Representation of cardiovascular magnetic resonance in the AHA / ACC guidelines

Cardiac Cine MRI Using a Commercially Available 0.55-T Scanner

Purpose To compare parameters of left ventricular (LV) and right ventricular (RV) volume and function between a commercially available 0.55-T low-field-strength cardiac cine MRI scanner and a 1.5-T scanner. Materials and Methods In this prospective study, healthy volunteers (May 2022 to July 2022) underwent same-day cine imaging using both scanners (0.55 T, 1.5 T). Volumetric and functional parameters were assessed by two experts. After analyzing the results of a blinded crossover reader study of the healthy volunteers, 20 participants with clinically indicated cardiac MRI were prospectively included (November 2022 to February 2023). In a second blinded expert reading, parameters from clinical 1.5-T scans in these participants were compared with those same-day 0.55-T scans. Results are displayed as Bland-Altman plots. Results Eleven healthy volunteers (mean age: 33 years [95% CI: 27, 40]; four of 11 [36%] female, seven of 11 [64%] male) were included. Very strong mean correlation was observed (r = 0.98 [95% CI: 0.97, 0.98]). Average deviation between MRI systems was 1.6% (95% CI: 0.3, 2.9) for both readers. Twenty participants with clinically indicated cardiac MRI were included (mean age: 55 years [95% CI: 48, 62], six of 20 [30%] female, 14 of 20 [70%] male). Mean correlation was very strong (r = 0.98 [95% CI: 0.97, 0.98]). LV and RV parameters demonstrated an average deviation of 1.1% (95% CI: 0.1, 2.1) between MRI systems. Conclusion Cardiac cine MRI at 0.55 T yielded comparable results for quantitative biventricular volumetric and functional parameters compared with routine imaging at 1.5 T, if acquisition time is doubled. Keywords: Cardiac, Comparative Studies, Heart, Cardiovascular MRI, Cine, Myocardium Supplemental material is available for this article. ©RSNA, 2024.

Head-to-Head Comparison and Temporal Trends of Cardiac MRI Recommendations in ESC versus ACC/AHA Guidelines: A Systematic Review and Meta-Analysis

Purpose To provide a comprehensive head-to-head comparison and temporal analysis of cardiac MRI indications between the European Society of Cardiology (ESC) and American College of Cardiology/American Heart Association (ACC/AHA) guidelines to identify areas of consensus and divergence. Materials and Methods A systematic review and meta-analysis was conducted. ESC and ACC/AHA guidelines published until May 2023 were systematically screened for recommendations related to cardiac MRI. The class of recommendation (COR) and level of evidence (LOE) for cardiac MRI recommendations were compared between the two guidelines and between newer versus older versions of each guideline using χ2 or Fisher exact tests. Results ESC guidelines included 109 recommendations regarding cardiac MRI, and ACC/AHA guidelines included 90 recommendations. The proportion of COR I and LOE B was higher in ACC/AHA versus ESC guidelines (60% [54 of 90] vs 46.8% [51 of 109]; P = .06 and 53% [48 of 90] vs 35.8% [39 of 109], respectively; P = .01). The increase in the number of cardiac MRI recommendations over time was significantly higher in ESC guidelines (from 63 to 109 for ESC vs from 65 to 90 for ACC/AHA; P = .03). The main areas of consensus were found in heart failure and hypertrophic cardiomyopathy, while the main divergences were in valvular heart disease, arrhythmias, and aortic disease. Conclusion ESC guidelines included more recommendations related to cardiac MRI use, whereas the ACC/AHA recommendations had higher COR and LOE. The number of cardiac MRI recommendations increased significantly over time in both guidelines, indicating the increasing role of cardiac MRI evaluation and management of cardiovascular disease. Keywords: Cardiovascular Magnetic Resonance, Guideline, European Society of Cardiology, ESC, American College of Cardiology/American Heart Association, ACC/AHA Supplemental material is available for this article. © RSNA, 2024.

Cardiac MRI at Low Field Strengths

Cardiac MR imaging is well established for assessment of cardiovascular structure and function, myocardial scar, quantitative flow, parametric mapping, and myocardial perfusion. Despite the clear evidence supporting the use of cardiac MRI for a wide range of indications, it is underutilized clinically. Recent developments in low-field MRI technology, including modern data acquisition and image reconstruction methods, are enabling high-quality low-field imaging that may improve the cost-benefit ratio for cardiac MRI. Studies to-date confirm that low-field MRI offers high measurement concordance and consistent interpretation with clinical imaging for several routine sequences. Moreover, low-field MRI may enable specific new clinical opportunities for cardiac imaging such as imaging near metal implants, MRI-guided interventions, combined cardiopulmonary assessment, and imaging of patients with severe obesity. In this review, we discuss the recent progress in low-field cardiac MRI with a focus on technical developments and early clinical validation studies. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

Unrolled and rapid motion-compensated reconstruction for cardiac CINE MRI

In recent years Motion-Compensated MR reconstruction (MCMR) has emerged as a promising approach for cardiac MR (CMR) imaging reconstruction. MCMR estimates cardiac motion and incorporates this information in the reconstruction. However, two obstacles prevent the practical use of MCMR in clinical situations: First, inaccurate motion estimation often leads to inferior CMR reconstruction results. Second, the motion estimation frequently leads to a long processing time for the reconstruction. In this work, we propose a learning-based and unrolled MCMR framework that can perform precise and rapid CMR reconstruction. We achieve accurate reconstruction by developing a joint optimization between the motion estimation and reconstruction, in which a deep learning-based motion estimation framework is unrolled within an iterative optimization procedure. With progressive iterations, a mutually beneficial interaction can be established in which the reconstruction quality is improved with more accurate motion estimation. Further, we propose a groupwise motion estimation framework to speed up the MCMR process. A registration template based on the cardiac sequence average is introduced, while the motion estimation is conducted between the cardiac frames and the template. By applying this framework, cardiac sequence registration can be accomplished with linear time complexity. Experiments on 43 in-house acquired 2D CINE datasets indicate that the proposed unrolled MCMR framework can deliver artifacts-free motion estimation and high-quality CMR reconstruction even for imaging acceleration rates up to 20x. We compare our approach with state-of-the-art reconstruction methods and it outperforms them quantitatively and qualitatively in all adapted metrics across all acceleration rates.

The Nottingham Ischaemic Cardiovascular Magnetic Resonance resource (NotIs CMR): a prospective paired clinical and imaging scar database-protocol

INTRODUCTION

Research utilising artificial intelligence (AI) and cardiovascular magnetic resonance (CMR) is rapidly evolving with various objectives, however AI model development, generalisation and performance may be hindered by availability of robust training datasets including contrast enhanced images.

METHODS

NotIs CMR is a large UK, prospective, multicentre, observational cohort study to guide the development of a biventricular AI scar model. Patients with ischaemic heart disease undergoing clinically indicated contrast-enhanced cardiac magnetic resonance imaging will be recruited at Nottingham University Hospitals NHS Trust and Mid-Yorkshire Hospital NHS Trust. Baseline assessment will include cardiac magnetic resonance imaging, demographic data, medical history, electrocardiographic and serum biomarkers. Participants will undergo monitoring for a minimum of 5 years to document any major cardiovascular adverse events. The main objectives include (1) AI training, validation and testing to improve the performance, applicability and adaptability of an AI biventricular scar segmentation model being developed by the authors and (2) develop a curated, disease-specific imaging database to support future research and collaborations and, (3) to explore associations in clinical outcome for future risk prediction modelling studies.

CONCLUSION

NotIs CMR will collect and curate disease-specific, paired imaging and clinical datasets to develop an AI biventricular scar model whilst providing a database to support future research and collaboration in Artificial Intelligence and ischaemic heart disease.

An artificial intelligence tool for automated analysis of large-scale unstructured clinical cine cardiac magnetic resonance databases

Aims

Artificial intelligence (AI) techniques have been proposed for automating analysis of short-axis (SAX) cine cardiac magnetic resonance (CMR), but no CMR analysis tool exists to automatically analyse large (unstructured) clinical CMR datasets. We develop and validate a robust AI tool for start-to-end automatic quantification of cardiac function from SAX cine CMR in large clinical databases.

Methods and results

Our pipeline for processing and analysing CMR databases includes automated steps to identify the correct data, robust image pre-processing, an AI algorithm for biventricular segmentation of SAX CMR and estimation of functional biomarkers, and automated post-analysis quality control to detect and correct errors. The segmentation algorithm was trained on 2793 CMR scans from two NHS hospitals and validated on additional cases from this dataset (n = 414) and five external datasets (n = 6888), including scans of patients with a range of diseases acquired at 12 different centres using CMR scanners from all major vendors. Median absolute errors in cardiac biomarkers were within the range of inter-observer variability: <8.4 mL (left ventricle volume), <9.2 mL (right ventricle volume), <13.3 g (left ventricular mass), and <5.9% (ejection fraction) across all datasets. Stratification of cases according to phenotypes of cardiac disease and scanner vendors showed good performance across all groups.

Conclusion

We show that our proposed tool, which combines image pre-processing steps, a domain-generalizable AI algorithm trained on a large-scale multi-domain CMR dataset and quality control steps, allows robust analysis of (clinical or research) databases from multiple centres, vendors, and cardiac diseases. This enables translation of our tool for use in fully automated processing of large multi-centre databases.

Granulomatous inflammation mimicking a hematoma around the replaced ascending aorta in magnetic resonance imaging: a case report

BACKGROUND

Granulomatous inflammation results from various causes including infections and allergic reactions. It can appear as high signal intensity in T2-weighted or contrast-enhanced T1-weighted magnetic resonance imaging (MRI). Here, we describe a case of granulomatous inflammation looking like a hematoma on an ascending aortic graft in MRI.

CASE PRESENTATION

A 75-year-old female was undergoing assessment for chest pain. She had a history of hemi-arch replacement for aortic dissection 10 years earlier. The initial chest computed tomography and subsequent chest MRI were suggestive of a hematoma, implying a pseudoaneurysm of the thoracic aorta, which is associated with high mortality in reoperation. Through redo median sternotomy, severe adhesion was found in the retrosternal space. A sac in the pericardial space contained yellowish and pus-like material, confirming that there was no hematoma around the ascending aortic graft. The pathologic finding was chronic necrotizing granulomatous inflammation. Microbiological tests including polymerase chain reaction analysis were negative.

CONCLUSION

Our experience indicates that an MRI finding of a hematoma at the site long after cardiovascular surgery suggests that there may be granulomatous inflammation.

Self-Attention MHDNet: A Novel Deep Learning Model for the Detection of R-Peaks in the Electrocardiogram Signals Corrupted with Magnetohydrodynamic Effect

Magnetic resonance imaging (MRI) is commonly used in medical diagnosis and minimally invasive image-guided operations. During an MRI scan, the patient's electrocardiogram (ECG) may be required for either gating or patient monitoring. However, the challenging environment of an MRI scanner, with its several types of magnetic fields, creates significant distortions of the collected ECG data due to the Magnetohydrodynamic (MHD) effect. These changes can be seen as irregular heartbeats. These distortions and abnormalities hamper the detection of QRS complexes, and a more in-depth diagnosis based on the ECG. This study aims to reliably detect R-peaks in the ECG waveforms in 3 Tesla (T) and 7T magnetic fields. A novel model, Self-Attention MHDNet, is proposed to detect R peaks from the MHD corrupted ECG signal through 1D-segmentation. The proposed model achieves a recall and precision of 99.83% and 99.68%, respectively, for the ECG data acquired in a 3T setting, while 99.87% and 99.78%, respectively, in a 7T setting. This model can thus be used in accurately gating the trigger pulse for the cardiovascular functional MRI.

Multilevel comparison of deep learning models for function quantification in cardiovascular magnetic resonance: On the redundancy of architectural variations

Background

Cardiac function quantification in cardiovascular magnetic resonance requires precise contouring of the heart chambers. This time-consuming task is increasingly being addressed by a plethora of ever more complex deep learning methods. However, only a small fraction of these have made their way from academia into clinical practice. In the quality assessment and control of medical artificial intelligence, the opaque reasoning and associated distinctive errors of neural networks meet an extraordinarily low tolerance for failure.

Aim

The aim of this study is a multilevel analysis and comparison of the performance of three popular convolutional neural network (CNN) models for cardiac function quantification.

Methods

U-Net, FCN, and MultiResUNet were trained for the segmentation of the left and right ventricles on short-axis cine images of 119 patients from clinical routine. The training pipeline and hyperparameters were kept constant to isolate the influence of network architecture. CNN performance was evaluated against expert segmentations for 29 test cases on contour level and in terms of quantitative clinical parameters. Multilevel analysis included breakdown of results by slice position, as well as visualization of segmentation deviations and linkage of volume differences to segmentation metrics via correlation plots for qualitative analysis.

Results

All models showed strong correlation to the expert with respect to quantitative clinical parameters (rz ' = 0.978, 0.977, 0.978 for U-Net, FCN, MultiResUNet respectively). The MultiResUNet significantly underestimated ventricular volumes and left ventricular myocardial mass. Segmentation difficulties and failures clustered in basal and apical slices for all CNNs, with the largest volume differences in the basal slices (mean absolute error per slice: 4.2 ± 4.5 ml for basal, 0.9 ± 1.3 ml for midventricular, 0.9 ± 0.9 ml for apical slices). Results for the right ventricle had higher variance and more outliers compared to the left ventricle. Intraclass correlation for clinical parameters was excellent (≥0.91) among the CNNs.

Conclusion

Modifications to CNN architecture were not critical to the quality of error for our dataset. Despite good overall agreement with the expert, errors accumulated in basal and apical slices for all models.

Towards automatic classification of cardiovascular magnetic resonance Task Force Criteria for diagnosis of arrhythmogenic right ventricular cardiomyopathy

BACKGROUND

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is diagnosed according to the Task Force Criteria (TFC) in which cardiovascular magnetic resonance (CMR) imaging plays an important role. Our study aims to apply an automatic deep learning-based segmentation for right and left ventricular CMR assessment and evaluate this approach for classification of the CMR TFC.

METHODS

We included 227 subjects suspected of ARVC who underwent CMR. Subjects were classified into (1) ARVC patients fulfilling TFC; (2) at-risk family members; and (3) controls. To perform automatic segmentation, a Bayesian Dilated Residual Neural Network was trained and tested. Performance of automatic versus manual segmentation was assessed using Dice-coefficient and Hausdorff distance. Since automatic segmentation is most challenging in basal slices, manual correction of the automatic segmentation in the most basal slice was simulated (automatic^-basal). CMR TFC calculated using manual and automatic^-basal segmentation were compared using Cohen's Kappa (κ).

RESULTS

Automatic segmentation was trained on CMRs of 70 subjects (39.6 ± 18.1 years, 47% female) and tested on 157 subjects (36.9 ± 17.6 years, 59% female). Dice-coefficient and Hausdorff distance showed good agreement between manual and automatic segmentations (≥ 0.89 and ≤ 10.6 mm, respectively) which further improved after simulated correction of the most basal slice (≥ 0.92 and ≤ 9.2 mm, p < 0.001). Pearson correlation of volumetric and functional CMR measurements was good to excellent (automatic (r = 0.78-0.99, p < 0.001) and automatic^-basal (r = 0.88-0.99, p < 0.001) measurements). CMR TFC classification using automatic^-basal segmentations was comparable to manual segmentations (κ 0.98 ± 0.02) with comparable diagnostic performance.

CONCLUSIONS

Combining automatic segmentation of CMRs with correction of the most basal slice results in accurate CMR TFC classification of subjects suspected of ARVC.

Translating principles of quality control to cardiovascular magnetic resonance: assessing quantitative parameters of the left ventricle in a large cohort

Cardiac magnetic resonance (CMR) examinations require standardization to achieve reproducible results. Therefore, quality control as known as in other industries such as in-vitro diagnostics, could be of essential value. One such method is the statistical detection of long-time drifts of clinically relevant measurements. Starting in 2010, reports from all CMR examinations of a high-volume center were stored in a hospital information system. Quantitative parameters of the left ventricle were analyzed over time with moving averages of different window sizes. Influencing factors on the acquisition and on the downstream analysis were captured. 26,902 patient examinations were exported from the clinical information system. The moving median was compared to predefined tolerance ranges, which revealed an overall of 50 potential quality relevant changes ("alerts") in SV, EDV and LVM. Potential causes such as change of staff, scanner relocation and software changes were found not to be causal of the alerts. No other influencing factors were identified retrospectively. Statistical quality assurance systems based on moving average control charts may provide an important step towards reliability of quantitative CMR. A prospective evaluation is needed for the effective root cause analysis of quality relevant alerts.

Clinical Utility of Strain Imaging in Assessment of Myocardial Fibrosis

Myocardial fibrosis (MF) is a non-reversible process that occurs following acute or chronic myocardial damage. MF worsens myocardial deformation, remodels the heart and raises myocardial stiffness, and is a crucial pathological manifestation in patients with end-stage cardiovascular diseases and closely related to cardiac adverse events. Therefore, early quantitative analysis of MF plays an important role in risk stratification, clinical decision, and improvement in prognosis. With the advent and development of strain imaging modalities in recent years, MF may be detected early in cardiovascular diseases. This review summarizes the clinical usefulness of strain imaging techniques in the non-invasive assessment of MF.

Evaluation of Left Ventricular Mass in Different Cardiac Geometry Using Three-Dimensional Contrast-Enhanced Echocardiography

A total of 69 patients were enrolled in the study, including 23 patients with hypertrophic cardiomyopathy (HCM), 26 patients with Left Ventricle (LV) enlargement comprising 16 dilated cardiomyopathy (DCM) patients and 10 ischemic cardiomyopathy (ICM) patients, and 20 control subjects. All patients underwent 2DE, contrast-enhanced 2DE (Contrast-2DE), 3DE, Contrast-3DE, and single photon emission computed tomography (SPECT) examinations. The 2DE-AL and 3DE methods measured the left ventricular mass (LVM). The results were compared with those measured by SPECT. The measured LVM of the 69 patients was systematically overestimated by 2DE-AL (177.4 ± 56.2 g), Contrast-2DE-AL (174.5 ± 55.5 g), 3DE (167.3 ± 59.2 g), and Contrast-3DE (154.2 ± 46.7 g) when compared with SPECT (148.5 ± 52.4 g) (P < 0.05), while Contrast-3DE provided the best agreement with SPECT in LVM measurement (r = 0.898, P < 0.001) and had the smallest deviation (5.7 ± 23.1 g). 3DE overestimated LVM more compared to Contrast-3DE in LV hypertrophy group (165.5 ± 37.9 g versus 153.5 ± 27.6 g, P = 0.003) and LV enlargement group (204.5 ± 69.3 g versus 183.5 ± 53.5 g, P = 0.006). For 2DE methods, there was no significant difference between the LVM obtained with or without contrast enhancement in control group (132.3 ± 23.6 g versus 128.4 ± 23.3 g), LV hypertrophy group (177.7 ± 38.6 versus 178.3 ± 30.9 g, P = 0.889), and LV enlargement group (211.9 ± 63.2 g versus 206.5 ± 66.0 g, P = 0.386). The difference between LVM measured by 2DE-AL and SPECT was the greatest (27.9 ± 34.0 g), especially in LV hypertrophy group and LV enlargement group (LV hypertrophy group 39.7 ± 26.0 g; LV enlargement group 24.2 ± 42.8 g). To conclude, Contrast-3DE and SPECT show greater consistency in LVM measurement, especially in cardiomyopathy, when compared with 2DE. Administering contrast can effectively reduce the overestimation of LVM by non-contrast DE.

Cardiac magnetic resonance feature tracking global and segmental strain in acute and chronic ST-elevation myocardial infarction

Strain is an important imaging parameter to determine myocardial deformation. This study sought to 1) assess changes in left ventricular strain and ejection fraction (LVEF) from acute to chronic ST-elevation myocardial infarction (STEMI) and 2) analyze strain as a predictor of late gadolinium enhancement (LGE). 32 patients with STEMI and 18 controls prospectively underwent cardiac magnetic resonance imaging. Patients were scanned 8 [Formula: see text] 5 days and six months after infarction (± 1.4 months). Feature tracking was performed and LVEF was calculated. LGE was determined visually and quantitatively on short-axis images and myocardial segments were grouped according to the LGE pattern (negative, non-transmural and transmural). Global strain was impaired in patients compared to controls, but improved within six months after STEMI (longitudinal strain from -14 ± 4 to -16 ± 4%, p < 0.001; radial strain from 38 ± 11 to 42 ± 13%, p = 0.006; circumferential strain from -15 ± 4 to -16 ± 4%, p = 0.023). Patients with microvascular obstruction showed especially attenuated strain results. Regional strain persisted impaired in LGE-positive segments. Circumferential strain could best distinguish between LGE-negative and -positive segments (AUC 0.73- 0.77). Strain improves within six months after STEMI, but remains impaired in LGE-positive segments. Strain may serve as an imaging biomarker to analyze myocardial viability. Especially circumferential strain could predict LGE.

The Merits, Limitations, and Future Directions of Cost-Effectiveness Analysis in Cardiac MRI with a Focus on Coronary Artery Disease: A Literature Review

Cardiac magnetic resonance (CMR) imaging has a wide range of clinical applications with a high degree of accuracy for many myocardial pathologies. Recent literature has shown great utility of CMR in diagnosing many diseases, often changing the course of treatment. Despite this, it is often underutilized possibly due to perceived costs, limiting patient factors and comfort, and longer examination periods compared to other imaging modalities. In this regard, we conducted a literature review using keywords “Cost-Effectiveness” and “Cardiac MRI” and selected articles from the PubMed MEDLINE database that met our inclusion and exclusion criteria to examine the cost-effectiveness of CMR. Our search result yielded 17 articles included in our review. We found that CMR can be cost-effective in quality-adjusted life years (QALYs) in select patient populations with various cardiac pathologies. Specifically, the use of CMR in coronary artery disease (CAD) patients with a pretest probability below a certain threshold may be more cost-effective compared to patients with a higher pretest probability, although its use can be limited based on geographic location, professional society guidelines, and differing reimbursement patterns. In addition, a stepwise combination of different imaging modalities, with conjunction of AHA/ACC guidelines can further enhance the cost-effectiveness of CMR.

Cardiac Magnetic Resonance and Ventricular Arrhythmia Risk Assessment in Chronic Ischemic Cardiomyopathy: An Unmet Need?

Ischemic cardiomyopathy (ICM) constitutes a major public health issue, directly involved in the prevalence and incidence of heart failure, ventricular arrhythmias (VA) and sudden cardiac death (SCD). Severe impairment of left ventricular ejection fraction (LVEF) is considered a high-risk marker for SCD, conditioning the criteria that determine an implantable cardiac defibrillator (ICD) placement in primary prevention according to current clinical guidelines. However, its sensitivity and specificity values for the prediction of SCD in ICM may not be highest. Myocardial characterization using cardiac magnetic resonance with late gadolinium enhancement (CMR-LGE) sequences has made it possible to answer clinically relevant questions that are currently not assessable with LVEF alone. There is growing scientific evidence in favor of the relationship between fibrosis evaluated with CMR and the appearance of VA/SCD in patients with ICM. This evidence should make us contemplate a more realistic clinical value of LVEF in our daily clinical decision-making.

Sustainable low-field cardiovascular magnetic resonance in changing healthcare systems

Cardiovascular disease continues to be a major burden facing healthcare systems worldwide. In the developed world, cardiovascular magnetic resonance (CMR) is a well-established non-invasive imaging modality in the diagnosis of cardiovascular disease. However, there is significant global inequality in availability and access to CMR due to its high cost, technical demands as well as existing disparities in healthcare and technical infrastructures across high-income and low-income countries. Recent renewed interest in low-field CMR has been spurred by the clinical need to provide sustainable imaging technology capable of yielding diagnosticquality images whilst also being tailored to the local populations and healthcare ecosystems. This review aims to evaluate the technical, practical and cost considerations of low field CMR whilst also exploring the key barriers to implementing sustainable MRI in both the developing and developed world.

Optical tissue clearing associated with 3D imaging: application in preclinical and clinical studies

Understanding the inner morphology of intact tissues is one of the most competitive challenges in modern biology. Since the beginning of the twentieth century, optical tissue clearing (OTC) has provided solutions for volumetric imaging, allowing the microscopic visualization of thick sections of tissue, organoids, up to whole organs and organisms (for example, mouse or rat). Recently, tissue clearing has also been introduced in clinical settings to achieve a more accurate diagnosis with the support of 3D imaging. This review aims to give an overview of the most recent developments in OTC and 3D imaging and to illustrate their role in the field of medical diagnosis, with a specific focus on clinical applications.

30-minute CMR for common clinical indications: a Society for Cardiovascular Magnetic Resonance white paper

BACKGROUND

Despite decades of accruing evidence supporting the clinical utility of cardiovascular magnetic resonance (CMR), adoption of CMR in routine cardiovascular practice remains limited in many regions of the world. Persistent use of long scan times of 60 min or more contributes to limited adoption, though techniques available on most scanners afford routine CMR examination within 30 min. Incorporating such techniques into standardize protocols can answer common clinical questions in daily practice, including those related to heart failure, cardiomyopathy, ventricular arrhythmia, ischemic heart disease, and non-ischemic myocardial injury. BODY: In this white paper, we describe CMR protocols of 30 min or shorter duration with routine techniques with or without stress perfusion, plus specific approaches in patient and scanner room preparation for efficiency. Minimum requirements for the scanner gradient system, coil hardware and pulse sequences are detailed. Recent advances such as quantitative myocardial mapping and other add-on acquisitions can be incorporated into the proposed protocols without significant extension of scan duration for most patients.

CONCLUSION

Common questions in clinical cardiovascular practice can be answered in routine CMR protocols under 30 min; their incorporation warrants consideration to facilitate increased access to CMR worldwide.

State-of-the-art myocardial strain by CMR feature tracking: clinical applications and future perspectives

Based on conventional cine sequences of cardiac magnetic resonance (CMR), feature tracking (FT) is an emerging tissue tracking technique that evaluates myocardial motion and deformation quantitatively by strain, strain rate, torsion, and dyssynchrony. It has been widely accepted in modern literature that strain analysis can offer incremental information in addition to classic global and segmental functional analysis. Furthermore, CMR-FT facilitates measurement of all cardiac chambers, including the relatively thin-walled atria and the right ventricle, which has been a difficult measurement to obtain with the reference standard technique of myocardial tagging. CMR-FT objectively quantifies cardiovascular impairment and characterizes myocardial function in a novel way through direct assessment of myocardial fiber deformation. The purpose of this review is to discuss the current status of clinical applications of myocardial strain by CMR-FT in a variety of cardiovascular diseases. KEY POINTS: • CMR-FT is of great value for differential diagnosis and provides incremental value for evaluating the progression and severity of diseases. • CMR-FT guides the early diagnosis of various cardiovascular diseases and provides the possibility for the early detection of myocardial impairment and additional information regarding subclinical cardiac abnormalities. • Direct assessment of myocardial fiber deformation using CMR-FT has the potential to provide prognostic information incremental to common clinical and CMR risk factors.

Influence of motion correction on the visual analysis of cardiac magnetic resonance stress perfusion imaging

OBJECTIVE

Image post-processing corrects for cardiac and respiratory motion (MoCo) during cardiovascular magnetic resonance (CMR) stress perfusion. The study analyzed its influence on visual image evaluation.

MATERIALS AND METHODS

Sixty-two patients with (suspected) coronary artery disease underwent a standard CMR stress perfusion exam during free-breathing. Image post-processing was performed without (non-MoCo) and with MoCo (image intensity normalization; motion extraction with iterative non-rigid registration; motion warping with the combined displacement field). Images were evaluated regarding the perfusion pattern (perfusion deficit, dark rim artifact, uncertain signal loss, and normal perfusion), the general image quality (non-diagnostic, imperfect, good, and excellent), and the reader's subjective confidence to assess the images (not confident, confident, very confident).

RESULTS

Fifty-three (non-MoCo) and 52 (MoCo) myocardial segments were rated as 'perfusion deficit', 113 vs. 109 as 'dark rim artifacts', 9 vs. 7 as 'uncertain signal loss', and 817 vs. 824 as 'normal'. Agreement between non-MoCo and MoCo was high with no diagnostic difference per-patient. The image quality of MoCo was rated more often as 'good' or 'excellent' (92 vs. 63%), and the diagnostic confidence more often as "very confident" (71 vs. 45%) compared to non-MoCo.

CONCLUSIONS

The comparison of perfusion images acquired during free-breathing and post-processed with and without motion correction demonstrated that both methods led to a consistent evaluation of the perfusion pattern, while the image quality and the reader's subjective confidence to assess the images were rated more favorably for MoCo.

Role of cardiac magnetic resonance imaging in the diagnosis and management of COVID-19 related myocarditis: Clinical and imaging considerations

There is a growing evidence of cardiovascular complications in coronavirus disease 2019 (COVID-19) patients. As evidence accumulated of COVID-19 mediated inflammatory effects on the myocardium, substantial attention has been directed towards cardiovascular imaging modalities that facilitate this diagnosis. Cardiac magnetic resonance imaging (CMRI) is the gold standard for the detection of structural and functional myocardial alterations and its role in identifying patients with COVID-19 mediated cardiac injury is growing. Despite its utility in the diagnosis of myocardial injury in this population, CMRI’s impact on patient management is still evolving. This review provides a framework for the use of CMRI in diagnosis and management of COVID-19 patients from the perspective of a cardiologist. We review the role of CMRI in the management of both the acutely and remotely COVID-19 infected patient. We discuss patient selection for this imaging modality; T1, T2, and late gadolinium enhancement imaging techniques; and previously described CMRI findings in other cardiomyopathies with potential implications in COVID-19 recovered patients.

Kompetenz und Innovation in der kardiovaskulären MRT: Stellungnahme der Deutschen Gesellschaft für Kardiologie – Herz- und Kreislaufforschung

Diese Stellungnahme der Deutschen Gesellschaft für Kardiologie (DGK) beschäftigt sich mit der Bedeutung kardiologischer Kompetenz im Gebiet der kardiovaskulären Magnetresonanztomographie (CMR) und deren Aus- und Wechselwirkungen auf klinisches Management im Bereich der Diagnostik, Therapieplanung und Therapie von kardiologischen Patienten. Zahlreiche Innovationen sowohl im technischen als auch klinischen Bereich der CMR basieren auf Publikationen deutscher und europäischer Kardiologen und haben Einzug in die nationalen, europäischen und auch US-amerikanischen Leitlinien gefunden. Hier sollen Empfehlungen zur sicheren, qualitativ hochwertigen und kompetenten Durchführung von CMR-Untersuchungen gegeben werden, im Sinne einer optimalen Nutzung dieser Technik mit unmittelbarer klinischer Einordnung des Untersuchungsergebnisses für die Planung einer Therapiestrategie des kardiovaskulär erkrankten Patienten.

Evidence and Applicability of Stress Cardiovascular Magnetic Resonance in Detecting Coronary Artery Disease: State of the Art

Cardiovascular magnetic resonance is increasingly used in clinical practice, as it has emerged over the years as an invaluable imaging technique for diagnosis and prognosis, with clear-cut applications in managing patients with both ischemic and non-ischemic heart disease. In this review, we focus on the evidence and clinical application of stress CMR in coronary artery disease from diagnosis to prognosis.

Noninvasive rapid cardiac magnetic resonance for the assessment of cardiomyopathies in low-middle income countries

Introduction: Cardiac Magnetic Resonance (CMR) is a crucial diagnostic imaging test that redefines diagnosis and enables targeted therapies, but the access to CMR is limited in low-middle Income Countries (LMICs) even though cardiovascular disease is an emergent primary cause of mortality in LMICs. New abbreviated CMR protocols can be less expensive, faster, whilst maintaining accuracy, potentially leading to a higher utilization in LMICs.Areas covered: This article will review cardiovascular disease in LMICs and the current role of CMR in cardiac diagnosis and enable targeted therapy, discussing the main obstacles to prevent the adoption of CMR in LMICs. We will then review the potential utility of abbreviated, cost-effective CMR protocols to improve cardiac diagnosis and care, the clinical indications of the exam, current evidence and future directions.Expert opinion: Rapid CMR protocols, provided that they are utilized in potentially high yield cases, could reduce cost and increase effectiveness. The adoption of these protocols, their integration into care pathways, and prioritizing key treatable diagnoses can potentially improve patient care. Several LMIC countries are now pioneering these approaches and the application of rapid CMR protocols appears to have a bright future if delivered effectively.

Aortic and mitral flow quantification using dynamic valve tracking and machine learning: Prospective study assessing static and dynamic plane repeatability, variability and agreement

Background

Blood flow is a crucial measurement in the assessment of heart valve disease. Time-resolved flow using magnetic resonance imaging (4 D flow MRI) can provide a comprehensive assessment of heart valve hemodynamics but it relies in manual plane analysis. In this study, we aimed to demonstrate the feasibility of automate the detection and tracking of aortic and mitral valve planes to assess blood flow from 4 D flow MRI.

Methods

In this prospective study, a total of n = 106 subjects were enrolled: 19 patients with mitral disease, 65 aortic disease patients and 22 healthy controls. Machine learning was employed to detect aortic and mitral location and motion in a cine three-chamber plane and a perpendicular projection was co-registered to the 4 D flow MRI dataset to quantify flow volume, regurgitant fraction, and a peak velocity. Static and dynamic plane association and agreement were evaluated. Intra- and inter-observer, and scan-rescan reproducibility were also assessed.

Results

Aortic regurgitant fraction was elevated in aortic valve disease patients as compared with controls and mitral valve disease patients (p < 0.05). Similarly, mitral regurgitant fraction was higher in mitral valve patients (p < 0.05). Both aortic and mitral total flow were high in aortic patients. Static and dynamic were good (r > 0.6, p < 0.005) for aortic total flow and peak velocity, and mitral peak velocity and regurgitant fraction. All measurements showed good inter- and intra-observer, and scan-rescan reproducibility.

Conclusion

We demonstrated that aortic and mitral hemodynamics can efficiently be quantified from 4 D flow MRI using assisted valve detection with machine learning.

A Myocardial Segmentation Method Based on Adversarial Learning

Congenital heart defects (CHD) are structural imperfections of the heart or large blood vessels that are detected around birth and their symptoms vary wildly, with mild case patients having no obvious symptoms and serious cases being potentially life-threatening. Using cardiovascular magnetic resonance imaging (CMRI) technology to create a patient-specific 3D heart model is an important prerequisite for surgical planning in children with CHD. Manually segmenting 3D images using existing tools is time-consuming and laborious, which greatly hinders the routine clinical application of 3D heart models. Therefore, automatic myocardial segmentation algorithms and related computer-aided diagnosis systems have emerged. Currently, the conventional methods for automatic myocardium segmentation are based on deep learning, rather than on the traditional machine learning method. Better results have been achieved, however, difficulties still exist such as CMRI often has, inconsistent signal strength, low contrast, and indistinguishable thin-walled structures near the atrium, valves, and large blood vessels, leading to challenges in automatic myocardium segmentation. Additionally, the labeling of 3D CMR images is time-consuming and laborious, causing problems in obtaining enough accurately labeled data. To solve the above problems, we proposed to apply the idea of adversarial learning to the problem of myocardial segmentation. Through a discriminant model, some additional supervision information is provided as a guide to further improve the performance of the segmentation model. Experiment results on real-world datasets show that our proposed adversarial learning-based method had improved performance compared with the baseline segmentation model and achieved better results on the automatic myocardium segmentation problem.

Trends in Cardiovascular MRI and CT in the U.S. Medicare Population from 2012 to 2017

Purpose

To assess the characteristics and trends of cardiovascular MRI and CT practitioners and practice in the United States.

Materials and Methods

A retrospective cross-sectional analysis of 2012-2017 Medicare Part B physician payments from the Provider Utilization and Payment Data Physician and Other Supplier Public Use Files (POSPUF) was performed. Characteristics of cardiovascular MRI and CT, including the number of providers and examinations, provider sex and location, and physician reimbursement were analyzed. Variable means, standard deviations, and changes per year were reported and compared.

Results

In 2017, 582 physicians provided cardiovascular MRI services in 45 states, a 16.6% increase from 2016 and an 84.8% increase from 2012. A total of 1645 physicians provided cardiovascular CT services in 49 states, a 14.2% increase from 2016 and a 77.3% increase from 2012. Of the providers, 18.0% and 13.3% of cardiovascular MRI and CT providers were women, respectively, similar to providers' respective medical specialties. Only 1.0% of radiologists and 0.2% of cardiologists provided cardiovascular MRI services. A total of 3.2% of radiologists and 0.5% of cardiologists provided cardiovascular CT services. Both cardiovascular MRI use (+75.5%) and cardiovascular CT use (+97.4%) increased markedly over the 6-year study period.

Conclusion

Although the availability of cardiovascular MRI and CT is increasing, both are used less frequently in comparison with other cardiovascular imaging modalities.See also the commentary by Bierhals in this issue.Supplemental material is available for this article.© RSNA, 2021.

Recent Trends and Potential Drivers of Non-invasive Cardiovascular Imaging Use in the United States of America and England

Background: Non-invasive Cardiovascular imaging (NICI), including cardiovascular magnetic resonance (CMR) imaging provides important information to guide the management of patients with cardiovascular conditions. Current rates of NICI use and potential policy determinants in the United States of America (US) and England remain unexplored. Methods: We compared NICI activity in the US (Medicare fee-for-service, 2011-2015) and England (National Health Service, 2012-2016). We reviewed recommendations related to CMR from Clinical Practice Guidelines, Appropriate Use Criteria (AUC), and Choosing Wisely. We then categorized recommendations according to whether CMR was the only recommended NICI technique (substitutable indications). Reimbursement policies in both settings were systematically collated and reviewed using publicly available information. Results: The 2015 rate of NICI activity in the US was 3.1 times higher than in England (31,055 vs. 9,916 per 100,000 beneficiaries). The proportion of CMR of all NICI was small in both jurisdictions, but nuclear cardiac imaging was more frequent in the US in absolute and relative terms. American and European CPGs were similar, both in terms of number of recommendations and proportions of indications where CMR was not the only recommended NICI technique (substitutable indications). Reimbursement schemes for NICI activity differed for physicians and hospitals between the two settings. Conclusions: Fee-for-service physician compensation in the US for NICI may contribute to higher NICI activity compared to England where physicians are salaried. Reimbursement arrangements for the performance of the test may contribute to the higher proportion of nuclear cardiac imaging out of the total NICI activity. Differences in CPG recommendations appear not to explain the variation in NICI activity between the US and England.

Cine and late gadolinium enhancement MRI registration and automated myocardial infarct heterogeneity quantification

PURPOSE

To develop an approach for automated quantification of myocardial infarct heterogeneity in late gadolinium enhancement (LGE) cardiac MRI.

METHODS

We acquired 2D short-axis cine and 3D LGE in 10 pigs with myocardial infarct. The 2D cine myocardium was segmented and registered to the LGE images. LGE image signal intensities within the warped cine myocardium masks were analyzed to determine the thresholds of infarct core (IC) and gray zone (GZ) for the standard-deviation (SD) and full-width-at-halfmaximum (FWHM) methods. The initial IC, GZ, and IC + GZ segmentations were postprocessed using a normalized cut approach. Cine segmentation and cine-LGE registration accuracies were evaluated using dice similarity coefficient and average symmetric surface distance. Automated IC, GZ, and IC + GZ volumes were compared with manual results using Pearson correlation coefficient (r), Bland-Altman analyses, and intraclass correlation coefficient.

RESULTS

For n = 87 slices containing scar, we achieved cine segmentation dice similarity coefficient = 0.87 ± 0.12, average symmetric surface distance = 0.94 ± 0.74 mm (epicardium), and 1.03 ± 0.82 mm (endocardium) in the scar region. For cine-LGE registration, dice similarity coefficient was 0.90 ± 0.06 and average symmetric surface distance was 0.72 ± 0.39 mm (epicardium) and 0.86 ± 0.53 mm (endocardium) in the scar region. For both SD and FWHM methods, automated IC, GZ, and IC + GZ volumes were strongly (r > 0.70) correlated with manual measurements, and the correlations were not significantly different from interobserver correlations (P > .05). The agreement between automated and manual scar volumes (intraclass correlation coefficient = 0.85-0.96) was similar to that between two observers (intraclass correlation coefficient = 0.81-0.99); automated scar segmentation errors were not significantly different from interobserver segmentation differences (P > .05).

CONCLUSIONS

Our approach provides fully automated cine-LGE MRI registration and LGE myocardial infarct heterogeneity quantification in preclinical studies.

Artificial Intelligence and Texture Analysis in Cardiac Imaging

PURPOSE OF REVIEW

The aim of this structured review is to summarize the current research applications and opportunities arising from artificial intelligence (AI) and texture analysis with regard to cardiac imaging.

RECENT FINDINGS

Current research findings suggest tremendous potential for AI in cardiac imaging, especially with regard to objective image analyses, overcoming the limitations of an observer-dependent subjective image interpretation. Researchers have used this technique across multiple imaging modalities, for instance to detect myocardial scars in cardiac MR imaging, to predict contrast enhancement in non-contrast studies, and to improve image acquisition and reconstruction. AI in medical imaging has the potential to provide novel, much-needed applications for improving patient care pertaining to the cardiovascular system. While several shortcomings are still present in the current methodology, AI may serve as a resourceful assistant to radiologists and clinicians alike.

Society for Cardiovascular Magnetic Resonance (SCMR) recommended CMR protocols for scanning patients with active or convalescent phase COVID-19 infection

The aim of this document is to provide specific recommendations on the use of cardiovascular magnetic resonance (CMR) protocols in the era of the COVID-19 pandemic. In patients without COVID-19, standard CMR protocols should be used based on clinical indication as usual. Protocols used in patients who have known / suspected active COVID-19 or post COVID-19 should be performed based on the specific clinical question with an emphasis on cardiac function and myocardial tissue characterization. Short and dedicated protocols are recommended.

Influence of contrast agent and spatial resolution on myocardial strain results using feature tracking MRI

OBJECTIVES

Feature tracking for assessing myocardial strain from cardiac magnetic resonance (CMR) cine images detects myocardial deformation abnormalities with prognostic implication, e.g., in myocardial infarction and cardiomyopathy. Standards for image acquisition and processing are not yet available. Study aim was analyzing the influence of spatial resolution and contrast agent on myocardial strain results.

METHODS

Seventy-five patients underwent CMR for analyzing peak systolic circumferential, longitudinal, and radial strain. Group A included n = 50 with normal left ventricular ejection fraction, no wall motion abnormality, and no fibrosis on late enhancement imaging. Group B included n = 25 with chronic myocardial infarct. For feature tracking, steady-state free precession cine images were acquired repeatedly. (1) Native standard cine (spatial resolution 1.4 × 1.4 × 8 mm³). (2) Native cine with lower spatial resolution (2.0 × 2.0 × 8 mm³). (3) Cine equal to variant 1 acquired after administration of gadoteracid.

RESULTS

Lower spatial resolution was associated with elevated longitudinal strain (- 21.7% vs. - 19.8%; p < 0.001) in viable myocardium in group A, and with elevated longitudinal (- 17.0% vs. - 14.3%; p = 0.001), circumferential (- 18.6% vs. - 14.6%; p = 0.002), and radial strain (36.8% vs. 31.0%; p = 0.013) in infarcted myocardium in group B. Gadolinium administration was associated with reduced circumferential (- 21.4% vs. - 22.3%; p = 0.001) and radial strain (44.4% vs. 46.9%; p = 0.016) in group A, whereas strain results of the infarcted tissue in group B did not change after contrast agent administration.

CONCLUSIONS

Variations in spatial resolution and the administration of contrast agent may influence myocardial strain results in viable and partly in infarcted myocardium. Standardized image acquisition seems important for CMR feature tracking.

KEY POINTS

• Feature tracking is used for calculating myocardial strain from cardiac magnetic resonance (CMR) cine images. • This prospective study demonstrated that CMR strain results may be influenced by spatial resolution and by the administration of gadolinium-based contrast agent. • The results underline the need for standardized image acquisition for CMR strain analysis, with constant imaging parameters and without contrast agent.

Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI With Limited Training Data

In this work we reduce undersampling artefacts in two-dimensional (2D) golden-angle radial cine cardiac MRI by applying a modified version of the U-net. The network is trained on 2D spatio-temporal slices which are previously extracted from the image sequences. We compare our approach to two 2D and a 3D deep learning-based post processing methods, three iterative reconstruction methods and two recently proposed methods for dynamic cardiac MRI based on 2D and 3D cascaded networks. Our method outperforms the 2D spatially trained U-net and the 2D spatio-temporal U-net. Compared to the 3D spatio-temporal U-net, our method delivers comparable results, but requiring shorter training times and less training data. Compared to the compressed sensing-based methods kt-FOCUSS and a total variation regularized reconstruction approach, our method improves image quality with respect to all reported metrics. Further, it achieves competitive results when compared to the iterative reconstruction method based on adaptive regularization with dictionary learning and total variation and when compared to the methods based on cascaded networks, while only requiring a small fraction of the computational and training time. A persistent homology analysis demonstrates that the data manifold of the spatio-temporal domain has a lower complexity than the one of the spatial domain and therefore, the learning of a projection-like mapping is facilitated. Even when trained on only one single subject without data-augmentation, our approach yields results which are similar to the ones obtained on a large training dataset. This makes the method particularly suitable for training a network on limited training data. Finally, in contrast to the spatial 2D U-net, our proposed method is shown to be naturally robust with respect to image rotation in image space and almost achieves rotation-equivariance where neither data-augmentation nor a particular network design are required.

Journal of Cardiovascular Magnetic Resonance: 2017/2018 in review

There were 89 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2017, including 76 original research papers, 4 reviews, 5 technical notes, 1 guideline, and 3 corrections. The volume was down slightly from 2017 with a corresponding 15% decrease in manuscript submissions from 405 to 346 and thus reflects a slight increase in the acceptance rate from 25 to 26%. The decrease in submissions for the year followed the initiation of the increased author processing charge (APC) for Society for Cardiovascular Magnetic Resonance (SCMR) members for manuscripts submitted after June 30, 2018. The quality of the submissions continues to be high. The 2018 JCMR Impact Factor (which is published in June 2019) was slightly lower at 5.1 (vs. 5.46 for 2017; as published in June 2018. The 2018 impact factor means that on average, each JCMR published in 2016 and 2017 was cited 5.1 times in 2018. Our 5 year impact factor was 5.82.In accordance with Open-Access publishing guidelines of BMC, the JCMR articles are published on-line in a continuus fashion in the chronologic order of acceptance, with no collating of the articles into sections or special thematic issues. For this reason, over the years, the Editors have felt that it is useful for the JCMR audience to annually summarize the publications into broad areas of interest or themes, so that readers can view areas of interest in a single article in relation to each other and contemporaneous JCMR publications. In this publication, the manuscripts are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought within the journal. In addition, as in the past two years, I have used this publication to also convey information regarding the editorial process and as a "State of our JCMR."This is the 12th year of JCMR as an open-access publication with BMC (formerly known as Biomed Central). The timing of the JCMR transition to the open access platform was "ahead of the curve" and a tribute to the vision of Dr. Matthias Friedrich, the SCMR Publications Committee Chair and Dr. Dudley Pennell, the JCMR editor-in-chief at the time. The open-access system has dramatically increased the reading and citation of JCMR publications and I hope that you, our authors, will continue to send your very best, high quality manuscripts to JCMR for consideration. It takes a village to run a journal and I thank our very dedicated Associate Editors, Guest Editors, Reviewers for their efforts to ensure that the review process occurs in a timely and responsible manner. These efforts have allowed the JCMR to continue as the premier journal of our field. This entire process would also not be possible without the dedication and efforts of our managing editor, Diana Gethers. Finally, I thank you for entrusting me with the editorship of the JCMR as I begin my 4th year as your editor-in-chief. It has been a tremendous experience for me and the opportunity to review manuscripts that reflect the best in our field remains a great joy and highlight of my week!

Characteristics of Cardiovascular Magnetic Resonance Imaging and Outcomes in Adults With Repaired Truncus Arteriosus

The cardiovascular magnetic resonance imaging (CMR) features of adults with repaired truncus arteriosus (rTA) are largely undefined. We sought to explore CMR characteristics in rTA and to identify associations between imaging findings and cardiovascular outcomes. Adults with rTA and CMR were identified and anatomic subtypes (1-4) were assigned (Collett and Edwards classification). CMR characteristics, clinical data at last follow-up and adverse cardiovascular outcome were recorded. Twenty-seven adults (19% male) were studied (median age at cardiovascular magnetic resonance 26 years [interquartile range 18 to 40]) over 5.2-year duration [interquartile range 2.5 to 7.5]. With the exception of mildly increased RV mass (30 ± 12 g/m²), cardiac chamber measurements were within the normal range. In CMR measurements, only pulmonary artery peak velocity differed in subtypes (highest in subtype 3, 318 ± 26 cm/s, p = 0.029). Number of cardiovascular interventions in adulthood was moderately correlated with left ventricular end-diastolic volume (r = 0.463, p = 0.015), left ventricular ejection fraction (r = 0.425, p = 0.027) and neoaortic root size (r = 0.398, p = 0.039). Cardiovascular events (nonmutually exclusive) in 5 of 27 patients (19%) included death (n = 1), heart failure (n = 1), ventricular tachycardia (n = 1), and atrial tachycardia (n = 3). Increased cardiovascular risk was associated with decreased right ventricular ejection fraction (odds ratio 1.153, confidence interval 1.003 to 1.326, p = 0.046) and smaller ascending aorta diameter (odds ratio 1.758, confidence interval 1.037 to 2.976, p = 0.036). In conclusion, decreased right ventricular ejection fraction and smaller ascending aorta on cardiovascular magnetic resonance were associated with adverse events in rTA.

Complete Free-breathing Adenosine Stress Cardiac MRI Using Compressed Sensing and Motion Correction: Comparison of Functional Parameters, Perfusion, and Late Enhancement with the Standard Breath-holding Examination

PURPOSE

To compare free-breathing (FB) stress cardiac MRI examinations with the reference standard breath-holding (BH) examination.

MATERIALS AND METHODS

A total of 40 consecutive patients were enrolled prospectively and were examined with 3-T MRI. Functional imaging, perfusion, and late gadolinium enhancement (LGE) sequences were performed in BH and FB by using compressed sensing and in-line motion correction. Left ventricle (LV) and right ventricle (RV) functional parameters in BH and FB examinations were compared by using Bland-Altman plots and linear mixed models. Subjective image quality was assessed with a five-point scale (1 = nondiagnostic, 5 = very good). For perfusion and LGE imaging, diagnostic confidence was rated with a three-point scale (1 = low, 3 = high), and image quality was rated with a five-point scale (1 = nondiagnostic, 5 = very good). The Wilcoxon test was used to compare image quality and diagnostic confidence.

RESULTS

Bland-Altman plots showed good agreement for LV and RV functional parameters in BH and FB sequences. Subjective image quality was significantly better with the BH sequences in the LV (P < .01) but was comparable in the RV (P > .99). Scanning time was 218 seconds (range, 130-385 seconds) for cine BH and 16 seconds (range, 11-27 seconds) for cine FB. Extent of perfusion defects, LGE, and diagnostic confidence was comparable between groups. Scanning time was 371 seconds (range, 239-502 seconds) for the LGE BH sequence and 189 seconds (range, 122-286 seconds) for the LGE FB sequence.

CONCLUSION

FB adenosine stress cardiac MRI delivers diagnostic image quality and could represent an alternative for use in patients who are unable to meet the demands of multiple BHs and long examination times.© RSNA, 2019.

Fully Automated, Quality-Controlled Cardiac Analysis From CMR: Validation and Large-Scale Application to Characterize Cardiac Function

Objectives

This study sought to develop a fully automated framework for cardiac function analysis from cardiac magnetic resonance (CMR), including comprehensive quality control (QC) algorithms to detect erroneous output.

Background

Analysis of cine CMR imaging using deep learning (DL) algorithms could automate ventricular function assessment. However, variable image quality, variability in phenotypes of disease, and unavoidable weaknesses in training of DL algorithms currently prevent their use in clinical practice.

Methods

The framework consists of a pre-analysis DL image QC, followed by a DL algorithm for biventricular segmentation in long-axis and short-axis views, myocardial feature-tracking (FT), and a post-analysis QC to detect erroneous results. The study validated the framework in healthy subjects and cardiac patients by comparison against manual analysis (n = 100) and evaluation of the QC steps’ ability to detect erroneous results (n = 700). Next, this method was used to obtain reference values for cardiac function metrics from the UK Biobank.

Results

Automated analysis correlated highly with manual analysis for left and right ventricular volumes (all r > 0.95), strain (circumferential r = 0.89, longitudinal r > 0.89), and filling and ejection rates (all r ≥ 0.93). There was no significant bias for cardiac volumes and filling and ejection rates, except for right ventricular end-systolic volume (bias +1.80 ml; p = 0.01). The bias for FT strain was <1.3%. The sensitivity of detection of erroneous output was 95% for volume-derived parameters and 93% for FT strain. Finally, reference values were automatically derived from 2,029 CMR exams in healthy subjects.

Conclusions

The study demonstrates a DL-based framework for automated, quality-controlled characterization of cardiac function from cine CMR, without the need for direct clinician oversight.

Evaluation of elevated left ventricular end diastolic pressure in patients with preserved ejection fraction using cardiac magnetic resonance

OBJECTIVES

This study aims to validate the reliability of cardiac magnetic resonance (CMR) parameters for estimating left ventricular end diastolic pressure (LVEDP) in heart failure patients with preserved ejection fraction (HFpEF) and compare their accuracy to conventional echocardiographic ones, with reference to left heart catheterisation.

METHODS

Sixty patients with exertional dyspnoea (New York Heart Association function class II to III) were consecutively enrolled. CMR-derived time-volume curve and deformation parameters, conventional echocardiographic diastolic indices as well as LVEDP evaluated by left heart catheterisation were collected and analysed.

RESULTS

Fifty-one patients, who accomplished all three examinations, were divided into HFpEF group and non-HFpEF group based on LVEDP measurements. Compared to the non-HFpEF group, CMR-derived time-volume curve showed lower peak filling rate adjusted for end diastolic volume (PFR/EDV, p = 0.027), longer time to peak filling rate (T-PFR, p < 0.001), and increased T-PFR in one cardiac cycle (%T-PFR, p < 0.001) in HFpEF group. In multivariable linear regression analysis, %T-PFR (β = 0.372, p = 0.024), left ventricular global peak longitudinal diastolic strain rate (LDSR, β = -0.471, p = 0.006), and E/e' (β = 0.547, p = 0.001) were independently associated with invasively measured LVEDP. The sensitivity and specificity of E/e' and LDSR for predicting the elevated LVEDP were 76%, 92% and 76%, 89%, respectively.

CONCLUSIONS

These findings suggest that CMR-derived time-volume curve and strain indices could predict HFpEF patients. Not only E/e' assessed by echocardiography but also the CMR-derived %T-PFR and LDSR correlated well with LVEDP. These non-invasive parameters were validated to evaluate the left ventricular diastolic function.

KEY POINTS

• The abnormal time-volume curve revealed insufficient early diastole in HFpEF patients. • Non-invasive parameters including E/e', %T-PFR, and LDSR correlated well with LVEDP.

The Added Value of Cardiac Magnetic Resonance in Muscular Dystrophies

Muscular dystrophies (MD) represent a heterogeneous group of rare genetic diseases that often lead to significant weakness due to progressive muscle degeneration. In many forms of MD, cardiac manifestations including heart failure, atrial and ventricular arrhythmias and conduction abnormalities can occur and may be a predominant feature of the disease. Cardiac magnetic resonance (CMR) can assess cardiac anatomy, global and regional ventricular function, volumes and mass as well as presence of myocardial inflammation, infiltration or fibrosis. The role for cardiac MRI has been well-established in a wide range of muscular dystrophies related cardiomyopathies. CMR is a more sensitive technique than echocardiography for early diagnosis of cardiac involvement. It has also great potential to improve the prediction of long-term outcome, particularly the development of heart failure and arrhythmic events; however it still has to be validated by longitudinal studies including large populations. This review will outline the utility of CMR in patients with muscular dystrophies for assessment of myocardial involvement, risk stratification, and in guiding therapeutic management.

Journal of Cardiovascular Magnetic Resonance 2017

There were 106 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2017, including 92 original research papers, 3 reviews, 9 technical notes, and 1 Position paper, 1 erratum and 1 correction. The volume was similar to 2016 despite an increase in manuscript submissions to 405 and thus reflects a slight decrease in the acceptance rate to 26.7%. The quality of the submissions continues to be high. The 2017 JCMR Impact Factor (which is published in June 2018) was minimally lower at 5.46 (vs. 5.71 for 2016; as published in June 2017), which is the second highest impact factor ever recorded for JCMR. The 2017 impact factor means that an average, each JCMR paper that were published in 2015 and 2016 was cited 5.46 times in 2017.In accordance with Open-Access publishing of Biomed Central, the JCMR articles are published on-line in continuus fashion and in the chronologic order of acceptance, with no collating of the articles into sections or special thematic issues. For this reason, over the years, the Editors have felt that it is useful to annually summarize the publications into broad areas of interest or theme, so that readers can view areas of interest in a single article in relation to each other and other contemporary JCMR articles. In this publication, the manuscripts are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought within the journal. In addition, I have elected to use this format to convey information regarding the editorial process to the readership.I hope that you find the open-access system increases wider reading and citation of your papers, and that you will continue to send your very best, high quality manuscripts to JCMR for consideration. I thank our very dedicated Associate Editors, Guest Editors, and Reviewers for their efforts to ensure that the review process occurs in a timely and responsible manner and that the JCMR continues to be recognized as the forefront journal of our field. And finally, I thank you for entrusting me with the editorship of the JCMR as I begin my 3rd year as your editor-in-chief. It has been a tremendous learning experience for me and the opportunity to review manuscripts that reflect the best in our field remains a great joy and highlight of my week!

The growth and evolution of cardiovascular magnetic resonance: a 20-year history of the Society for Cardiovascular Magnetic Resonance (SCMR) annual scientific sessions

BACKGROUND AND PURPOSE

The purpose of this work is to summarize cardiovascular magnetic resonance (CMR) research trends and highlights presented at the annual Society for Cardiovascular Magnetic Resonance (SCMR) scientific sessions over the past 20 years.

METHODS

Scientific programs from all SCMR Annual Scientific Sessions from 1998 to 2017 were obtained. SCMR Headquarters also provided data for the number and the country of origin of attendees and the number of accepted abstracts according to type. Data analysis included text analysis (key word extraction) and visualization by 'word clouds' representing the most frequently used words in session titles for 5-year intervals. In addition, session titles were sorted into 17 major subject categories to further evaluate research and clinical CMR trends over time.

RESULTS

Analysis of SCMR annual scientific sessions locations, attendance, and number of accepted abstracts demonstrated substantial growth of CMR research and clinical applications. As an international field of study, significant growth of CMR was documented by a strong increase in SCMR scientific session attendance (> 500%, 270 to 1406 from 1998 to 2017, number of accepted abstracts (> 700%, 98 to 701 from 1998 to 2018) and number of international participants (42-415% increase for participants from Asia, Central and South America, Middle East and Africa in 2004-2017). 'Word clouds' based evaluation of research trends illustrated a shift from early focus on 'MRI technique feasibility' to new established techniques (e.g. late gadolinium enhancement) and their clinical applications and translation (key words 'patient', 'disease') and more recently novel techniques and quantitative CMR imaging (key words 'mapping', 'T1', 'flow', 'function'). Nearly every topic category demonstrated an increase in the number of sessions over the 20-year period with 'Clinical Practice' leading all categories. Our analysis identified three growth areas 'Congenital', 'Clinical Practice', and 'Structure/function/flow'.

CONCLUSION

The analysis of the SCMR historical archives demonstrates a healthy and internationally active field of study which continues to undergo substantial growth and expansion into new and emerging CMR topics and clinical application areas.