Functional aortic valve area differs significantly between sexes: A phase-contrast cardiac MRI study in patients with severe aortic stenosis

Background

Aortic stenosis (AS) is one of the most prevalent valvular heart-diseases in Europe. Currently, diagnosis and classification are not sex-sensitive; however, due to a distinctly different natural history of AS, further investigations of sex-differences in AS-patients are needed. Thus, this study aimed to detect sex-differences in severe AS, especially concerning flow-patterns, via phase-contrast cardiac magnetic resonance imaging (PC-CMR).

Methods

Forty-four severe AS-patients (20 women, 45 % vs. 24 men, 55 %) with a median age of 72 years underwent transthoracic echocardiography (TTE), cardiac catheterization (CC) and CMR. Aortic valve area (AVA) and stroke volume (SV) were determined in all modalities, with CMR yielding geometrical AVA via cine-planimetry and functional AVA via PC-CMR, the latter being also used to examine flow-properties.

Results

Geometrical AVA showed no sex-differences (0.91 cm2, IQR: 0.61-1.14 vs. 0.94 cm2, IQR: 0.77-1.22, p = 0.322). However, functional AVA differed significantly between sexes in all three modalities (TTE: p = 0.044; CC/PC-CMR: p < 0.001). In men, no significant intermethodical biases in functional AVA-measurements between modalities were found (p = 0.278); yet, in women the particular measurements differed significantly (p < 0.001). Momentary flowrate showed sex-differences depending on momentary opening-degree (at 50 %, 75 % and 90 % of peak-AVA, all p < 0.001), with men showing higher flowrates with increasing opening-area. In women, flowrate did not differ between 75 % and 90 % of peak-AVA (p = 0.191).

Conclusions

In severe AS-patients, functional AVA showed marked sex-differences in all modalities, whilst geometrical AVA did not differ. Inter-methodical biases were negligible in men, but not in women. Lastly, significant sex-differences in flow-patterns fit in with the different pathogenesis of AS.

Two-center validation of Pilot Tone based cardiac triggering of a comprehensive cardiovascular magnetic resonance examination

The electrocardiogram (ECG) signal is prone to distortions from gradient and radiofrequency interference and the magnetohydrodynamic effect during cardiovascular magnetic resonance imaging (CMR). Although Pilot Tone Cardiac (PTC) triggering has the potential to overcome these limitations, effectiveness across various CMR techniques has yet to be established. To evaluate the performance of PTC triggering in a comprehensive CMR exam. Fifteen volunteers and 20 patients were recruited at two centers. ECG triggered images were collected for comparison in a subset of sequences. The PTC trigger accuracy was evaluated against ECG in cine acquisitions. Two experienced readers scored image quality in PTC-triggered cine, late gadolinium enhancement (LGE), and T1- and T2-weighted dark-blood turbo spin echo (DB-TSE) images. Quantitative cardiac function, flow, and parametric mapping values obtained using PTC and ECG triggered sequences were compared. Breath-held segmented cine used for trigger timing analysis was collected in 15 volunteers and 14 patients. PTC calibration failed in three volunteers and one patient; ECG trigger recording failed in one patient. Out of 1987 total heartbeats, three mismatched trigger PTC-ECG pairs were found. Image quality scores showed no significant difference between PTC and ECG triggering. There was no significant difference found in quantitative measurements in volunteers. In patients, the only significant difference was found in post-contrast T1 (p = 0.04). ICC showed moderate to excellent agreement in all measurements. PTC performance was equivalent to ECG in terms of triggering consistency, image quality, and quantitative image measurements across multiple CMR applications.

Radiomics from Cardiovascular MR Cine Images for Identifying Patients with Hypertrophic Cardiomyopathy at High Risk for Heart Failure

Purpose To develop a model integrating radiomics features from cardiac MR cine images with clinical and standard cardiac MRI predictors to identify patients with hypertrophic cardiomyopathy (HCM) at high risk for heart failure (HF). Materials and Methods In this retrospective study, 516 patients with HCM (median age, 51 years [IQR: 40-62]; 367 [71.1%] men) who underwent cardiac MRI from January 2015 to June 2021 were divided into training and validation sets (7:3 ratio). Radiomics features were extracted from cardiac cine images, and radiomics scores were calculated based on reproducible features using the least absolute shrinkage and selection operator Cox regression. Radiomics scores and clinical and standard cardiac MRI predictors that were significantly associated with HF events in univariable Cox regression analysis were incorporated into a multivariable analysis to construct a combined prediction model. Model performance was validated using time-dependent area under the receiver operating characteristic curve (AUC), and the optimal cutoff value of the combined model was determined for patient risk stratification. Results The radiomics score was the strongest predictor for HF events in both univariable (hazard ratio, 10.37; P < .001) and multivariable (hazard ratio, 10.25; P < .001) analyses. The combined model yielded the highest 1- and 3-year AUCs of 0.81 and 0.80, respectively, in the training set and 0.82 and 0.77 in the validation set. Patients stratified as high risk had more than sixfold increased risk of HF events compared with patients at low risk. Conclusion The combined model with radiomics features and clinical and standard cardiac MRI parameters accurately identified patients with HCM at high risk for HF. Keywords: Cardiomyopathies, Outcomes Analysis, Cardiovascular MRI, Hypertrophic Cardiomyopathy, Radiomics, Heart Failure Supplemental material is available for this article. © RSNA, 2024.

Temporal Uncertainty Localization to Enable Human-in-the-loop Analysis of Dynamic Contrast-enhanced Cardiac MRI Datasets

Dynamic contrast-enhanced (DCE) cardiac magnetic resonance imaging (CMRI) is a widely used modality for diagnosing myocardial blood flow (perfusion) abnormalities. During a typical free-breathing DCE-CMRI scan, close to 300 time-resolved images of myocardial perfusion are acquired at various contrast "wash in/out" phases. Manual segmentation of myocardial contours in each time-frame of a DCE image series can be tedious and time-consuming, particularly when non-rigid motion correction has failed or is unavailable. While deep neural networks (DNNs) have shown promise for analyzing DCE-CMRI datasets, a "dynamic quality control" (dQC) technique for reliably detecting failed segmentations is lacking. Here we propose a new space-time uncertainty metric as a dQC tool for DNN-based segmentation of free-breathing DCE-CMRI datasets by validating the proposed metric on an external dataset and establishing a human-in-the-loop framework to improve the segmentation results. In the proposed approach, we referred the top 10% most uncertain segmentations as detected by our dQC tool to the human expert for refinement. This approach resulted in a significant increase in the Dice score ( p < 0.001 ) and a notable decrease in the number of images with failed segmentation (16.2% to 11.3%) whereas the alternative approach of randomly selecting the same number of segmentations for human referral did not achieve any significant improvement. Our results suggest that the proposed dQC framework has the potential to accurately identify poor-quality segmentations and may enable efficient DNN-based analysis of DCE-CMRI in a human-in-the-loop pipeline for clinical interpretation and reporting of dynamic CMRI datasets.

Temporal Uncertainty Localization to Enable Human-in-the-Loop Analysis of Dynamic Contrast-Enhanced Cardiac MRI Datasets

Dynamic contrast-enhanced (DCE) cardiac magnetic resonance imaging (CMRI) is a widely used modality for diagnosing myocardial blood flow (perfusion) abnormalities. During a typical free-breathing DCE-CMRI scan, close to 300 time-resolved images of myocardial perfusion are acquired at various contrast "wash in/out" phases. Manual segmentation of myocardial contours in each time-frame of a DCE image series can be tedious and time-consuming, particularly when non-rigid motion correction has failed or is unavailable. While deep neural networks (DNNs) have shown promise for analyzing DCE-CMRI datasets, a "dynamic quality control" (dQC) technique for reliably detecting failed segmentations is lacking. Here we propose a new space-time uncertainty metric as a dQC tool for DNN-based segmentation of free-breathing DCE-CMRI datasets by validating the proposed metric on an external dataset and establishing a human-in-the-loop framework to improve the segmentation results. In the proposed approach, we referred the top 10% most uncertain segmentations as detected by our dQC tool to the human expert for refinement. This approach resulted in a significant increase in the Dice score (p < 0.001) and a notable decrease in the number of images with failed segmentation (16.2% to 11.3%) whereas the alternative approach of randomly selecting the same number of segmentations for human referral did not achieve any significant improvement. Our results suggest that the proposed dQC framework has the potential to accurately identify poor-quality segmentations and may enable efficient DNN-based analysis of DCE-CMRI in a human-in-the-loop pipeline for clinical interpretation and reporting of dynamic CMRI datasets.

Radiofrequency antenna concepts for human cardiac MR at 14.0 T

OBJECTIVE

To examine the feasibility of human cardiac MR (CMR) at 14.0 T using high-density radiofrequency (RF) dipole transceiver arrays in conjunction with static and dynamic parallel transmission (pTx).

MATERIALS AND METHODS

RF arrays comprised of self-grounded bow-tie (SGBT) antennas, bow-tie (BT) antennas, or fractionated dipole (FD) antennas were used in this simulation study. Static and dynamic pTx were applied to enhance transmission field (B₁⁺) uniformity and efficiency in the heart of the human voxel model. B₁⁺ distribution and maximum specific absorption rate averaged over 10 g tissue (SAR_10g) were examined at 7.0 T and 14.0 T.

RESULTS

At 14.0 T static pTx revealed a minimum B₁⁺_ROI efficiency of 0.91 μT/√kW (SGBT), 0.73 μT/√kW (BT), and 0.56 μT/√kW (FD) and maximum SAR_10g of 4.24 W/kg, 1.45 W/kg, and 2.04 W/kg. Dynamic pTx with 8 kT points indicate a balance between B₁⁺_ROI homogeneity (coefficient of variation < 14%) and efficiency (minimum B₁⁺_ROI > 1.11 µT/√kW) at 14.0 T with a maximum SAR_10g < 5.25 W/kg.

DISCUSSION

MRI of the human heart at 14.0 T is feasible from an electrodynamic and theoretical standpoint, provided that multi-channel high-density antennas are arranged accordingly. These findings provide a technical foundation for further explorations into CMR at 14.0 T.

Mitochondrial Cardiomyopathy: Distinctive Cardiac Phenotype Detected with Cardiovascular MRI

Left ventricular hypertrophy (LVH) has a broad differential diagnosis. Pathogenic variants of mitochondrial DNA are a rare cause of LVH, and cardiac MRI is a powerful technique that may aid in differentiating such rare causes. This case report presents three siblings with a pathogenic variant of the mitochondrially encoded tRNA isoleucine (MT-TI) gene. A distinctive cardiac phenotype was detected with cardiac MRI. Extensive LVH and dilatation and decreased ejection fraction were observed with a pattern of increased T2 signal and extensive late gadolinium enhancement, which was remarkably consistent among all three siblings. Keywords: Cardiomyopathies, MR Imaging, Hypertrophic Cardiomyopathy, Mitochondrial, Inherited Cardiomyopathy, Left Ventricular Hypertrophy, Cardiovascular MRI, Late Gadolinium Enhancement Supplemental material is available for this article. © RSNA, 2023.

The role of multi-modality cardiovascular imaging in a patient presenting with acute liver failure secondary to constrictive pericarditis: a case report

Background

Constrictive pericarditis is a rare cause of heart failure which often presents a diagnostic challenge to clinicians.

Case summary

We describe the case of a 62-year-old male who presented to our institution with symptoms and signs suggestive of acute liver failure. Abdominal imaging demonstrated congestive hepatopathy. Clinical suspicion despite a 'normal' echocardiogram and sub-threshold NT-proBNP led to multi-modality cardiovascular imaging investigations to determine the cause of the heart failure syndrome. His cardiovascular magnetic resonance scan confirmed ventricular interdependence and extensive late enhancement in the pericardium with associated pericardial effusion. An 18F-fluorodeoxyglucose-positron emission tomography scan confirmed active pericardial inflammation. Cardiac computed tomography showed minimal pericardial calcification. Following confirming the diagnosis of effusive-constrictive pericarditis with evidence of active pericardial inflammation on imaging, a discussion within the Heart multidisciplinary team concluded that a trial of medical therapy with steroids is justifiable to avoid high-risk pericardiectomy. The patient was successfully treated with a combination of ibuprofen, colchicine, and prednisolone resulting in clinical improvement and remission of his symptoms. The imaging investigations were repeated 6 months later and confirmed radiological remission and medical therapy was discontinued.

Discussion

We stress the importance of multi-modality cardiovascular imaging in the diagnosis of constrictive pericarditis and also emphasize its role in identifying the subset of patients who may respond to medical therapy, therefore reducing the risk of high need surgical pericardiectomy.

Compressed Sensing Cardiac Cine Imaging Compared with Standard Balanced Steady-State Free Precession Cine Imaging in a Pediatric Population

Purpose

To compare real-time compressed sensing (CS) and standard balanced steady-state free precession (bSSFP) cardiac cine imaging in children.

Materials and Methods

Twenty children (mean age, 15 years ± 5 [SD], range, 7-21 years; 10 male participants) with biventricular congenital heart disease (n = 11) or cardiomyopathy (n = 9) were prospectively included. Examinations were performed with 1.5-T imagers by using both bSSFP and CS sequences in all participants. Quantification of ventricular volumes and function was performed for all images by two readers blinded to patient diagnosis and type of sequence. Values were correlated with phase-contrast flow measurements by one reader. Intra- and interreader agreement were analyzed.

Results

There were no significant differences between ventricular parameters measured on CS compared with those of bSSFP (P > .05) for reader 1. Only ejection fraction showed a significant difference (P = .02) for reader 2. Intrareader agreement was considerable for both sequences (bSSFP: mean difference range, +1 to -2.6; maximum CI, +7.9, -13; bias range, 0.1%-4.1%; intraclass correlation coefficient [ICC] range, 0.931-0.997. CS: mean difference range, +7.4 to -5.6; maximum CI, +37.2, -48.8; bias range, 0.5%-7.5%; ICC range, 0.717-0.997). Interreader agreement was acceptable but less robust, especially for CS (bSSFP: mean difference range, +2.6 to -5.6; maximum CI, +60.7, -65.3; bias range, 1.6%-6.2%; ICC range, 0.726-0.951. CS: mean difference range, +10.7 to -9.1; maximum CI, +87.5, -84.6; bias range, 1.1%-17.3%; ICC range, 0.509-0.849). The mean acquisition time was shorter for CS (20 seconds; range, 17-25 seconds) compared with that for bSSFP (160 seconds; range, 130-190 seconds) (P < .001).

Conclusion

CS cardiac cine imaging provided equivalent ventricular volume and function measurements with shorter acquisition times compared with those of bSSFP and may prove suitable for the pediatric population.Keywords: Compressed Sensing, Balanced Steady-State Free Precession, Cine Imaging, Cardiovascular MRI, Pediatrics, Cardiac, Heart, Cardiomyopathies, Congenital, Segmentation© RSNA, 2022.

Tangent vector-based gradient method with l12-regularization: Iterative half thresholding algorithm for CS-MRI

OBJECT

This paper presents a new method using tangent vector-based l₁₂-regularization for compressed sensing MR image reconstruction.

MATERIALS AND METHODS

The proposed method with l₁₂-regularization is tested on four datasets: (i) 1-D sparse signal (ii) numerical cardiac phantom, (iii & iv) two sets of in-vivo cardiac MRI datasets acquired using 30 receiver coil elements with Cartesian and radial trajectories on 3T scanner. The results are compared with standard CS reconstruction, which utilizes l₁-regularization. The experiments were also conducted for two different types of samplings: (i) cartesian sub-sampling and (ii) 2D random Gaussian sub-sampling.

RESULTS

The quality of the reconstructed images is validated through Root Mean Square Error (RMSE) and Peak Signal-to-Noise Ratio (PSNR). The results show that the proposed method outperforms the standard CS reconstructions in our experiments with an improvement of 54.8% in RMSE and 14.3% in terms of PSNR. Moreover, the Gaussian random sub-sampling-based image reconstruction results are better than the Cartesian sub-sampling-based reconstruction results.

CONCLUSION

The results show that the proposed method yields a good sparse signal approximation and superior convergence behavior, which implies a promising technique for the reconstruction of cardiac MR images as compared to the conventional CS algorithm.

Quantification of Myocardial Deformation Applying CMR-Feature-Tracking-All About the Left Ventricle?

Purpose of Review

Cardiac magnetic resonance-feature-tracking (CMR-FT)-based deformation analyses are key tools of cardiovascular imaging and applications in heart failure (HF) diagnostics are expanding. In this review, we outline the current range of application with diagnostic and prognostic implications and provide perspectives on future trends of this technique.

Recent Findings

By applying CMR-FT in different cardiovascular diseases, increasing evidence proves CMR-FT-derived parameters as powerful diagnostic and prognostic imaging biomarkers within the HF continuum partly outperforming traditional clinical values like left ventricular ejection fraction. Importantly, HF diagnostics and deformation analyses by CMR-FT are feasible far beyond sole left ventricular performance evaluation underlining the holistic nature and accuracy of this imaging approach.

Summary

As an established and continuously evolving technique with strong prognostic implications, CMR-FT deformation analyses enable comprehensive cardiac performance quantification of all cardiac chambers.

Deep neural network ensemble for on-the-fly quality control-driven segmentation of cardiac MRI T1 mapping

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Quality control-driven framework for cardiac segmentation and quality control.

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Exploiting variability within deep neural network ensemble to estimate uncertainty.

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Novel on-the-fly selection mechanism for the final optimal segmentation.

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Accurate, reliable, and fully automated analysis of T1 map with visualization.

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Highlighting a potential flaw of the Pearson correlation to evaluate quality score.

Recent developments in artificial intelligence have generated increasing interest to deploy automated image analysis for diagnostic imaging and large-scale clinical applications. However, inaccuracy from automated methods could lead to incorrect conclusions, diagnoses or even harm to patients. Manual inspection for potential inaccuracies is labor-intensive and time-consuming, hampering progress towards fast and accurate clinical reporting in high volumes. To promote reliable fully-automated image analysis, we propose a quality control-driven (QCD) segmentation framework. It is an ensemble of neural networks that integrate image analysis and quality control. The novelty of this framework is the selection of the most optimal segmentation based on predicted segmentation accuracy, on-the-fly. Additionally, this framework visualizes segmentation agreement to provide traceability of the quality control process. In this work, we demonstrated the utility of the framework in cardiovascular magnetic resonance T1-mapping - a quantitative technique for myocardial tissue characterization. The framework achieved near-perfect agreement with expert image analysts in estimating myocardial T1 value (r=0.987,p<.0005; mean absolute error (MAE)=11.3ms), with accurate segmentation quality prediction (Dice coefficient prediction MAE=0.0339) and classification (accuracy=0.99), and a fast average processing time of 0.39 second/image. In summary, the QCD framework can generate high-throughput automated image analysis with speed and accuracy that is highly desirable for large-scale clinical applications.

The Role of Cardiovascular MRI in Cardio-Oncology

"Cardiac imaging is an essential tool in the field of cardio-oncology. Cardiovascular magnetic resonance (CMR) stands out for its accuracy, reproducibility, and ability to provide tissue characterization. These attributes are particularly helpful in screening and diagnosing cardiotoxicity, infiltrative disease, and inflammatory cardiac disease. The ability of CMR to detect subtle changes in cardiac function and tissue composition has made it a useful tool for understanding the pathophysiology of cardiotoxicity. Because of these unique features, CMR is gaining prominence in both the clinical and research aspects of cardio-oncology."

Cardiovascular MRI evidence of reduced systolic function and reduced LV mass in rheumatoid arthritis: impact of disease phenotype

The accelerated risk of cardiovascular disease (CVD) in Rheumatoid Arthritis (RA) requires further study of the underlying pathophysiology and determination of the at-risk RA phenotype. Our objectives were to describe the cardiac structure and function and arterial stiffness, and association with disease phenotype in patients with established) RA, in comparison to healthy controls, as measured by cardiovascular magnetic resonance imaging (CMR). 76 patients with established RA and no history of CVD/diabetes mellitus were assessed for RA and cardiovascular profile and underwent a non-contrast 3T-CMR, and compared to 26 healthy controls. A univariable analysis and multivariable linear regression model determined associations between baseline variables and CMR-measures. Ten-year cardiovascular risk scores were increased in RA compared with controls. Adjusting for age, sex and traditional cardiovascular risk factors, patients with RA had reduced left ventricular ejection fraction (mean difference - 2.86% (- 5.17, - 0.55) p = 0.016), reduced absolute values of mid systolic strain rate (p < 0.001) and lower late/active diastolic strain rate (p < 0.001) compared to controls. There was evidence of reduced LV mass index (LVMI) (- 4.56 g/m2 (- 8.92, - 0.20), p = 0.041). CMR-measures predominantly associated with traditional cardiovascular risk factors; male sex and systolic blood pressure independently with increasing LVMI. Patients with established RA and no history of CVD have evidence of reduced LV systolic function and LVMI after adjustment for traditional cardiovascular risk factors; the latter suggesting cardiac pathology other than atherosclerosis in RA. Traditional cardiovascular risk factors, rather than RA disease phenotype, appear to be key determinants of subclinical CVD in RA potentially warranting more effective cardiovascular risk reduction programs.

Understanding Fetal Hemodynamics Using Cardiovascular Magnetic Resonance Imaging

Human fetal circulatory physiology has been investigated extensively using grey-scale ultrasound, which provides excellent visualization of cardiac anatomy and function, while velocity profiles in the heart and vessels can be interrogated using Doppler. Measures of cerebral and placental vascular resistance, as well as indirect measures of intracardiac pressure obtained from the velocity waveform in the ductus venosus are routinely used to guide the management of fetal cardiovascular and placental disease. However, the characterization of some key elements of cardiovascular physiology such as vessel blood flow and the oxygen content of blood in the arteries and veins, as well as fetal oxygen delivery and consumption are not readily measured using ultrasound. To study these parameters, we have historically relied on data obtained using invasive measurements made in animal models, which are not equivalent to the human in every respect. Over recent years, a number of technical advances have been made that have allowed us to examine the human fetal circulatory system using cardiovascular magnetic resonance (CMR). The combination of vessel blood flow measurements made using cine phase contrast magnetic resonance imaging and vessel blood oxygen saturation and hematocrit measurements made using T1 and T2 mapping have enabled us to emulate those classic fetal sheep experiments defining the distribution of blood flow and oxygen transport across the fetal circulation in the human fetus. In addition, we have applied these techniques to study the relationship between abnormal fetal cardiovascular physiology and fetal development in the setting of congenital heart disease and placental insufficiency. CMR has become an important diagnostic tool in the assessment of cardiovascular physiology in the setting of postnatal cardiovascular disease, and is now being applied to the fetus to enhance our understanding of normal and abnormal fetal circulatory physiology and its impact on fetal well-being.

Automatic localization of the left ventricular blood pool centroid in short axis cardiac cine MR images

In this paper, we develop and validate an open source, fully automatic algorithm to localize the left ventricular (LV) blood pool centroid in short axis cardiac cine MR images, enabling follow-on automated LV segmentation algorithms. The algorithm comprises four steps: (i) quantify motion to determine an initial region of interest surrounding the heart, (ii) identify potential 2D objects of interest using an intensity-based segmentation, (iii) assess contraction/expansion, circularity, and proximity to lung tissue to score all objects of interest in terms of their likelihood of constituting part of the LV, and (iv) aggregate the objects into connected groups and construct the final LV blood pool volume and centroid. This algorithm was tested against 1140 datasets from the Kaggle Second Annual Data Science Bowl, as well as 45 datasets from the STACOM 2009 Cardiac MR Left Ventricle Segmentation Challenge. Correct LV localization was confirmed in 97.3% of the datasets. The mean absolute error between the gold standard and localization centroids was 2.8 to 4.7 mm, or 12 to 22% of the average endocardial radius. Graphical abstract Fully automated localization of the left ventricular blood pool in short axis cardiac cine MR images.

Clinical feasibility and validation of 3D principal strain analysis from cine MRI: comparison to 2D strain by MRI and 3D speckle tracking echocardiography

Two-dimensional (2D) strain analysis is constrained by geometry-dependent reference directions of deformation (i.e. radial, circumferential, and longitudinal) following the assumption of cylindrical chamber architecture. Three-dimensional (3D) principal strain analysis may overcome such limitations by referencing intrinsic (i.e. principal) directions of deformation. This study aimed to demonstrate clinical feasibility of 3D principal strain analysis from routine 2D cine MRI with validation to strain from 2D tagged cine analysis and 3D speckle tracking echocardiography. Thirty-one patients undergoing cardiac MRI were studied. 3D strain was measured from routine, multi-planar 2D cine SSFP images using custom software designed to apply 4D deformation fields to 3D cardiac models to derive principal strain. Comparisons of strain estimates versus those by 2D tagged cine, 2D non-tagged cine (feature tracking), and 3D speckle tracking echocardiography (STE) were performed. Mean age was 51 ± 14 (36% female). Mean LV ejection fraction was 66 ± 10% (range 37–80%). 3D principal strain analysis was feasible in all subjects and showed high inter- and intra-observer reproducibility (ICC range 0.83–0.97 and 0.83–0.98, respectively—p < 0.001 for all directions). Strong correlations of minimum and maximum principal strain were respectively observed versus the following: 3D STE estimates of longitudinal (r = 0.81 and r = −0.64), circumferential (r = 0.76 and r = −0.58) and radial (r = −0.80 and r = 0.63) strain (p < 0.001 for all); 2D tagged cine estimates of longitudinal (r = 0.81 and r = −0.81), circumferential (r = 0.87 and r = −0.85), and radial (r = −0.76 and r = 0.81) strain (p < 0.0001 for all); and 2D cine (feature tracking) estimates of longitudinal (r = 0.85 and −0.83), circumferential (r = 0.88 and r = −0.87), and radial strain (r = −0.79 and r = 0.84, p < 0.0001 for all). 3D principal strain analysis is feasible using routine, multi-planar 2D cine MRI and shows high reproducibility with strong correlations to 2D conventional strain analysis and 3D STE-based analysis. Given its independence from geometry-related directions of deformation this technique may offer unique benefit for the detection and prognostication of myocardial disease, and warrants expanded investigation.

Caffeine intake inverts the effect of adenosine on myocardial perfusion during stress as measured by T1 mapping

Caffeine intake before adenosine stress myocardial perfusion imaging may cause false negative findings. We hypothesized that the antagonistic effect of caffeine can be measured by T1 relaxation times in rest and adenosine stress cardiac magnetic resonance imaging (CMR), as T1 mapping techniques are sensitive to changes in myocardial blood volume. We prospectively analyzed 105 consecutive patients with adenosine stress perfusion CMR on a 1.5-T MRI system. Rest and stress T1 mapping was performed using Modified Look-Locker Inversion recovery. T1 reactivity was defined as difference in T1_rest and T1_stress (∆T1). Fifteen patients drank coffee within 4 h of CMR (<4H caffeine group), and 10 patients had coffee the day before (>8H caffeine group). Comparison was made to patients without self-reported coffee intake: 50 with normal CMR (control group), 18 with myocardial ischemia, and 12 with myocardial infarction. The national review board approved the study; all patients gave written informed consent. The <4H caffeine group showed inverted ∆T1 of −7.8 % (T1_rest 975 ± 42 ms, T1_stress 898 ± 51 ms, p < 0.0005). The >8H caffeine group showed reduced T1 reactivity (1.8 %; T1_rest 979 ms, T1_stress 997 ms) compared to the controls (4.3 %; T1_rest 977 ± 40 ms, T1_stress 1018 ± 40 ms), p < 0.0005. Ischemic and infarcted myocardium showed minimal T1 reactivity (0.2 and 0.3 %, respectively). Caffeine intake inverts the adenosine effect during stress perfusion CMR as measured by T1 mapping. T1 reactivity can assess the adequacy of adenosine-induced stress in perfusion CMR.

Multimodality cardiac imaging in Turner syndrome

Congenital and acquired cardiovascular diseases contribute significantly to the threefold elevated risk of premature death in Turner syndrome. A multitude of cardiovascular anomalies and disorders, many of which deleteriously impact morbidity and mortality, is frequently left undetected and untreated because of poor adherence to screening programmes and complex clinical presentations. Imaging is essential for timely and effective primary and secondary disease prophylaxis that may alleviate the severe impact of cardiovascular disease in Turner syndrome. This review illustrates how cardiovascular disease in Turner syndrome manifests in a complex manner that ranges in severity from incidental findings to potentially fatal anomalies. Recommendations regarding the use of imaging for screening and surveillance of cardiovascular disease in Turner syndrome are made, emphasising the key role of non-invasive and invasive cardiovascular imaging to the management of all patients with Turner syndrome.

Safety and tolerability of regadenoson CMR

AIMS

Knowledge of adverse events associated with regadenoson perfusion cardiac magnetic resonance (CMR) and patient tolerability has implications for patient safety and staff training. We sought to assess the safety and tolerability of regadenoson stress CMR.

MATERIALS AND METHODS

A group of 728 consecutive patients (median age 58, 44% female) and 25 normal volunteers (median age 21, 24% female) were recruited from August 2009 to March 2012 using a prospective, cross-sectional study design. Subjects were stressed using fixed-dose regadenoson and imaged using a 1.5T MRI scanner. Symptoms and adverse events including death, myocardial infarction (MI), ventricular tachycardia (VT)/ventricular fibrillation (VF), hospitalization, arrhythmias, and haemodynamic stability were assessed.

RESULTS

There were no occurrences of death, MI, VT/VF, high-grade atrioventricular block, or stress-induced atrial fibrillation. Notable adverse events included one case of bronchospasm and one case of heart failure exacerbation resulting in hospitalization. The most common symptoms in patients were dyspnoea (30%, n = 217), chest discomfort (27%, n = 200), and headache (15%, n = 111). There was minimal change between baseline and peak systolic and diastolic blood pressure in both patients and volunteers (P > 0.05). A blunted heart rate response to regadenoson was noted in patients with body mass index (BMI) ≥ 30 kg/m(2) (P < 0.001), and diabetes (P = 0.001).

CONCLUSIONS

Regadenoson CMR is well tolerated and can be performed safely with few adverse events.

Cardiovascular MRI in Detection and Measurement of Aortic Atheroma in Stroke/TIA patients

Background

Aortic Atheroma (AoA) is an independent risk factor for new and recurrent stroke. AoA ulceration and mobility are associated with an increased risk for brain embolism. Transesophageal echocardiography (TEE) is the gold standard for detection and measurement of AoA in stroke/TIA patients. Cardiovascular MRI (cMRI) could be an alternative, non-invasive imaging modality for stroke/TIA patients. The objective of this study was to assess the accuracy and correlation of AoA detected and measured by cMRI versus TEE in patients with recent stroke/TIA.

Methods and results

Twenty-two stroke/TIA patients undergoing TEE as a part of their stroke workup consented to a protocol-mandated cMRI performed on a 1.5 T magnet. The protocol included an axial non-breathhold EKG-gated dual-echo spin echo MRI of the thoracic aorta (TR/TE1/TE2=900/29/69) and a contrast-enhanced breathhold 3D gradient-echo image of the thorax (flip/TR/TE=12/4.0/1.71). Maximum plaque thickness, ulceration (≥ 2 mm) and mobility of AoA were assessed in the proximal (ascending and proximal arch) and distal (distal arch and descending) segments of thoracic aorta by a cardiologist to interpret the TEE and a radiologist to interpret the cMRI. There was good correlation between cMRI and TEE in measurement of plaque thickness in the proximal segments (R=0.73, p<0.0001) and the distal segments (R=0.81, p<0.0001) of the aortic arch (AA). cMRI had a high degree of accuracy in detecting measurable AoA (≥ 1 mm) in the proximal segments (sensitivity 90%, specificity 100%), as well as the distal segments (sensitivity 67%, specificity 100%). cMRI also had a high degree of accuracy in detecting significant AoA (≥ 4 mm) in proximal segments (sensitivity 71%, specificity 93%), as well as distal segments (sensitivity 71%, specificity 100%).

Conclusion

The study showed a high degree of accuracy and correlation of AoA detected and measured by cMRI as compared to TEE in patients with recent stroke/TIA. This technique has limitations in detection of AoA ulceration, and protocols assessing AoA mobility need to be developed.

ACCELERATING CARDIOVASCULAR IMAGING BY EXPLOITING REGIONAL LOW-RANK STRUCTURE VIA GROUP SPARSITY

Sparse sampling of (k, t)-space has proved useful for cardiac MRI. This paper builds on previous work on using partial separability (PS) and spatial-spectral sparsity for high-quality image reconstruction from highly undersampled (k, t)-space data. This new method uses a more flexible control over the PS-induced low-rank constraint via group-sparse regularization. A novel algorithm is also described to solve the corresponding (1,2)-norm regularized inverse problem. Reconstruction results from simulated cardiovascular imaging data are presented to demonstrate the performance of the proposed method.