Tissue-Based Predictors of Impaired Right Ventricular Strain in Coronary Artery Disease: A Multicenter Stress Perfusion Study.

BACKGROUND: Right ventricular (RV) dysfunction is known to impact prognosis, but its determinants in coronary artery disease are poorly understood. Stress cardiac magnetic resonance (CMR) has been used to assess ischemia and infarction in relation to the left ventricle (LV); the impact of myocardial tissue properties on RV function is unknown. METHODS: Vasodilator stress CMR was performed in patients with known coronary artery disease at 7 sites between May 2005 and October 2018. Myocardial infarction was identified on late gadolinium enhancement-CMR, and infarct transmurality was graded on a per-segment basis. Ischemia was assessed on stress CMR based on first-pass perfusion and localized by using segment partitions corresponding to cine and late gadolinium enhancement analyses. RV function was evaluated by CMR-feature tracking for primary analysis with a global longitudinal strain threshold of 20% used to define impaired RV strain (RVIS); secondary functional analysis via RV ejection fraction was also performed. RESULTS: A total of 2604 patients were studied, among whom RVIS was present in 461 patients (18%). The presence and magnitude of RVIS were strongly associated with LV dysfunction, irrespective of whether measured by LV ejection fraction or wall motion score (P<0.001 for all). Regarding tissue substrate, regions of ischemic and dysfunctional myocardium (ie, hibernating myocardium) and infarct size were each independently associated with RVIS (both P<0.001). During follow-up (median, 4.62 [interquartile range, 2.15-7.67] years), 555 deaths (21%) occurred. Kaplan-Meier analysis for patients stratified by presence and magnitude of RV dysfunction by global longitudinal strain and RV ejection fraction each demonstrated strong prognostic utility for all-cause mortality (P<0.001). RVIS conferred increased mortality risk (hazard ratio, 1.35 [95% CI, 1.11-1.66]; P=0.003) even after controlling for LV function, infarction, and ischemia. CONCLUSIONS: RVIS in patients with known coronary artery disease is associated with potentially reversible LV processes, including LV functional impairment due to ischemic and predominantly viable myocardium, which confers increased mortality risk independent of LV function and tissue substrate.

Association of Adverse Clinical Outcomes With Peri-Infarct Ischemia Detected by Stress Cardiac Magnetic Imaging.

BACKGROUND: Early invasive revascularization guided by moderate to severe ischemia did not improve outcomes over medical therapy alone, underlying the need to identify high-risk patients for a more effective invasive referral. CMR could determine the myocardial extent and matching locations of ischemia and infarction. OBJECTIVES: This study sought to investigate if CMR peri-infarct ischemia is associated with adverse events incremental to known risk markers. METHODS: Consecutive patients were included in an expanded cohort of the multicenter SPINS (Stress CMR Perfusion Imaging in the United States) study. Peri-infarct ischemia was defined by the presence of any ischemic segment neighboring an infarcted segment by late gadolinium enhancement imaging. Primary outcome events included acute myocardial infarction and cardiovascular death, whereas secondary events included any primary events, hospitalization for unstable angina, heart failure hospitalization, and late coronary artery bypass surgery. RESULTS: Among 3,915 patients (age: 61.0 ± 12.9 years; 54.7% male), ischemia, infarct, and peri-infarct ischemia were present in 752 (19.2%), 1,123 (28.8%), and 382 (9.8%) patients, respectively. At 5.3 years (Q1-Q3: 3.9-7.2 years) of median follow-up, primary and secondary events occurred in 406 (10.4%) and 745 (19.0%) patients, respectively. Peri-infarct ischemia was the strongest multivariable predictor for primary and secondary events (HRadjusted: 1.72 [95% CI: 1.23-2.41] and 1.71 [95% CI: 1.32-2.20], respectively; both P < 0.001), adjusted for clinical risk factors, left ventricular function, ischemia extent, and infarct size. The presence of peri-infarct ischemia portended to a >6-fold increased annualized primary event rate compared to those with no infarct and ischemia (6.5% vs 0.9%). CONCLUSIONS: Peri-infarct ischemia is a novel and robust prognostic marker of adverse cardiovascular events.

Risk prediction of heart diseases in patients with breast cancer: A deep learning approach with longitudinal electronic health records data.

Accurately predicting heart disease risks in patients with breast cancer is crucial for clinical decision support and patient safety. This study developed and evaluated predictive models for six heart diseases using real-world electronic health records (EHRs) data. We incorporated a trainable decay mechanism to handle missing values in the long short-term memory (LSTM) model, creating LSTM-D models to predict heart disease risk based on longitudinal EHRs data. Additionally, we deployed NLP methods to extract breast cancer phenotypes from clinical texts, integrating unstructured and structured data to enhance predictions. Our LSTM-D models outperformed baseline models in predicting congestive heart failure, coronary artery disease, cardiomyopathy, myocardial infarction, transient ischemic attack, and aortic regurgitation, with AUC scores ranging from 0.7189 to 0.9548. Observation windows of 12-24 months were found optimal for model performance. This research advances precise, personalized care strategies, enabling early intervention and improved management of cardiovascular risks in breast cancer survivors.

Multi-modality risk prediction of cardiovascular diseases for breast cancer cohort in the All of Us Research Program.

OBJECTIVE: This study leverages the rich diversity of the All of Us Research Program (All of Us)'s dataset to devise a predictive model for cardiovascular disease (CVD) in breast cancer (BC) survivors. Central to this endeavor is the creation of a robust data integration pipeline that synthesizes electronic health records (EHRs), patient surveys, and genomic data, while upholding fairness across demographic variables. MATERIALS AND METHODS: We have developed a universal data wrangling pipeline to process and merge heterogeneous data sources of the All of Us dataset, address missingness and variance in data, and align disparate data modalities into a coherent framework for analysis. Utilizing a composite feature set including EHR, lifestyle, and social determinants of health (SDoH) data, we then employed Adaptive Lasso and Random Forest regression models to predict 6 CVD outcomes. The models were evaluated using the c-index and time-dependent Area Under the Receiver Operating Characteristic Curve over a 10-year period. RESULTS: The Adaptive Lasso model showed consistent performance across most CVD outcomes, while the Random Forest model excelled particularly in predicting outcomes like transient ischemic attack when incorporating the full multi-model feature set. Feature importance analysis revealed age and previous coronary events as dominant predictors across CVD outcomes, with SDoH clustering labels highlighting the nuanced impact of social factors. DISCUSSION: The development of both Cox-based predictive model and Random Forest Regression model represents the extensive application of the All of Us, in integrating EHR and patient surveys to enhance precision medicine. And the inclusion of SDoH clustering labels revealed the significant impact of sociobehavioral factors on patient outcomes, emphasizing the importance of comprehensive health determinants in predictive models. Despite these advancements, limitations include the exclusion of genetic data, broad categorization of CVD conditions, and the need for fairness analyses to ensure equitable model performance across diverse populations. Future work should refine clinical and social variable measurements, incorporate advanced imputation techniques, and explore additional predictive algorithms to enhance model precision and fairness. CONCLUSION: This study demonstrates the liability of the All of Us's diverse dataset in developing a multi-modality predictive model for CVD in BC survivors risk stratification in oncological survivorship. The data integration pipeline and subsequent predictive models establish a methodological foundation for future research into personalized healthcare.

The Society for Cardiovascular Magnetic Resonance Registry at 150,000.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is increasingly utilized to evaluate expanding cardiovascular conditions. The Society for Cardiovascular Magnetic Resonance (SCMR) Registry is a central repository for real-world clinical data to support cardiovascular research, including those relating to outcomes, quality improvement, and machine learning. The SCMR Registry is built on a regulatory-compliant, cloud-based infrastructure that houses searchable content and Digital Imaging and Communications in Medicine images. The goal of this study is to summarize the status of the SCMR Registry at 150,000 exams. METHODS: The processes for data security, data submission, and research access are outlined. We interrogated the Registry and presented a summary of its contents. RESULTS: Data were compiled from 154,458 CMR scans across 20 United States sites, containing 299,622,066 total images (∼100 terabytes of storage). Across reported values, the human subjects had an average age of 58 years (range 1 month to >90 years old), were 44% (63,070/145,275) female, 72% (69,766/98,008) Caucasian, and had a mortality rate of 8% (9,962/132,979). The most common indication was cardiomyopathy (35,369/131,581, 27%), and most frequently used current procedural terminology code was 75561 (57,195/162,901, 35%). Macrocyclic gadolinium-based contrast agents represented 89% (83,089/93,884) of contrast utilization after 2015. Short-axis cines were performed in 99% (76,859/77,871) of tagged scans, short-axis late gadolinium enhancement (LGE) in 66% (51,591/77,871), and stress perfusion sequences in 30% (23,241/77,871). Mortality data demonstrated increased mortality in patients with left ventricular ejection fraction <35%, the presence of wall motion abnormalities, stress perfusion defects, and infarct LGE, compared to those without these markers. There were 456,678 patient-years of all-cause mortality follow-up, with a median follow-up time of 3.6 years. CONCLUSION: The vision of the SCMR Registry is to promote evidence-based utilization of CMR through a collaborative effort by providing a web mechanism for centers to securely upload de-identified data and images for research, education, and quality control. The Registry quantifies changing practice over time and supports large-scale real-world multicenter observational studies of prognostic utility.

Large-scale 3D non-Cartesian coronary MRI reconstruction using distributed memory-efficient physics-guided deep learning with limited training data.

OBJECT: To enable high-quality physics-guided deep learning (PG-DL) reconstruction of large-scale 3D non-Cartesian coronary MRI by overcoming challenges of hardware limitations and limited training data availability. MATERIALS AND METHODS: While PG-DL has emerged as a powerful image reconstruction method, its application to large-scale 3D non-Cartesian MRI is hindered by hardware limitations and limited availability of training data. We combine several recent advances in deep learning and MRI reconstruction to tackle the former challenge, and we further propose a 2.5D reconstruction using 2D convolutional neural networks, which treat 3D volumes as batches of 2D images to train the network with a limited amount of training data. Both 3D and 2.5D variants of the PG-DL networks were compared to conventional methods for high-resolution 3D kooshball coronary MRI. RESULTS: Proposed PG-DL reconstructions of 3D non-Cartesian coronary MRI with 3D and 2.5D processing outperformed all conventional methods both quantitatively and qualitatively in terms of image assessment by an experienced cardiologist. The 2.5D variant further improved vessel sharpness compared to 3D processing, and scored higher in terms of qualitative image quality. DISCUSSION: PG-DL reconstruction of large-scale 3D non-Cartesian MRI without compromising image size or network complexity is achieved, and the proposed 2.5D processing enables high-quality reconstruction with limited training data.

Right Ventricular Function on Cardiovascular Magnetic Resonance Imaging and Long-Term Outcomes in Stable Heart Transplant Recipients.

BACKGROUND: In heart transplant recipients, right ventricular (RV) dysfunction may occur for a variety of reasons. Whether RV dysfunction in the stable phase after heart transplantation is associated with long-term adverse outcomes is unknown. We aimed to determine the long-term prognostic significance of RV dysfunction identified on cardiovascular magnetic resonance imaging (CMR) at least 1 year after heart transplantation. METHODS: In consecutive heart transplant recipients who underwent CMR for surveillance, we assessed 2 CMR measures of RV function: RV ejection fraction and RV global longitudinal strain (RVGLS). We investigated associations between RV dysfunction and a composite end point of death or major adverse cardiac events, including retransplantation, nonfatal myocardial infarction, coronary revascularization, and heart failure hospitalization. RESULTS: A total of 257 heart transplant recipients (median age, 59 years; 75% men) who had CMR at a median of 4.3 years after heart transplantation were included. Over a median follow-up of 4.4 years after the CMR, 108 recipients experienced death or major adverse cardiac events. In a multivariable Cox regression analysis adjusted for age, time since transplantation, indication for transplantation, cardiac allograft vasculopathy, history of rejection, and CMR covariates, RV ejection fraction was not associated with the composite end point, but RVGLS was independently associated with the composite end point with a hazard ratio of 1.08 per 1% worsening in RVGLS ([95% CI, 1.00-1.17]; P=0.046). RVGLS provided incremental prognostic value over other variables in multivariable analyses. The association was replicated in subgroups of recipients with normal RV ejection fraction and recipients with late gadolinium enhancement imaging. A similar association was seen with a composite end point of cardiovascular death or major adverse cardiac events. CONCLUSIONS: CMR feature tracking-derived RVGLS assessed at least 1 year after heart transplantation was independently associated with the long-term risk of death or major adverse cardiac events. Future studies should investigate its role in guiding clinical decision-making in heart transplant recipients.

Nonischemic or Dual Cardiomyopathy in Patients With Coronary Artery Disease.

BACKGROUND: Randomized trials in obstructive coronary artery disease (CAD) have largely shown no prognostic benefit from coronary revascularization. Although there are several potential reasons for the lack of benefit, an underexplored possible reason is the presence of coincidental nonischemic cardiomyopathy (NICM). We investigated the prevalence and prognostic significance of NICM in patients with CAD (CAD-NICM). METHODS: We conducted a registry study of consecutive patients with obstructive CAD on coronary angiography who underwent contrast-enhanced cardiovascular magnetic resonance imaging for the assessment of ventricular function and scar at 4 hospitals from 2004 to 2020. We identified the presence and cause of cardiomyopathy using cardiovascular magnetic resonance imaging and coronary angiography data, blinded to clinical outcomes. The primary outcome was a composite of all-cause death or heart failure hospitalization, and secondary outcomes were all-cause death, heart failure hospitalization, and cardiovascular death. RESULTS: Among 3023 patients (median age, 66 years; 76% men), 18.2% had no cardiomyopathy, 64.8% had ischemic cardiomyopathy (CAD+ICM), 9.3% had CAD+NICM, and 7.7% had dual cardiomyopathy (CAD+dualCM), defined as both ICM and NICM. Thus, 16.9% had CAD+NICM or dualCM. During a median follow-up of 4.8 years (interquartile range, 2.9, 7.6), 1116 patients experienced the primary outcome. In Cox multivariable analysis, CAD+NICM or dualCM was independently associated with a higher risk of the primary outcome compared with CAD+ICM (adjusted hazard ratio, 1.23 [95% CI, 1.06-1.43]; P=0.007) after adjustment for potential confounders. The risks of the secondary outcomes of all-cause death and heart failure hospitalization were also higher with CAD+NICM or dualCM (hazard ratio, 1.21 [95% CI, 1.02-1.43]; P=0.032; and hazard ratio, 1.37 [95% CI, 1.11-1.69]; P=0.003, respectively), whereas the risk of cardiovascular death did not differ from that of CAD+ICM (hazard ratio, 1.15 [95% CI, 0.89-1.48]; P=0.28). CONCLUSIONS: In patients with CAD referred for clinical cardiovascular magnetic resonance imaging, NICM or dualCM was identified in 1 of every 6 patients and was associated with worse long-term outcomes compared with ICM. In patients with obstructive CAD, coincidental NICM or dualCM may contribute to the lack of prognostic benefit from coronary revascularization.

High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI.

Real-time cine cardiac MRI provides an ECG-free free-breathing alternative to clinical gold-standard ECG-gated breath-hold segmented cine MRI for evaluation of heart function. Real-time cine MRI data acquisition during free breathing snapshot imaging enables imaging of patient cohorts that cannot be imaged with segmented or breath-hold acquisitions, but requires rapid imaging to achieve sufficient spatial-temporal resolutions. However, at high acceleration rates, conventional reconstruction techniques suffer from residual aliasing and temporal blurring, including advanced methods such as compressed sensing with radial trajectories. Recently, deep learning (DL) reconstruction has emerged as a powerful tool in MRI. However, its utility for free-breathing real-time cine MRI has been limited, as database-learning of spatio-temporal correlations with varying breathing and cardiac motion patterns across subjects has been challenging. Zero-shot self-supervised physics-guided deep learning (PG-DL) reconstruction has been proposed to overcome such challenges of database training by enabling subject-specific training. In this work, we adapt zero-shot PG-DL for real-time cine MRI with a spatio-temporal regularization. We compare our method to TGRAPPA, locally low-rank (LLR) regularized reconstruction and database-trained PG-DL reconstruction, both for retrospectively and prospectively accelerated datasets. Results on highly accelerated real-time Cartesian cine MRI show that the proposed method outperforms other reconstruction methods, both visibly in terms of noise and aliasing, and quantitatively.

Cardiac magnetic resonance in histologically proven eosinophilic myocarditis.

BACKGROUND: Eosinophilic myocarditis (EM) is a life-threatening acute heart disease. Cardiac magnetic resonance (CMR) excels in the assessment of myocardial diseases but CMR studies of EM are limited. We aimed to describe CMR findings in histologically proven EM. METHODS: Patients with histologically proven EM seen at an academic center from 2000 through 2020 were identified. Of the 28 patients ascertained, 15 had undergone CMR for diagnosis and constitute our study cohort. RESULTS: The patients, aged 51 ± 17 years, presented with fever (53%), dyspnea (47%), chest pain (53%), heart block (20%), and blood eosinophilia (60%). On CMR, all 15 patients had myocardial edema with 10 of them (67%) having abnormally high left ventricular (LV) mass as well. LV ejection fraction measured < 50% in 11 patients (73%) and < 30% in 2 (13%), but only 6 (40%) had dilated LV size. Eight patients (53%) had pericardial effusion. LV late gadolinium enhancement (LGE) was found in all but one patient (13/14; 93%). LGE was always multifocal and subendocardial but could involve any myocardial layer. Patients with necrotizing EM by histopathology (n = 6) had higher LGE mass (32.1 ± 16.6% vs 14.5 ± 7.7%, p = 0.050) and more LV segments with LGE (15 ± 2 vs 9 ± 3 out of 17, p = 0.003) than patients (n = 9) without myocyte necrosis. Two patients had LV thrombosis accompanying widespread subendocardial LGE. CONCLUSIONS: In EM, CMR shows myocardial edema and LGE that is typically subendocardial but can involve any myocardial layer. The left ventricle is often non-dilated with moderate-to-severe systolic dysfunction. Pericardial effusion is common. Necrotizing EM presents with extensive myocardial LGE on CMR.

The primary cardiomyopathy of systemic sclerosis on cardiovascular magnetic resonance imaging.

AIMS: Cardiac disease in systemic sclerosis (SSc) may be primary or secondary to other disease manifestations of SSc. The prevalence of the primary cardiomyopathy of SSc is unknown. Cardiovascular magnetic resonance (CMR) imaging can help accurately determine the presence and cause of cardiomyopathy. We aimed to investigate the prevalence, the CMR features, and the prognostic implications of the primary cardiomyopathy of SSc. METHODS AND RESULTS: We conducted a retrospective cohort study of consecutive patients with SSc who had a clinical CMR for suspected cardiac involvement. We identified the prevalence, the CMR features of the primary cardiomyopathy of SSc, and its association with the long-term incidence of death or major adverse cardiac events (MACEs): heart failure hospitalization, ventricular assist device implantation, heart transplantation, and sustained ventricular tachycardia. Of 130 patients with SSc, 80% were women, and the median age was 58 years. On CMR, 22% had an abnormal left ventricular ejection fraction, and 40% had late gadolinium enhancement (LGE). The prevalence of the primary cardiomyopathy of SSc was 21%. A third of these patients had a distinct LGE phenotype. Over a median follow-up of 3.6 years after the CMR, patients with the primary cardiomyopathy of SSc had a greater incidence of death or MACE (adjusted hazard ratio 2.01; 95% confidence interval 1.03-3.92; P = 0.041). CONCLUSION: The prevalence of the primary cardiomyopathy of SSc was 21%, with a third demonstrating a distinct LGE phenotype. The primary cardiomyopathy of SSc was independently associated with a greater long-term incidence of death or MACE.

Sex-Specific Stress Perfusion Cardiac Magnetic Resonance Imaging in Suspected Ischemic Heart Disease: Insights From SPINS Retrospective Registry.

BACKGROUND: Cardiovascular disease (CVD) remains the leading cause of mortality in women, but current noninvasive cardiac imaging techniques have sex-specific limitations. OBJECTIVES: In this study, the authors sought to investigate the effect of sex on the prognostic utility and downstream invasive revascularization and costs of stress perfusion cardiac magnetic resonance (CMR) for suspected CVD. METHODS: Sex-specific prognostic performance was evaluated in a 2,349-patient multicenter SPINS (Stress CMR Perfusion Imaging in the United States [SPINS] Study) Registry. The primary outcome measure was a composite of cardiovascular death and nonfatal myocardial infarction; secondary outcomes were hospitalization for unstable angina or heart failure, and late unplanned coronary artery bypass grafting. RESULTS: SPINS included 1,104 women (47% of cohort); women had higher prevalence of chest pain (62% vs 50%; P < 0.0001) but lower use of medical therapies. At the 5.4-year median follow-up, women with normal stress CMR had a low annualized rate of primary composite outcome similar to men (0.54%/y vs 0.75%/y, respectively; P = NS). In contrast, women with abnormal CMR were at higher risk for both primary (3.74%/y vs 0.54%/y; P < 0.0001) and secondary (9.8%/y vs 1.6%/y; P < 0.0001) outcomes compared with women with normal CMR. Abnormal stress CMR was an independent predictor for the primary (HR: 2.64 [95% CI: 1.20-5.90]; P = 0.02) and secondary (HR: 2.09 [95% CI: 1.43-3.08]; P < 0.0001) outcome measures. There was no effect modification for sex. Women had lower rates of invasive coronary angiography (3.6% vs 7.3%; P = 0.0001) and downstream costs ($114 vs $171; P = 0.001) at 90 days following CMR. There was no effect of sex on diagnostic image quality. CONCLUSIONS: Stress CMR demonstrated excellent prognostic performance with lower rates of invasive coronary angiography referral in women. Stress CMR should be considered as a first-line noninvasive imaging tool for the evaluation of women. (Stress CMR Perfusion Imaging in the United States [SPINS] Study [SPINS]; NCT03192891).

High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI.

Real-time cine cardiac MRI provides an ECG-free free-breathing alternative to clinical gold-standard ECG-gated breath-hold segmented cine MRI for evaluation of heart function. Real-time cine MRI data acquisition during free breathing snapshot imaging enables imaging of patient cohorts that cannot be imaged with segmented or breath-hold acquisitions, but requires rapid imaging to achieve sufficient spatial-temporal resolutions. However, at high acceleration rates, conventional reconstruction techniques suffer from residual aliasing and temporal blurring, including advanced methods such as compressed sensing with radial trajectories. Recently, deep learning (DL) reconstruction has emerged as a powerful tool in MRI. However, its utility for free-breathing real-time cine MRI has been limited, as database-learning of spatio-temporal correlations with varying breathing and cardiac motion patterns across subjects has been challenging. Zero-shot self-supervised physics-guided deep learning (PG-DL) reconstruction has been proposed to overcome such challenges of database training by enabling subject-specific training. In this work, we adapt zero-shot PG-DL for real-time cine MRI with a spatio-temporal regularization. We compare our method to TGRAPPA, locally low-rank (LLR) regularized reconstruction and database-trained PG-DL reconstruction, both for retrospectively and prospectively accelerated datasets. Results on highly accelerated real-time Cartesian cine MRI show that the proposed method outperforms other reconstruction methods, both visibly in terms of noise and aliasing, and quantitatively.

Cardiac magnetic resonance in giant cell myocarditis: a matched comparison with cardiac sarcoidosis.

AIMS: Giant cell myocarditis (GCM) is an inflammatory cardiomyopathy akin to cardiac sarcoidosis (CS). We decided to study the findings of GCM on cardiac magnetic resonance (CMR) imaging and to compare GCM with CS. METHODS AND RESULTS: CMR studies of 18 GCM patients were analyzed and compared with 18 CS controls matched for age, sex, left ventricular (LV) ejection fraction and presenting cardiac manifestations. The analysts were blinded to clinical data. On admission, the duration of symptoms (median) was 0.2 months in GCM vs. 2.4 months in CS (P = 0.002), cardiac troponin T was elevated (>50 ng/L) in 16/17 patients with GCM and in 2/16 with CS (P < 0.001), their respective median plasma B-type natriuretic propeptides measuring 4488 ng/L and 1223 ng/L (P = 0.011). On CMR imaging, LV diastolic volume was smaller in GCM (177 ± 32 mL vs. 211 ± 58 mL, P = 0.014) without other volumetric or wall thickness measurements differing between the groups. Every GCM patient had multifocal late gadolinium enhancement (LGE) in a distribution indistinguishable from CS both longitudinally, circumferentially, and radially across the LV segments. LGE mass averaged 17.4 ± 6.3% of LV mass in GCM vs 25.0 ± 13.4% in CS (P = 0.037). Involvement of insertion points extending across the septum into the right ventricular wall, the "hook sign" of CS, was present in 53% of GCM and 50% of CS. CONCLUSION: In GCM, CMR findings are qualitatively indistinguishable from CS despite myocardial inflammation being clinically more acute and injurious. When matched for LV dysfunction and presenting features, LV size and LGE mass are smaller in GCM.

Signal intensity informed multi-coil encoding operator for physics-guided deep learning reconstruction of highly accelerated myocardial perfusion CMR.

PURPOSE: To develop a physics-guided deep learning (PG-DL) reconstruction strategy based on a signal intensity informed multi-coil (SIIM) encoding operator for highly-accelerated simultaneous multislice (SMS) myocardial perfusion cardiac MRI (CMR). METHODS: First-pass perfusion CMR acquires highly-accelerated images with dynamically varying signal intensity/SNR following the administration of a gadolinium-based contrast agent. Thus, using PG-DL reconstruction with a conventional multi-coil encoding operator leads to analogous signal intensity variations across different time-frames at the network output, creating difficulties in generalization for varying SNR levels. We propose to use a SIIM encoding operator to capture the signal intensity/SNR variations across time-frames in a reformulated encoding operator. This leads to a more uniform/flat contrast at the output of the PG-DL network, facilitating generalizability across time-frames. PG-DL reconstruction with the proposed SIIM encoding operator is compared to PG-DL with conventional encoding operator, split slice-GRAPPA, locally low-rank (LLR) regularized reconstruction, low-rank plus sparse (L + S) reconstruction, and regularized ROCK-SPIRiT. RESULTS: Results on highly accelerated free-breathing first pass myocardial perfusion CMR at three-fold SMS and four-fold in-plane acceleration show that the proposed method improves upon the reconstruction methods use for comparison. Substantial noise reduction is achieved compared to split slice-GRAPPA, and aliasing artifacts reduction compared to LLR regularized reconstruction, L + S reconstruction and PG-DL with conventional encoding. Furthermore, a qualitative reader study indicated that proposed method outperformed all methods. CONCLUSION: PG-DL reconstruction with the proposed SIIM encoding operator improves generalization across different time-frames /SNRs in highly accelerated perfusion CMR.

Utilization of Cardiovascular Magnetic Resonance Imaging for Resumption of Athletic Activities Following COVID-19 Infection: An Expert Consensus Document on Behalf of the American Heart Association Council on Cardiovascular Radiology and Intervention Leadership and Endorsed by the Society for Cardiovascular Magnetic Resonance.

The global pandemic of COVID-19 caused by infection with SARS-CoV-2 is now entering its fourth year with little evidence of abatement. As of December 2022, the World Health Organization Coronavirus (COVID-19) Dashboard reported 643 million cumulative confirmed cases of COVID-19 worldwide and 98 million in the United States alone as the country with the highest number of cases. Although pneumonia with lung injury has been the manifestation of COVID-19 principally responsible for morbidity and mortality, myocardial inflammation and systolic dysfunction though uncommon are well-recognized features that also associate with adverse prognosis. Given the broad swath of the population infected with COVID-19, the large number of affected professional, collegiate, and amateur athletes raises concern regarding the safe resumption of athletic activity (return to play) following resolution of infection. A variety of different testing combinations that leverage ECG, echocardiography, circulating cardiac biomarkers, and cardiovascular magnetic resonance imaging have been proposed and implemented to mitigate risk. Cardiovascular magnetic resonance in particular affords high sensitivity for myocarditis but has been employed and interpreted nonuniformly in the context of COVID-19 thereby raising uncertainty as to the generalizability and clinical relevance of findings with respect to return to play. This consensus document synthesizes available evidence to contextualize the appropriate utilization of cardiovascular magnetic resonance in the return to play assessment of athletes with prior COVID-19 infection to facilitate informed, evidence-based decisions, while identifying knowledge gaps that merit further investigation.

Utilization of cardiovascular magnetic resonance (CMR) imaging for resumption of athletic activities following COVID-19 infection: an expert consensus document on behalf of the American Heart Association Council on Cardiovascular Radiology and Intervention (CVRI) Leadership and endorsed by the Society for Cardiovascular Magnetic Resonance (SCMR).

The global pandemic of coronavirus disease 2019 (COVID-19) caused by infection with severe acute respiratory suyndrome coronavirus 2 (SARS-CoV-2) is now entering its 4th year with little evidence of abatement. As of December 2022, the World Health Organization Coronavirus (COVID-19) Dashboard reported 643 million cumulative confirmed cases of COVID-19 worldwide and 98 million in the United States alone as the country with the highest number of cases. While pneumonia with lung injury has been the manifestation of COVID-19 principally responsible for morbidity and mortality, myocardial inflammation and systolic dysfunction though uncommon are well-recognized features that also associate with adverse prognosis. Given the broad swath of the population infected with COVID-19, the large number of affected professional, collegiate, and amateur athletes raises concern regarding the safe resumption of athletic activity (return to play, RTP) following resolution of infection. A variety of different testing combinations that leverage the electrocardiogram, echocardiography, circulating cardiac biomarkers, and cardiovascular magnetic resonance (CMR) imaging have been proposed and implemented to mitigate risk. CMR in particular affords high sensitivity for myocarditis but has been employed and interpreted non-uniformly in the context of COVID-19 thereby raising uncertainty as to the generalizability and clinical relevance of findings with respect to RTP. This consensus document synthesizes available evidence to contextualize the appropriate utilization of CMR in the RTP assessment of athletes with prior COVID-19 infection to facilitate informed, evidence-based decisions, while identifying knowledge gaps that merit further investigation.

Acute Myocarditis Associated With Desmosomal Gene Variants.

BACKGROUND: The risk of adverse cardiovascular events in patients with acute myocarditis (AM) and desmosomal gene variants (DGV) remains unknown. OBJECTIVES: The purpose of this study was to ascertain the risk of death, ventricular arrhythmias, recurrent myocarditis, and heart failure (main endpoint) in patients with AM and pathogenic or likely pathogenetic DGV. METHODS: In a retrospective international study from 23 hospitals, 97 patients were included: 36 with AM and DGV (DGV[+]), 25 with AM and negative gene testing (DGV[-]), and 36 with AM without genetics testing. All patients had troponin elevation plus findings consistent with AM on histology or at cardiac magnetic resonance (CMR). In 86 patients, CMR changes in function and structure were re-assessed at follow-up. RESULTS: In the DGV(+) AM group (88.9% DSP variants), median age was 24 years, 91.7% presented with chest pain, and median left ventricular ejection fraction (LVEF) was 56% on CMR (P = NS vs the other 2 groups). Kaplan-Meier curves demonstrated a higher risk of the main endpoint in DGV(+) AM compared with DGV(-) and without genetics testing patients (62.3% vs 17.5% vs 5.3% at 5 years, respectively; P < 0.0001), driven by myocarditis recurrence and ventricular arrhythmias. At follow-up CMR, a higher number of late gadolinium enhanced segments was found in DGV(+) AM. CONCLUSIONS: Patients with AM and evidence of DGV have a higher incidence of adverse cardiovascular events compared with patients with AM without DGV. Further prospective studies are needed to ascertain if genetic testing might improve risk stratification of patients with AM who are considered at low risk.