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.

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.

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.

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.

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.

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.

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.

Association of stress hyperglycemia ratio with left ventricular function and microvascular obstruction in patients with ST-segment elevation myocardial infarction: a 3.0 T cardiac magnetic resonance study.

BACKGROUND: Stress hyperglycemia, which is associated with poor prognosis in patients with acute myocardial infarction (AMI), can be determined using the stress hyperglycemia ratio (SHR). Impaired left ventricular function and microvascular obstruction (MVO) diagnosed using cardiac magnetic resonance (CMR) have also been proven to be linked to poor prognosis in patients with AMI and aid in risk stratification. However, there have been no studies on the correlation between fasting SHR and left ventricular function and MVO in patients with acute ST-segment elevation myocardial infarction (ASTEMI). Therefore, this study aimed to investigate the additive effect of fasting SHR on left ventricular function and global deformation in patients with ASTEMI and to explore the association between fasting SHR and MVO. METHODS: Consecutive patients who underwent CMR at index admission (3-7 days) after primary percutaneous coronary intervention (PPCI) were enrolled in this study. Basic clinical, biochemical, and CMR data were obtained and compared among all patients grouped by fasting SHR tertiles: SHR1: SHR < 0.85; SHR2: 0.85 ≤ SHR < 1.01; and SHR3: SHR ≥ 1.01. Spearman's rho (r) was used to assess the relationship between fasting SHR and left ventricular function, myocardial strain, and the extent of MVO. Multivariable linear regression analysis was performed to evaluate the determinants of left ventricular function and myocardial strain impairment in all patients with AMI. Univariable and multivariable regression analyses were performed to investigate the correlation between fasting SHR and the presence and extent of MVO in patients with AMI and those with AMI and diabetes mellitus (DM). RESULTS: A total of 357 patients with ASTEMI were enrolled in this study. Left ventricular ejection fraction (LVEF) and left ventricular global function index (LVGFI) were significantly lower in SHR2 and SHR3 than in SHR1. Compared with SHR1 and SHR2 groups, left ventricular strain was lower in SHR3, as evidenced by global radial (GRS), global circumferential (GCS), and global longitudinal (GLS) strains. Fasting SHR were negatively correlated with LVEF, LVGFI, and GRS (r = - 0.252; r = - 0.261; and r = - 0.245; all P<0.001) and positively correlated with GCS (r = 0.221) and GLS (r = 0.249; all P <0.001). Multivariable linear regression analysis showed that fasting SHR was an independent determinant of impaired LVEF, LVGFI, GRS, and GLS. Furthermore, multivariable regression analysis after adjusting for covariates signified that fasting SHR was associated with the presence and extent of MVO in patients with AMI and those with AMI and DM. CONCLUSION: Fasting SHR in patients with ASTEMI successfully treated using PPCI is independently associated with impaired cardiac function and MVO. In patients with AMI and DM, fasting SHR is an independent determinant of the presence and extent of MVO.

Arrhythmogenic right ventricular cardiomyopathy with sustained ventricular tachycardia: a case report.

INTRODUCTION: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an infrequent hereditary disorder distinguished by fibrofatty replacement of the myocardium in the right ventricular, which predisposes individuals to life-threatening arrhythmias. This case delineates an ARVC patient who suffered recurrent bouts of sustained ventricular tachycardia (VT). In this case, we mainly discuss the application of myocardial contrast echocardiography (MCE) in displaying myocardial fibrosis in patients with ARVC. CASE PRESENTATION: A 43-year-old male experienced three episodes of unexplained VT over an eight-year period, accompanied by symptoms of chest discomfort, palpitations and dizziness. Coronary angiography revealed no significant coronary stenosis. The electrocardiogram (ECG) results indicated characteristic epsilon waves in right precordial leads, and subsequent echocardiography identified right ventricular enlargement and right ventricular systolic dysfunction. MCE further disclosed regional myocardial ischemia at the epicardium of the left ventricular apex. Ultimately, cardiovascular magnetic resonance imaging (CMR) corroborated the ARVC diagnosis, highlighting linear intensification in the right ventricle during the delayed enhancement. CONCLUSION: Prompt identification of ARVC is crucial for timely intervention and management. MCE may offer an effective and valuable technique for the detection of myocardial involvement in ARVC patient.

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.

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.

"Interstitial fibrosis is associated with left atrial remodeling and adverse clinical outcomes in selected low-risk patients with hypertrophic cardiomyopathy".

BACKGROUND: Cardiovascular magnetic resonance (CMR) extracellular volume (ECV) allows non-invasive detection of myocardial interstitial fibrosis, which may be related to diastolic dysfunction and left atrial (LA) remodeling in hypertrophic cardiomyopathy (HCM). While the prognostic role of LGE is well-established, interstitial fibrosis and LA dysfunction are emerging novel markers in HCM. This study aimed to explore the interaction between interstitial fibrosis by ECV, LA morpho-functional parameters and adverse clinical outcomes in selected low-risk patients with HCM. METHODS: 115 HCM patients and 61 matched controls underwent CMR to identify: i) interstitial fibrosis by ECV in hypertrophied left ventricular LGE-negative remote myocardium (r-ECV); ii) LA indexed maximum (LAVi max) and minimum (LAVi min) volumes, ejection fraction (LA-EF) and strain (reservoir εs, conduit εe and booster εa), by CMR feature-tracking. 2D-echocardiographic assessment of diastolic function was also performed within 6 months from CMR. A composite endpoint including worsening NYHA class, heart failure hospitalization, atrial fibrillation and all-cause death was evaluated at 2.3 years follow-up. HCM patients were divided into two groups, according to r-ECV values of controls. RESULTS: Patients with r-ECV ≥29% (n = 45) showed larger LA volumes (LAVimax 63 vs. 54 ml/m2, p < 0.001; LAVimin 43 vs. 28 ml/m2, p ã€ˆ0001), worse LA function (εs 16 vs. 28%, εe 8 vs. 15%, εa 8 vs. 14%, LA-EF 33 vs. 49%, all p < 0.001) and elevated Nt-proBNP (1115 vs. 382 pg/ml, p = 0.002). LA functional parameters inversely correlated with r-ECV (εs r = -0.54; LA-EF r = -0.46; all p < 0.001) and E/e' (εs r = -0.52, LA-EF r = -0.46; all p < 0.006). r-ECV ≥29% and LAVi min >30 ml/m2 have been identified as possible independent factors associated with the endpoint. CONCLUSIONS: In HCM diffuse interstitial fibrosis detected by increased r-ECV is associated with LA remodeling and emerged as a potential independent predictor of adverse clinical outcomes, on top of the well-known prognostic impact of LGE.

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.

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.

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.