Deformation-encoding Deep Learning Transformer for High-Frame-Rate Cardiac Cine MRI.

Purpose To develop a deep learning model for increasing cardiac cine frame rate while maintaining spatial resolution and scan time. Materials and Methods A transformer-based model was trained and tested on a retrospective sample of cine images from 5840 patients (mean age, 55 years ± 19 [SD]; 3527 male patients) referred for clinical cardiac MRI from 2003 to 2021 at nine centers; images were acquired using 1.5- and 3-T scanners from three vendors. Data from three centers were used for training and testing (4:1 ratio). The remaining data were used for external testing. Cines with downsampled frame rates were restored using linear, bicubic, and model-based interpolation. The root mean square error between interpolated and original cine images was modeled using ordinary least squares regression. In a prospective study of 49 participants referred for clinical cardiac MRI (mean age, 56 years ± 13; 25 male participants) and 12 healthy participants (mean age, 51 years ± 16; eight male participants), the model was applied to cines acquired at 25 frames per second (fps), thereby doubling the frame rate, and these interpolated cines were compared with actual 50-fps cines. The preference of two readers based on perceived temporal smoothness and image quality was evaluated using a noninferiority margin of 10%. Results The model generated artifact-free interpolated images. Ordinary least squares regression analysis accounting for vendor and field strength showed lower error (P < .001) with model-based interpolation compared with linear and bicubic interpolation in internal and external test sets. The highest proportion of reader choices was "no preference" (84 of 122) between actual and interpolated 50-fps cines. The 90% CI for the difference between reader proportions favoring collected (15 of 122) and interpolated (23 of 122) high-frame-rate cines was -0.01 to 0.14, indicating noninferiority. Conclusion A transformer-based deep learning model increased cardiac cine frame rates while preserving both spatial resolution and scan time, resulting in images with quality comparable to that of images obtained at actual high frame rates. Keywords: Functional MRI, Heart, Cardiac, Deep Learning, High Frame Rate Supplemental material is available for this article. © RSNA, 2024.

Magnetic Resonance Imaging Characterization and Clinical Outcomes of Dilated and Arrhythmogenic Left Ventricular Cardiomyopathies.

BACKGROUND: Nondilated left ventricular cardiomyopathy (NDLVC) has been recently differentiated from dilated cardiomyopathy (DCM). A comprehensive characterization of these 2 entities using cardiac magnetic resonance (CMR) and genetic testing has never been performed. OBJECTIVES: This study sought to provide a thorough characterization and assess clinical outcomes in a large multicenter cohort of patients with DCM and NDLVC. METHODS: A total of 462 patients with DCM (227) or NDLVC (235) with CMR data from 4 different referral centers were retrospectively analyzed. The study endpoint was a composite of sudden cardiac death or major ventricular arrhythmias. RESULTS: In comparison to DCM, NDLVC had a higher prevalence of pathogenic or likely pathogenic variants of arrhythmogenic genes (40% vs 23%; P < 0.001), higher left ventricular (LV) systolic function (LV ejection fraction: 51% ± 12% vs 36% ± 15%; P < 0.001) and higher prevalence of free-wall late gadolinium enhancement (LGE) (27% vs 14%; P < 0.001). Conversely, DCM showed higher prevalence of pathogenic or likely pathogenic variants of nonarrhythmogenic genes (23% vs 12%; P = 0.002) and septal LGE (45% vs 32%; P = 0.004). Over a median follow-up of 81 months (Q1-Q3: 40-132 months), the study outcome occurred in 98 (21%) patients. LGE with septal location (HR: 1.929; 95% CI: 1.033-3.601; P = 0.039) was independently associated with the risk of sudden cardiac death or major ventricular arrhythmias together with LV dilatation, older age, advanced NYHA functional class, frequent ventricular ectopic activity, and nonsustained ventricular tachycardia. CONCLUSIONS: In a multicenter cohort of patients with DCM and NDLVC, septal LGE together with LV dilatation, age, advanced disease, and frequent and repetitive ventricular arrhythmias were powerful predictors of major arrhythmic events.

Cardiovascular involvement in children with COVID-19 temporally related multisystem inflammatory syndrome (MIS-C): can cardiac magnetic resonance arrive to the heart of the problem?

BACKGROUND: Multisystem inflammatory syndrome in children (MIS-C) shows a significant overlap of symptoms with other hyper-inflammatory diseases such as Kawasaki disease (KD), but the real difference of the two conditions is still matter of debate. Coronary artery lesions (CAL) are the most relevant complication in KD. Nonetheless, CAL, myocarditis, pericarditis, arrhythmia are the main cardiovascular complications in MIS-C. A close clinical assessment is mandatory, both at the diagnosis and during the follow-up, by ECG and echocardiography. Cardiac magnetic resonance (MRI) adds important data to ultrasound findings. However, cardiac MRI studies in MIS-C are limited to a small number of cohorts. METHODS: We enrolled 20 children (age:1-16 years; 11 F; 9 M) with cardiac involvement secondary to MIS-C, all evaluated by cardiac MRI. RESULTS: 8 children showed pathological cardiac MRI: 2 showed pericardial effusion; 2 showed myocardial oedema; 1 showed aortic insufficiency; 3 showed delayed enhancement (one for acute myocarditis with oedema; 2 for myocardial fibrosis). Delayed enhancement was reduced significantly 5.6-9 months after the first MRI evaluation. 25% of patients with pathological MRI had CAL associated with valvular insufficiency of 2 valves. 17% of patients with normal MRI had CAL, associated with valvular insufficiency of 1 valve in 1 patient. The correlations between haematological, clinical, cardiologic parameters, treatment, did not reach the statistical significance. 4 patients were treated with anakinra. Among those, 2 patients showed a normal cardiac MRI. Cardiac lesions resolved in all the patients during the follow-up. Some patients with pathological cardiac MRI could not underwent a control with MRI, for the low compliance. However, echocardiography and ECG, documented the resolution of the pathological data in these cases. CONCLUSIONS: A higher risk of CAL was documented in patients with an association of other cardiac lesions. Cardiac MRI is difficult to perform routinely; however, it is useful for evaluating the acute myocardial damage and the outcome of patients with MIS-C.

Training deep learning based dynamic MR image reconstruction using open-source natural videos.

To develop and assess a deep learning (DL) pipeline to learn dynamic MR image reconstruction from publicly available natural videos (Inter4K). Learning was performed for a range of DL architectures (VarNet, 3D UNet, FastDVDNet) and corresponding sampling patterns (Cartesian, radial, spiral) either from true multi-coil cardiac MR data (N = 692) or from synthetic MR data simulated from Inter4K natural videos (N = 588). Real-time undersampled dynamic MR images were reconstructed using DL networks trained with cardiac data and natural videos, and compressed sensing (CS). Differences were assessed in simulations (N = 104 datasets) in terms of MSE, PSNR, and SSIM and prospectively for cardiac cine (short axis, four chambers, N = 20) and speech cine (N = 10) data in terms of subjective image quality ranking, SNR and Edge sharpness. Friedman Chi Square tests with post-hoc Nemenyi analysis were performed to assess statistical significance. In simulated data, DL networks trained with cardiac data outperformed DL networks trained with natural videos, both of which outperformed CS (p < 0.05). However, in prospective experiments DL reconstructions using both training datasets were ranked similarly (and higher than CS) and presented no statistical differences in SNR and Edge Sharpness for most conditions.The developed pipeline enabled learning dynamic MR reconstruction from natural videos preserving DL reconstruction advantages such as high quality fast and ultra-fast reconstructions while overcoming some limitations (data scarcity or sharing). The natural video dataset, code and pre-trained networks are made readily available on github.

Incremental value of myocardial global longitudinal strain in predicting major adverse cardiac events among patients with hypertrophic cardiomyopathy.

OBJECTIVES: Endocardial global longitudinal strain (endo-GLS) measured with echocardiography (echo) has been demonstrated to be associated with myocardial fibrosis (MF) and is a prognostic predictor in patients with hypertrophic cardiomyopathy (HCM). Late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging showed that MF is primarily located in the myocardial layer of the extremely hypertrophic septal or ventricular wall. We hypothesized that GLS of the myocardial layer (myo-GLS) is more strongly correlated with the extent of LGE (%LGE) and is a more powerful prognostic factor than endo-GLS. METHODS: A total of 177 inpatients (54.0 [IQR: 43.0, 64.0] years, female 37.3%) with HCM were retrospectively included from May 2019 to April 2021. Among them, 162 patients underwent echocardiographic examination and contrast-enhanced CMR within 7 days. Myo-GLS and %LGE were blindly assessed in a core laboratory. All the patients were followed after they were discharged. RESULTS: During a mean follow-up of 33.77 [IQR 30.05, 35.40] months, 14 participants (7.91%) experienced major adverse cardiac events (MACE). The MACE (+) group showed lower absolute endo-GLS and myo-GLS than the MACE (-) group. Myo-GLS was more associated with %LGE (r = -.68, P < .001) than endo-GLS (r = -.64, P < .001). Cox multivariable analysis indicated that absolute myo-GLS was independently associated with MACE (adjusted hazard ratio = .75, P < .05). Myo-GLS was better than endo-GLS at detecting MACE (+) patients (-8.64%, AUC .939 vs. - 16.375%, AUC .898, P < .05). CONCLUSIONS: Myo-GLS is a stronger predictor of MACE than endo-GLS in patients with HCM and is highly correlated with %LGE.

Cardiovascular magnetic resonance parametric techniques to characterize myocardial effects of anthracycline therapy in adults with normal left ventricular ejection fraction: a systematic review and meta-analysis.

BACKGROUND: The cardiotoxic effects of anthracyclines therapy are well recognized, both in the short and long term. Echocardiography allows monitoring of cancer patients treated with this class of drugs by serial assessment of left ventricle ejection fraction (LVEF) as a surrogate of systolic function. However, changes in myocardial function may occur late in the process when cardiac damage is already established. Novel cardiac magnetic resonance (CMR) parametric techniques, like native T1 mapping and extra-cellular volume (ECV), may detect subclinical myocardial damage in these patients, recognizing early signs of cardiotoxicity before development of overt cancer therapy-related cardiac dysfunction (CTRCD) and prompting tailored therapeutic and follow-up strategies to improve outcome. METHODS AND RESULTS: We conducted a systematic review and a meta-analysis to investigate the difference in CMR derived native T1 relaxation time and ECV values, respectively, in anthracyclines-treated cancer patients with preserved EF versus healthy controls. PubMed, Embase, Web of Science and Cochrane Central were searched for relevant studies. A total of 6 studies were retrieved from 1057 publications, of which, four studies with 547 patients were included in the systematic review on T1 mapping and five studies with 481 patients were included in the meta-analysis on ECV. Three out of the four included studies in the systematic review showed higher T1 mapping values in anthracyclines treated patients compared to healthy controls. The meta-analysis demonstrated no statistically significant difference in ECV values between the two groups in the main analysis (Hedges´s g =3.20, 95% CI -0.72-7.12, p =0.11, I2 =99%), while ECV was significantly higher in the anthracyclines-treated group when sensitivity analysis was performed. CONCLUSIONS: Higher T1 mapping and ECV values in patients exposed to anthracyclines could represent early biomarkers of CTRCD, able to detect subclinical myocardial changes present before the development of overt myocardial dysfunction. Our results highlight the need for further studies to investigate the correlation between anthracyclines-based chemotherapy and changes in CMR mapping parameters that may guide future tailored follow-up strategies in this group of patients.

Arrhythmogenic right ventricular cardiomyopathy: Unveiling clinical presentations, CMR insights and prognosis in a single-center retrospective study.

Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) is a hereditary condition with a prevalence ranging from 1 in 2000 to 1 in 5000 individuals. ARVC is a significant contributor to sudden cardiac death, particularly in young individuals and athletes, and remains challenging to diagnose definitively. We conducted a single-center retrospective study to evaluate the presentations, electrocardiogram findings, and imaging characteristics of ARVC patients evaluated at our center between 2021 and 2023. Notably, our study is the second investigation of ARVC conducted in Pakistan. We report divergent symptom prevalence as compared to the current literature and have incorporated the Task Force Criteria. Despite limited access to cardiac magnetic resonance (CMR) facilities worldwide, our findings underscore the critical role ofCMR in ARVC diagnosis. Our cohort had a mortality rate of 17 % highlighting the importance of early detection and the need for improved diagnostic facilities for ARVC in the region.

Screening and diagnosis of cardiovascular disease using artificial intelligence-enabled cardiac magnetic resonance imaging.

Cardiac magnetic resonance imaging (CMR) is the gold standard for cardiac function assessment and plays a crucial role in diagnosing cardiovascular disease (CVD). However, its widespread application has been limited by the heavy resource burden of CMR interpretation. Here, to address this challenge, we developed and validated computerized CMR interpretation for screening and diagnosis of 11 types of CVD in 9,719 patients. We propose a two-stage paradigm consisting of noninvasive cine-based CVD screening followed by cine and late gadolinium enhancement-based diagnosis. The screening and diagnostic models achieved high performance (area under the curve of 0.988 ± 0.3% and 0.991 ± 0.0%, respectively) in both internal and external datasets. Furthermore, the diagnostic model outperformed cardiologists in diagnosing pulmonary arterial hypertension, demonstrating the ability of artificial intelligence-enabled CMR to detect previously unidentified CMR features. This proof-of-concept study holds the potential to substantially advance the efficiency and scalability of CMR interpretation, thereby improving CVD screening and diagnosis.

CMR provides comparable measurements of diastolic function as echocardiography.

Clinical application of cardiac magnetic resonance (CMR) is expanding but CMR assessment of LV diastolic function is still being validated. The purpose of this study was to validate assessments of left ventricular (LV) diastolic dysfunction (DD) using CMR by comparing with transthoracic echocardiography (TTE) performed on the same day. Patients with suspected or diagnosed cardiomyopathy (n = 63) and healthy volunteers (n = 24) were prospectively recruited and included in the study. CMR diastolic parameters were measured on cine images and velocity-encoded phase contrast cine images and compared with corresponding parameters measured on TTE. A contextual correlation feature tracking method was developed to calculate the mitral annular velocity curve. LV DD was classified by CMR and TTE following 2016 guidelines. Overall DD classification was 78.1% concordant between CMR and TTE (p < 0.0001). The trans-mitral inflow parameters correlated well between the two modalities (E, r = 0.78; A, r = 0.90; E/A, r = 0.82; all p < 0.0001) while the remaining diastolic parameters showed moderate correlation (e', r = 0.64; E/e', r = 0.54; left atrial volume index (LAVi), r = 0.61; all p < 0.0001). Classification of LV diastolic function by CMR showed good concordance with standardized grades established for TTE. CMR-based LV diastolic function may be integrated in routine clinical practice.Name of the registry: Technical Development of Cardiovascular Magnetic Resonance Imaging. Trial registration number: NCT00027170. Date of registration: November 26, 2001. URL of trial registry record: https://clinicaltrials.gov/ct2/show/NCT00027170.

Cardiac function in a large animal model of myocardial infarction at 7 T: deep learning based automatic segmentation increases reproducibility.

Cardiac magnetic resonance (CMR) imaging allows precise non-invasive quantification of cardiac function. It requires reliable image segmentation for myocardial tissue. Clinically used software usually offers automatic approaches for this step. These are, however, designed for segmentation of human images obtained at clinical field strengths. They reach their limits when applied to preclinical data and ultrahigh field strength (such as CMR of pigs at 7 T). In our study, eleven animals (seven with myocardial infarction) underwent four CMR scans each. Short-axis cine stacks were acquired and used for functional cardiac analysis. End-systolic and end-diastolic images were labelled manually by two observers and inter- and intra-observer variability were assessed. Aiming to make the functional analysis faster and more reproducible, an established deep learning (DL) model for myocardial segmentation in humans was re-trained using our preclinical 7 T data (n = 772 images and labels). We then tested the model on n = 288 images. Excellent agreement in parameters of cardiac function was found between manual and DL segmentation: For ejection fraction (EF) we achieved a Pearson's r of 0.95, an Intraclass correlation coefficient (ICC) of 0.97, and a Coefficient of variability (CoV) of 6.6%. Dice scores were 0.88 for the left ventricle and 0.84 for the myocardium.

Heart Failure with Normal Natriuretic Peptide Levels and Preserved Ejection Fraction: A Prospective Clinical and Cardiac MRI Study.

Purpose To describe the clinical presentation, comprehensive cardiac MRI characteristics, and prognosis of individuals with predisposed heart failure with preserved ejection fraction (HFpEF). Materials and Methods This prospective cohort study (part of MISSION-HFpEF [Multimodality Imaging in the Screening, Diagnosis, and Risk Stratification of HFpEF]; NCT04603404) was conducted from January 1, 2019, to September 30, 2021, and included individuals with suspected HFpEF who underwent cardiac MRI. Participants who had primary cardiomyopathy and primary valvular heart disease were excluded. Participants were split into a predisposed HFpEF group, defined as HFpEF with normal natriuretic peptide levels based on an HFA-PEFF (Heart Failure Association Pretest Assessment, Echocardiography and Natriuretic Peptide, Functional Testing, and Final Etiology) score of 4 from the latest European Society of Cardiology guidelines, and an HFpEF group (HFA-PEFF score of ≥ 5). An asymptomatic control group without heart failure was also included. Clinical and cardiac MRI-based characteristics and outcomes were compared between groups. The primary end points were death, heart failure hospitalization, or stroke. Results A total of 213 participants with HFpEF, 151 participants with predisposed HFpEF, and 100 participants in the control group were analyzed. Compared with the control group, participants with predisposed HFpEF had worse left ventricular remodeling and function and higher systemic inflammation. Compared with participants with HFpEF, those with predisposed HFpEF, whether obese or not, were younger and had higher plasma volume, lower prevalence of atrial fibrillation, lower left atrial volume index, and less impaired left ventricular global longitudinal strain (-12.2% ± 2.8 vs -13.9% ± 3.1; P < .001) and early-diastolic global longitudinal strain rate (eGLSR, 0.52/sec ± 0.20 vs 0.57/sec ± 0.15; P = .03) but similar prognosis. Atrial fibrillation occurrence (hazard ratio [HR] = 3.90; P = .009), hemoglobin level (HR = 0.94; P = .001), and eGLSR (per 0.2-per-second increase, HR = 0.28; P = .002) were independently associated with occurrence of primary end points in participants with predisposed HFpEF. Conclusion Participants with predisposed HFpEF showed relatively unique clinical and cardiac MRI features, warranting greater clinical attention. eGLSR should be considered as a prognostic factor in participants with predisposed HFpEF. Keywords: Heart Failure with Preserved Ejection Fraction, Normal Natriuretic Peptide Levels, Cardiovascular Magnetic Resonance, Myocardial Strain, Prognosis Clinical trial registration no. NCT04603404 Supplemental material is available for this article. © RSNA, 2024.

Clinical Outcomes Associated With Various Microvascular Injury Patterns Identified by CMR After STEMI.

BACKGROUND: The prognostic significance of various microvascular injury (MVI) patterns after ST-segment elevation myocardial infarction (STEMI) is not well known. OBJECTIVES: This study sought to investigate the prognostic implications of different MVI patterns in STEMI patients. METHODS: The authors analyzed 1,109 STEMI patients included in 3 prospective studies. Cardiac magnetic resonance (CMR) was performed 3 days (Q1-Q3: 2-5 days) after percutaneous coronary intervention (PCI) and included late gadolinium enhancement imaging for microvascular obstruction (MVO) and T2∗ mapping for intramyocardial hemorrhage (IMH). Patients were categorized into those without MVI (MVO-/IMH-), those with MVO but no IMH (MVO+/IMH-), and those with IMH (IMH+). RESULTS: MVI occurred in 633 (57%) patients, of whom 274 (25%) had an MVO+/IMH- pattern and 359 (32%) had an IMH+ pattern. Infarct size was larger and ejection fraction lower in IMH+ than in MVO+/IMH- and MVO-/IMH- (infarct size: 27% vs 19% vs 18% [P < 0.001]; ejection fraction: 45% vs 50% vs 54% [P < 0.001]). During a median follow-up of 12 months (Q1-Q3: 12-35 months), a clinical outcome event occurred more frequently in IMH+ than in MVO+/IMH- and MVO-/IMH- subgroups (19.5% vs 3.6% vs 4.4%; P < 0.001). IMH+ was the sole independent MVI parameter predicting major adverse cardiovascular events (HR: 3.88; 95% CI: 1.93-7.80; P < 0.001). CONCLUSIONS: MVI is associated with future adverse outcomes only in patients with a hemorrhagic phenotype (IMH+). Patients with only MVO (MVO+/IMH-) had a prognosis similar to patients without MVI (MVO-/IMH-). This highlights the independent prognostic importance of IMH in assessing and managing risk after STEMI.

Automatic left ventricle volume and mass quantification from 2D cine-MRI: Investigating papillary muscle influence.

OBJECTIVE: Early detection of cardiovascular diseases is based on accurate quantification of the left ventricle (LV) function parameters. In this paper, we propose a fully automatic framework for LV volume and mass quantification from 2D-cine MR images already segmented using U-Net. METHODS: The general framework consists of three main steps: Data preparation including automatic LV localization using a convolution neural network (CNN) and application of morphological operations to exclude papillary muscles from the LV cavity. The second step consists in automatically extracting the LV contours using U-Net architecture. Finally, by integrating temporal information which is manifested by a spatial motion of myocytes as a third dimension, we calculated LV volume, LV ejection fraction (LVEF) and left ventricle mass (LVM). Based on these parameters, we detected and quantified cardiac contraction abnormalities using Python software. RESULTS: CNN was trained with 35 patients and tested on 15 patients from the ACDC database with an accuracy of 99,15 %. U-Net architecture was trained using ACDC database and evaluated using local dataset with a Dice similarity coefficient (DSC) of 99,78 % and a Hausdorff Distance (HD) of 4.468 mm (p < 0,001). Quantification results showed a strong correlation with physiological measures with a Pearson correlation coefficient (PCC) of 0,991 for LV volume, 0.962 for LVEF, 0.98 for stroke volume (SV) and 0.923 for LVM after pillars' elimination. Clinically, our method allows regional and accurate identification of pathological myocardial segments and can serve as a diagnostic aid tool of cardiac contraction abnormalities. CONCLUSION: Experimental results prove the usefulness of the proposed method for LV volume and function quantification and verify its potential clinical applicability.

Cardiac MRI for clinical dilated cardiomyopathy: Improved diagnostic power via combined T1, T2, and ECV.

INTRODUCTION: Early diagnosis of patients with dilated cardiomyopathy (DCM) remains challenging. Cardiac MR can correlate myocardial changes with their pathological basis. There have been some previous studies on the effect of T1 mapping in DCM, but there is limited data on the incremental value of T2 mapping for DCM in routine clinical practice. This study will examine whether the combination of MRI T1 and T2 mapping offers greater advantages in the diagnosis of DCM. METHODS: The study included 28 patients with DCM and 21 healthy controls. CMR evaluation included late gadolinium enhancement (LGE), T1 mapping, extracellular volume (ECV) fraction and T2 mapping. The DCM group was divided into LGE (+) and LGE (-) subgroups. The main modes of LGE are subendocardial, midwall, subepicardial, or transmural. T1 values, T2 values, and ECV in the 16 segments myocardial levels were measured by post-processing software. Student's t-tests or Mann-Whitney U test was used to compare between two groups, and one-way ANOVA or Kruskal-Wallis H test was used to compare between multiple groups, with p values corrected by Bonferroni. The difference was considered statistically significant at P < 0.05. ROC curve analysis was used to compare the area under the curve (AUC) of each index and its combined value, and the cut-off value, sensitivity and specificity were determined by Jordan's index. RESULTS: Mean native myocardial T1, ECV and T2 were significantly higher in the DCM group compared to controls (p ≤ 0.001, respectively). The best cut-off values for T1, T2 and ECV to discriminate DCM from controls were 1184 ms, 40.9 ms and 29.2%, respectively. The AUC of T1, ECV and T2 were 0.87, 0.89, and 0.83, respectively. The combined AUC of the three values was 0.96. CONCLUSION: Native T1 value and ECV overcome some of the limitations of LGE, and the T2 helps to understand the extent of myocardial damage. The combination of T1 and T2 mapping techniques can reveal fibrotic and oedematous changes in the early stages of DCM, providing a more comprehensive assessment of DCM and better guidance for individualised clinical management of patients. IMPLICATIONS FOR PRACTICE: We suggest that the addition of T2 mapping to the routine CMR examination of patients with suspected DCM, and the combined assessment of T1mapping and T2 mapping can provide complementary information about the disease and improve the early diagnosis of DCM.

A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data.

Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like the CHA 2 DS 2 -VASc score, often lack the granularity required for personalized predictions. In this study, we present a nuanced and thorough stroke risk assessment by integrating functional insights from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations. Our cohort, evenly split between control and stroke groups, comprises eight patients. Utilizing CINE CMR, we compute kinematic features, revealing smaller left atrial volumes for stroke patients. The incorporation of patient-specific atrial displacement into our hemodynamic simulations unveils the influence of atrial compliance on the flow fields, emphasizing the importance of LA motion in CFD simulations and challenging the conventional rigid wall assumption in hemodynamics models. Standardizing hemodynamic features with functional metrics enhances the differentiation between stroke and control cases. While standalone assessments provide limited clarity, the synergistic fusion of CMR-derived functional data and patient-informed CFD simulations offers a personalized and mechanistic understanding, distinctly segregating stroke from control cases. Specifically, our investigation reveals a crucial clinical insight: normalizing hemodynamic features based on ejection fraction fails to differentiate between stroke and control patients. Differently, when normalized with stroke volume, a clear and clinically significant distinction emerges and this holds true for both the left atrium and its appendage, providing valuable implications for precise stroke risk assessment in clinical settings. This work introduces a novel framework for seamlessly integrating hemodynamic and functional metrics, laying the groundwork for improved predictive models, and highlighting the significance of motion-informed, personalized risk assessments.

Rate of Change in Cardiac Magnetic Resonance Imaging Measures Is Associated With Death in Duchenne Muscular Dystrophy.

BACKGROUND: Cardiovascular disease is the leading cause of death among patients with Duchenne muscular dystrophy (DMD). Identifying patients at risk of early death could allow for increased monitoring and more intensive therapy. Measures that associate with death could serve as surrogate outcomes in clinical trials. METHODS AND RESULTS: Duchenne muscular dystrophy subjects prospectively enrolled in observational studies were included. Models using generalized least squares were used to assess the difference of cardiac magnetic resonance measurements between deceased and alive subjects. A total of 63 participants underwent multiple cardiac magnetic resonance imaging and were included in the analyses. Twelve subjects (19.1%) died over a median follow-up of 5 years (interquartile range, 3.1-7.0). Rate of decline in left ventricular ejection fraction was faster in deceased than alive subjects (P<0.0001). Rate of increase in indexed left ventricular end-diastolic (P=0.0132) and systolic (P<0.0001) volumes were higher in deceased subjects. Faster worsening in midcircumferential strain was seen in deceased subjects (P=0.049) while no difference in global circumferential strain was seen. The rate of increase in late gadolinium enhancement, base T1, and mid T1 did not differ between groups. CONCLUSIONS: Duchenne muscular dystrophy death is associated with the rate of change in left ventricular ejection fraction, midcircumferential strain, and ventricular volumes. Aggressive medical therapy to decrease the rate of progression may improve the mortality rate in this population. A decrease in the rate of progression may serve as a valid surrogate outcome for therapeutic trials.

Correlation of epicardial adipose tissue and inflammatory indices in patients with STEMI and implications for atrial arrhythmias.

BACKGROUND: Epicardial adipose tissue(EAT) is associated with inflammation in previous studies but is unknown in patients with ST-segment elevation myocardial infarction(STEMI).This study investigated the correlation between epicardial fat and inflammatory cells obtained by cardiac magnetic resonance (CMR) and the effect on atrial arrhythmias in patients with STEMI. METHODS: This was a single-center, retrospective study. We consecutively selected patients who all completed CMR after Percutaneous Coronary Intervention (PCI) from January 2019 to December 2022 and then had regular follow-ups at 1, 3, 6, 9, and 12 months. The enrolled patients were grouped according to the presence or absence of atrial arrhythmia and divided into atrial and non-atrial arrhythmia groups. RESULTS: White blood cell, neutrophil, lymphocyte, C-reactive protein, EATV, LVES, LVED were higher in the atrial arrhythmia group than in the non-atrial arrhythmia group, and LVEF was lower than that in the non-atrial arrhythmia group (p < 0.05); EATV was significantly positively correlated with each inflammatory indices (white blood cell: r = 0.415 p < 0.001, neutrophil:r = 0.386 p < 0.001, lymphocyte:r = 0.354 p < 0.001, C-reactive protein:r = 0.414 p < 0.001); one-way logistic regression analysis showed that risk factors for atrial arrhythmias were age, heart rate, white blood cell, neutrophil, lymphocyte, C-reactive protein, EATV, LVES, LVED; multifactorial logistic regression analysis showed that neutrophil, lymphocyte, C-reactive protein, EATV, and LVES were independent risk factors for atrial arrhythmias; ROC analysis showed that the area under the curve (AUC) for neutrophil was 0.862; the AUC for lymphocyte was 1.95; and the AUC for C-reactive protein was 0.862. reactive protein was 0.852; AUC for LVES was 0.683; and AUC for EATV was 0.869. CONCLUSION: In patients with STEMI, EAT was significantly and positively correlated with inflammatory indices; neutrophil, lymphocyte, C-reactive protein, EATV, and LVES were independent risk factors for atrial arrhythmias and had good predictive value.

Multimodality imaging in arrhythmogenic cardiomyopathy - From diagnosis to management.

Arrhythmogenic Cardiomyopathy (AC), an inherited cardiac disorder characterized by myocardial fibrofatty replacement, carries a significant risk of sudden cardiac death (SCD) due to ventricular arrhythmias. A comprehensive multimodality imaging approach, including echocardiography, cardiac magnetic resonance imaging (CMR), and cardiac computed tomography (CCT), allows for accurate diagnosis, effective risk stratification, vigilant monitoring, and appropriate intervention, leading to improved patient outcomes and the prevention of SCD. Echocardiography is primary tool ventricular morphology and function assessment, CMR provides detailed visualization, CCT is essential in early stages for excluding congenital anomalies and coronary artery disease. Echocardiography is preferred for follow-up, with CMR capturing changes over time. The strategic use of these imaging methods aids in confirming AC, differentiating it from other conditions, tracking its progression, managing complications, and addressing end-stage scenarios.

Cardiac Magnetic Resonance Feature-Tracking Identifies Preclinical Abnormalities in Hypertrophic Cardiomyopathy Sarcomere Gene Mutation Carriers.

BACKGROUND: Assessing myocardial strain by cardiac magnetic resonance feature tracking (FT) has been found to be useful in patients with overt hypertrophic cardiomyopathy (HCM). Little is known, however, of its role in sarcomere gene mutation carriers without overt left ventricular hypertrophy (subclinical HCM). METHODS: Thirty-eight subclinical HCM subjects and 42 healthy volunteers were enrolled in this multicenter case-control study. They underwent a comprehensive cardiac magnetic resonance study. Two-dimensional global radial, circumferential, and longitudinal strain of the left ventricle (LV) were evaluated by FT analysis. RESULTS: The subclinical HCM sample was 41 (22-51) years old and 32% were men. FT analysis revealed a reduction in global radial strain (29±7.2 versus 47.9±7.4; P<0.0001), global circumferential strain (-17.3±2.6 -versus -20.8±7.4; P<0.0001) and global longitudinal strain (-16.9±2.4 versus -20.5±2.6; P<0.0001) in subclinical HCM compared with control subjects. The significant differences persisted when considering the 23 individuals free of all the structural and functional ECG and cardiac magnetic resonance abnormalities previously described. Receiver operating characteristic curve analyses showed that the differential diagnostic performances of FT in discriminating subclinical HCM from normal subjects were good to excellent (global radial strain with optimal cut-off value of 40.43%: AUC, 0.946 [95% CI, 0.93-1.00]; sensitivity 90.48%, specificity 94.44%; global circumferential strain with cut-off, -18.54%: AUC, 0.849 [95% CI, 0.76-0.94]; sensitivity, 88.10%; specificity, 72.22%; global longitudinal strain with cut-off, -19.06%: AUC, 0.843 [95% CI, 0.76-0.93]; sensitivity, 78.57%; specificity, 78.95%). Similar values were found for discriminating those subclinical HCM subjects without other phenotypic abnormalities from healthy volunteers (global radial strain with optimal cut-off 40.43%: AUC, 0.966 [95% CI, 0.92-1.00]; sensitivity, 90.48%; specificity, 95.45%; global circumferential strain with cut-off, -18.44%: AUC, 0.866 [95% CI, 0.76-0.96]; sensitivity, 92.86%; specificity, 77.27%; global longitudinal strain with cut-off, -17.32%: AUC, 0.838 [95% CI, 0.73-0.94]; sensitivity, 90.48%; specificity, 65.22%). CONCLUSIONS: Cardiac magnetic resonance FT-derived parameters are consistently lower in subclinical patients with HCM, and they could emerge as a good tool for discovering the disease during a preclinical phase.