Net based reconstructions contain significantly less noise than the NLINV-based counterpart. ROVir coils effectively suppress streakings which are not suppressed by the neural networks while the ROVir-based focussed loss leads to visually sharper time series for the movement of the myocardial wall in cardiac real-time imaging. For quantitative imaging, T1-maps reconstructed using NLINV-Net show similar quality as PI-CS reconstructions, but NLINV-Net does not require slice-specific tuning of the regularization parameter. CONCLUSION: NLINV-Net is a versatile tool for calibrationless imaging which can be used in challenging imaging scenarios where a ground truth is not available.

A specific and portable gene expression program underlies antigen archiving by lymphatic endothelial cells.

Antigens from protein subunit vaccination traffic from the tissue to the draining lymph node, either passively via the lymph or carried by dendritic cells at the local injection site. Lymph node (LN) lymphatic endothelial cells (LEC) actively acquire and archive foreign antigens, and archived antigen can be released during subsequent inflammatory stimulus to improve immune responses. Here, we answer questions about how LECs achieve durable antigen archiving and whether there are transcriptional signatures associated with LECs containing high levels of antigen. We used single cell sequencing in dissociated LN tissue to quantify antigen levels in LEC and dendritic cell populations at multiple timepoints after immunization, and used machine learning to define a unique transcriptional program within archiving LECs that can predict LEC archiving capacity in independent data sets. Finally, we validated this modeling, showing we could predict antigen archiving from a transcriptional dataset of CHIKV infected mice and demonstrated in vivo the accuracy of our prediction. Collectively, our findings establish a unique transcriptional program in LECs that promotes antigen archiving that can be translated to other systems.

Immunization-induced antigen archiving enhances local memory CD8+ T cell responses following an unrelated viral infection.

Antigens from viruses or immunizations can persist or are archived in lymph node stromal cells such as lymphatic endothelial cells (LEC) and fibroblastic reticular cells (FRC). Here, we find that, during the time frame of antigen archiving, LEC apoptosis caused by a second, but unrelated, innate immune stimulus such as vaccina viral infection or CpG DNA administration resulted in cross-presentation of archived antigens and boosted memory CD8 + T cells specific to the archived antigen. In contrast to "bystander" activation associated with unrelated infections, the memory CD8 + T cells specific to the archived antigen from the immunization were significantly higher than memory CD8 + T cells of a different antigen specificity. Finally, the boosted memory CD8 + T cells resulted in increased protection against Listeria monocytogenes expressing the antigen from the immunization, but only for the duration that the antigen was archived. These findings outline an important mechanism by which lymph node stromal cell archived antigens, in addition to bystander activation, can augment memory CD8 + T cell responses during repeated inflammatory insults.

Assessment of deep learning segmentation for real-time free-breathing cardiac magnetic resonance imaging at rest and under exercise stress.

In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been developed and analyzed. However, nearly all of them are focused on cine CMR under breathold. In this work, accuracy of deep learning methods is assessed for volumetric analysis (via segmentation) of the left ventricle in real-time free-breathing CMR at rest and under exercise stress. Data from healthy volunteers (n = 15) for cine and real-time free-breathing CMR at rest and under exercise stress were analyzed retrospectively. Exercise stress was performed using an ergometer in the supine position. Segmentations of two deep learning methods, a commercially available technique (comDL) and an openly available network (nnU-Net), were compared to a reference model created via the manual correction of segmentations obtained with comDL. Segmentations of left ventricular endocardium (LV), left ventricular myocardium (MYO), and right ventricle (RV) are compared for both end-systolic and end-diastolic phases and analyzed with Dice's coefficient. The volumetric analysis includes the cardiac function parameters LV end-diastolic volume (EDV), LV end-systolic volume (ESV), and LV ejection fraction (EF), evaluated with respect to both absolute and relative differences. For cine CMR, nnU-Net and comDL achieve Dice's coefficients above 0.95 for LV and 0.9 for MYO, and RV. For real-time CMR, the accuracy of nnU-Net exceeds that of comDL overall. For real-time CMR at rest, nnU-Net achieves Dice's coefficients of 0.94 for LV, 0.89 for MYO, and 0.90 for RV and the mean absolute differences between nnU-Net and the reference are 2.9 mL for EDV, 3.5 mL for ESV, and 2.6% for EF. For real-time CMR under exercise stress, nnU-Net achieves Dice's coefficients of 0.92 for LV, 0.85 for MYO, and 0.83 for RV and the mean absolute differences between nnU-Net and reference are 11.4 mL for EDV, 2.9 mL for ESV, and 3.6% for EF. Deep learning methods designed or trained for cine CMR segmentation can perform well on real-time CMR. For real-time free-breathing CMR at rest, the performance of deep learning methods is comparable to inter-observer variability in cine CMR and is usable for fully automatic segmentation. For real-time CMR under exercise stress, the performance of nnU-Net could promise a higher degree of automation in the future.

Rational Approximation of Golden Angles: Accelerated Reconstructions for Radial MRI.

PURPOSE: To develop a generic radial sampling scheme that combines the advantages of golden ratio sampling with simplicity of equidistant angular patterns. The irrational angle between consecutive spokes in golden ratio based sampling schemes enables a flexible retrospective choice of temporal resolution, while preserving good coverage of k-space for each individual bin. Nevertheless, irrational increments prohibit precomputation of the point-spread function (PSF), can lead to numerical problems, and require more complex processing steps. To avoid these problems, a new sampling scheme based on a rational approximation of golden angles (RAGA) is developed. METHODS: The theoretical properties of RAGA sampling are mathematically derived. Sidelobe-to-peak ratios (SPR) are numerically computed and compared to the corresponding golden ratio sampling schemes. The sampling scheme is implemented in the BART toolbox and in a radial gradient-echo sequence. Feasibility is shown for quantitative imaging in a phantom and a cardiac scan of a healthy volunteer. RESULTS: RAGA sampling can accurately approximate golden ratio sampling and has almost identical PSF and SPR. In contrast to golden ratio sampling, each frame can be reconstructed with the same equidistant trajectory using different sampling masks, and the angle of each acquired spoke can be encoded as a small index, which simplifies processing of the acquired data. CONCLUSION: RAGA sampling provides the advantages of golden ratio sampling while simplifying data processing, rendering it a valuable tool for dynamic and quantitative MRI.

Evaluation of MR-safe bioptomes for MR-guided endomyocardial biopsy in minipigs: a potential radiation-free clinical approach.

BACKGROUND: Diagnostic accuracy of endomyocardial biopsy could improve if clinically safe magnetic resonance (MR)-compatible bioptomes were available. We explored two novel MR-compatible cardiac bioptomes for performance, safety, and clinical viability, employing in vivo minipig trials and phase-contrast synchrotron radiation computed microtomography (SRµCT). METHODS: Analysis of ex vivo obtained pig endomyocardial biopsies was performed using phase-contrast SRµCT and conventional two-dimensional histology. The technical performance was evaluated by measuring volume, inner and outer integrities, compression, and histological diagnostic value in 3 sets (6 per set) of biopsies for each experimental bioptome. The bioptomes were tested in vivo in 3 healthy minipigs per bioptome. The clinical feasibility was evaluated by procedural and cutting success as well as histological diagnostic value. RESULTS: The bioptome with the 'grind-grind' design achieved similar values to control in compression (p = 0.822), inner (p = 0.628), and outer (p = 0.507), integrities ex vivo. It showed a better performance in the in vivo real-time MRI setting demonstrating a higher cutting success (91.7%) than the 'grind-anvil' (86.2%) design. In both ex vivo and in vivo evaluations, the 'grind-grind' design displayed sufficient diagnostic value (83% and 95%). The 'grind-anvil' design showed adequate diagnostic value both ex vivo and in vivo (78% and 87.5%) but was not comparable to control according to the three-dimensional (3D) analysis. CONCLUSION: A novel MR-compatible bioptome was identified as plausible in a clinical setting. Additionally, SRµCT and subsequent 3D structural analysis could be valuable in the label-free investigation of myocardial tissue at a micrometer level. RELEVANCE STATEMENT: Implementation of MR-guided biopsy can improve animal studies on structural myocardial changes at any point in an experimental setup. With further improvements in guiding catheters, MR-guided biopsy, using the new bioptome, has a potential to increase quality and diagnostic accuracy in patients both with structural and inflammatory cardiomyopathies. KEY POINTS: • Novel MR-compatible bioptomes show promise for a clinical application. • SRµCT enabled detailed analysis of endomyocardial biopsies. • The bioptomes showed adequate in vivo performance without major complications.

Visualization of deglutition and gastroesophageal reflux using real-time MRI: a standardized approach to image acquisition and assessment.

This study aims to develop a standardized algorithm for gastroesophageal image acquisition and diagnostic assessment using real-time MRI. Patients with GERD symptoms undergoing real-time MRI of the esophagus and esophagogastric junction between 2015 and 2018 were included. A 10 ml bolus of pineapple juice served as an oral contrast agent. Patients performed Valsalva maneuver to provoke reflux and hiatal hernia. Systematic MRI assessment included visual presence of achalasia, fundoplication failure in patients with previous surgical fundoplication, gastroesophageal reflux, and hiatal hernia. A total of 184 patients (n = 92 female [50%], mean age 52.7 ± 15.8 years) completed MRI studies without adverse events at a mean examination time of 15 min. Gastroesophageal reflux was evident in n = 117 (63.6%), hiatal hernia in n = 95 (52.5%), and achalasia in 4 patients (2.2%). Hiatal hernia was observed more frequently in patients with reflux at rest (n = 67 vs. n = 6, p < 0.01) and during Valsalva maneuver (n = 87 vs. n = 8, p < 0.01). Real-time MRI visualized a morphologic correlate for recurring GERD symptoms in 20/22 patients (90%) after fundoplication procedure. In a large-scale single-center cohort of patients with GERD symptoms undergoing real-time MRI, visual correlates for clinical symptoms were evident in most cases. The proposed assessment algorithm could aid in wider-spread utilization of real-time MRI and provides a comprehensive approach to this novel imaging modality.

Vaccine-induced antigen archiving enhances local memory CD8+ T cell responses following an unrelated viral infection.

Viral and vaccine antigens persist or are archived in lymph node stromal cells (LNSC) such as lymphatic endothelial cells (LEC) and fibroblastic reticular cells (FRC). Here, we find that, during the time frame of antigen archiving, LEC apoptosis caused by a second, but unrelated, innate immune stimulus such as vaccina viral infection or CpG DNA administration boosted memory CD8+ T cells specific to the archived antigen. In contrast to "bystander" activation associated with unrelated infections, the memory CD8+ T cells specific to the vaccine archived antigen were significantly higher than memory CD8+ T cells of a different antigen specificity. Finally, the boosted memory CD8+ T cells resulted in increased protection against Listeria monocytogenes expressing the vaccine antigen, but only for the duration that the vaccine antigen was archived. These findings outline a novel mechanism by which LNSC archived antigens, in addition to bystander activation, can augment memory CD8+ T cell responses during repeated inflammatory insults.

Free-Breathing Liver Fat, R2* and B0 Field Mapping Using Multi-Echo Radial FLASH and Regularized Model-Based Reconstruction.

This work introduced a stack-of-radial multi-echo asymmetric-echo MRI sequence for free-breathing liver volumetric acquisition. Regularized model-based reconstruction was implemented in Berkeley Advanced Reconstruction Toolbox (BART) to jointly estimate all physical parameter maps (water, fat, R2∗ , and B0 field inhomogeneity maps) and coil sensitivity maps from self-gated k -space data. Specifically, locally low rank and temporal total variation regularization were employed directly on physical parameter maps. The proposed free-breathing radial technique was tested on a water/fat & iron phantom, a young volunteer, and obesity/diabetes/hepatic steatosis patients. Quantitative fat fraction and R2∗ accuracy were confirmed by comparing our technique with the reference breath-hold Cartesian scan. The multi-echo radial sampling sequence achieves fast k -space coverage and is robust to motion. Moreover, the proposed motion-resolved model-based reconstruction allows for free-breathing liver fat and R2∗ quantification in multiple motion states. Overall, our proposed technique offers a convenient tool for non-invasive liver assessment with no breath holding requirement.

Quantitative MRI by nonlinear inversion of the Bloch equations.

PURPOSE: Development of a generic model-based reconstruction framework for multiparametric quantitative MRI that can be used with data from different pulse sequences. METHODS: Generic nonlinear model-based reconstruction for quantitative MRI estimates parametric maps directly from the acquired k-space by numerical optimization. This requires numerically accurate and efficient methods to solve the Bloch equations and their partial derivatives. In this work, we combine direct sensitivity analysis and pre-computed state-transition matrices into a generic framework for calibrationless model-based reconstruction that can be applied to different pulse sequences. As a proof-of-concept, the method is implemented and validated for quantitative T 1 $$ {\mathrm{T}}_1 $$ and T 2 $$ {\mathrm{T}}_2 $$ mapping with single-shot inversion-recovery (IR) FLASH and IR bSSFP sequences in simulations, phantoms, and the human brain. RESULTS: The direct sensitivity analysis enables a highly accurate and numerically stable calculation of the derivatives. The state-transition matrices efficiently exploit repeating patterns in pulse sequences, speeding up the calculation by a factor of 10 for the examples considered in this work, while preserving the accuracy of native ordinary differential equations solvers. The generic model-based method reproduces quantitative results of previous model-based reconstructions based on the known analytical solutions for radial IR FLASH. For IR bSFFP it produces accurate T 1 $$ {\mathrm{T}}_1 $$ and T 2 $$ {\mathrm{T}}_2 $$ maps for the National Insitute of Standards and Technology (NIST) phantom in numerical simulations and experiments. Feasibility is also shown for human brain, although results are affected by magnetization transfer effects. CONCLUSION: By developing efficient tools for numerical optimizations using the Bloch equations as forward model, this work enables generic model-based reconstruction for quantitative MRI.

Bayesian MRI reconstruction with joint uncertainty estimation using diffusion models.

PURPOSE: We introduce a framework that enables efficient sampling from learned probability distributions for MRI reconstruction. METHOD: Samples are drawn from the posterior distribution given the measured k-space using the Markov chain Monte Carlo (MCMC) method, different from conventional deep learning-based MRI reconstruction techniques. In addition to the maximum a posteriori estimate for the image, which can be obtained by maximizing the log-likelihood indirectly or directly, the minimum mean square error estimate and uncertainty maps can also be computed from those drawn samples. The data-driven Markov chains are constructed with the score-based generative model learned from a given image database and are independent of the forward operator that is used to model the k-space measurement. RESULTS: We numerically investigate the framework from these perspectives: (1) the interpretation of the uncertainty of the image reconstructed from undersampled k-space; (2) the effect of the number of noise scales used to train the generative models; (3) using a burn-in phase in MCMC sampling to reduce computation; (4) the comparison to conventional ℓ 1 $$ {\ell}_1 $$ -wavelet regularized reconstruction; (5) the transferability of learned information; and (6) the comparison to fastMRI challenge. CONCLUSION: A framework is described that connects the diffusion process and advanced generative models with Markov chains. We demonstrate its flexibility in terms of contrasts and sampling patterns using advanced generative priors and the benefits of also quantifying the uncertainty for every pixel.

Concomitant latent pulmonary vascular disease leads to impaired global cardiac performance in heart failure with preserved ejection fraction.

AIMS: The REDUCE-LAP II trial demonstrated adverse outcomes after interatrial shunt device (IASD) placement in heart failure with preserved ejection fraction (HFpEF) attributed to latent pulmonary vascular disease (PVD). We hypothesized that exercise stress cardiovascular magnetic resonance (CMR) imaging could provide non-invasive characterization of cardiac and pulmonary physiology for improved patient selection. METHODS AND RESULTS: The HFpEF-Stress trial prospectively enrolled 75 patients with exertional dyspnoea and diastolic dysfunction. Patients underwent rest and exercise stress right heart catheterization, echocardiography and CMR imaging. Pulmonary artery and capillary wedge pressures, cardiac index (CI) and pulmonary vascular resistance (PVR) were calculated. Latent PVD was defined as increased PVR ≥ 1.74 Wood units during exercise stress. CMR assessed long-axis strains (LAS) and filling volumes of all cardiac chambers. Right ventricular (RV) function was further quantified by stroke and peak flow volumes. Patients with latent PVD (n = 24) showed lower RV function (rest tricuspid annular plane systolic excursion, p = 0.010; stress RV LAS, p < 0.001) compared to patients without (n = 43). During exercise stress, RV stroke and peak flow volumes (p < 0.001) were reduced and led to impaired left atrial filling (p = 0.040) with a strong statistical trend to impaired ventricular (LV) filling (p = 0.098). This subsequently resulted in reduced LV-CI (p < 0.001) despite preserved LV systolic function (LV LAS p ≥ 0.255). The degree of RV dysfunction during exercise stress best predicted latent PVD (RV peak flow, area under the curve at rest 0.73 vs. stress 0.89, p = 0.004). CONCLUSIONS: Latent PVD is a feature of HFpEF and is associated with impaired RV functional reserve, global diastolic filling and LV-CI. This can be quantified by CMR and used to identify patients likely to benefit from IASD implantation.

Free-breathing myocardial T1 mapping using inversion-recovery radial FLASH and motion-resolved model-based reconstruction.

PURPOSE: To develop a free-breathing myocardial T 1 $$ {\mathrm{T}}_1 $$ mapping technique using inversion-recovery (IR) radial fast low-angle shot (FLASH) and calibrationless motion-resolved model-based reconstruction. METHODS: Free-running (free-breathing, retrospective cardiac gating) IR radial FLASH is used for data acquisition at 3T. First, to reduce the waiting time between inversions, an analytical formula is derived that takes the incomplete T 1 $$ {\mathrm{T}}_1 $$ recovery into account for an accurate T 1 $$ {\mathrm{T}}_1 $$ calculation. Second, the respiratory motion signal is estimated from the k-space center of the contrast varying acquisition using an adapted singular spectrum analysis (SSA-FARY) technique. Third, a motion-resolved model-based reconstruction is used to estimate both parameter and coil sensitivity maps directly from the sorted k-space data. Thus, spatiotemporal total variation, in addition to the spatial sparsity constraints, can be directly applied to the parameter maps. Validations are performed on an experimental phantom, 11 human subjects, and a young landrace pig with myocardial infarction. RESULTS: In comparison to an IR spin-echo reference, phantom results confirm good T 1 $$ {\mathrm{T}}_1 $$ accuracy, when reducing the waiting time from 5 s to 1 s using the new correction. The motion-resolved model-based reconstruction further improves T 1 $$ {\mathrm{T}}_1 $$ precision compared to the spatial regularization-only reconstruction. Aside from showing that a reliable respiratory motion signal can be estimated using modified SSA-FARY, in vivo studies demonstrate that dynamic myocardial T 1 $$ {\mathrm{T}}_1 $$ maps can be obtained within 2 min with good precision and repeatability. CONCLUSION: Motion-resolved myocardial T 1 $$ {\mathrm{T}}_1 $$ mapping during free-breathing with good accuracy, precision and repeatability can be achieved by combining inversion-recovery radial FLASH, self-gating and a calibrationless motion-resolved model-based reconstruction.

Deep, deep learning with BART.

PURPOSE: To develop a deep-learning-based image reconstruction framework for reproducible research in MRI. METHODS: The BART toolbox offers a rich set of implementations of calibration and reconstruction algorithms for parallel imaging and compressed sensing. In this work, BART was extended by a nonlinear operator framework that provides automatic differentiation to allow computation of gradients. Existing MRI-specific operators of BART, such as the nonuniform fast Fourier transform, are directly integrated into this framework and are complemented by common building blocks used in neural networks. To evaluate the use of the framework for advanced deep-learning-based reconstruction, two state-of-the-art unrolled reconstruction networks, namely the Variational Network and MoDL, were implemented. RESULTS: State-of-the-art deep image-reconstruction networks can be constructed and trained using BART's gradient-based optimization algorithms. The BART implementation achieves a similar performance in terms of training time and reconstruction quality compared to the original implementations based on TensorFlow. CONCLUSION: By integrating nonlinear operators and neural networks into BART, we provide a general framework for deep-learning-based reconstruction in MRI.

Imaging of arrhythmia: Real-time cardiac magnetic resonance imaging in atrial fibrillation.

Objectives: Quantitative evaluations of function, volume and mass are fundamental in the diagnostic workup of different cardiovascular diseases and can be exactly determined by CMRI in sinus rhythm. This does not hold true in arrhythmia as CMR is hampered by reconstruction artifacts caused by inconsistent data from multiple heartbeats. Real-time (RT) MRI at high temporal resolution might reduce these problems. Methods: Consecutive patients with atrial fibrillation were prospectively included and underwent RT and conventional CINE CMR in randomized order. 29 patients were studied at 1.5 T and 30 patients at 3 T. At 3 T a group of 20 subjects in sinus rhythm served as controls. RT and CINE image quality was evaluated in different planes and for different wall sections using a Likert scale (from zero to four). Volumetric analysis was performed using two types of software and differences between RT and CINE CMR were evaluated. Results: In patients with atrial fibrillation RT CMR short axis (SA) resulted in a significantly higher image quality compared to CINE imaging both at 1.5 T and 3 T (1.5 T: mid SA: 3.55 ± 0.5 RT vs 2.6 ± 0.9 CINE, p = 0.0001; 3 T: mid SA: 3.15 ± 0.9 RT vs 2.6 ±1.0 CINE, p = 0.03); This qualitative difference was more marked and significant for the long axis views (2CV and 4CV) at 1.5 T (1.5 T: 2CV: 3.2 ± 0.6 RT vs 2.65 ± 1.1 CINE; p = 0.011; 4CV: 2.9 ± 0.69 RT vs 2.4 ± 0.9 CINE; p = 0.0044). During sinus rhythm CINE images were superior concerning diagnostic quality (3 T mid SA: 3.35 ± 0.45 RT vs 3.8 ± 0.5 CINE, p = 0.008). Quantitative analysis was successful with both software packages and the results showed a good correlation (Pearson correlation between 0.679 and 0.921 for patients). RT CMR resulted in slightly lower functional volumes than CINE CMR (3 T: patients: EDVI 86 ± 29 ml/m2 RT vs 93 29 ml/m2± 29 CINE, Pearson r = 0.902) but similar ejection fractions (3 T: patients: EF 47 ± 16% RT vs 45 ± 13% CINE, Pearson r = 0679; controls: EF 63 ± 6 RT vs 63 ± 3 CINE, Pearson r = 0.695). Conclusion: RT CMR improves image quality in arrhythmic patients and renders studies more comfortable. Volumetric analysis is feasible with slightly lower values relative to CINE CMR, while ejection fractions are comparable.

Real-time radial tagging for quantification of left ventricular torsion.

PURPOSE: To develop a real-time radial tagging MRI for accurate measurement of rotational motion and twist of the left ventricle (LV). METHODS: A FLASH-based radial tagging sequence with an undersampled radial reading scheme was developed for both single and double-slice imaging in real-time. The Polar Fourier Transform was used for reconstruction to push the undersampling artifacts out of a reduced FOV. The developed technique was used to image five normal subjects during rest, plus one during both exercise and rest conditions. LV rotational motions were estimated for five consecutive cardiac cycles in all cases. The process was validated using a numerical phantom. The real-time measurement of global rotational motion was compared with those measured from a non-real-time exam using linear regression analysis and the Bland-Altman plot. RESULTS: The real-time acquisition was performed successfully with a temporal resolution of 46.2 ms. Image quality was sufficient for the reproducible calculation of rotation at rest and exercise. The feasibility of double-slice acquisition on human was further studied and a real-time twist of the left ventricle was demonstrated. The difference between LV global rotations from real-time and non-real-time approaches was 0.27 degrees. A significant reverse recoiling, induced by exercise, was reproducibly measured by the technique. CONCLUSION: A real-time radial tagging MRI technique was developed based on the undersampled radial acquisition and Polar Fourier Transform reconstruction, for accurate measuring of the heart rotational motion and twist. The technique was able to extract a meaningful change of diastolic recoiling under stress test conditions during physical activities (cycling).

Assessment of esophagogastric junction morphology by dynamic real-time MRI: comparison of imaging features to high-resolution manometry.

PURPOSE: To assess the esophagogastric junction (EGJ) on real-time MRI and compare imaging parameters to EGJ morphology on high-resolution manometry (HRM). METHODS: A total of 105 of 117 eligible patients who underwent real-time MRI and high-resolution manometry for GERD-like symptoms between 2015 and 2018 at a single center were retrospectively evaluated (male n = 57; female n = 48; mean age 52.5 ± 15.4 years). Real-time MRI was performed at a median investigation time of 15 min (1 frame/40 ms). On HRM, EGJ morphology was assessed according to the Chicago classification of esophageal motility disorders. Real-time MRI was performed at 3 T using highly undersampled radial fast low-angle shot acquisitions with NLINV image reconstruction. A 10 mL pineapple juice bolus served as oral contrast agent at supine position. Real-time MRI films of the EGJ were acquired during swallowing events and during Valsalva maneuver. Anatomic and functional MRI parameters were compared to EGJ morphology on HRM. RESULTS: On HRM, n = 42 patients presented with EGJ type I (40.0%), n = 33 with EGJ type II (31.4%), and n = 30 with EGJ type III (28.6%). On real-time MRI, hiatal hernia was more common in patients with EGJ type III (66.7%) than in patients with EGJ type I (26.2%) and EGJ type II (30.3%; p < 0.001). Sliding hiatal hernia was more frequent in patients with EGJ type II (33.3%) than in patients with EGJ type III (16.7%) and EGJ type I (7.1%; p = 0.017). The mean esophagus-fundus angle of patients was 85 ± 31° at rest and increased to 101 ± 36° during Valsalva maneuver. CONCLUSION: Real-time MRI is a non-invasive imaging method for assessment of the esophagogastric junction. Real-time MRI can visualize dynamic changes of the EGJ during swallowing events.

Impaired Exercise Tolerance in Repaired Tetralogy of Fallot Is Associated With Impaired Biventricular Contractile Reserve: An Exercise-Stress Real-Time Cardiovascular Magnetic Resonance Study.

BACKGROUND: Correction of tetralogy of Fallot (cTOF) often results in pulmonary valve pathology and right ventricular (RV) dysfunction. Reduced exercise capacity in cTOF patients cannot be explained by these findings alone. We aimed to explore why cTOF patients exhibit impaired exercise capacity with the aid of a comprehensive cardiopulmonary exercise testing (CPET) and real-time cardiovascular magnetic resonance exercise testing (CMR-ET) protocol. METHODS: Thirty three cTOF patients and 35 matched healthy controls underwent CPET and CMR-ET in a prospective case-control study. Real-time steady-state free precession cine and phase-contrast sequences were obtained during incremental supine in-scanner cycling at 50, 70, and 90 W. RV and left ventricle (LV) volumes and pulmonary blood flow (Qp) were calculated. Differences of CPET and CMR-ET between cTOF versus controls and correlations between CPET and CMR-ET parameters in cTOF were evaluated statistically for all CMR exercise levels using Mann-Whitney U and Spearman rank-order correlation tests. RESULTS: CPET capacity was significantly lower in cTOF than in controls. cTOF patients exhibited not only significantly reduced Qp and RV function but also lower LV function on CMR-ET. Higher CPET values in cTOF correlated with higher Qp (Qp 90 W versus carbon dioxide ventilatory equivalent %: R=-0.519, P<0.05), higher LV-end-diastolic volume indexed to body surface area (LV-end-diastolic volume indexed to body surface area at 50 W versus oxygen uptake in % at maximum exercise on CPET R=0.452, P<0.05), and change in LV ejection fraction (EF; LV-EF at 90 W versus Watt %: r=-0.463, P<0.05). No correlation was found with regard to RV-EF. Significant RV-LV interaction was observed during CMR-ET (RV-EF versus LV-EF at 50 W and 70 W: r=0.66, P<0.02 and r=0.52, P<0.05, respectively). CONCLUSIONS: Impaired exercise capacity in cTOF resulted from a reduction in not only RV, but also LV function. cTOF with good exercise capacity on CPET demonstrated higher LV reserve and pulmonary blood flow during incremental CMR-ET. Apart from RV parameters, CMR-ET-derived LV function could be a valuable tool to stratify cTOF patients for pulmonary valve replacement.