Journal of Cardiovascular Magnetic Resonance最新文献

Muscular dystrophies encompass a heterogeneous spectrum of inherited myopathies characterized by progressive skeletal muscle degeneration frequently accompanied by life-threatening cardiac involvement. Cardiovascular magnetic resonance (CMR) has become the reference non-invasive imaging modality for the detection, characterization, and longitudinal monitoring of cardiomyopathy involvement across this group of disorders. This state-of-the-art review synthesizes contemporary evidence on the diagnostic and prognostic value of CMR in the most prevalent muscular dystrophies, including Myotonic dystrophy, Duchenne and Becker muscular dystrophies, Emery-Dreifuss muscular dystrophy, laminopathies, facioscapulohumeral muscular dystrophy, and mitochondrial myopathies. CMR uniquely enables high-resolution assessment of ventricular volumes and function, tissue characterization through late gadolinium enhancement (LGE) and parametric mapping (native T1, T2, extracellular volume fraction), and quantitative strain imaging. These techniques uncover subclinical myocardial involvement years before overt dysfunction occurs, providing a robust substrate for early therapeutic intervention. Disease-specific CMR signatures, such as inferolateral subepicardial fibrosis in dystrophinopathies or mid-wall septal enhancement in laminopathies, allow for refined etiological diagnosis and targeted risk stratification. LGE burden and distribution are independently associated with ventricular arrhythmias and adverse cardiac events, transcending the limitations of traditional criteria based on left ventricular ejection fraction for implantable cardioverter-defibrillator selection. Emerging evidence further supports the integration of CMR biomarkers into genotype-guided management strategies and prospective therapeutic trials.

Aims: A T2* ≤ 20 ms in cardiovascular magnetic resonance (CMR) sequences suggests the presence of iron overload cardiomyopathy in patients with transfusion-dependent β-thalassemia (TDT). However, there is still a gap in evidence regarding the independent role of T1 mapping in identifying early myocardial dysfunction. The aim of this study is to investigate the role of T1 mapping in identifying early cardiac mechanical dysfunction in TDT patients with normal T2* values.

Methods and results: 154 consecutive TDT patients with T2* > 20 ms were enrolled and stratified by reduced (≤ 955 ms) or normal (> 955 ms) T1 mapping values. CMR T1 mapping and speckle tracking echocardiography (STE) indices were evaluated. The primary endpoint was the correlation between T1 mapping and STE indices. The secondary endpoint was the prevalence of cardiac mechanical dysfunction between patients with reduced or normal T1 mapping. T1 mapping showed statistically significant correlations with global longitudinal strain (GLS, r = -0.19, p = 0.01), global work index (GWI, r = 0.15, p = 0.04), global constructive work (GCW, r = 0.18, p = 0.02), and peak atrial longitudinal strain (PALS, r = 0.2, p < 0.01). The prevalence of cardiac mechanical dysfunction was low, without any difference between patient with reduced or normal T1 mapping.

Conclusions: In TDT patients with normal T2*, T1 mapping demonstrated a weak but significant correlation with echocardiographic indices of cardiac mechanics. The prevalence of cardiac mechanical dysfunction was low without any difference between those with reduced or normal T1 mapping.

Aims: Diffuse fibrosis is central to the pathophysiology of aortic stenosis (AS), can be assessed using cardiovascular magnetic resonance (CMR) with extracellular volume fraction (ECV%), and associates with mortality. The relevance of this signal to long-term prognosis remains unclear. We aim to assess predictors of long-term mortality with focus on diffuse fibrosis.

Methods and results: Single-centre prospective observational cohort study of patients with severe, symptomatic AS undergoing AVR. Patients were assessed using echocardiography, high-sensitivity cardiac troponin T (hs-cTnT), N-terminal pro-B type natriuretic peptide (NT-proBNP) and CMR including T1 mapping for ECV% quantification. All-cause mortality was identified using the NHS National Spine Database. Univariable and multivariable Cox regression models were fitted to assess all-cause mortality associations. 168 patients (age 72 [65-77] years, 55% male) underwent CMR. Over a follow-up period of 9.7 (6.8-10.9) years, 76 deaths occurred. Patients who died had higher ECV% (29.9% vs 27.6%, p=0.014) and greater LGE (3.9% vs 2.0%, p=0.013). Univariable predictors of mortality were age, atrial fibrillation (AF), left atrial area, left atrial volume, total cholesterol, triglycerides, HDL:LDL ratio, non-bicuspid aortic valve, hs-cTnT, NT-proBNP, EuroSCORE II and ECV%. On multivariable regression, age, AF and ECV% remained significant predictors of mortality, independently of sex. AIC indicated that the model with four covariates was preferable to the one also including EuroSCORE II and coronary artery disease, and this result was confirmed by a likelihood ratio test (p=0.387).

Conclusions: In the longest follow-up cohort of T1 mapping in severe AS, we demonstrate diffuse fibrosis remains an independent predictor of long-term mortality. Integration of ECV% in baseline risk stratification should be explored further in patients with AS undergoing AVR.

Aims: Cardiovascular Magnetic Resonance-feature tracking (CMR-FT) derived left atrial global longitudinal strain (LA-GLS) has prognostic relevance, even in the early stages of cardiovascular diseases. Identifying technical and subject-related confounders is essential for ensuring comparability across sites and for reliably distinguishing healthy from pathological conditions. This study aimed to evaluate the influence of post-processing software and subject-related factors on CMR-FT derived LA-GLS, diagnostic accuracy and to evaluate inter-site reproducibility.

Methods: This study included 149 healthy individuals and 40 patients with atrial fibrillation (AF; 19 persistent, 21 paroxysmal) from a single site. A subgroup of 18 traveling volunteers underwent CMR at four different sites. All participants underwent CMR in sinus rhythm. LA-GLS was assessed using three post-processing software packages (CVI42, TrufiStrain Research Prototype, Medis). Mixed models with repeated measures were applied to evaluate the effect of software, site and subject-related factors on LA-GLS components. ROC curve analysis was used to assess diagnostic accuracy across software in distinguishing healthy controls from AF patients.

Results: All GLS components differed across post-processing software (p<.001). Reservoir and contractile GLS were lowest in CVI42 (23.9% ± 3.3%, 9.9% ± 2.2%), followed by TrufiStrain (27.4% ± 6.3%, 15.0% ± 4.8%) and Medis (45.4% ± 9.7%, 20.3% ± 5.7%). Conduit GLS was lowest in TrufiStrain (12.4%±4.8%), followed by CVI42 (16.3% ± 4.5%) and Medis (25.1% ± 8.2%). Among traveling volunteers, LA-GLS values were consistent across sites when the same software was used. Across all software, reservoir GLS negatively correlated with age. Diagnostic accuracy was comparable across software packages (AUC for reservoir strain: CVI: 0.81 [0.69-0.90], TrufiStrain 0.76 [0.64-0.88], Medis: 0.84 [0.72-0.94]).

Conclusion: Post-processing software is a significant confounder in CMR-FT based LA-GLS analysis and age substantially influences LA-GLS. LA-GLS demonstrates excellent inter-site reproducibility when analyzed with the same software and offers comparable diagnostic accuracy across platforms.

Aim: To assess the utility of cardiovascular magnetic resonance (CMR)-derived measurements as diagnostic indicators for left ventricular outflow tract obstruction (LVOTO) in hypertrophic cardiomyopathy (HCM) patients.

Methods and results: 448 adult HCM patients (301 (67%) males, median (interquartile range) age 55 (45-62)) with transthoracic echocardiography (TTE) and CMR within a 6-month time window were enrolled. Doppler LVOT gradient was measured both at rest and under provocative maneuvers. LVOTO -defined as peak gradient ≥30mmHg- was present in 42% HCM patients. The total cohort was randomly divided into a training (80%) and validation (20%) cohort, maintaining the same proportions of patients with and without LVOTO in both cohorts. CMR metrics were examined in relation to LVOTO by means of multivariable logistic regression models. A model including the minimum distance between the mitral leaflet tip and the interventricular septum indexed to body surface area (minimum MV-IVSi distance), left ventricular (LV) stroke volume, and signal intensity ratio LVOT/LV showed an outstanding discriminatory ability in the validation cohort with an area under the curve (AUC) of 0.91 (95% confidence interval (CI) 0.85-0.97). The univariable model of the minimum MV-IVSi distance showed an AUC of 0.88 (95%CI 0.81-0.95). An MV-IVSi distance ≤6.5mm/m² yielded a specificity of 94% and a positive predictive value of 89%, and >9.0mm/m2, a sensitivity of 97% and a negative predictive value (NPV) of 97%. The minimum MV-IVSi distance showed excellent intra- and inter-observer reproducibility with an intraclass correlation coefficient of ≥0.95.

Conclusion: CMR-derived parameters, particularly the minimum MV-IVSi distance, can accurately identify LVOTO in HCM patients and easily be integrated into a standard CMR analysis.

Background: Coronary computed tomographic angiography (CCTA) is a first-line test for anatomical evaluation of the coronary arteries in stable chest pain. Despite technical advances, CCTA requires breath hold and exposes patients to ionising radiation and contrast agents. Coronary cardiovascular magnetic resonance angiography (CCMRA) has been limited by long and unpredictable scan times, lower spatial resolution, and restricted plaque characterisation. We developed a novel CMR sequence, BOOST, which produces a co-registered bright-blood image for lumen visualisation and a T1-weighted black-blood image for vessel wall and plaque assessment from a single scan with predictable scan times.

Objectives: To compare the BOOST-CCMRA sequence with CCTA for plaque characterisation and stenosis evaluation in patients with stable chest pain.

Methods: 60 consecutive patients (mean age 56 years, 60% male) with stable chest pain were prospectively enrolled. All underwent CCTA followed by BOOST-CCMRA on a 1.5T MRI scanner. Coronary plaques identified on CCTA and were analysed on the black-blood BOOST image using the signal from plaque to derive the plaque-to-myocardium ratio (PMR); a healthy vessel-to-myocardium ratio (HVMR) was derived as reference. Plaque morphology was assessed by CCTA appearance. Luminal stenosis was assessed on BOOST bright-blood images and compared with CCTA.

Results: Of 60 patients, 35 had plaque on CCTA, with 72 plaques identified. Nine were not detected on BOOST, giving an 88% detection success. BOOST showed agreement with CCTA in stenosis grading for 51 of 63 lesions (81%): 23/26 (88%) minimal, 20/24 (83%) mild, 4/7 (57%) moderate, 3/5 (60%) severe, and 1/1 (100%) occlusion. PMR was significantly higher than HVMR (0.64 ± 0.16 vs 0.36 ± 0.11; p < 0.001) across all plaque subtypes (calcified 0.53 ± 0.11, partially calcified 0.70 ± 0.15, non-calcified 0.69 ± 0.16, all p < 0.001 vs HVMR). Hypertension and family history of premature cardiovascular disease were associated with higher PMR values.

Conclusions: The BOOST sequence allows simultaneous evaluation of coronary lumen and plaque characteristics in a single non-contrast CCMRA acquisition, with reliable plaque identification and good agreement with CCTA for stenosis severity assessment. This approach may offer free-breathing alternative, without radiation or contrast, for integrated anatomical and plaque imaging in patients with stable chest pain.

Background: Carotid and coronary atherosclerosis are critical determinants of cardiovascular risk, yet their interrelationship in middle-aged populations is incompletely understood. This study assessed carotid plaque composition, risk-factor associations, coronary disease, and sex differences in a subclinical cohort.

Methods: Within the Swedish CArdioPulmonary bioImage Study (SCAPIS), 533 asymptomatic individuals aged 50-64 years with carotid plaque ≥2.7mm on ultrasound underwent 3T multi-contrast carotid cardiovascular magnetic resonance (CMR) and coronary computed tomography angiography. Carotid plaque characteristics were determined manually using established criteria on multi-contrast weighted carotid CMR. Bayesian regression models evaluated associations between cardiovascular risk factors and coronary atherosclerosis.

Results: Lipid rich necrotic core (LRNC) was present in 60% and intraplaque hemorrhage (IPH) in 5.4%; calcification occurred in 48.6%. Maximum carotid wall thickness was 1.8 (1.6-2.0) mm, and mean lumen area 31.3 (26.7-36.1) mm². Coronary atherosclerosis was present in 63.6% of participants, with ≥50% stenosis in 12.9%, and coronary artery calcium score >400 in 12.8%. Men (N=367) had larger carotid lumen area, mean wall area, and maximum wall thickness (all p < 0.001) than women (N=166), differences that persisted after body-surface-area adjustment (all p < 0.01). LRNC was present in 66% of men compared to 47% of women (p < 0.001). LRNC presence was not associated with coronary atherosclerosis, whereas IPH was associated with coronary involvement.

Conclusion: In middle-aged individuals, distinct cardiovascular risk factors were positively linked to presence and volume of LRNC and calcified plaques. The substantial prevalence of high-risk plaque features, particularly LRNC and especially in men, highlights a significant subclinical carotid disease burden.

Lay summary: This study used state-of-the-art magnetic resonance imaging to characterize atherosclerotic plaques in the carotid arteries in middle-aged individuals without clinical cardiovascular disease, offering the following insight into early, subclinical atherosclerosis.

Background: Quantification of coronary sinus (CS) flow has been used with pharmacologic stress as a noninvasive surrogate of global myocardial blood flow and coronary flow reserve (CFR). Whether CS flow assessment can be extended to physiological exercise stress remains uncertain. Accurate measurement during exercise is technically challenging due to the small caliber of the CS and its rapidly varying flow dynamics, particularly under exercise conditions. In this study, we evaluated the feasibility of a high-resolution, high-frame-rate CMR approach for measuring post-exercise CS flow and CFR and compared these measures with quantitative myocardial perfusion imaging.

Methods: We implemented a phase-contrast sequence with non-interleaved velocity-compensated and velocity-encoded k-space acquisition and truncated phase encoding. Generative artificial intelligence (AI) synthesized high-resolution images from the low-resolution inputs and interpolated intermediate frames, effectively doubling temporal resolution. In a prospective exercise CMR study, patients with stable coronary artery disease (n = 13, 50±20 years) underwent AI-enabled CS flow imaging at 1.1×1.1mm² spatial and 27 ms temporal resolution, performed twice at rest for scan/re-scan repeatability and once after exercise. Quantitative perfusion imaging was performed before and post-exercise. Scan/re-scan repeatability of rest CS flow, and inter-observer repeatability of rest and post-exercise CS flow and CS flow-derived CFR were assessed using intraclass correlation coefficients (ICC). CS flow and CFR were compared with perfusion-derived myocardial blood flow and myocardial perfusion reserve (MPR) using linear regression and Pearson correlation (r).

Results: Analysis was successful in all rest and 11 of 13 stress scans; two were excluded due to ECG mis-gating. CS flow showed excellent scan/re-scan (ICC = 0.97 [0.91-0.99]) and inter-observer repeatability (ICC = 0.97 [0.92-0.99]). CS flow showed good correlation with perfusion-derived myocardial blood flow (y = 0.95×, r = 0.61, P = 0.002). CS flow-based CFR also correlated well with perfusion-derived MPR (y = 1.02×, r = 0.67, P = 0.025).

Conclusion: We demonstrate the feasibility of a high-resolution, high-frame-rate CMR technique for quantifying post-exercise CS flow and CFR, with excellent repeatability and good agreement with perfusion-derived measures. This approach shows promise for assessing global myocardial perfusion after physiological exercise without pharmacologic stress, warranting further validation.

Background: High-resolution magnetic resonance imaging (HR-MRI) provides a non-invasive, radiation-free approach for evaluating stenosis caused by carotid atherosclerosis. However, manual recognition is time-consuming and inter-observer variability. We propose a novel architecture for automated segmentation and stenosis evaluation of extracranial carotid arteries by HR-MRI in comparison with digital subtraction angiography (DSA).

Methods: The 641 stenotic arteries from 422 patients retrospectively collected from three tertiary hospitals were divided into a training-validation set (372 patients, 545 lesions) and an independent test set (50 patients, 96 lesions). An external validation set (89 patients, 168 lesions) was collected from the fourth tertiary hospital.

Results: The architecture demonstrated high consistency with manual segmentation and DSA diagnostic criteria, with mean Dice similarity coefficients of 0.97 ± 0.01, 0.96 ± 0.01, and stenosis evaluation accuracies of 0.88, 0.86 on the independent test and external validation set, respectively.

Conclusion: Thus, the proposed architecture achieved accuracy comparable to manual segmentation by physicians and demonstrated high consistency with DSA diagnostic criteria. By shortening diagnostic time and minimizing inter-observer variability, the proposed architecture is promising to offer a reliable, efficient, and intelligent tool for diagnosing head and neck atherosclerotic disease and assessing stroke risk.

Background: Physiological remodeling of the athlete's heart can resemble certain cardiomyopathies, underscoring the importance of robust reference standards. However, most cardiac magnetic resonance imaging (CMR) based studies focus on a narrow subset of adult athletes, providing limited insight into the broader spectrum of exercise-induced changes. Here, we aimed to characterize volumetric, functional, and strain-based adaptations across varying physical activity levels, age groups, and sexes and to establish reference ranges.

Methods: We enrolled 656 participants (13-35 years) in a cardiovascular screening program at our tertiary center (2009-2020). We excluded individuals with cardiac disease, risk factors, or abnormal screening findings. Participants were categorized as sedentary (≤3hours/week), recreational (4-6hours/week), or highly trained (>6hours/week) athletes. CMR was performed using 1.5T scanners to assess ventricular and atrial volumes, myocardial mass, ejection fractions, and feature-tracking strain. We derived 95% prediction intervals stratified by age, sex, and training volume.

Results: Of the 575 healthy subjects, 390 were highly trained athletes (22±6 years, 64% male, 19±7 training hours/week), 102 recreational athletes (23±6 years, 60% male, 4±1 training hours/week), and 83 sedentary individuals (26±4 years, 42% male, 1±1 training hours/week). Increasing weekly training hours were associated with larger ventricular volumes, higher myocardial mass, lower ejection fractions, and strain. Compared to sedentary individuals, highly trained athletes had significantly larger left and right ventricular volumes (LVEDVi estimate [95% CI]: 0.82 [0.52-1.12], p<0.001), higher myocardial mass (LVMI 0.59 [0.31-0.86], p<0.001), and increased left and right atrial volumes, even after adjusting for age, sex, and weekly training hours. We observed a non-uniform dose-response relationship across activity levels, with the most prominent cardiac adaptations occurring in highly trained athletes. Endurance athletes exhibited the most pronounced volumetric changes among the sport types. Finally, we derived stratified prediction intervals to provide CMR reference ranges in young, healthy individuals stratified by age, sex, general activity level, and weekly training hours.

Conclusions: This work underscores the influence of age, sex, physical activity level, and type of sports on cardiac adaptation. We provide prediction interval-based CMR reference ranges of volumes, mass, ejection fraction, and strain to improve disease discrimination in athletes.