Improved Robustness for Deep Learning-based Segmentation of Multi-Center Myocardial Perfusion MRI Datasets Using Data Adaptive Uncertainty-guided Space-time Analysis.

BACKGROUND: Fully automatic analysis of myocardial perfusion MRI datasets enables rapid and objective reporting of stress/rest studies in patients with suspected ischemic heart disease. Developing deep learning techniques that can analyze multi-center datasets despite limited training data and variations in software (pulse sequence) and hardware (scanner vendor) is an ongoing challenge. METHODS: Datasets from 3 medical centers acquired at 3T (n = 150 subjects; 21,150 first-pass images) were included: an internal dataset (inD; n = 95) and two external datasets (exDs; n = 55) used for evaluating the robustness of the trained deep neural network (DNN) models against differences in pulse sequence (exD-1) and scanner vendor (exD-2). A subset of inD (n = 85) was used for training/validation of a pool of DNNs for segmentation, all using the same spatiotemporal U-Net architecture and hyperparameters but with different parameter initializations. We employed a space-time sliding-patch analysis approach that automatically yields a pixel-wise "uncertainty map" as a byproduct of the segmentation process. In our approach, dubbed Data Adaptive Uncertainty-Guided Space-time (DAUGS) analysis, a given test case is segmented by all members of the DNN pool and the resulting uncertainty maps are leveraged to automatically select the "best" one among the pool of solutions. For comparison, we also trained a DNN using the established approach with the same settings (hyperparameters, data augmentation, etc.). RESULTS: The proposed DAUGS analysis approach performed similarly to the established approach on the internal dataset (Dice score for the testing subset of inD: 0.896 ± 0.050 vs. 0.890 ± 0.049; p = n.s.) whereas it significantly outperformed on the external datasets (Dice for exD-1: 0.885 ± 0.040 vs. 0.849 ± 0.065, p < 0.005; Dice for exD-2: 0.811 ± 0.070 vs. 0.728 ± 0.149, p < 0.005). Moreover, the number of image series with "failed" segmentation (defined as having myocardial contours that include bloodpool or are noncontiguous in ≥1 segment) was significantly lower for the proposed vs. the established approach (4.3% vs. 17.1%, p < 0.0005). CONCLUSIONS: The proposed DAUGS analysis approach has the potential to improve the robustness of deep learning methods for segmentation of multi-center stress perfusion datasets with variations in the choice of pulse sequence, site location or scanner vendor.

Improved Robustness for Deep Learning-based Segmentation of Multi-Center Myocardial Perfusion MRI Datasets Using Data Adaptive Uncertainty-guided Space-time Analysis.

Background: Fully automatic analysis of myocardial perfusion MRI datasets enables rapid and objective reporting of stress/rest studies in patients with suspected ischemic heart disease. Developing deep learning techniques that can analyze multi-center datasets despite limited training data and variations in software (pulse sequence) and hardware (scanner vendor) is an ongoing challenge. Methods: Datasets from 3 medical centers acquired at 3T (n = 150 subjects; 21,150 first-pass images) were included: an internal dataset (inD; n = 95) and two external datasets (exDs; n = 55) used for evaluating the robustness of the trained deep neural network (DNN) models against differences in pulse sequence (exD-1) and scanner vendor (exD-2). A subset of inD (n = 85) was used for training/validation of a pool of DNNs for segmentation, all using the same spatiotemporal U-Net architecture and hyperparameters but with different parameter initializations. We employed a space-time sliding-patch analysis approach that automatically yields a pixel-wise "uncertainty map" as a byproduct of the segmentation process. In our approach, dubbed Data Adaptive Uncertainty-Guided Space-time (DAUGS) analysis, a given test case is segmented by all members of the DNN pool and the resulting uncertainty maps are leveraged to automatically select the "best" one among the pool of solutions. For comparison, we also trained a DNN using the established approach with the same settings (hyperparameters, data augmentation, etc.). Results: The proposed DAUGS analysis approach performed similarly to the established approach on the internal dataset (Dice score for the testing subset of inD: 0.896 ± 0.050 vs. 0.890 ± 0.049; p = n.s.) whereas it significantly outperformed on the external datasets (Dice for exD-1: 0.885 ± 0.040 vs. 0.849 ± 0.065, p < 0.005; Dice for exD-2: 0.811 ± 0.070 vs. 0.728 ± 0.149, p < 0.005). Moreover, the number of image series with "failed" segmentation (defined as having myocardial contours that include bloodpool or are noncontiguous in ≥1 segment) was significantly lower for the proposed vs. the established approach (4.3% vs. 17.1%, p < 0.0005). Conclusions: The proposed DAUGS analysis approach has the potential to improve the robustness of deep learning methods for segmentation of multi-center stress perfusion datasets with variations in the choice of pulse sequence, site location or scanner vendor.

Does Disopyramide Still Have a Place in the Management of Obstructive Hypertrophic Cardiomyopathy?

Hypertrophic cardiomyopathy (HCM) is a relatively common inherited cardiac disorder associated with a left ventricular hypertrophy that cannot be explained by another cardiac or systemic disorder. One of the core pathophysiology features is left ventricular outflow tract obstruction (obstructive HCM [oHCM]), and this pathology could lead to complications, including sudden cardiac death and heart failure. Current treatment strategies for symptomatic oHCM consist of historical pharmacologic agents that are often based on nonrandomized, limited data or expert opinion. This article presents a critical appraisal of disopyramide, one of the pharmacologic options available in Canada for managing oHCM. The author concludes that robust clinical evidence supporting the use of disopyramide in treating oHCM is lacking, and that disopyramide should be reserved as a last resort for nonresponders to pharmacologic treatment and for those in whom invasive therapies are not indicated.

La cardiomyopathie hypertrophique (CMH) est une maladie cardiaque congénitale relativement fréquente associée à une hypertrophie ventriculaire gauche qui ne peut s'expliquer par un autre trouble cardiaque ou général. L'une des principales caractéristiques physiopathologiques est l'obstruction à l'éjection du ventricule gauche (CMH obstructive [CMHo]), une pathologie qui peut entraîner certaines complications, comme la mort subite d'origine cardiaque et l'insuffisance cardiaque. Les stratégies thérapeutiques actuelles pour prendre en charge la CMHo symptomatique utilisent des agents pharmacologiques classiques et reposent sur des données limitées, recueillies dans le cadre d'études sans répartition aléatoire, ou sur l'avis de spécialistes. Cet article fournit une évaluation critique du disopyramide, l'une des options pharmacologiques offertes au Canada pour prendre en charge la CMHo. Les auteurs concluent que faute de données cliniques robustes à l'appui de l'utilisation du disopyramide dans le traitement de la CMHo, cette option devrait être utilisée en dernier recours chez les patients qui ne répondent pas au traitement pharmacologique ou chez qui les traitements invasifs ne sont pas indiqués.

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.

Canadian Cardiovascular Society Clinical Practice Update on Contemporary Management of the Patient With Hypertrophic Cardiomyopathy.

Numerous guidelines on the diagnosis and management of hypertrophic cardiomyopathy (HCM) have been published, by learned societies, over the past decade. Although helpful they are often long and less adapted to nonexperts. This writing panel was challenged to produce a document that grew as much from years of practical experience as it did from the peer-reviewed literature. As such, rather than produce yet another set of guidelines, we aim herein to deliver a concentrate of our own experiential learning and distill for the reader the essence of effective and appropriate HCM care. This Clinical Practice Update on HCM is therefore aimed at general cardiologists and other cardiovascular practitioners rather than for HCM specialists. We set the stage with a description of the condition and its clinical presentation, discuss the central importance of "obstruction" and how to look for it, review the role of cardiac magnetic resonance imaging, reflect on the appropriate use of genetic testing, review the treatment options for symptomatic HCM-crucially including cardiac myosin inhibitors, and deal concisely with practical issues surrounding risk assessment for sudden cardiac death, and management of the end-stage HCM patient. Uniquely, we have captured the pediatric experience on our panel to discuss appropriate differences in the management of younger patients with HCM. We ask the reader to remember that this document represents expert consensus opinion rather than dogma and to use their best judgement when dealing with the HCM patient in front of them.

Cardiac Magnetic Resonance Evaluation of LV Remodeling Post-Myocardial Infarction: Prognosis, Monitoring and Trial Endpoints.

Adverse left ventricular remodeling (ALVR) and subsequent heart failure after myocardial infarction (MI) remain a major cause of patient morbidity and mortality worldwide. Overt inflammation has been identified as the common pathway underlying myocardial fibrosis and development of ALVR post-MI. With its ability to simultaneously provide information about cardiac structure, function, perfusion, and tissue characteristics, cardiac magnetic resonance (CMR) is well poised to inform prognosis and guide early surveillance and therapeutics in high-risk cohorts. Further, established and evolving CMR-derived biomarkers may serve as clinical endpoints in prospective trials evaluating the efficacy of novel anti-inflammatory and antifibrotic therapies. This review provides an overview of post-MI ALVR and illustrates how CMR may help clinical adoption of novel therapies via mechanistic or prognostic imaging markers.

Effect of six month's treatment with omega-3 acid ethyl esters on long-term outcomes after acute myocardial infarction: The OMEGA-REMODEL randomized clinical trial.

BACKGROUND: Omega-3 polyunsaturated fatty acids (O3-FA) have been shown to reduce inflammation and adverse cardiac remodeling after acute myocardial infarction (AMI). However, the impact of O3-FA on long-term clinical outcomes remains uncertain. AIMS: To investigate the impact of O3-FA on adverse cardiac events in long-term follow up post AMI in a pilot-study. METHODS: Consecutive patients with AMI were randomized 1:1 to receive 6 months of O3-FA (4 g/daily) or placebo in the prospective, multicenter OMEGA-REMODEL trial. Primary endpoint was a composite of major adverse cardiovascular events (MACE) encompassing all-cause death, heart failure hospitalizations, recurrent acute coronary syndrome, and late coronary artery bypass graft (CABG). RESULTS: A total of 358 patients (62.8% male; 48.1 ± 16.1 years) were followed for a median of 6.6 (IQR: 5.0-9.1) years. Among those receiving O3-FA (n = 180), MACE occurred in 65 (36.1%) compared to 62 (34.8%) of 178 assigned to placebo. By intention-to-treat analysis, O3-FA treatment assignment did not reduce MACE (HR = 1.014; 95%CI = 0.716-1.436; p = 0.938), or its individual components. However, patients with a positive response to O3-FA treatment (n = 43), defined as an increase in the red blood cell omega-3 index (O3I) ≥5% after 6 months of treatment, had lower annualized MACE rates compared to those without (2.9% (95%CI = 1.2-5.1) vs 7.1% (95%CI = 5.7-8.9); p = 0.001). This treatment benefit persisted after adjustment for baseline characteristics (HRadjusted = 0.460; 95%CI = 0.218-0.970; p = 0.041). CONCLUSION: In long-term follow-up of the OMEGA-REMODEL randomized trial, O3-FA did not reduce MACE after AMI by intention to treat principle, however, patients who achieved a ≥ 5% increase of O3I subsequent to treatment had favorable outcomes.

Cardiac magnetic resonance biomarkers as surrogate endpoints in cardiovascular trials for myocardial diseases.

Cardiac magnetic resonance offers multiple facets in the diagnosis, risk stratification, and management of patients with myocardial diseases. Particularly, its feature to precisely monitor disease activity lends itself to quantify response to novel therapeutics. This review critically appraises the value of cardiac magnetic resonance imaging biomarkers as surrogate endpoints for prospective clinical trials. The primary focus is to comprehensively outline the value of established cardiac magnetic resonance parameters in myocardial diseases. These include heart failure, cardiac amyloidosis, iron overload cardiomyopathy, hypertrophic cardiomyopathy, cardio-oncology, and inflammatory cardiomyopathies like myocarditis and sarcoidosis.

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

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

Thymoma-Associated Myasthenia Gravis With Myocarditis.

Myasthenia gravis (MG) complicated by myocarditis is a rare autoimmune manifestation. We present a patient who initially presented with a suspected ST-segment elevation myocardial infarction (STEMI) with angiographically normal coronary arteries. A chest CT scan revealed a large homogenous soft-tissue density anterior mediastinal mass suspicious of thymoma. Neurological deterioration in the hospital suggested a diagnosis of MG with subsequent electromyography and nerve conduction studies (EMG/NCS) and repetitive nerve stimulation (RNS) confirmation. A cardiac magnetic resonance imaging study (CMR) demonstrated diffuse myocardial edema and severe left ventricular (LV) dysfunction and sub-epicardial late gadolinium enhancement (LGE) involving all basal and mid-LV segments in addition to apical inferior and lateral segments. A diagnosis of thymoma-associated MG with myocarditis was made and the patient was successfully treated with immunosuppression. This case highlights the association of myocarditis with MG as a potential complication that should be considered in patients with cardiac symptoms, ECG changes, or biomarker elevation.

Patients with non-ischemic cardiomyopathy and mid-wall striae have similar arrhythmic outcomes as ischemic cardiomyopathy.

PURPOSE: While implantable cardioverter-defibrillator (ICD) therapy provides clear benefit in patients with ischemic cardiomyopathy (ICM), this is less clear in patients with non-ischemic cardiomyopathy (NICM). Mid-wall striae (MWS) fibrosis is an established cardiovascular magnetic resonance (CMR) risk marker observed in patients with NICM. We evaluated whether patients with NICM and MWS have similar risk of arrhythmia-related cardiovascular events as patients with ICM. METHODS: We studied a cohort of patients undergoing CMR. The presence of MWS was adjudicated by experienced physicians. The primary outcome was a composite of implantable cardioverter-defibrillator (ICD) implant, hospitalization for ventricular tachycardia, resuscitated cardiac arrest, or sudden cardiac death. Propensity-matched analysis was performed to compare outcomes for patients NICM with MWS and ICM. RESULTS: A total of 1,732 patients were studied, 972 NICM (706 without MWS, 266 with MWS) and 760 ICM. NICM patients with MWS were more likely to experience the primary outcome versus those without MWS (unadjusted subdistribution hazard ratio (subHR) 2.26, 95% confidence interval [CI] 1.51-3.41) with no difference versus ICM patients (unadjusted subHR 1.32, 95% CI 0.93-1.86). Similar results were seen in a propensity-matched population (adjusted subHR 1.11, 95% CI 0.63-1.98, p = 0.711). CONCLUSION: Patients with NICM and MWS demonstrate significantly higher arrhythmic risk compared to NICM without MWS. After adjustment, the arrhythmia risk of patients with NICM and MWS was similar to patients with ICM. Accordingly, physicians could consider the presence of MWS when making clinical decisions regarding arrhythmia risk management in patients with NICM.

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).

3-Dimensional Strain Analysis of Hypertrophic Cardiomyopathy: Insights From the NHLBI International HCM Registry.

BACKGROUND: Abnormal global longitudinal strain (GLS) has been independently associated with adverse cardiac outcomes in both obstructive and nonobstructive hypertrophic cardiomyopathy. OBJECTIVES: The goal of this study was to understand predictors of abnormal GLS from baseline data from the National Heart, Lung, and Blood Institute (NHLBI) Hypertrophic Cardiomyopathy Registry (HCMR). METHODS: The study evaluated comprehensive 3-dimensional left ventricular myocardial strain from cine cardiac magnetic resonance in 2,311 patients from HCMR using in-house validated feature-tracking software. These data were correlated with other imaging markers, serum biomarkers, and demographic variables. RESULTS: Abnormal median GLS (> -11.0%) was associated with higher left ventricular (LV) mass index (93.8 ± 29.2 g/m2 vs 75.1 ± 19.7 g/m2; P < 0.0001) and maximal wall thickness (21.7 ± 5.2 mm vs 19.3 ± 4.1 mm; P < 0.0001), lower left (62% ± 9% vs 66% ± 7%; P < 0.0001) and right (68% ± 11% vs 69% ± 10%; P < 0.01) ventricular ejection fractions, lower left atrial emptying functions (P < 0.0001 for all), and higher presence and myocardial extent of late gadolinium enhancement (6 SD and visual quantification; P < 0.0001 for both). Elastic net regression showed that adjusted predictors of GLS included female sex, Black race, history of syncope, presence of systolic anterior motion of the mitral valve, reverse curvature and apical morphologies, LV ejection fraction, LV mass index, and both presence/extent of late gadolinium enhancement and baseline N-terminal pro-B-type natriuretic peptide and troponin levels. CONCLUSIONS: Abnormal strain in hypertrophic cardiomyopathy is associated with other imaging and serum biomarkers of increased risk. Further follow-up of the HCMR cohort is needed to understand the independent relationship between LV strain and adverse cardiac outcomes in hypertrophic cardiomyopathy.

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

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

Stress Perfusion Cardiac Magnetic Resonance Imaging With a 3.0-Tesla Scanner for Myocardial Viability in a Patient With a Conditional Pacemaker.

Cardiac magnetic resonance (CMR) imaging provides images with high spatial and temporal resolution, with high diagnostic and prognostic performance. An abundance of data indicate the safety and efficacy of noncardiac magnetic resonance imaging at both 1.5 Tesla (T) and 3T in patients with cardiac implantable electronic devices (CIEDs). Safety and efficacy have also been evaluated for stress perfusion (SP)-CMR for pateints with CIEDs, using 1.5T scanners, but no previous reports have been made of SP-CMR using 3T scanners. Herein, we report a case of a patient with a CIED who successfully and safely underwent SP-CMR imaging using a 3T scanner.

L'imagerie par résonance magnétique cardiaque (IRMC) procure des images à haute résolution spatiale et temporelle en plus d'offrir une capacité diagnostique et pronostique élevée, mais une multitude de données mettent en lumière l'innocuité et l'efficacité de l'imagerie non cardiaque réalisée au moyen d'appareils d'IRM produisant un champ magnétique de 1,5 ou de 3 teslas (T) chez des patients porteurs d'un dispositif cardiaque électronique implantable (DCEI). L'innocuité et l'efficacité de l'évaluation de la perfusion à l'effort (EPE) par IRMC ont aussi été évaluées chez des patients porteurs d'un DCEI au moyen d'appareils produisant un champ magnétique de 1,5 T, mais pas au moyen d'appareils produisant un champ magnétique de 3 T. Nous rapportons ici le cas d'un patient porteur d'un DCEI ayant subi avec succès et en toute sécurité une EPE par IRMC réalisée au moyen d'un appareil produisant un champ magnétique de 3 T.

Mid-wall striae fibrosis predicts heart failure admission, composite heart failure events, and life-threatening arrhythmias in dilated cardiomyopathy.

Heart failure (HF) admission is a dominant contributor to morbidity and healthcare costs in dilated cardiomyopathy (DCM). Mid-wall striae (MWS) fibrosis by late gadolinium enhancement (LGE) imaging has been associated with elevated arrhythmia risk. However, its capacity to predict HF-specific outcomes is poorly defined. We investigated its role to predict HF admission and relevant secondary outcomes in a large cohort of DCM patients. 719 patients referred for LGE MRI assessment of DCM were enrolled and followed for clinical events. Standardized image analyses and interpretations were conducted inclusive of coding the presence and patterns of fibrosis observed by LGE imaging. The primary clinical outcome was hospital admission for decompensated HF. Secondary heart failure and arrhythmic composite endpoints were also studied. Median age was 57 (IQR 47-65) years and median LVEF 40% (IQR 29-47%). Any fibrosis was observed in 228 patients (32%) with MWS fibrosis pattern present in 178 (25%). At a median follow up of 1044 days, 104 (15%) patients experienced the primary outcome, and 127 (18%) the secondary outcome. MWS was associated with a 2.14-fold risk of the primary outcome, 2.15-fold risk of the secondary HF outcome, and 2.23-fold risk of the secondary arrhythmic outcome. Multivariable analysis adjusting for all relevant covariates, inclusive of LVEF, showed patients with MWS fibrosis to experience a 1.65-fold increased risk (95% CI 1.11-2.47) of HF admission and 1-year event rate of 12% versus 7% without this phenotypic marker. Similar findings were observed for the secondary outcomes. Patients with LVEF > 35% plus MWS fibrosis experienced similar event rates to those with LVEF ≤ 35%. MWS fibrosis is a powerful and independent predictor of clinical outcomes in patients with DCM, identifying patients with LVEF > 35% who experience similar event rates to those with LVEF below this conventionally employed high-risk phenotype threshold.

The Future of Cardiac Magnetic Resonance Clinical Trials.

Over the past 2 decades, cardiac magnetic resonance (CMR) has become an essential component of cardiovascular clinical care and contributed to imaging-guided diagnosis and management of coronary artery disease, cardiomyopathy, congenital heart disease, cardio-oncology, valvular, and vascular disease, amongst others. The widespread availability, safety, and capability of CMR to provide corresponding anatomical, physiological, and functional data in 1 imaging session can improve the design and conduct of clinical trials through both a reduction of sample size and provision of important mechanistic data that may augment clinical trial findings. Moreover, prospective imaging-guided strategies using CMR can enhance safety, efficacy, and cost-effectiveness of cardiovascular pathways in clinical practice around the world. As the future of large-scale clinical trial design evolves to integrate personalized medicine, cost-effectiveness, and mechanistic insights of novel therapies, the integration of CMR will continue to play a critical role. In this document, the attributes, limitations, and challenges of CMR's integration into the future design and conduct of clinical trials will also be covered, and recommendations for trialists will be explored. Several prominent examples of clinical trials that test the efficacy of CMR-imaging guided pathways will also be discussed.

Prognostic Value of Stress Cardiac Magnetic Resonance in Patients With Known Coronary Artery Disease.

OBJECTIVES: This study sought to determine whether stress cardiac magnetic resonance (CMR) provides clinically relevant risk reclassification in patients with known coronary artery disease (CAD) in a multicenter setting in the United States. BACKGROUND: Despite improvements in medical therapy and coronary revascularization, patients with previous CAD account for a disproportionately large portion of CV events and pose a challenge for noninvasive stress testing. METHODS: From the Stress Perfusion Imaging in the United States (SPINS) registry, we identified consecutive patients with documented CAD who were referred to stress CMR for evaluation of myocardial ischemia. The primary outcome was nonfatal myocardial infarction (MI) or cardiovascular (CV) death. Major adverse CV events (MACE) included MI/CV death, hospitalization for heart failure or unstable angina, and late unplanned coronary artery bypass graft. The prognostic association and net reclassification improvement by ischemia for MI/CV death were determined. RESULTS: Out of 755 patients (age 64 ± 11 years, 64% male), we observed 97 MI/CV deaths and 210 MACE over a median follow-up of 5.3 years. Presence of ischemia demonstrated a significant association with MI/CV death (HR: 2.30; 95% CI: 1.54-3.44; P < 0.001) and MACE (HR: 2.24 ([95% CI: 1.69-2.95; P < 0.001). In a multivariate model adjusted for CV risk factors, ischemia maintained strong association with MI/CV death (HR: 1.84; 95% CI: 1.17-2.88; P = 0.008) and MACE (HR: 1.77; 95% CI: 1.31-2.40; P < 0.001) and reclassified 95% of patients at intermediate pretest risk (62% to low risk, 33% to high risk) with corresponding changes in the observed event rates of 1.4% and 5.3% per year for low and high post-test risk, respectively. CONCLUSIONS: In a multicenter cohort of patients with known CAD, CMR-assessed ischemia was strongly associated with MI/CV death and reclassified patient risk beyond CV risk factors, especially in those considered to be at intermediate risk. Absence of ischemia was associated with a <2% annual rate of MI/CV death. (Stress CMR Perfusion Imaging in the United States [SPINS] Study; NCT03192891).

Stress Cardiac Magnetic Resonance Myocardial Perfusion Imaging: JACC Review Topic of the Week.

Stress cardiovascular magnetic resonance imaging (CMR) is a cost-effective, noninvasive test that accurately assesses myocardial ischemia, myocardial viability, and cardiac function without the need for ionizing radiation. There is a large body of literature, including randomized controlled trials, validating its diagnostic performance, risk stratification capabilities, and ability to guide appropriate use of coronary intervention. Specifically, stress CMR has shown higher diagnostic sensitivity than single-photon emission computed tomography imaging in detecting angiographically significant coronary artery disease. Stress CMR is particularly valuable for the evaluation of patients with moderate to high pretest probability of having stable ischemic heart disease and for patients known to have challenging imaging characteristics, including women, individuals with prior revascularization, and those with left ventricular dysfunction. This paper reviews the basics principles of stress CMR, the data supporting its clinical use, the added-value of myocardial blood flow quantification, and the assessment of myocardial function and viability routinely obtained during a stress CMR study.