Cine Images Research Articles

Deep learning-based prognostic model using non-enhanced cardiac cine MRI for outcome prediction in patients with heart failure.

To evaluate the performance of a deep learning-based multi-source model for survival prediction and risk stratification in patients with heart failure. Patients with heart failure with reduced ejection fraction (HFrEF) who underwent cardiac magnetic resonance between January 2015 and April 2020 were retrospectively included in this study. Baseline electronic health record data, including clinical demographic information, laboratory data, and electrocardiographic information, were collected. Short-axis non-contrast cine images of the whole heart were acquired to estimate the cardiac function parameters and the motion features of the left ventricle. Model accuracy was evaluated using the Harrell's concordance index. All patients were followed up for major adverse cardiac events (MACEs), and survival prediction was assessed using Kaplan-Meier curves. A total of 329 patients were evaluated (age 54 ± 14years; men, 254) in this study. During a median follow-up period of 1041days, 62 patients experienced MACEs and their median survival time was 495days. When compared with conventional Cox hazard prediction models, deep learning models showed better survival prediction performance. Multi-data denoising autoencoder (DAE) model reached the concordance index of 0.8546 (95% CI: 0.7902-0.8883). Furthermore, when divided into phenogroups, the multi-data DAE model could significantly discriminate between the survival outcomes of the high-risk and low-risk groups compared with other models (p < 0.001). The proposed deep learning (DL) model based on non-contrast cardiac cine magnetic resonance imaging could independently predict the outcome of patients with HFrEF and showed better prediction efficiency than conventional methods. The proposed multi-source deep learning model based on cardiac magnetic resonance enables survival prediction in patients with heart failure. • A multi-source deep learning model based on non-contrast cardiovascular magnetic resonance (CMR) cine images was built to make robust survival prediction in patients with heart failure. • The ground truth definition contains electronic health record data as well as DL-based motion data, and cardiac motion information is extracted by optical flow method from non-contrast CMR cine images. • The DL-based model exhibits better prognostic value and stratification performance when compared with conventional prediction models and could aid in the risk stratification in patients with HF.

Intravenous thrombolysis for bioprosthetic valve thrombosis.

A 77-year-old woman experienced new-onset dyspnoea on exertion 1 year after alcohol septal ablation and transcatheter aortic valve implantation (TAVI) with a balloon-expandable valve for symptomatic severe aortic stenosis and basal septal hypertrophy. Transthoracic echocardiographic assessment (TTE) revealed an incremental transvalvular peak velocity from 2.9 m/s 3 days after TAVI to 4.3 m/s. Multislice computed tomography (MSCT) demonstrated hypoattenuated leaflet thickening (HALT) of all leaflets and reduced leaflet motion (RLM) of one leaflet (Panel A). Her antithrombotic regimen was changed from apixaban 5 mg bi-daily to acenocoumarol with a target international normalized ratio (INR) of 2.5–3.5. Six weeks later, symptoms persisted and the transvalvular peak velocity was 3.9 m/s (Panel B). A decision was made to attempt to resolve the thrombus with repeated intravenous infusions of alteplase.1,2 Four sequential infusions of 25 mg alteplase/25 h resulted in an uneventful but stepwise decrease of the transvalvular peak velocity to 2.8 m/s (Panel C–F). Multislice computed tomography confirmed normalization of leaflet motion with some residual remaining leaflet thickening (Panel F). MSCT cine images before and after alteplase infusion are available in the Supplementary data online (Videos S1 and S2).

Phenotyping heart failure by cardiac magnetic resonance imaging of cardiac macro- and microscopic structure: state of the art review.

Heart failure demographics have evolved in past decades with the development of improved diagnostics, therapies, and prevention. Cardiac magnetic resonance (CMR) has developed in a similar timeframe to become the gold-standard non-invasive imaging modality for characterizing diseases causing heart failure. CMR techniques to assess cardiac morphology and function have progressed since their first use in the 1980s. Increasingly efficient acquisition protocols generate high spatial and temporal resolution images in less time. This has enabled new methods of characterizing cardiac systolic and diastolic function such as strain analysis, exercise real-time cine imaging and four-dimensional flow. A key strength of CMR is its ability to non-invasively interrogate the myocardial tissue composition. Gadolinium contrast agents revolutionized non-invasive cardiac imaging with the late gadolinium enhancement technique. Further advances enabled quantitative parametric mapping to increase sensitivity at detecting diffuse pathology. Novel methods such as diffusion tensor imaging and artificial intelligence-enhanced image generation are on the horizon. Magnetic resonance spectroscopy (MRS) provides a window into the molecular environment of the myocardium. Phosphorus (31P) spectroscopy can inform the status of cardiac energetics in health and disease. Proton (1H) spectroscopy complements this by measuring creatine and intramyocardial lipids. Hyperpolarized carbon (13C) spectroscopy is a novel method that could further our understanding of dynamic cardiac metabolism. CMR of other organs such as the lungs may add further depth into phenotypes of heart failure. The vast capabilities of CMR should be deployed and interpreted in context of current heart failure challenges.

Accelerated Cardiac MRI Cine with Use of Resolution Enhancement Generative Adversarial Inline Neural Network.

Background Cardiac cine can benefit from deep learning-based image reconstruction to reduce scan time and/or increase spatial and temporal resolution. Purpose To develop and evaluate a deep learning model that can be combined with parallel imaging or compressed sensing (CS). Materials and Methods The deep learning model was built on the enhanced super-resolution generative adversarial inline neural network, trained with use of retrospectively identified cine images and evaluated in participants prospectively enrolled from September 2021 to September 2022. The model was applied to breath-hold electrocardiography (ECG)-gated segmented and free-breathing real-time cine images collected with reduced spatial resolution with use of generalized autocalibrating partially parallel acquisitions (GRAPPA) or CS. The deep learning model subsequently restored spatial resolution. For comparison, GRAPPA-accelerated cine images were collected. Diagnostic quality and artifacts were evaluated by two readers with use of Likert scales and compared with use of Wilcoxon signed-rank tests. Agreement for left ventricle (LV) function, volume, and strain was assessed with Bland-Altman analysis. Results The deep learning model was trained on 1616 patients (mean age ± SD, 56 years ± 16; 920 men) and evaluated in 181 individuals, 126 patients (mean age, 57 years ± 16; 77 men) and 55 healthy subjects (mean age, 27 years ± 10; 15 men). In breath-hold ECG-gated segmented cine and free-breathing real-time cine, the deep learning model and GRAPPA showed similar diagnostic quality scores (2.9 vs 2.9, P = .41, deep learning vs GRAPPA) and artifact score (4.4 vs 4.3, P = .55, deep learning vs GRAPPA). Deep learning acquired more sections per breath-hold than GRAPPA (3.1 vs one section, P < .001). In free-breathing real-time cine, the deep learning showed a similar diagnostic quality score (2.9 vs 2.9, P = .21, deep learning vs GRAPPA) and lower artifact score (3.9 vs 4.3, P < .001, deep learning vs GRAPPA). For both sequences, the deep learning model showed excellent agreement for LV parameters, with near-zero mean differences and narrow limits of agreement compared with GRAPPA. Conclusion Deep learning-accelerated cardiac cine showed similarly accurate quantification of cardiac function, volume, and strain to a standardized parallel imaging method. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Vannier and Wang in this issue.

Dual-domain accelerated MRI reconstruction using transformers with learning-based undersampling.

Acceleration in MRI has garnered much attention from the deep-learning community in recent years, particularly for imaging large anatomical volumes such as the abdomen or moving targets such as the heart. A variety of deep learning approaches have been investigated, with most existing works using convolutional neural network (CNN)-based architectures as the reconstruction backbone, paired with fixed, rather than learned, k-space undersampling patterns. In both image domain and k-space, CNN-based architectures may not be optimal for reconstruction due to its limited ability to capture long-range dependencies. Furthermore, fixed undersampling patterns, despite ease of implementation, may not lead to optimal reconstruction. Lastly, few deep learning models to date have leveraged temporal correlation across dynamic MRI data to improve reconstruction. To address these gaps, we present a dual-domain (image and k-space), transformer-based reconstruction network, paired with learning-based undersampling that accepts temporally correlated sequences of MRI images for dynamic reconstruction. We call our model DuDReTLU-net. We train the network end-to-end against fully sampled ground truth dataset. Human cardiac CINE images undersampled at different factors (5-100) were tested. Reconstructed images were assessed both visually and quantitatively via the structural similarity index, mean squared error, and peak signal-to-noise. Experimental results show superior performance of DuDReTLU-net over state-of-the-art methods (LOUPE, k-t SLR, BM3D-MRI) in accelerated MRI reconstruction; ablation studies show that transformer-based reconstruction outperformed CNN-based reconstruction in both image domain and k-space; dual-domain reconstruction architectures outperformed single-domain reconstruction architectures regardless of reconstruction backbone (CNN or transformer); and dynamic sequence input leads to more accurate reconstructions than single frame input. We expect our results to encourage further research in the use of dual-domain architectures, transformer-based architectures, and learning-based undersampling, in the setting of accelerated MRI reconstruction. The code for this project is made freely available at https://github.com/william2343/dual-domain-mri-recon-nets (Hong et al., 2022).

Left atrial sphericity in relation to atrial strain and strain rate in atrial fibrillation patients

PurposeLeft atrial (LA) sphericity is a novel, geometry-based parameter that has been used to visualize and quantify LA geometrical remodeling in patients with atrial fibrillation (AF). This study examined the association between LA sphericity, and LA longitudinal strain and strain rate measured by feature-tracking in AF patients.Methods128 AF patients who underwent cardiovascular magnetic resonance (CMR) imaging in sinus rhythm prior to their pulmonary vein isolation (PVI) procedure were retrospectively analyzed. LA sphericity was calculated by segmenting the LA (excluding the pulmonary veins and the LA appendage) on a 3D contrast enhanced MR angiogram and comparing the resulting shape with a perfect sphere. LA global reservoir strain, conduit strain, contractile strain and corresponding strain rates were derived from cine images using feature-tracking. For statistical analysis, Pearson correlations, multivariable logistic regression analysis, and Student t-tests were used.ResultsPatients with a spherical LA (dichotomized by the median value) had a lower reservoir strain and conduit strain compared to patients with a non-spherical LA (-15.4 ± 4.2% vs. -17.1 ± 3.5%, P = 0.02 and − 8.2 ± 3.0% vs. -9.5 ± 2.6%, P = 0.01, respectively). LA strain rate during early ventricular diastole was also different between both groups (-0.7 ± 0.3s− 1 vs. -0.9 ± 0.3s− 1, P = 0.001). In contrast, no difference was found for LA contractile strain (-7.2 ± 2.6% vs. -7.6 ± 2.2%, P = 0.30).ConclusionsLA passive strain is significantly impaired in AF patients with a spherical LA, though this relation was not independent from LA volume.

Associations of aortic stiffness and intra-aortic flow parameters with epicardial adipose tissue in patients with type-2 diabetes.

It has been shown that increased aortic stiffness is related to type-2 diabetes (T2D) which is considered as a risk factor for cardiovascular disease. Among other risk factors is epicardial adipose tissue (EAT) which is increased in T2D and is a relevant biomarker of metabolic severity and adverse outcome. To assess aortic flow parameters in T2D patients as compared to healthy individuals and to evaluate their associations with EAT accumulation as an index of cardiometabolic severity in T2D patients. Thirty-six T2D patients as well as 29 healthy controls matched by age and sex were included in this study. Participants had cardiac and aortic MRI exams at 1.5 T. Imaging sequences included cine SSFP for left ventricle (LV) function and EAT assessment and aortic cine and phase-contrast imaging for strain and flow parameters quantification. In this study, we found LV phenotype to be characterized by concentric remodeling with decreased stroke volume index despite global LV mass within a normal range. EAT was increased in T2D patients compared to controls (p<0.0001). Moreover, EAT, a biomarker of metabolic severity, was negatively correlated to ascending aortic (AA) distensibility (p=0.048) and positively to the normalized backward flow volume (p=0.001). These relationships remained significant after further adjustment for age, sex and central mean blood pressure. In a multivariate model, presence/absence of T2D and AA normalized backward flow (BF) to forward flow (FF) volumes ratio are both significant and independent correlates of EAT. In our study, aortic stiffness as depicted by an increased backward flow volume and decreased distensibility seems to be related to EAT volume in T2D patients. This observation should be confirmed in the future on a larger population while considering additional biomarkers specific to inflammation and using a longitudinal prospective study design.

Extreme cardiac remodelling observed in elite endurance athletes: analysis of myocardial deformation and estimated hemodynamic forces

Abstract Funding Acknowledgements Type of funding sources: None. Background Athletes of endurance disciplines present the highest level of cardiac remodelling often generating concerns for differential diagnosis with cardiomyopathies. In addition to standard morpho-functional evaluation, left ventricle (LV) myocardial deformation (MD) and estimated intra-ventricular hemodynamic forces (HDFs) are emerging diagnostic tools, particularly in heart failure patients. In the athletic population MD data are scarce while HDFs are lacking. Purpose To describe MD and HDFs evaluated by CMR feature-tracking in a cohort of endurance Olympic athletes and to evaluate the possible relationship with LV geometry. Methods A group of endurance Olympic athletes evaluated prior the Olympic games and with unremarkable cardiac pre-participation screening tests was enrolled. All athletes underwent CMR without contrast administration. Cine images were post-processed to evaluate end-diastolic and end-systolic LV volumes, ejection fraction (LVEF), global longitudinal and circumferential strain (GLS and GCS) and estimated HDFs by a dedicated feature-tracking software. HDFs were measured in apex-base (AB) and latero-septal (LS) directions, over the entire cardiac cycle, in systole and diastole. LS/AB ratio was also derived to determine forces distribution. Athletes were divided in subgroups according to the 3D sphericity index (&amp;lt; 40% or 40%). A group of sedentary subjects was enrolled as a control group. Results 109 endurance Olympic athletes (62% male; mean age 26 ± 5 years) and 21 sedentary subjects were enrolled. Athletes with increased sphericity index (≥40%) were 61 (56%) and presented with greater EDV, ESV and lower LVEF compared to those without increased sphericity and controls (Table). No significant differences were found between athletes and controls regarding LV-GLS and GCS. HDFs distribution was not different between groups and even athletes with a more spherical LV shape showed an HDFs diastolic ratio comparable to those of athletes with lower sphericity index and control. Conclusion Although more than half of endurance athletes presented with altered geometry (increased sphericity index), strain parameters and hemodynamic forces were not different from sedentary controls and those athletes without increased sphericity. The use of advanced parameters to evaluate cardiac function could be used as a tool to confirm the benign nature of cardiac adaptation due to intense exercise training.

Characterization of biatrial sports adaption in a large, highly trained athletes cohort using feature tracking cardiac magnetic resonance

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Project no. TKP2021-NKTA-46 has been implemented with the support provided by the Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021-NKTA funding scheme. This project was also supported by a grant from the National Research, Development, and Innovation Office (NKFIH) of Hungary (K135076 to BM). Introduction Feature tracking strain analysis using cardiac magnetic resonance (CMR) imaging enables the appreciation of complex mechanics of the athlete’s heart without adding extra sequences and increasing image acquisition time. Purpose We evaluated the associations of the left (LA) and right atrial (RA) functional and strain parameters with sports activity and demographic characteristics in a large cohort of competitive athletes. We compared the athlete’s biatrial remodelling with healthy, sex-matched control subjects. Methods We performed a retrospective analysis on native CMR cine images acquired between 2009 and 2021. Standard two-chamber and four-chamber long-axis cine movies were analyzed using Medis Suite software. We excluded images with foreshortening or apparent planning flaw. Subjects were categorized into four groups based on their weekly training loads (&amp;lt;6 hours, 6-10 hours, 11-20 hours and 21&amp;lt; hours). Results We performed CMR on 510 subjects, of which 375 were highly trained athletes (median age 20 ys, IQR 16-25; 244 male). A group of 135 healthy volunteers [median (mdn) age 25 ys, IQR 23-28, 64 male] served as controls. Left atrial global longitudinal strain (GLS) was lower (p=.002) in athletes (mdn 41%) than in controls (mdn 43%), whereas RA GLS showed a more pronounced decrease (mdn 32% vs 43%, p&amp;lt;.0001). Between male athletes and controls, LA global circumferential strain [(GCS), mdn 40% vs 47%, p=.0001], LA conduit (mdn 26% vs 28%, p=.025), RA GLS (mdn 31% vs 38%, p&amp;lt;.0001), RA GCS (mdn 17% vs 20%, p=.024), RA booster (mdn 10% vs 9%, p&amp;lt;.001) and RA conduit (mdn 21% vs 24%, p=.001) strain values showed a difference. Between female athletes and controls, RA GLS (mdn 34% vs 44%, p&amp;lt;.0001), RA GCS (mdn 19% vs 29%, p&amp;lt;.001), RA booster (mdn 9% vs 13%, p=.006), and RA conduit (mdn 25% vs 32%, p&amp;lt;.001) were significantly different, while LA strain values were comparable. We found a significant difference between male and female athletes in terms of LA GLS (mdn 39%, vs 43%, p=.0001), LA GCS (mdn 40% vs 42%, p=.01) and LA conduit strain (mdn 26% vs 29%, p&amp;lt;.001). Regarding the right atrium, GLS (mdn 31% vs 34%, p=.047) and conduit strain (mdn 21% vs 25%, p=.004) were significantly lower in male athletes. LA GLS only differed between the lowest and highest training volumes (p=0.048). LA GCS was higher in the least trained group (p&amp;lt;.001) than in the other three categories. Interestingly, the LA end-diastolic volume index was less (r=0.13, p=0.008) correlated to weekly training volume than the left ventricular end-diastolic volume index (r=0.51, p&amp;lt;.0001). Conclusion The atrial adaptation of the athlete’s heart shows distinct mechanic properties, which are further stratified with exercise level and sex. The RA seems to be more prone to increasing exercise load than the LA. Sophisticated atrial function characterization by strain analysis might provide novel insight into healthy sports adaptation.

Association of Internal and External Motion Based on Cine MR Images Acquired During Real-Time Treatment on MRI–Guided Linear Accelerator for Patients With Lung Cancer

With the recent clinical implementation of magnetic resonance imaging (MRI)-guided linear accelerators, a large number of real-time planar MR images has been acquired during lung cancer treatment as a standard of care. In this study, associations among lung tumor, diaphragm, and external skin movement were studied based on MR cine imaging during the entire duration of each treatment fraction. This retrospective study used 181,798 planar MRI frames acquired over 55 treatment/imaging sessions of 13 patients with lung cancer treated on 2 MRI-guided linear accelerators. From each planar MR image frame, in-house software automatically extracted 9 features: the superior-interior (SI) and posterior-anterior (PA) positions of a lung tumor; the area of the lung (Lung_Area); the posterior (Dia_Post), dome/apex (Dia_Dome), and anterior (Dia_Ant) points of a diaphragmatic curve; the diaphragm curve point (Dia_Max); and the chest (Chest) and belly (Belly) skin points experienced the maximum range of motions. Correlation analyses were performed among the 9 features for every session. Lung tumor motion range and standard deviations were calculated based on positions obtained in cine images and compared with motion ranges obtained from 4-dimensional computed tomography images. In the study, 177,009 frames of images were successfully analyzed. For all patients, correlation coefficients were as follows: 0.91 ± 0.10 between any 2 features among Lung_Area, Dia_Post, Dia_Dome, and Dia_Max; 0.82 ± 0.21 between SI and any feature among Lung_Area, Dia_Post, Dia_Dome, and Dia_Max; 0.75 ± 0.24 between SI and Belly. Six of 13 patients were considered large amplitude motion (patients with lung tumor SI motion standard deviation >5 mm). Furthermore, 92,956 frames of images were analyzed for the 6 large-amplitude motion patients. For this set, correlation coefficients were 0.93 ± 0.07 between any 2 features among Lung_Area, Dia_Post, Dia_Dome, and Dia_Max; 0.94 ± 0.06 between SI and any feature among Lung_Area, Dia_Post, Dia_Dome, and Dia_Max; and 0.90 ± 0.09 between SI and Belly. Both belly and diaphragmatic motions as assessed by cine MRI are highly correlated with large amplitude lung tumor motion in the longitudinal axis.

C44 ATRIAL SEPTAL ABNORMALITIES: A CASE OF DOUBLE INTERATRIAL SEPTUM

Abstract The Case A 41–year–old asymptomatic male was referred to our cardiology outpatient clinic for diagnostic evaluation of a suspected bicuspid aortic valve at transthoracic echocardiography. Trans–oesophageal imaging ruled–out the bicuspid aortic valve, but detected an accessory membrane lining the interatrial septum with a double–layered appearance encompassing most of the fossa ovalis. Agitated saline infusion demonstrated an inter–atrial communication with right–to–left shunt under Valsalva manoeuvre. Cardiovascular magnetic resonance cine imaging confirmed the presence of a double interatrial septum featuring a midline recess enclosed by the two septa. Under end–expiratory breath–holding conditions, a transient right–to–left shunt was observed confirming the echocardiographic evaluation (Panel 1). No history of cerebrovascular disease and no clinical or imaging findings of right heart overload were registered. Discussion Double interatrial septum is a rare congenital condition, by morphological side, allegedly associated with an increased risk of left–sided embolic events due to blood stasis within the accessory interatrial chamber, that is often found in continuity with both atria through patent foramen ovale or additional septal fenestrations. In this case, multimodality imaging effectively was able to detect the presence of this rare atrial septal abnormality and to distinguish that from others alterations of the interatrial septum shown in the table below (Table 1). Nevertheless, the clinical significance of double interatrial septum remains uncertain, no clear relationship with embolic stroke is known and no recommendation can be made regarding the decision–making for long–term anti–thrombotic management. High quality evidences are needed to evaluate whether double atrial septum or other atrial septal abnormalities might be considered as actionable risk factors of ischemic stroke or not.

PET/MRI Assessment of Acute Cardiac Inflammation 1 Month After Left-Sided Breast Cancer Radiation Therapy.

Our purpose was to investigate the utility of 18F-FDG PET/MRI and serial blood work to detect early inflammatory responses and cardiac functionality changes at 1 mo after radiation therapy (RT) in patients with left-sided breast cancer. Methods: Fifteen left-sided breast cancer patients who enrolled in the RICT-BREAST study underwent cardiac PET/MRI at baseline and 1 mo after standard RT. Eleven patients received deep-inspiration breath-hold RT, whereas the others received free-breathing RT. A list-mode 18F-FDG PET scan with glucose suppression was acquired. Myocardial inflammation was quantified by the change in 18F-FDG SUVmean (based on body weight) and analyzed on the basis of the myocardial tissue associated with the left anterior descending, left circumflex, or right coronary artery territories. MRI assessments, including left ventricular functional and extracellular volumes (ECVs), were extracted from T1 (before and during a constant infusion of gadolinium) and cine images, respectively, acquired simultaneously during the PET acquisition. Cardiac injury and inflammation biomarker measurements of high-sensitivity troponin T, high-sensitivity C-reactive protein, and erythrocyte sedimentation rate were measured at the 1-mo follow-up and compared with preirradiation values. Results: At the 1-mo follow-up, a significant increase (10%) in myocardial SUVmean in left anterior descending segments (P = 0.04) and ECVs in slices at the apex (6%) and base (5%) was detected (P ≤ 0.02). Further, a significant reduction in left ventricular stroke volume (-7%) was seen (P < 0.02). No significant changes in any circulating biomarkers were seen at follow-up. Conclusion: Myocardial 18F-FDG uptake and functional MRI, including stroke volume and ECVs, were sensitive to changes at 1 mo after breast cancer RT, with findings suggesting an acute cardiac inflammatory response to RT.

Three-dimensional sector-wise golden angle-improved k-space uniformity after electrocardiogram binning.

To develop and evaluate a 3D sector-wise golden-angle (3D-SWIG) profile ordering scheme for cardiovascular MR cine imaging that maintains high k-space uniformity after electrocardiogram (ECG) binning. Cardiovascular MR (CMR) was performed at 1.5 T. A balanced SSFP pulse sequence was implemented with a novel 3D-SWIG radial ordering, where k-space was divided into wedges, and each wedge was acquired in a separate heartbeat. The high uniformity of k-space coverage after physiological binning can be used to perform functional imaging using a very short acquisition. The 3D-SWIG was compared with two commonly used 3D radial trajectories for CMR (i.e., double golden angle and spiral phyllotaxis) in numerical simulations. Free-breathing 3D-SWIG and conventional breath-held 2D cine were compared in patients (n = 17) referred clinically for CMR. Quantitative comparison was performed based on left ventricular segmentation. Numerical simulations showed that 3D-SWIG both required smaller steps between successive readouts and achieved better k-space sampling uniformity after binning than either the double golden angle or spiral phyllotaxis trajectories. In vivo evaluation showed that measurements of left ventricular ejection fraction calculated from a 48 heart-beat free-breathing 3D-SWIG acquisition were highly reproducible and agreed with breath-held 2D-Cartesian cine (mean ± SD difference of -3.1 ± 3.5% points). The 3D-SWIG acquisition offers a simple solution for highly improved k-space uniformity after physiological binning. The feasibility of the 3D-SWIG method is demonstrated in this study through whole-heart cine imaging during free breathing with an acquisition time of less than 1 min.

Single-heartbeat cardiac cine imaging via jointly regularized nonrigid motion-corrected reconstruction.

The aim of the current study was to develop a novel approach for 2D breath-hold cardiac cine imaging from a single heartbeat, by combining cardiac motion-corrected reconstructions and nonrigidly aligned patch-based regularization. Conventional cardiac cine imaging is obtained via motion-resolved reconstructions of data acquired over multiple heartbeats. Here, we achieve single-heartbeat cine imaging by incorporating nonrigid cardiac motion correction into the reconstruction of each cardiac phase, in conjunction with a motion-aligned patch-based regularization. The proposed Motion-Corrected CINE (MC-CINE) incorporates all acquired data into the reconstruction of each (motion-corrected) cardiac phase, resulting in a better posed problem than motion-resolved approaches. MC-CINE was compared with iterative sensitivity encoding (itSENSE) and Extra-Dimensional Golden Angle Radial Sparse Parallel (XD-GRASP) in 14 healthy subjects in terms of image sharpness, reader scoring (range: 1-5) and reader ranking (range: 1-9) of image quality, and single-slice left ventricular assessment. MC-CINE was significantly superior to both itSENSE and XD-GRASP using 20 heartbeats, two heartbeats, and one heartbeat. Iterative SENSE, XD-GRASP, and MC-CINE achieved a sharpness of 74%, 74%, and 82% using 20 heartbeats, and 53%, 66%, and 82% with one heartbeat, respectively. The corresponding results for reader scoring were 4.0, 4.7, and 4.9 with 20 heartbeats, and 1.1, 3.0, and 3.9 with one heartbeat. The corresponding results for reader ranking were 5.3, 7.3, and 8.6 with 20 heartbeats, and 1.0, 3.2, and 5.4 with one heartbeat. MC-CINE using a single heartbeat presented nonsignificant differences in image quality to itSENSE with 20 heartbeats. MC-CINE and XD-GRASP at one heartbeat both presented a nonsignificant negative bias of less than 2% in ejection fraction relative to the reference itSENSE. It was concluded that the proposed MC-CINE significantly improves image quality relative to itSENSE and XD-GRASP, enabling 2D cine from a single heartbeat.

Prognostic impact of artificial intelligence-based fully automated global circumferential strain in patients undergoing stress CMR

To determine whether fully automated artificial intelligence-based global circumferential strain (GCS) assessed during vasodilator stress cardiovascular magnetic resonance (CMR) can provide incremental prognostic value. Between 2016 and 2018, a longitudinal study included all consecutive patients with abnormal stress CMR defined by the presence of inducible ischaemia and/or late gadolinium enhancement (LGE). Control subjects with normal stress CMR were selected using a propensity score-matching. Stress-GCS was assessed using a fully automatic machine learning algorithm based on featured-tracking imaging from short-axis cine images. The primary outcome was the occurrence of major adverse clinical events (MACE) defined as cardiovascular mortality or nonfatal myocardial infarction. Cox regressions evaluated the association between stress-GCS and the primary outcome after adjustment for traditional prognosticators. In 2670 patients [65 ± 12 years, 68% men, 1:1 matched patients (1335 with normal and 1335 with abnormal CMR)], stress-GCS was associated with MACE [median follow-up 5.2 (4.8–5.5) years] after adjustment for risk factors in the propensity-matched population (adjusted hazard ratio [HR]: 1.12 [95% CI: 1.06–1.18]) and patients with normal CMR (HR: 1.43 [95% CI: 1.30–1.57], both P < 0.001), but not in patients with abnormal CMR (P = 0.33). In patients with normal CMR, an increased stress-GCS > −10% showed the best improvement in model discrimination and reclassification above traditional and stress CMR findings (C-statistic improvement: 0.27; NRI = 0.538; IDI = 0.108, all P < 0.001; LR-test P < 0.001). Stress-GCS is independently associated with MACE in patients undergoing stress CMR, with an incremental prognostic value over traditional risk factors and stress CMR findings in the group of patients with normal CMR. Prognostic value of AI-based Stress-GCS (Fig. 1).

Ramping down a clinical 3 T scanner: a journey into MRI and MRS at 0.75 T

ObjectLower-field MR is reemerging as a viable, potentially cost-effective alternative to high-field MR, thanks to advances in hardware, sequence design, and reconstruction over the past decades. Evaluation of lower field strengths, however, is limited by the availability of lower-field systems on the market and their considerable procurement costs. In this work, we demonstrate a low-cost, temporary alternative to purchasing a dedicated lower-field MR system.Materials and MethodsBy ramping down an existing clinical 3 T MRI system to 0.75 T, proton signals can be acquired using repurposed 13C transmit/receive hardware and the multi-nuclei spectrometer interface. We describe the ramp-down procedure and necessary software and hardware changes to the system.ResultsApart from presenting system characterization results, we show in vivo examples of cardiac cine imaging, abdominal two- and three-point Dixon-type water/fat separation, water/fat-separated MR Fingerprinting, and point-resolved spectroscopy. In addition, the ramp-down approach allows unique comparisons of, e.g., gradient fidelity of the same MR system operated at different field strengths using the same receive chain, gradient coils, and amplifiers.DiscussionRamping down an existing MR system may be seen as a viable alternative for lower-field MR research in groups that already own multi-nuclei hardware and can also serve as a testing platform for custom-made multi-nuclei transmit/receive coils.

Prognostic impact of artificial intelligence-based fully automated global circumferential strain in patients undergoing stress CMR.

To determine whether fully automated artificial intelligence-based global circumferential strain (GCS) assessed during vasodilator stress cardiovascular (CV) magnetic resonance (CMR) can provide incremental prognostic value. Between 2016 and 2018, a longitudinal study included all consecutive patients with abnormal stress CMR defined by the presence of inducible ischaemia and/or late gadolinium enhancement. Control subjects with normal stress CMR were selected using a propensity score-matching. Stress-GCS was assessed using a fully automatic machine-learning algorithm based on featured-tracking imaging from short-axis cine images. The primary outcome was the occurrence of major adverse clinical events (MACE) defined as CV mortality or nonfatal myocardial infarction. Cox regressions evaluated the association between stress-GCS and the primary outcome after adjustment for traditional prognosticators. In 2152 patients [66 ± 12 years, 77% men, 1:1 matched patients (1076 with normal and 1076 with abnormal CMR)], stress-GCS was associated with MACE [median follow-up 5.2 (4.8-5.5) years] after adjustment for risk factors in the propensity-matched population [adjusted hazard ratio (HR), 1.12 (95% CI, 1.06-1.18)], and patients with normal CMR [adjusted HR, 1.35 (95% CI, 1.19-1.53), both P < 0.001], but not in patients with abnormal CMR (P = 0.058). In patients with normal CMR, an increased stress-GCS showed the best improvement in model discrimination and reclassification above traditional and stress CMR findings (C-statistic improvement: 0.14; NRI = 0.430; IDI = 0.089, all P < 0.001; LR-test P < 0.001). Stress-GCS is not a predictor of MACE in patients with ischaemia, but has an incremental prognostic value in those with a normal CMR although the absolute event rate remains low.

Parametric mapping by cardiovascular magnetic resonance imaging in sudden cardiac arrest survivors.

Etiology of sudden cardiac arrest (SCA) is identified in less than 30% of survivors without coronary artery disease. We sought to assess the diagnostic role of myocardial parametric mapping using cardiovascular magnetic resonance (CMR) in identifying SCA etiology. Consecutive SCA survivors undergoing CMR with myocardial parametric mapping were included in the study. The determination if CMR was decisive or contributory in identifying SCA etiology was made if the diagnosis was unclear prior to CMR, and the discharge diagnosis was consistent with the CMR result. Parametric mapping was considered essential for establishing probable SCA etiology by CMR if the SCA cause could not have been determined without its utilization. If the CMR diagnosis could have been potentially based on the combination of cine and LGE imaging, parametric mapping was considered contributory. Of the 35 patients (mean age 46.9 ± 14.1years; 57% males) included, SCA diagnosis was based on CMR in 23 (66%) patients. Of those, parametric mapping was essential for the diagnosis of myocarditis and tako-tsubo cardiomyopathy (11/48%) and contributed to the diagnosis in 10 (43%) additional cases. Inclusion of quantitative T1 and T2 parametric mapping in the SCA CMR protocol has the potential to increase diagnostic yield of CMR and further specify SCA etiology, especially myocarditis.

CMR-derived left ventricular intraventricular pressure gradients identify different patterns associated with prognosis in dilated cardiomyopathy.

Left ventricular (LV) blood flow is determined by intraventricular pressure gradients (IVPG). Changes in blood flow initiate remodelling and precede functional decline. Novel cardiac magnetic resonance (CMR) post-processing LV-IVPG analysis might provide a sensitive marker of LV function in dilated cardiomyopathy (DCM). Therefore, the aim of our study was to evaluate LV-IVPG patterns and their prognostic value in DCM. LV-IVPGs between apex and base were measured on standard CMR cine images in DCM patients (n = 447) from the Maastricht Cardiomyopathy registry. Major adverse cardiovascular events, including heart failure hospitalisations, life-threatening arrhythmias, and sudden/cardiac death, occurred in 66 DCM patients (15%). A temporary LV-IVPG reversal during systolic-diastolic transition, leading to a prolonged transition period or slower filling, was present in 168 patients (38%). In 14%, this led to a reversal of blood flow, which predicted outcome corrected for univariable predictors [hazard ratio (HR) = 2.57, 95% confidence interval (1.01-6.51), P = 0.047]. In patients without pressure reversal (n = 279), impaired overall LV-IVPG [HR = 0.91 (0.83-0.99), P = 0.033], systolic ejection force [HR = 0.91 (0.86-0.96), P < 0.001], and E-wave decelerative force [HR = 0.83 (0.73-0.94), P = 0.003] predicted outcome, independent of known predictors (age, sex, New York Heart Association class ≥ 3, LV ejection fraction, late gadolinium enhancement, LV-longitudinal strain, left atrium (LA) volume-index, and LA-conduit strain). Pressure reversal during systolic-diastolic transition was observed in one-third of DCM patients, and reversal of blood flow direction predicted worse outcome. In the absence of pressure reversal, lower systolic ejection force, E-wave decelerative force (end of passive LV filling), and overall LV-IVPG are powerful predictors of outcome, independent of clinical and imaging parameters.

Pancreatic fatty replacement as risk marker for altered glucose metabolism and cardiac iron and complications in thalassemia major

ObjectivesThis multicenter study assessed the extent of pancreatic fatty replacement and its correlation with demographics, iron overload, glucose metabolism, and cardiac complications in a cohort of well-treated patients with thalassemia major (TM).MethodsWe considered 308 TM patients (median age: 39.79 years; 182 females) consecutively enrolled in the Extension-Myocardial Iron Overload in Thalassemia Network. Magnetic resonance imaging was used to quantify iron overload (IO) and pancreatic fat fraction (FF) by T2* technique, cardiac function by cine images, and to detect replacement myocardial fibrosis by late gadolinium enhancement technique. The glucose metabolism was assessed by the oral glucose tolerance test.ResultsPancreatic FF was associated with age, body mass index, and history of hepatitis C virus infection. Patients with normal glucose metabolism showed a significantly lower pancreatic FF than patients with impaired fasting glucose (p = 0.030), impaired glucose tolerance (p < 0.0001), and diabetes (p < 0.0001). A normal pancreatic FF (< 6.6%) showed a negative predictive value of 100% for abnormal glucose metabolism. A pancreatic FF > 15.33% predicted the presence of abnormal glucose metabolism. Pancreas FF was inversely correlated with global pancreas and heart T2* values. A normal pancreatic FF showed a negative predictive value of 100% for cardiac iron. Pancreatic FF was significantly higher in patients with myocardial fibrosis (p = 0.002). All patients with cardiac complications had fatty replacement, and they showed a significantly higher pancreatic FF than complications-free patients (p = 0.002).ConclusionPancreatic FF is a risk marker not only for alterations of glucose metabolism, but also for cardiac iron and complications, further supporting the close link between pancreatic and cardiac disease.Key Points• In thalassemia major, pancreatic fatty replacement by MRI is a frequent clinical entity, predicted by a pancreas T2* < 20.81 ms and associated with a higher risk of alterations in glucose metabolism.• In thalassemia major, pancreatic fatty replacement is a strong risk marker for cardiac iron, replacement fibrosis, and complications, highlighting a deep connection between pancreatic and cardiac impairment.