AI-based Fully-Automated Stress Left Ventricular Ejection Fraction as a Prognostic Marker in Patients Undergoing Stress-CMR.

AIM: To determine in patients undergoing stress CMR whether fully automated stress artificial intelligence (AI)-based left ventricular ejection fraction (LVEFAI) can provide incremental prognostic value to predict death above traditional prognosticators. MATERIEL AND RESULTS: Between 2016 and 2018, we conducted a longitudinal study that included all consecutive patients referred for vasodilator stress CMR. LVEFAI was assessed using AI-algorithm combines multiple deep learning networks for LV segmentation. The primary outcome was all-cause death assessed using the French National Registry of Death. Cox regression was used to evaluate the association of stress LVEFAI with death after adjustment for traditional risk factors and CMR findings.In 9,712 patients (66±15 years, 67% men), there was an excellent correlation between stress LVEFAI and LVEF measured by expert (LVEFexpert) (r=0.94, p<0.001). Stress LVEFAI was associated with death (median [IQR] follow-up 4.5 [3.7-5.2] years) before and after adjustment for risk factors (adjusted hazard ratio [HR], 0.84 [95% CI, 0.82-0.87] per 5% increment, p<0.001). Stress LVEFAI had similar significant association with death occurrence compared with LVEFexpert. After adjustment, stress LVEFAI value showed the greatest improvement in model discrimination and reclassification over and above traditional risk factors and stress CMR findings (C-statistic improvement: 0.11; NRI=0.250; IDI=0.049, all p<0.001; LR-test p<0.001), with an incremental prognostic value over LVEFAI determined at rest. CONCLUSION: AI-based fully automated LVEF measured at stress is independently associated with the occurrence of death in patients undergoing stress CMR, with an additional prognostic value above traditional risk factors, inducible ischemia and LGE.

Clinical impact of novel CMR technology on patients with congenital heart disease. A scientific statement of the Association for European Pediatric and Congenital Cardiology (AEPC) and the European Association of Cardiovascular Imaging (EACVI) of the ESC.

Cardiovascular magnetic resonance (CMR) imaging is recommended in patients with congenital heart disease (CHD) in clinical practice guidelines as the imaging standard for a large variety of diseases. As CMR is evolving, novel techniques are becoming available. Some of them are already used clinically, whereas others still need further evaluation. In this statement the authors give an overview of relevant new CMR techniques for the assessment of CHD. Studies with reference values for these new techniques are listed in the supplement.

The Association of Epicardial Adipose Tissue Volume and Atrial Fibrillation in Patients With Hypertrophic Cardiomyopathy: As Assessed by Cardiac MR.

BACKGROUND: Epicardial adipose tissue (EAT) is a metabolically active visceral fat linked to cardiovascular disease. Prior studies demonstrated the predictive value of EAT volume (EATV) in atrial fibrillation (AF) among hypertrophic obstructive cardiomyopathy patients. PURPOSE: To investigate the association between EATV and AF in hypertrophic cardiomyopathy (HCM). STUDY TYPE: Retrospective. POPULATION: Two hundred and twenty-four HCM patients (including 79 patients with AF and 145 patients without AF, 154 men) and 80 healthy controls (54 men). FIELD STRENGTH/SEQUENCE: 3.0 T scanner; balanced steady-state free precession (SSFP) cine sequence, gradient echo. ASSESSMENT: EAT thickness was assessed in the 4-chamber and basal short-axis planes. EAT volume was calculated by outlining the epicardial border and visceral pericardium layer on short-axis cine images. STATISTICAL TESTS: Shapiro-Wilk test, Student's t test or the Mann-Whitney U test, chi-square test or Fisher's exact test, Multivariate linear regression analyses, Multivariable binary logistic regression analysis. Intraclass correlation coefficient. Significance was determined at P < 0.05. RESULTS: EATV and EAT volume index (EATVI) were significantly greater in HCM patients with AF than those without AF (126.6 ± 25.9 mL vs. 90.5 ± 24.5 mL, and 73.0 ± 15.9 mL/m2 vs. 51.3 ± 13.4 mL/m2). EATVI was associated with AF in multivariable linear regression analysis among HCM patients (ß = 0.62). Multivariable logistic regression analysis revealed that compared to other indicators, the area under curve (AUC) of EATVI was 0.86 (cut-off, 53.9 mL/m2, 95% CI, 0.80-0.89), provided a better performance, with the sensitivity of 96.2% and specificity of 58.6%. The combined model exhibited superior association with AF presence compared to the clinical model (AUC 0.96 vs. 0.76) and the imaging model (AUC 0.96 vs. 0.93). DATA CONCLUSION: EATVI was associated with AF. EATVI was significantly correlated with incident AF, and provided a better performance in HCM patients compared to other indicators. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Left ventricular reverse remodeling and reduction of interstitial fibrosis in patients with severe aortic stenosis who underwent transcatheter aortic valve implantation.

BACKGROUND: Left ventricular (LV) structural and functional changes have been reported in patients with aortic stenosis (AS) who have undergone transcatheter aortic valve implantation (TAVI); however, the relationship between change in LV structure and systolic function and tissue characteristics assessed via cardiovascular magnetic resonance imaging (CMRI) post-TAVI has been not fully elucidated. This study aimed to investigate this relationship in patients with severe AS who underwent TAVI and CMRI. METHODS: In this retrospective study, 65 patients who underwent TAVI and CMRI at the 6-month follow-up were analyzed. The relationship between percent changes in LV end-diastolic volume (LVEDV), LV end-systolic volume (LVESV), LV ejection fraction (LVEF), and LV mass (LVM) (⊿LVEDV, ⊿LVESV, ⊿LVEF, and ⊿LVM) and those in the native T1 value (⊿native T1) was analyzed using a correlation analysis. Moreover, extracellular volume fraction (ECV) value changes were analyzed. RESULTS: The ⊿native T1 significantly decreased from 1292.8 (1269.9-1318.4) ms at pre-TAVI to 1282.3 (1262.6-1310.2) ms at the 6-month follow-up (P = 0.022). A significant positive correlation between ⊿LVEDV, ⊿LVESV, and ⊿LVM and ⊿native T1 (r = 0.351, P = 0.004; r = 0.339, P = 0.006; r = 0.261, P = 0.035, respectively) and a tendency toward a negative correlation between ⊿LVEF and ⊿native T1 (r = -0.237, P = 0.058) were observed. The ECV value increased significantly from 26.7 % (25.3-28.3) to 28.2 % (25.7-30.5) (P = 0.002). CONCLUSIONS: The decrease in native T1 might be associated with LV reverse remodeling. Evaluating structural and functional changes using CMRI may be useful for patient management.

Prognostic value of cardiovascular magnetic resonance in immune checkpoint inhibitor-associated myocarditis: A systematic review and meta-analysis.

Background: Immune checkpoint inhibitors (ICI) are increasingly used in the first-line treatment of malignant tumors. There is increasing recognition of their cardiotoxicity and, in particular, their potential to lead to myocarditis. Cardiovascular magnetic resonance (CMR) can quantify pathological changes, such as myocardial edema and fibrosis. The purpose of this systematic review and meta-analysis was to examine the evidence for the roles of CMR in predicting prognosis in ICI-associated myocarditis. Methods: PubMed, Cochrane Library, and Web of Science databases were searched until October 2023 for published works investigating the relationship between CMR parameters and adverse events in patients with ICI-associated myocarditis. The analysis included studies reporting the incidence of late gadolinium enhancement (LGE), T1 values, T2 values, and CMR-derived left ventricular ejection fraction (LVEF). Odds ratios (OR) and weighted mean differences (WMD) were combined for binary and continuous data, respectively. Newcastle-Ottawa Scale was used to assess the methodological quality of the included studies. Results: Five cohort studies were included (average age 65-68 years; 25.4% female). Of these, four studies were included in the meta-analysis of LGE-related findings. Patients with major adverse cardiovascular events (MACE) had a higher incidence of LGE compared with patients without MACE (OR = 4.18, 95% CI: 1.72-10.19, p = 0.002). A meta-analysis, incorporating data from two studies, showed that patients who developed MACE exhibited significantly higher T1 value (WMD = 36.16 ms, 95% CI: 21.43-50.89, p < 0.001) and lower LVEF (WMD = - 8.00%, 95% CI: -13.60 to -2.40, p = 0.005). Notably, T2 value (WMD = -0.23 ms, 95% CI: -1.86 to -1.39, p = 0.779) was not associated with MACE in patients with ICI-related myocarditis. Conclusions: LGE, T1 value, and LVEF measured by CMR imaging have potential prognostic value for long-term adverse events in patients with ICI-related myocarditis.

Prognostic value of myocardial deformation parameters for outcome prediction in tetralogy of Fallot.

INTRODUCTION: The prognostic value of myocardial deformation parameters in adults with repaired tetralogy of Fallot (rTOF) has not been well-elucidated. We therefore aimed to explore myocardial deformation parameters for outcome prediction in adults with rTOF using cardiovascular magnetic resonance imaging (CMR). METHODS: Adults with rTOF and at least moderate pulmonary regurgitation (PR) were identified from an institutional prospective CMR registry. Left (LV) and right ventricular (RV) global strain were recorded in longitudinal (GLS), circumferential (GCS) and radial (GRS) directions. Major adverse cardiovascular events (MACE) were defined as a composite of mortality, resuscitated sudden death, sustained ventricular tachycardia (>30seconds) or heart failure (hospital admission >24hours). In patients with pulmonary valve replacement (PVR), pre-and post-PVR CMR studies were analysed to assess for predictors of complete RV reverse remodelling, which we defined as RV end-diastolic volume indexed (RVEDVi) <110ml/m2. Logistic regression models were used to estimate the odds ratio (OR) per unit change in absolute strain value associated with clinical outcomes and receiver operator characteristic (ROC) curves were constructed with area under the curve (AUC) for select CMR variables. RESULTS: We included 307 patients (age 35±13 years, 59% male). During 6.1 years (3.3-8.8) of follow-up, pulmonary valve replacement (PVR) was performed in 142 (46%) and MACE occurred in 31 (10%). On univariate analysis, baseline biventricular ejection fraction (EF), mass and all strain parameters were associated with MACE. After adjustment for LVEF, only LVGLS remained independently predictive of MACE (OR 0.822 [0.693-0.976] p=0.025). Receiver operator curves identified an absolute LVGLS value less than 15 and LVEF <51% as thresholds for MACE prediction (AUC 0.759 [0.655-0.840] and 0.720 [0.608-0.810]). After adjusting for baseline RVEDVi, RVGCS (OR 1.323 [1.094-1.600] p=0.004), LVGCS (OR 1.276 [1.029-1.582] p=0.027) and LVGRS (OR 1.101 [1.0210-1.200], p=0.028) were independent predictors of complete remodelling post-PVR remodelling. CONCLUSIONS: Biventricular strain parameters predict clinical outcomes and post-PVR remodelling in rTOF. Further study will be necessary to establish the role of myocardial deformation parameters in clinical practice.

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

OBJECTIVES: To summarize the status of the SCMR Registry at 150,000 exams. BACKGROUND: Cardiovascular magnetic resonance (CMR) is increasingly utilized to evaluate expanding cardiovascular conditions. The 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 (DICOM) images. METHODS: The processes for data security, data submission, and research access are outlined. We interrogated the Registry and present 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). The human subjects had an average age of 58 years (range 1 month to >90 years old), were 44% female, 72% Caucasian, and had a mortality rate of 8%. The most common indication was cardiomyopathy (27%), and most frequently used current procedural terminology (CPT) code was 75561 (35%). Macrocyclic gadolinium-based contrast agents represented 89% of contrast utilization after 2015. Short-axis cines were performed in 99% of scans, short-axis LGE in 66%, and stress perfusion sequences in 30%. Mortality data demonstrated increased mortality in patients with left ventricular ejection fraction (LVEF) < 35%, the presence of wall motion abnormalities, stress perfusion defects, and infarct late gadolinium enhancement (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. CONCLUSIONS: 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. CONDENSED ABSTRACT: The SCMR Registry is a central regulatory-compliant cloud-based repository for real-world clinical data and DICOM images for multicenter cardiovascular research, including outcomes-based data. The Registry contains 299,622,066 DICOM images and 456,678 patient-years follow-up. Data compiled from 154,458 CMR scans across 20 US sites demonstrated cardiomyopathy as the most common indication and 89% macrocyclic gadolinium contrast utilization after 2015. There was an overall mortality rate of 8%, with higher rates in those with LVEF<35%, abnormal wall motion, ischemia presence, or infarct LGE. The Registry aims to promote evidence-based CMR utilization through a collaborative effort to positively impact cardiovascular outcomes.

Global longitudinal strain by cardiac magnetic resonance is associated with cardiac iron and complications in beta-thalassemia major patients.

BACKGROUND: The aim of this cross-sectional study was to investigate the association of left ventricular (LV) strain parameters with demographics, clinical data, cardiovascular magnetic resonance (CMR) findings, and cardiac complications (heart failure and arrhythmias) in patients with ß-thalassemia major (ß-TM). METHOD: We considered 266 ß-TM patients (134 females, 37.08 ±â€¯11.60 years) consecutively enrolled in the Extension-Myocardial Iron Overload in Thalassemia (E-MIOT) project and 80 healthy controls (50 females, mean age 39.77 ±â€¯11.29 years). The CMR protocol included cine images for the assessment of global longitudinal strain (GLS), global circumferential strain (GCS), and global radial strain (GRS) using feature tracking (FT) and for the quantification of LV function parameters, the T2* technique for the assessment of myocardial iron overload, and late gadolinium enhancement (LGE) technique. RESULTS: In comparison to the healthy control group, ß-TM patients showed impaired GLS, GCS, and GRS values. Among ß-TM patients, sex was identified as the sole independent determinant of all LV strain parameters. All LV strain parameters displayed a significant correlation with LV end-diastolic volume index, end-systolic volume index, mass index, and ejection fraction, and with the number of segments exhibiting LGE. Only GLS exhibited a significant correlation with global heart T2* values and the number of segments with T2* < 20 ms. Patients with cardiac complications exhibited significantly impaired GLS compared to those without cardiac complications. CONCLUSION: In patients with ß-TM, GLS, GCS, and GRS were impaired in comparison with control subjects. Among LV strain parameters, only GLS demonstrated a significant association with cardiac iron levels and complications.

Multi-organ imaging-derived polygenic indexes for brain and body health.

The UK Biobank (UKB) imaging project is a crucial resource for biomedical research, but is limited to 100,000 participants due to cost and accessibility barriers. Here we used genetic data to predict heritable imaging-derived phenotypes (IDPs) for a larger cohort. We developed and evaluated 4,375 IDP genetic scores (IGS) derived from UKB brain and body images. When applied to UKB participants who were not imaged, IGS revealed links to numerous phenotypes and stratified participants at increased risk for both brain and somatic diseases. For example, IGS identified individuals at higher risk for Alzheimer's disease and multiple sclerosis, offering additional insights beyond traditional polygenic risk scores of these diseases. When applied to independent external cohorts, IGS also stratified those at high disease risk in the All of Us Research Program and the Alzheimer's Disease Neuroimaging Initiative study. Our results demonstrate that, while the UKB imaging cohort is largely healthy and may not be the most enriched for disease risk management, it holds immense potential for stratifying the risk of various brain and body diseases in broader external genetic cohorts.

Time Course of Left Ventricular Strain Assessment via Cardiovascular Magnetic Resonance Myocardial Feature Tracking in Takotsubo Syndrome.

Background: Although takotsubo syndrome (TTS) is characterized by transient systolic dysfunction of the left ventricle (LV), the time course and mechanism of LV function recovery remain elusive. The aim of this study is to evaluate cardiac functional recovery in TTS via serial cardiac magnetic resonance feature tracking (CMR-FT). Methods: In this Japanese multicenter registry, patients with newly diagnosed TTS were prospectively enrolled. In patients who underwent serial cardiovascular magnetic resonance (CMR) imaging at 1 month and 1 year after the onset, CMR-FT was performed to determine the global circumferential strain (GCS), global radial strain (GRS) and global longitudinal strain (GLS). We compared LV ejection fraction, GCS, GRS and GLS at 1 month and 1 year after the onset of TTS. Results: Eighteen patients underwent CMR imaging in one month and one year after the onset in the present study. LV ejection fraction had already normalized at 1 month after the onset, with no significant difference between 1 month and 1 year (55.8 ± 9.2% vs. 58.9 ± 7.3%, p = 0.09). CMR-FT demonstrated significant improvement in GCS from 1 month to 1 year (-16.7 ± 3.4% vs. -18.5 ± 3.2%, p < 0.01), while there was no significant difference in GRS and GLS between 1 month and year (GRS: 59.6 ± 24.2% vs. 59.4 ± 17.3%, p = 0.95, GLS: -12.8 ± 5.9% vs. -13.8 ± 4.9%, p = 0.42). Conclusions: Serial CMR-FT analysis revealed delayed improvement of GCS compared to GRS and GLS despite of rapid recovery of LV ejection fraction. CMR-FT can detect subtle impairment of LV systolic function during the recovery process in patients with TTS.

Prevalence of Abnormal Cardiovascular Magnetic Resonance Findings in Athletes Recovered from COVID-19 Infection: A Systematic Review and Meta-Analysis.

Background: Competitive sports and high-level athletic training result in a constellation of changes in the myocardium that comprise the 'athlete's heart'. With the spread of the COVID-19 pandemic, there have been concerns whether elite athletes would be at higher risk of myocardial involvement after infection with the virus. This systematic review and meta-analysis evaluated the prevalence of abnormal cardiovascular magnetic resonance (CMR) findings in elite athletes recovered from COVID-19 infection. Methods: The PubMed, Cochrane and Web of Science databases were systematically search from inception to 15 November 2023. The primary endpoint was the prevalence of abnormal cardiovascular magnetic resonance findings, including the pathological presence of late gadolinium enhancement (LGE), abnormal T1 and T2 values and pericardial enhancement, in athletes who had recovered from COVID-19 infection. Results: Out of 3890 records, 18 studies with a total of 4446 athletes were included in the meta-analysis. The pooled prevalence of pathological LGE in athletes recovered from COVID-19 was 2.0% (95% CI 0.9% to 4.4%, I2 90%). The prevalence of elevated T1 and T2 values was 1.2% (95% CI 0.4% to 3.6%, I2 87%) and 1.2% (95% CI 0.4% to 3.7%, I2 89%), respectively, and the pooled prevalence of pericardial involvement post COVID-19 infection was 1.1% (95% CI 0.5% to 2.5%, I2 85%). The prevalence of all abnormal CMR findings was much higher among those who had a clinical indication of CMR. Conclusions: Among athletes who have recently recovered from COVID-19 infection, there is a low prevalence of abnormal CMR findings. However, the prevalence is much higher among athletes with symptoms and/or abnormal initial cardiac screening. Further studies and longer follow up are needed to evaluate the clinical relevance of these findings and to ascertain if they are associated with adverse events.

Development and Validation of a Mortality Risk Score for Repaired Tetralogy of Fallot.

BACKGROUND: Robust risk assessment is crucial for the growing repaired tetralogy of Fallot population at risk of major adverse clinical outcomes; however, current tools are hindered by lack of validation. This study aims to develop and validate a risk prediction model for death in the repaired tetralogy of Fallot population. METHODS AND RESULTS: Patients with repaired tetralogy of Fallot enrolled in the INDICATOR (International Multicenter Tetralogy of Fallot Registry) cohort with clinical, arrhythmia, cardiac magnetic resonance, and outcome data were included. Patients from London, Amsterdam, and Boston sites were placed in the development cohort; patients from the Toronto site were used for external validation. Multivariable Cox regression was used to evaluate factors associated with time from cardiac magnetic resonance until the primary outcome: all-cause death. Of 1552 eligible patients (n=1221 in development, n=331 in validation; median age at cardiac magnetic resonance 23.4 [interquartile range, 15.6-35.6] years; median follow up 9.5 years), 102 (6.6%) experienced the primary outcome. The multivariable Cox model performed similarly during development (concordance index, 0.83 [95% CI, 0.78-0.88]) and external validation (concordance index, 0.80 [95% CI, 0.71-0.90]) and identified older age at cardiac magnetic resonance, obesity, type of tetralogy of Fallot repair, higher right ventricular end-systolic volume index, and lower biventricular global function index as independent predictors of death. A risk-scoring algorithm dividing patients into low-risk (score ≤4) versus high-risk (score >4) groups was validated to effectively discriminate risk of death (15-year survival of 95% versus 74%, respectively; P<0.001). CONCLUSIONS: This externally validated mortality risk prediction algorithm can help identify vulnerable patients with repaired tetralogy of Fallot who may benefit from targeted interventions.

Improving the efficiency and accuracy of CMR with AI - review of evidence and proposition of a roadmap to clinical translation.

Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment of heart disease; however, limitations of CMR include long exam times and high complexity compared to other cardiac imaging modalities. Recently advancements in artificial intelligence (AI) technology have shown great potential to address many CMR limitations. While the developments are remarkable, translation of AI-based methods into real-world CMR clinical practice remains at a nascent stage and much work lies ahead to realize the full potential of AI for CMR. Herein we review recent cutting-edge and representative examples demonstrating how AI can advance CMR in areas such as exam planning, accelerated image reconstruction, post-processing, quality control, classification and diagnosis. These advances can be applied to speed up and simplify essentially every application including cine, strain, late gadolinium enhancement, parametric mapping, 3D whole heart, flow, perfusion and others. AI is a unique technology based on training models using data. Beyond reviewing the literature, this paper discusses important AI-specific issues in the context of CMR, including (1) properties and characteristics of datasets for training and validation, (2) previously published guidelines for reporting CMR AI research, (3) considerations around clinical deployment, (4) responsibilities of clinicians and the need for multi-disciplinary teams in the development and deployment of AI in CMR, (5) industry considerations, and (6) regulatory perspectives. Understanding and consideration of all these factors will contribute to the effective and ethical deployment of AI to improve clinical CMR.

Coronary artery wall contrast enhancement imaging impact on disease activity assessment in IgG4-RD: a direct marker of coronary involvement.

BACKGROUND: Coronary artery wall contrast enhancement (CE) has been applied to non-invasive visualization of changes to the coronary artery wall in systemic lupus erythematosus (SLE). This study investigated the feasibility of quantifying CE to detect coronary involvement in IgG4-related disease (IgG4-RD), as well as the influence on disease activity assessment. METHODS: A total of 93 subjects (31 IgG4-RD; 29 SLE; 33 controls) were recruited in the study. Coronary artery wall imaging was performed in a 3.0 T MRI scanner. Serological markers and IgG4-RD Responder Index (IgG4-RD-RI) scores were collected for correlation analysis. RESULTS: Coronary wall CE was observed in 29 (94 %) IgG4-RD patients and 22 (76 %) SLE patients. Contrast-to-noise ratio (CNR) and total CE area were significantly higher in patient groups compared to controls (CNR: 6.1 ± 2.7 [IgG4-RD] v. 4.2 ± 2.3 [SLE] v. 1.9 ± 1.5 [control], P < 0.001; Total CE area: 3.0 [3.0-6.6] v. 1.7 [1.5-2.6] v. 0.3 [0.3-0.9], P < 0.001). In the IgG4-RD group, CNR and total CE area were correlated with the RI (CNR: r = 0.55, P = 0.002; total CE area: r = 0.39, P = 0.031). RI´ scored considering coronary involvement by CE, differed significantly from RI scored without consideration of CE (RI v. RI´: 15 ± 6 v. 16 ± 6, P < 0.001). CONCLUSIONS: Visualization and quantification of CMR coronary CE by CNR and total CE area could be utilized to detect subclinical and clinical coronary wall involvement, which is prevalent in IgG4-RD. The potential inclusion of small and medium-sized vessel involvements in the assessment of disease activity in IgG4-RD is worthy of further investigation.

Myocardial Transit Time Mapping by CMR: A Novel Indicator of Microcirculatory Dysfunction in Cardiac Amyloidosis.

Cardiac amyloidosis (CA) is characterized by the deposition of amyloid fibrils within the myocardium, resulting in a restrictive physiology. Although microvascular dysfunction is a common feature, it is difficult to assess. This study aimed to explore myocardial transit time (MyoTT) by cardiovascular magnetic resonance (CMR) as a potential novel parameter of microcirculatory dysfunction in CA. This prospective study enrolled 20 CA patients and 20 control subjects. CMR acquisition included cine imaging, pre- and post-contrast T1 mapping, and MyoTT assessment, which was calculated from the time delay in contrast agent arrival between the aortic root and coronary sinus (CS). Compared to the control group, patients with CA exhibited significantly reduced left ventricular (LV) ejection fraction and myocardial strain, an increase in LV global peak wall thickness (LVGPWT), extracellular volume fraction (ECV), and prolonged MyoTT (14.4 ± 3.8 s vs. 7.7 ± 1.5 s, p < 0.001). Moreover, patients at Mayo stage III had a significantly longer MyoTT compared to those at stage I/II. MyoTT showed a positive correlation with the ECV, LVGPWT, and LV global longitudinal strain (LV-GLS) (p < 0.05). The area under the curve (AUC) for MyoTT was 0.962, demonstrating diagnostic performance comparable to that of the ECV (AUC 0.995) and LV-GLS (AUC 0.950) in identifying CA. MyoTT is significantly prolonged in patients with CA, correlating with fibrosis markers, remodeling, and dysfunction. As a novel parameter of coronary microvascular dysfunction (CMD), MyoTT has the potential to be an integral biomarker in multiparametric CMR assessment of CA.

Complete Transposition of the Great Arteries in the Pediatric Field: A Multimodality Imaging Approach.

The complete transposition of the great arteries (C-TGA) is a congenital cardiac anomaly characterized by the reversal of the main arteries. Early detection and precise management are crucial for optimal outcomes. This review emphasizes the integral role of multimodal imaging, including fetal echocardiography, transthoracic echocardiography (TTE), cardiovascular magnetic resonance (CMR), and cardiac computed tomography (CCT) in the diagnosis, treatment planning, and long-term follow-up of C-TGA. Fetal echocardiography plays a pivotal role in prenatal detection, enabling early intervention strategies. Despite technological advances, the detection rate varies, highlighting the need for improved screening protocols. TTE remains the cornerstone for initial diagnosis, surgical preparation, and postoperative evaluation, providing essential information on cardiac anatomy, ventricular function, and the presence of associated defects. CMR and CCT offer additional value in C-TGA assessment. CMR, free from ionizing radiation, provides detailed anatomical and functional insights from fetal life into adulthood, becoming increasingly important in evaluating complex cardiac structures and post-surgical outcomes. CCT, with its high-resolution imaging, is indispensable in delineating coronary anatomy and vascular structures, particularly when CMR is contraindicated or inconclusive. This review advocates for a comprehensive imaging approach, integrating TTE, CMR, and CCT to enhance diagnostic accuracy, guide therapeutic interventions, and monitor postoperative conditions in C-TGA patients. Such a multimodal strategy is vital for advancing patient care and improving long-term prognoses in this complex congenital heart disease.

Diagnostic efficacy of complexity metrics from cardiac MRI myocardial segmental motion curves in detecting late gadolinium enhancement in myocardial infarction patients.

Background: Myocardial segmental motion is associated with cardiovascular pathology, often assessed through myocardial strain features. The stability of the motion can be influenced by myocardial fibrosis. This research aimed to explore the complexity metrics (CM) of myocardial segmental motion curves, observe their correlation with late gadolinium enhancement (LGE) transmural extension (TE), and assess diagnostic efficacy combined with segmental strains in different TE segments. Methods: We included 42 myocardial infarction patients, dividing images into 672 myocardial segments (208 remote, 384 viable, and 80 unviable segments based on TE). Radial and circumferential segmental strain, along with CM for motion curves, were extracted. Correlation between CM and LGE, as well as the potential distinguishing role of CM, was evaluated using Pearson correlation, univariate linear regression (F-test), multivariate regression analysis (T-test), area under curve (AUC), machine learning models, and DeLong test. Results: All CMs showed significant linear correlation with TE (P < 0.001). Six CMs were correlated with TE (r > 0.3), with radial frequency drift (FD) displayed the strongest correlation (r = 0.496, P < 0.001). Radial and circumferential FD significantly differed in higher TE myocardium than in remote segments (P < 0.05). Radial FD had practical diagnostic efficacy (remote vs. unviable AUC = 0.89, viable vs. unviable AUC = 0.77, remote vs. viable AUC = 0.65). Combining CM with segmental strain features boosted diagnostic efficacy than models using only segmental strain features (DeLong test, P < 0.05). Conclusions: The CM of myocardial motion curves has been associated with LGE infarction, and combining CM with strain features improves the diagnosis of different myocardial LGE infarction degrees.

The role of artificial intelligence in cardiovascular magnetic resonance imaging.

Cardiovascular magnetic resonance (CMR) imaging is the gold standard test for myocardial tissue characterization and chamber volumetric and functional evaluation. However, manual CMR analysis can be time-consuming and is subject to intra- and inter-observer variability. Artificial intelligence (AI) is a field that permits automated task performance through the identification of high-level and complex data relationships. In this review, we review the rapidly growing role of AI in CMR, including image acquisition, sequence prescription, artifact detection, reconstruction, segmentation, and data reporting and analysis including quantification of volumes, function, myocardial infarction (MI) and scar detection, and prediction of outcomes. We conclude with a discussion of the emerging challenges to widespread adoption and solutions that will allow for successful, broader uptake of this powerful technology.

Noninvasive Pressure-Volume Loops Predict Major Adverse Cardiac Events in Heart Failure With Reduced Ejection Fraction.

Background: Heart failure with reduced ejection fraction (HFrEF) is characterized by ventricular remodeling and impaired myocardial energetics. Left ventricular pressure-volume (PV) loop analysis can be performed noninvasively using cardiovascular magnetic resonance (CMR) imaging to assess cardiac thermodynamic efficiency. Objectives: The aim of the study was to investigate whether noninvasive PV loop parameters, derived from CMR, could predict major adverse cardiac events (MACE) in HFrEF patients. Methods: PV loop parameters (stroke work, ventricular efficiency, external power, contractility, and energy per ejected volume) were computed from CMR cine images and brachial blood pressure. The primary end point was MACE (cardiovascular death, heart failure (HF) hospitalization, myocardial infarction, revascularization, ventricular tachycardia/fibrillation, heart transplantation, or left ventricular assist device implantation within 5 years). Associations between PV loop parameters and MACE were evaluated using multivariable Cox regression. Results: One hundred and sixty-four HFrEF patients (left ventricular ejection fraction ≤40%, age 63 [IQR: 55-70] years, 79% male) who underwent clinical CMR examination between 2004 and 2014 were included. Eighty-eight patients (54%) experienced at least one MACE after an average of 2.8 years. Unadjusted models demonstrated a significant association between MACE and all PV loop parameters (P < 0.05 for all), HF etiology (P < 0.001), left ventricular ejection fraction (P = 0.003), global longitudinal strain (P < 0.001), and N-terminal prohormone of brain natriuretic peptide level (P = 0.001). In the multivariable Cox regression analysis adjusted for age, sex, hypertension, diabetes, and HF etiology, ventricular efficiency was associated with MACE (HR: 1.04 (95% CI: 1.01-1.08) per-% decrease, P = 0.01). Conclusions: Ventricular efficiency, derived from noninvasive PV loop analysis from standard CMR scans, is associated with MACE in patients with HFrEF.