Evaluation of left ventricular blood flow kinetic energy in patients with acute myocardial infarction by 4D Flow MRI: a preliminary study.

PURPOSE: To evaluate the intracavity left ventricular (LV) blood flow kinetic energy (KE) parameters using four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) in patients with acute myocardial infarction (AMI). METHODS: Thirty AMI patients and twenty controls were examined via CMR, which included cine imaging, late gadolinium enhancement (LGE) and global heart 4D flow imaging. The KE parameters were indexed to LV end-diastolic volume (EDV) to obtain average, systolic and diastolic KE as well as the proportion of LV in-plane KE (%). These parameters were compared between the AMI patients and controls and between the two subgroups. RESULTS: Analysis of the LV blood flow KE parameters at different levels of the LV cavity and in different segments of the same level showed that the basal level had the highest blood flow KE while the apical level had the lowest in the control group. There were no significant differences in diastolic KE, systolic in-plane KE and diastolic in-plane KE between the anterior wall and posterior wall (p > 0.05), only the systolic KE had a significant difference between them (p < 0.05). Compared with those in the control group, the average (10.7 ± 3.3 µJ/mL vs. 14.7 ± 3.6 µJ/mL, p < 0.001), systolic (14.6 ± 5.1 µJ/mL vs. 18.9 ± 3.9 µJ/mL, p = 0.003) and diastolic KE (7.9 ± 2.5 µJ/mL vs. 10.6 ± 3.8 µJ/mL, p = 0.018) were significantly lower in the AMI group. The average KE in the infarct segment was lower than that in the noninfarct segment in the AMI group (49.5 ± 18.7 µJ/mL vs. 126.3 ± 50.7 µJ/mL, p < 0.001), while the proportion of systolic in-plane KE increased significantly (61.8%±11.5 vs. 42.9%±14.4, p = 0.001). CONCLUSION: The 4D Flow MRI technique can be used to quantitatively evaluate LV regional hemodynamic parameters. There were differences in the KE parameters of LV blood flow at different levels and in different segments of the same level in healthy people. In AMI patients, the average KE of the infarct segment decreased, while the proportion of systolic in-plane KE significantly increased.

Correlation of Noninvasive Cardiac MRI Measures of Left Ventricular Myocardial Function and Invasive Pressure-Volume Parameters in a Porcine Ischemia-Reperfusion Model.

Purpose To assess the correlation between noninvasive cardiac MRI-derived parameters with pressure-volume (PV) loop data and evaluate changes in left ventricular function after myocardial infarction (MI). Materials and Methods Sixteen adult female swine were induced with MI, with six swine used as controls and 10 receiving platelet-derived growth factor-AB (PDGF-AB). Load-independent measures of cardiac function, including slopes of end-systolic pressure-volume relationship (ESPVR) and preload recruitable stroke work (PRSW), were obtained on day 28 after MI. Cardiac MRI was performed on day 2 and day 28 after infarct. Global longitudinal strain (GLS) and global circumferential strain (GCS) were measured. Ventriculo-arterial coupling (VAC) was derived from PV loop and cardiac MRI data. Pearson correlation analysis was performed. Results GCS (r = 0.60, P = .01), left ventricular ejection fraction (LVEF) (r = 0.60, P = .01), and cardiac MRI-derived VAC (r = 0.61, P = .01) had a significant linear relationship with ESPVR. GCS (r = 0.75, P < .001) had the strongest significant linear relationship with PRSW, followed by LVEF (r = 0.67, P = .005) and cardiac MRI-derived VAC (r = 0.60, P = .01). GLS was not significantly correlated with ESPVR or PRSW. There was a linear correlation (r = 0.82, P < .001) between VAC derived from cardiac MRI and from PV loop data. GCS (-3.5% ± 2.3 vs 0.5% ± 1.4, P = .007) and cardiac MRI-derived VAC (-0.6 ± 0.6 vs 0.3 ± 0.3, P = .001) significantly improved in the animals treated with PDGF-AB 28 days after MI compared with controls. Conclusion Cardiac MRI-derived parameters of MI correlated with invasive PV measures, with GCS showing the strongest correlation. Cardiac MRI-derived measures also demonstrated utility in assessing therapeutic benefit using PDGF-AB. Keywords: Cardiac MRI, Myocardial Infarction, Pressure Volume Loop, Strain Imaging, Ventriculo-arterial Coupling Supplemental material is available for this article. © RSNA, 2024.

Right Ventricular Strain Derived from Cardiac MRI Feature Tracking for the Diagnosis and Prognosis of Arrhythmogenic Right Ventricular Cardiomyopathy.

Purpose To demonstrate the myocardial strain characteristics of patients with arrhythmogenic right ventricular cardiomyopathy (ARVC), based on revised Task Force Criteria (rTFC), and to explore the prognostic value of strain analysis in ARVC. Materials and Methods This retrospective study included 247 patients (median age, 38 years [IQR, 28-48 years]; 167 male, 80 female) diagnosed with ARVC, based on rTFC, between 2014 and 2018. Patients were divided into "possible" (n =25), "borderline" (n = 40), and "definite" (n = 182) ARVC groups following rTFC. Biventricular global strain parameters were calculated using cardiac MRI feature tracking (FT). The primary outcome was defined as a composite of cardiovascular events, including cardiovascular death, heart transplantation, and appropriate implantable cardioverter defibrillator discharge. Univariable and multivariable cumulative logistic regression and Cox proportional hazards regression analysis were used to evaluate the diagnostic and prognostic value of right ventricle (RV) strain parameters. Results Patients with definite ARVC had significantly reduced RV global strain in all three directions compared with possible or borderline groups (all P < .001). RV global longitudinal strain (GLS) was an independent predictor for disease (odds ratio, 1.09 [95% CI: 1.02, 1.16]; P = .009). During a median follow-up of 3.4 years (IQR, 2.0-4.9 years), 55 patients developed primary end point events. Multivariable analysis showed that RV GLS was independently associated with the occurrence of cardiovascular events (hazard ratio, 1.15 [95% CI: 1.07, 1.24]; P < .001). Kaplan-Meier analysis showed that patients with RV GLS worse than median had a higher risk of combined cardiovascular events (log-rank P < .001). Conclusion RV GLS derived from cardiac MRI FT demonstrated good diagnostic and prognostic value in ARVC. Keywords: MR Imaging, Image Postprocessing, Cardiac, Right Ventricle, Cardiomyopathies, Arrhythmogenic Right Ventricular Cardiomyopathy, Revised Task Force Criteria, Cardiovascular MR, Feature Tracking, Cardiovascular Events Supplemental material is available for this article. © RSNA, 2024.

Cardiovascular Magnetic Resonance in the Management of Cardiac Amyloidosis: Current and Future Clinical Applications.

Cardiac magnetic resonance represents the gold standard imaging technique to assess cardiac volumes, wall thickness, mass, and systolic function but also to provide noninvasive myocardial tissue characterization across almost all cardiac diseases. In patients with cardiac amyloidosis, increased wall thickness of all heart chambers, a mildly reduced ejection fraction and occasionally pleural and pericardial effusion are the characteristic morphologic anomalies. The typical pattern after contrast injection is represented by diffuse areas of late gadolinium enhancement, which can be focal and patchy in very early stages, circumferential, and subendocardial in intermediate stages or even diffuse transmural in more advanced stages.

Cardiac magnetic resonance in advanced heart failure.

Heart failure (HF) is a chronic and progressive disease that often progresses to an advanced stage where conventional therapy is insufficient to relieve patients' symptoms. Despite the availability of advanced therapies such as mechanical circulatory support or heart transplantation, the complexity of defining advanced HF, which requires multiple parameters and multimodality assessment, often leads to delays in referral to dedicated specialists with the result of a worsening prognosis. In this review, we aim to explore the role of cardiac magnetic resonance (CMR) in advanced HF by showing how CMR is useful at every step in managing these patients: from diagnosis to prognostic stratification, hemodynamic evaluation, follow-up and advanced therapies such as heart transplantation. The technical challenges of scanning advanced HF patients, which often require troubleshooting of intracardiac devices and dedicated scans, will be also discussed.

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.

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.

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.

A study on the application of radiomics based on cardiac MR non-enhanced cine sequence in the early diagnosis of hypertensive heart disease.

BACKGROUND: The prevalence of hypertensive heart disease (HHD) is high and there is currently no easy way to detect early HHD. Explore the application of radiomics using cardiac magnetic resonance (CMR) non-enhanced cine sequences in diagnosing HHD and latent cardiac changes caused by hypertension. METHODS: 132 patients who underwent CMR scanning were divided into groups: HHD (42), hypertension with normal cardiac structure and function (HWN) group (46), and normal control (NOR) group (44). Myocardial regions of the end-diastolic (ED) and end-systolic (ES) phases of the CMR short-axis cine sequence images were segmented into regions of interest (ROI). Three feature subsets (ED, ES, and ED combined with ES) were established after radiomic least absolute shrinkage and selection operator feature selection. Nine radiomic models were built using random forest (RF), support vector machine (SVM), and naive Bayes. Model performance was analyzed using receiver operating characteristic curves, and metrics like accuracy, area under the curve (AUC), precision, recall, and specificity. RESULTS: The feature subsets included first-order, shape, and texture features. SVM of ED combined with ES achieved the highest accuracy (0.833), with a macro-average AUC of 0.941. AUCs for HHD, HWN, and NOR identification were 0.967, 0.876, and 0.963, respectively. Precisions were 0.972, 0.740, and 0.826; recalls were 0.833, 0.804, and 0.863, respectively; and specificities were 0.989, 0.863, and 0.909, respectively. CONCLUSIONS: Radiomics technology using CMR non-enhanced cine sequences can detect early cardiac changes due to hypertension. It holds promise for future use in screening for latent cardiac damage in early HHD.

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.

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.

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.

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.

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.

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.

Aortic geometry and long-term outcome in patients with a repaired coarctation.

OBJECTIVE: This study aims to compare aortic morphology between repaired coarctation patients and controls, and to identify aortic morphological risk factors for hypertension and cardiovascular events (CVEs) in coarctation patients. METHODS: Repaired coarctation patients with computed tomography angiography (CTA) or magnetic resonance angiography (MRA) were included, followed-up and compared with sex-matched and age-matched controls. Three-dimensional aortic shape was reconstructed using patients' CTA or MRA, or four-dimensional flow cardiovascular magnetic resonance in controls, and advanced geometrical characteristics were calculated and visualised using statistical shape modelling. In patients, we examined the association of geometrical characteristics with (1) baseline hypertension, using multivariable logistic regression; and (2) cardiovascular events (CVE, composite of aortic complications, coronary artery disease, ventricular arrhythmias, heart failure hospitalisation, stroke, transient ischaemic attacks and cardiovascular death), using multivariable Cox regression. The least absolute shrinkage and selection operator (LASSO) method selected the most informative multivariable model. RESULTS: Sixty-five repaired coarctation patients (23 years (IQR 19-38)) were included, of which 44 (68%) patients were hypertensive at baseline. After a median follow-up of 8.7 years (IQR 4.8-15.4), 27 CVEs occurred in 20 patients. Aortic arch dimensions were smaller in patients compared with controls (diameter p<0.001, wall surface area p=0.026, volume p=0.007). Patients had more aortic arch torsion (p<0.001) and a higher curvature (p<0.001). No geometrical characteristics were associated with hypertension. LASSO selected left ventricular mass, male sex, tortuosity and age for the multivariable model. Left ventricular mass (p=0.014) was independently associated with CVE, and aortic tortuosity showed a trend towards significance (p=0.070). CONCLUSION: Repaired coarctation patients have a smaller aortic arch and a more tortuous course of the aorta compared with controls. Besides left ventricular mass index, geometrical features might be of importance in long-term risk assessment in coarctation patients.

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.

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.