Journal of Cardiovascular Magnetic Resonance最新文献

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.

Background: Cardiovascular magnetic resonance (CMR) imaging with contrast enhancement (CE) of the coronary artery wall was proved effective for detecting coronary involvement in IgG4-related disease (IgG4-RD). This study seeks to further investigate the value of coronary wall CE on CMR in assessing treatment response.

Methods: We prospectively enrolled 30 IgG4-RD patients with coronary involvement and conducted follow-up evaluations. All participants underwent coronary wall imaging with CMR, both before and after treatment with a combination of glucocorticoids and steroid-sparing immunosuppression. Concurrently, inflammatory-related laboratory markers and IgG4-RD Responder Index (RI) scores were collected and analyzed.

Results: Most patients (87%) exhibited a significant monthly reduction in total coronary wall CE area (ΔCE area/months=0.32 [IQR: 0.03-0.88] cm²/month) and contrast-to-noise ratio (CNR) (ΔCNR/months=0.09 [IQR: 0.01-0.41]/month). Both parameters were positively correlated with monthly changes in inflammatory markers, including ΔIgG4/months (r=0.366 and 0.388, respectively), ΔESR/months (r=0.617 and 0.539), ΔIgG/months (r=0.565 and 0.578), and ΔIgE/months (r=0.512 and 0.499) (all P<0.05). In the "heart/pericardium" organ-specific domain of the IgG4-RD RI, the rate of change in the modified index (RI') incorporating coronary wall CE was significantly greater than that of the standard RI (ΔRI'/months vs. ΔRI/months: 0.1 vs. 0, P=0.006). Similarly, in the overall multi-organ assessment, ΔRI'/months showed a significant improvement over ΔRI/months (0.68 vs. 0.67, P=0.006). Moreover, ΔCE area/months correlated positively with both ΔRI/months (r =0.627, P<0.001) and ΔRI'/months (r=0.683, P< 0.001). ΔCNR/months also correlated positively with ΔRI/months (r=0.500, P =0.005) and ΔRI'/months (r=0.548, P=0.002).

Conclusion: Glucocorticoid combined with steroid-sparing immunosuppression therapy is effective in treating IgG4-RD with coronary involvement. Coronary wall CE on CMR emerges as a valuable imaging biomarker that complements serological markers in assessing treatment response. Incorporating coronary wall CE enhances Responder Index scoring, aiding therapeutic decisions and disease monitoring.

Background: Reduced biventricular global function index (BVGFI) is associated with adverse outcomes in repaired tetralogy of Fallot (rTOF). The change in BVGFI associated with pulmonary valve replacement (PVR) is unknown.

Objectives: To characterize BVGFI following PVR in rTOF and identify pre-PVR factors associated with severely depressed post-PVR BVGFI.

Methods: Single-center retrospective cohort study of rTOF patients with a cardiac magnetic resonance (CMR) examination within 1 year before and 2 years after their first PVR and no interval cardiac procedures (n=133). CMR parameters between rTOF and normal controls (n=136) were compared. BVGFI was categorized as normal (≥46.2), mild-moderately depressed (40.0-46.1), or severely depressed (<40.0). Pre- vs. post-PVR changes and pre-PVR correlates of severely depressed post-PVR BVGFI were explored.

Results: When adjusted for age and sex, pre-PVR BVGFI was lower in patients with rTOF compared to controls (47.7±0.6 vs. 56.0±0.5, p<0.001), with 48% of rTOF patients having subnormal pre-PVR BVGFI. Overall, compared with pre-PVR values, mean BVGFI did not change after PVR (46.6±7.7 vs. 45.6±6.7, p=0.28), while RVGFI declined from 49.6±10.2 pre-PVR to 46.1±9.0 post-PVR (p=0.003). Among patients with normal pre-PVR BVGFI (n=69), 64% remained normal, whereas 36% declined. Of those with severely depressed pre-PVR BVGFI (n=24), 50% remained severely depressed, and only 4% achieved normalization of BVGFI after PVR. Factors independently associated with severely depressed post-PVR BVGFI were lower pre-PVR BVGFI, male sex, moderate or severe pulmonary regurgitation (PR), and higher left ventricular end-systolic volume index (LVESVi). Type of pre-PVR hemodynamic load was not associated with the odds of severely depressed BVGFI post-PVR.

Conclusions: BVGFI is depressed in about half of rTOF patients pre-PVR and did not significantly change post-PVR remaining stable in most patients. Lower pre-PVR BVGFI, male sex, moderate or severe PR, and higher LVESVi are independently associated with severely depressed post-PVR BVGFI.

Background: Right heart catheterisation (RHC) with pulmonary capillary wedge pressure (PCWP) assessment is the reference standard for diagnosis of heart failure with preserved ejection fraction (HFpEF), remains however largely underused. Different approaches for non-invasive PCWP calculation have been proposed. However, as left atrial strain (LA Es) and volume index (ESVi) emerge as a key-criteria in HFpEF, we sought to investigate them for PCWP calculation.

Methods: The derivation population consisted of patients referred to RHC and cardiovascular magnetic resonance (CMR) imaging who were enrolled in a prospective monocentric registry. Patients were classified by RHC according to current guideline recommendations. The external validation population consisted of patients included in the HFpEF-Stress trial who underwent exercise-stress RHC and CMR with follow-up after 4 years for hospitalised cardiovascular events. Performance of strain-derived PCWP was compared to a published LA volume (LAV) and LV mass (LVM) derived method.

Results: The derivation population consisted of n=209 patients, n=123 underwent exercise-stress RHC (n=55 without PH, n=72 pre-capillary, n=27 combined post- and pre-capillary pulmonary hypertension (CpcPH), n=15 isolated post-capillary pulmonary hypertension (IpcPH), n=34 exercise and n=6 unclassified PH). Linear regressions models identified the following formulae for functional PCWPrest 10.304-0.095*Es+0.098*ESVi and functional PCWPstress 24.666-0.251*Es+0.056*ESVi calculation. The validation population consisted of n=74 patients (n=15 without, n=5 pre-capillary, n=8 CpcPH, n=10 IpcPH and n=32 exercise PH with n=4 remaining unclassified). Functional PCWPrest (11.8) and RHC-derived PCWPrest (11mmHg) were statistically similar (p=0.285) and showed moderate correlation (r=0.53, p<0.001). Functional PCWPrest (AUC 0.80) and PCWPstress (AUC 0.85) accurately identified HFpEF patients, were superior to LAV/LVM based PCWP (AUC 0.67, p≤0.002) and showed prognostic implications (HR 1.37 (1.16-1.62) and 1.29 (1.14-1.46), p<0.001).

Conclusions: Functional PCWP may aide in the identification of post-capillary involvement in PH and HFpEF superiorly compared to morphology-derived PCWP and shows prognostic implications.

Background: Extracellular volume fraction (ECV) is an independent predictor of mortality in aortic stenosis (AS). ECV can be measured using myocardial T1 maps acquired before and after contrast administration. Standard ECV measurements do not consider the limited rate of water exchange (WX) between cardiomyocytes and the extracellular matrix which can result in underestimated ECV at higher contrast agent concentrations.

Objectives: The objective was to estimate ECV in patients with severe AS before and after surgical aortic valve replacement (AVR) using a 2-site exchange model (2SXM) that also enables estimates of the intracellular lifetime of water (τ_ic; an indicator of the minor diameter of the cardiomyocytes).

Methods: 20 patients (67±6 years) with severe AS, referred for AVR, underwent MRI on a 3 T MR system before and 6 months after AVR. T1 measurements were made using a multiparametric saturation-recovery single-shot acquisition before and at four time points post-injection of contrast agent. A 2SXM and standard linear model (LM) were used to estimate ECV and, when combined with indexed left ventricular mass (LVMI), to calculate cell and matrix volumes, (LVMI × (1-ECV)/1.05) and (LVMI × ECV/1.05), respectively. The 2SXM model was also used to estimate τ_ic.

Results: Data were acquired before and 174 (157 to 267) days after AVR. LVMI reduced following AVR, from 78±15 g/m² to 63±11 g/m² (p<0.001). ECV estimates increased from 22±3% to 28±5% (p<0.001) using the LM compared to 28±5% to 32±4% (p = 0.005) using the 2SXM. Indexed cell volume decreased from 58±12 cm³/m² to 43±9 cm³/m² (p<0.001; LM) and from 54±12 cm³/m² to 41±8 cm³/m² (p<0.001; 2SXM). Indexed matrix volume did not change significantly by either method (LM, 16±4 cm³/m² to 17±3 cm³/m²; 2SXM, 20±5 cm³/m² to 19±3 cm³/m²). τ_ic decreased from 0.21±0.12 s to 0.12±0.09 s (p = 0.007).

Conclusion: Cellular hypertrophy regressed 6 months following AVR; the extracellular matrix volume did not change significantly. τ_ic decreased post-AVR, indicating that the reduction in cell volume can be largely attributed to a reduction in cardiomyocyte diameter.

Background: Free-running (FR) cardiac MRI enables free-breathing ECG-free fully dynamic 5D (3D spatial+cardiac+respiration dimensions) imaging but poses significant challenges for clinical integration due to the volume of data and complexity of image analysis. Existing segmentation methods are tailored to 2D cine or static 3D acquisitions and cannot leverage the unique spatial-temporal wealth of FR data.

Purpose: To develop and validate a deep learning (DL)-based segmentation framework for isotropic 3D+cardiac cycle FR cardiac MRI that enables accurate, fast, and clinically meaningful anatomical and functional analysis.

Methods: Free-running, contrast-free bSSFP acquisitions at 1.5T and contrast-enhanced GRE acquisitions at 3T were used to reconstruct motion-resolved 5D datasets. From these, the end-expiratory respiratory phase was retained to yield fully isotropic 4D datasets. Automatic propagation of a limited set of manual segmentations was used to segment the left and right ventricular blood pool (LVB, RVB) and left ventricular myocardium (LVM) on reformatted short-axis (SAX) end-systolic (ES) and end-diastolic (ED) images. These were used to train a 3D nnU-Net model. Validation was performed using geometric metrics (Dice similarity coefficient [DSC], relative volume difference [RVD]), clinical metrics (ED and ES volumes, ejection fraction [EF]), and physiological consistency metrics (systole-diastole LVM volume mismatch and LV-RV stroke volume agreement). To assess the robustness and flexibility of the approach, we evaluated multiple additional DL training configurations such as using 4D propagation-based data augmentation to incorporate all cardiac phases into training.

Results: The main proposed method achieved automatic segmentation within a minute, delivering high geometric accuracy and consistency (DSC: 0.94 ± 0.01 [LVB], 0.86 ± 0.02 [LVM], 0.92 ± 0.01 [RVB]; RVD: 2.7%, 5.8%, 4.5%). Clinical LV metrics showed excellent agreement (ICC > 0.98 for EDV/ESV/EF, bias < 2mL for EDV/ESV, < 1% for EF), while RV metrics remained clinically reliable (ICC > 0.93 for EDV/ESV/EF, bias < 1mL for EDV/ESV, < 1% for EF) but exhibited wider limits of agreement. Training on all cardiac phases improved temporal coherence, reducing LVM volume mismatch from 4.0% to 2.6%.

Conclusion: This study validates a DL-based method for fast and accurate segmentation of whole-heart free-running 4D cardiac MRI. Robust performance across diverse protocols and evaluation with complementary metrics that match state-of-the-art benchmarks supports its integration into clinical and research workflows, helping to overcome a key barrier to the broader adoption of free-running imaging.