Journal of Cardiovascular Magnetic Resonance最新文献

Background: Alpha-protein kinase 3 (ALPK3) was recently identified as a candidate gene associated with hypertrophic cardiomyopathy (HCM). However, clinical data regarding carriers of ALPK3 variants are limited. Therefore, this study amied to evaluate the prevalence of heterozygous ALPK3 variants in adult patients with HCM and to elucidate the phenotypes of individuals harboring these variants.

Methods: 575 consecutive patients diagnosed with HCM who underwent 3T cardiovascular magnetic resonance (CMR) imaging and whole-exome sequencing genetic testing were recruited. Patients harboring ALPK3 rare missense variants (minor allele frequency < 0.0005) or truncating variants were considered genotype-positive.

Results: Among the 575 included patients (65.0% [374/575] male; median age: 50 [40-61] years), 37 (6.43%) showed heterozygous ALPK3 variants. In comparison with sarcomere variant carriers, ALPK3 heterozygotes showed a higher prevalence of apical hypertrophy (59.5% [22/37] vs 20.2% [66/326], P < 0.001) and a lower fibrosis burden, with a two-fold reduction in the incidence of extensive fibrosis (≥15% left ventricle [LV] mass: 8.1% [3/37] vs 14.7% [48/326], P < 0.001). Patients with single ALPK3 variants were more likely to present with apical HCM (ApHCM; 80.0% [16/20]vs 35.3% [6/17], P, 0.006) and show a lower extent of late gadolinium enhancement (LGE; 1.26 [0.00-5.77] % vs 6.00 [3.63-8.50] %, P, 0.011) than those with both ALPK3 and sarcomere variants. CMR characteristics showed no significant differences between carriers with truncating and missense ALPK3 variants. Moreover, among patients with ApHCM, those with single ALPK3 variants were more likely to present with mixed ApHCM (87.5% [14/16] vs 55.2% [16/29] vs 14.3% [1/7], P < 0.05), a lower extent of LGE (0.67 [0-5.77] % vs 6.32 [2.39-10.90] % vs 3.32 [0.00-4.68] %, P < 0.05), and greater free-wall and apex LGE involvement (85.7% [6/7] vs 41.6% [10/24] vs 50% [2/4]) than those with myosin-binding protein C or β-myosin heavy chain variants.

Conclusion: The clinical phenotype of individuals harboring heterozygous ALPK3 variants showed distinct characteristics, characterized by apical hypertrophy, especially mixed apical hypertrophy, and a lower extent of fibrosis.

Background and purpose: Epicardial adipose tissue (EAT) plays a crucial role in the progression of heart failure (HF). This study employs cardiovascular magnetic resonance (CMR) imaging to investigate potential differences in EAT between patients with heart failure with reduced ejection fraction (HFrEF) and those with heart failure with preserved ejection fraction (HFpEF), as well as the correlation between EAT and biventricular function (myocardial strain).

Methods: We collected data from patients diagnosed with HF at the Second Affiliated Hospital of Kunming Medical University between January 2021 and December 2023. All patients underwent CMR imaging and were categorized into two groups based on left ventricular ejection fraction (LVEF): the HFrEF group and the HFpEF group. Patients without heart failure served as the control group. We gathered clinical baseline data and utilized CVI-42 post-processing software to obtain parameters related to cardiac structure and function, including LVEF, global radial strain (GRS), global longitudinal strain (GLS), EAT, pericardial adipose tissue (PeAT), paracardial adipose tissue (PaAT), and wall stress. We compared differences in parameters among the three groups and conducted pairwise comparisons. Additionally, we performed correlation analyses of EAT and PeAT with GLS and body mass index (BMI) within the HFrEF and HFpEF cohorts.

Results: A total of 104 patients with HFrEF, 226 patients with HFpEF, and 172 patients without heart failure were ultimately included in the study. Significant statistical differences were observed among the three groups regarding age, smoking status, diabetes, brain natriuretic peptide (BNP) levels, BMI, EAT, PeAT, PaAT, wall stress, GLS, and GRS of both ventricles (p<0.05). The EAT volume in HFrEF patients (32±14 mL) was lower than that in HFpEF patients (51±21 mL) and the control group (33±19 mL). Additionally, PeAT and PaAT levels were higher in HFpEF patients compared to those in HFrEF and the control group. Correlation analysis revealed that in HFrEF patients, EAT accumulation was associated with better left ventricular (LV) function (LVGLS, r=0.85, p<0.01) and right ventricular (RV) function (RVGLS, r=0.73, p<0.01). Conversely, in HFpEF patients, EAT accumulation correlated with poorer LV (LVGLS, r=-0.67, p<0.01) and RV (RVGLS, r=0.55, p<0.01) function.

Conclusion: EAT was greater in patients with HFpEF compared to HFrEF. In the HFpEF group, increased EAT was correlated with worsening biventricular function, while the opposite trend was observed in the HFrEF group.

Background: Sodium-glucose cotransporter 2 (SGLT2) inhibitors improve metabolic and cardiovascular outcomes, but the mechanisms remain incompletely understood. We utilized cardiovascular magnetic resonance (CMR) and complementary methods to investigate whether preventive SGLT2 inhibitor administration attenuates the development of metabolic heart disease in a high-fat, high-sucrose diet (HFHSD) mouse model.

Methods: Male wild-type (WT) C57BL/6 J mice were fed an HFHSD for 18 weeks to induce obesity, coronary microvascular disease, and diastolic dysfunction. WT mice treated preventively with an SGLT2 inhibitor, empagliflozin (EMPA), were compared to untreated WT mice, and mice fed either an HFHSD or standard chow diet with myeloid cell-specific knockout of the Nos2 gene (Nos2^LysMCre) were compared to floxed controls (Nos2^fl/fl). CMR assessed epicardial adipose tissue (EAT) volume, fatty acid composition (FAC), proton density fat fraction (PDFF), and T1, and myocardial perfusion, and strain. EAT FAC, PDFF, and T1 were quantified using an inversion-recovery multi-echo gradient-echo sequence and a multi-resonance triglyceride model. EAT volume was quantified using cine images. Myocardial perfusion reserve (MPR) and strain were measured using arterial spin labeling, and displacement encoding with stimulated echoes (DENSE), respectively. Histology and flow cytometry assessed EAT remodeling and macrophage polarization.

Results: EMPA treatment reduced EAT volume (0.36±0.18 µL/g vs 0.61±0.25 µL/g, p<0.01) and saturated fatty acid fraction (38.81 [32.83-47.71]% vs 48.06 [43.82-52.65]%, p<0.05), increased EAT T1 (0.799 [0.764-0.859] s vs 0.755 [0.678-0.772] s, p<0.05), and decreased EAT NOS2⁺ macrophages (34.74 [21.38-42.098^]% vs 46.36 [38.08-61.30]%, p<0.05) compared to controls. EMPA improved diastolic strain rate (2.96 [2.61-3.99] s^-1 vs 1.68 [1.21-2.80] s^-1, p<0.01) and adenosine MPR (2.00±0.54 vs 1.37±0.40, p<0.01) compared to controls. Myeloid cell NOS2 knockout mice fed an HFHSD exhibited improved adenosine MPR (1.90±0.47 vs 1.39±0.38, p<0.01) compared to floxed controls.

Conclusions: In this obesity-related metabolic heart disease model, EMPA treatment prevents cardiometabolic dysfunction by improving EAT quantity and quality, coronary microvascular function, and diastolic function. These benefits are mediated in part through macrophage NOS2.

Background: Heart failure (HF) is a leading cause of morbidity and mortality in the United States and is projected to increase in the next decade. Left ventricular ejection fraction (LVEF) is used to guide optimal medical therapy and is typically quantified using two-dimensional transthoracic echocardiography (TTE) due to ease of accessibility and cost. However, LVEF measurements by cardiovascular magnetic resonance (CMR) are considered the gold standard due to their accuracy and precision. Despite this, CMR is not the first imaging modality selected for LVEF evaluation due to perceptions of long study time, high cost, and inaccessibility. Our study aims to determine the cost of imaging studies (e.g., CMR, TTE) relative to the overall HF-related health care costs and associated outcomes.

Methods: A retrospective single-center cohort study of 420 participants with same-day TTE and CMR from 2009-2019, including participants >18 years of age with good image quality with or at risk for cardiovascular disease. Primary outcome was a composite outcome defined as HF admission, left ventricular assist device, cardiovascular disease-related death, heart transplantation, and implantable cardioverter defibrillator implantation. HF risk groups were determined based on clinically relevant LVEF cutoffs. All costs were calculated and adjusted to 2022 US$.

Results: Participants were 49 ± 17 years old, 52% (219/420) female, 50% (209/420) White, and 41% (174/420) Black. Median follow-up was 4 years. HF was the most common co-morbidity (31%). LVEF measured by CMR predicted HF outcomes better than TTE (p = 0.005). Continuous net reclassification index of CMR LVEF was 0.36 (95% confidence interval: 0.16-0.56); p = 0.001 due to predominant reclassification to lower risk groups. On an individual level, HF health care cost increased from low- to high-risk groups irrespective of modality. High-risk individuals classified by CMR had lower average per-person HF health care costs compared to TTE counterparts. Cost of CMR and TTE was <1% of the total HF health care cost.

Conclusion: The cost of non-invasive imaging studies accounted for <1% of the cost compared to other components of HF care. Downstream cost prediction based on LVEF classification using CMR has the potential to better predict cost burden compared to TTE in patients with HF.

Background: Cardiac functional metrics such as ejection fraction, strain, and valve excursion are important diagnostic and prognostic measures of cardiac disease. However, they ignore a large amount of systolic shape change information available from modern cardiovascular magnetic resonance (CMR) examinations. We aimed to automatically quantify multidimensional shape and motion scores from CMR, investigate covariates, and test their discrimination of disease in the UK Biobank compared against standard functional metrics.

Methods: An automated analysis pipeline was used to obtain quality-controlled three-dimensional left and right ventricular shape models in 38,858 UK Biobank participants, 5149 of whom had one or more diagnoses of cardiovascular or cardiometabolic disease. Principal component analysis was used to obtain a statistical shape atlas and quantify each participant's left and right ventricular shape at both end-diastole and end-systole simultaneously. Systolic strain was obtained from arc length changes computed from the shape model, and mitral/tricuspid annular plane systolic excursion (MAPSE/TAPSE) was computed from the displacement of the valves. Discrimination for prevalent disease was quantified using linear discriminant analysis area under the receiver operating characteristic curve.

Results: The first 25 principal component scores captured >90% of the total shape variance. Significantly stronger discrimination for atrial fibrillation, heart failure, diabetes, ischemic disease, and conduction disorders (p<0.001 for each) was obtained using shape scores compared with volumes, ejection fractions, strains, MAPSE, and TAPSE.

Conclusion: Automatically derived shape and motion z-scores capture more discriminative information on disease effects than standard metrics, including volumes, ejection fraction, strain and valve excursions.

Background: Cardiovascular magnetic resonance (CMR) is a complex imaging modality requiring a broad variety of image processing tasks for comprehensive assessment of the study. Recently, foundation models (FM) have shown promise for automated image analyses in natural images (NI). In this study, a CMR-specific vision FM was developed and then finetuned in a supervised manner for nine different imaging tasks typical to a CMR workflow, including classification, segmentation, landmark localization, and pathology detection.

Methods: A ViT-S/8 model was trained in a self-supervised manner using DINO on 36 million CMR images from 27,524 subjects from three sources (UK Biobank and two clinical centers). The model was then finetuned for nine tasks: classification (sequence, cine view), segmentation (cine SAX, cine LAX, LGE SAX, Mapping SAX), landmark localization, pathology detection (LGE, cardiac disease), on data from various sources (both public and three clinical datasets). The results were compared against metrics from state-of-the-art methods on the same tasks. A comparable baseline model was also trained on the same datasets for direct comparison. Additionally, the effect of pretraining strategy, as well as generalization and few-shot performance (training on few labeled samples) was explored for the pretrained model, compared to the baseline.

Results: The proposed model obtained similar performance or moderate improvements to results reported in the literature in most tasks (except disease detection), without any task-specific optimization of methodology. The proposed model outperformed the baseline in most cases, with an average increase of 6.8% points (pp) for cine view classification, and 0.1 to 1.8 pp for segmentation tasks. The proposed method also obtained generally lower standard deviations in the metrics. Improvements of 3.7 and 6.6 pp for hyperenhancement detection from LGE and 14 pp for disease detection were observed. Ablation studies highlighted the importance of pretraining strategy, architecture, and the impact of domain shifts from pretraining to finetuning. Moreover, CMR-pretrained model achieved better generalization and few-shot performance compared to the baseline.

Conclusions: Vision FM specialized for medical imaging can improve accuracy and robustness over NI-FM. Self-supervised pretraining offers a resource-efficient, unified framework for CMR assessment, with the potential to accelerate the development of deep learning-based solutions for image analysis tasks, even with few annotated data available.

Background: Exercise cardiovascular magnetic resonance (ExCMR) imaging using supine in-scanner ergometer has shown promise in differentiating pathological dilated cardiomyopathy (DCM) from physiological exercise-induced cardiac remodeling. Since 2020, the National Heart Centre Singapore (NHCS) has incorporated ExCMR into its clinical workflow for patients with suspected DCM. This study aims to compare the costs associated with ExCMR versus conventional CMR in the evaluation of DCM.

Methods: A retrospective analysis was conducted on patients referred for conventional CMR between 2016 and 2019, and those referred for ExCMR from 2020 to 2023. Both imaging modalities followed standardized protocols, with ExCMR incorporating additional assessments during peak exercise. Costs were recorded in Singapore dollars (SGD) prior to the application of healthcare subsidies.

Results: The total cost for conventional CMR was SGD 1831.36, while ExCMR was associated with a higher initial cost of SGD 2336.48. However, ExCMR resulted in significantly fewer abnormal imaging findings and a reduced need for follow-up investigations (6.5% (9/139) vs 56.8% (71/125), p<0.001). A decision tree analysis and probabilistic sensitivity analysis (PSA) revealed that diagnosing 1000 suspected DCM patients with ExCMR could result in a cost savings of approximately SGD 182,323 compared to conventional CMR, with a 64% probability of being cost-effective.

Conclusion: These findings indicate that ExCMR offers a physiologically informative approach for diagnosing DCM, with the potential to reduce overdiagnosis of cardiac dilatation in active, healthy adults. Although further research is necessary to assess long-term outcomes, ExCMR appears to be a cost-effective imaging modality for DCM diagnosis, warranting reconsideration of its perceived higher cost.

Myocardial perfusion imaging plays a central role in the management of patients with known or suspected coronary artery disease (CAD) and increasingly in patients with suspected ischemia with normal coronary arteries (INOCA) as well as anomalous origins of the coronary arteries and Kawasaki disease. Stress perfusion cardiovascular magnetic resonance (CMR) is recognized by international guidelines, with several Class 1 indications for the detection of abnormal myocardial blood flow in these clinical scenarios and offers excellent diagnostic accuracy and independent prognostic value. While visual interpretation of the perfusion data is the prevailing analysis method in clinical practice, quantitative perfusion CMR is at least as accurate for the detection of significant obstructive CAD and provides a more accurate estimation of the total ischemic burden in patients with CAD. Moreover, quantitative myocardial perfusion analysis provides unique insights into the pathophysiology of myocardial ischemia, including microvascular disease in INOCA. Quantitative perfusion CMR can be fully automated, is user-independent, and may facilitate more widespread use of the modality. The aim of this Society for Cardiovascular Magnetic Resonance (SCMR) expert consensus document is to provide recommendations for the acquisition and analysis of quantitative myocardial perfusion CMR to facilitate standardization of methodology. This paper also discusses research and development goals to address current limitations, to ensure data reliability and validity, to create the basis for future multi-vendor and multicenter research, and to broaden the clinical use of quantitative perfusion CMR.

Background: Conventional cardiovascular magnetic resonance (CMR) examinations require patients to repeatedly hold their breath, which can reduce examination efficiency and pose challenges for patients unable to do so. This study aimed to demonstrate the feasibility and effectiveness of a full free-breathing CMR protocol in clinical practice.

Methods: Patients prospectively enrolled in this study underwent a full free-breathing CMR exam on a 3T scanner between June 1 and June 30, 2024. Acquisition time and image quality were assessed. Cine and flow imaging were compared with those acquired with the conventional breath-holding CMR protocol. Other sequences, including T1/T2 mapping and late gadolinium enhancement (LGE), were evaluated quantitatively and qualitatively, respectively. Group comparisons were performed using the Wilcoxon signed-rank test or paired t-test. Consistency was assessed using Kappa statistics, Bland-Altman statistics, intraclass correlation coefficient (ICC), and linear regression.

Results: A total of 211 patients were evaluated (median age: 53 years [IQR: 38-63]; range: 10-82 years; 145 men). The mean acquisition time for full free-breathing CMR was 22.6±3.7 min. The median image quality scores for cine and LGE images acquired with free-breathing CMR were 4 (IQR: 4-4) and 5 (IQR: 4-5), respectively. Compared with conventional breath-holding CMR, the end-diastolic volume (EDV), end-systolic volume (ESV), EDV index, and ESV index measured by free-breathing CMR were slightly higher (all P＜0.05), whereas the left ventricular ejection fraction and left ventricular mass were slightly lower (both P＜0.05). Nonetheless, the two methods demonstrated good agreement and correlation (r values: 0.85-0.99). Native T1 and T2 values in healthy subjects from free-breathing CMR were 1214.9±16.7ms and 38.4±3.2ms, respectively. Among the 211 patients, 147 were LGE positive. Except for five patients with image quality scores below 3, all others had scores of 3 or higher.

Conclusion: Full free-breathing CMR examinations are feasible and effective in clinical practice, significantly reduce scan time while maintaining high image quality.

Background: Electrocardiogram (ECG)-triggered cardiovascular magnetic resonance (CMR) can be challenging in patients with ECG unreliability. Pilot tone (PT)-triggered CMR may offer a reliable alternative.

Purpose: To evaluate the feasibility of PT-triggered CMR and compare its performance with ECG-triggered imaging across various sequences in patients with common cardiovascular diseases.

Methods: This prospective study included 50 participants (26 males, 24 females; mean age 46.0±19.0y), including 15 with normal CMR findings and 35 with various cardiovascular diseases. All participants underwent both PT-triggered and ECG-triggered CMR on a 3T MRI system. Imaging included T2-weighted imaging (T2WI), T1-mapping, T2-mapping, cine, late gadolinium enhancement (LGE), and post-contrast T1-mapping sequences. Image quality and quantitative measurements were evaluated, including T2WI signal intensity, native T1-mapping, T2-mapping, and extracellular volume fraction (ECV) values, and comparative signal-to-noise ratio (compSNR) and comparative contrast-to-noise ratio (compCNR) of cine and LGE images, left/right ventricular function. Inter-reader agreement was evaluated using the intraclass correlation coefficient (ICC). Comparisons between the two methods were performed using paired t-test or the Wilcoxon signed-rank test.

Results: No significant differences were observed in scanning times (p=.253-.864) or image quality (ICC: .589-1.000, p=.057-1.000) between PT- and ECG-triggered scans and images. Quantitative assessments showed good to excellent consistency (ICC=.843-.987). While PT-triggered LGE images showed higher compCNR (14.14±7.68 vs. 13.24±7.52, p=.016), other quantitative parameters showed no significant differences between PT- and ECG-triggered images. Six participants with hypertrophic cardiomyopathy or heart valve disease experienced false R-wave triggering during ECG gating, leading to motion artifacts, which were not visible in PT-triggered images.

Conclusion: PT-triggered cardiac MRI provides comparable image quality and quantitative assessments to ECG-triggered sequences and may offer advantages in minimizing motion artifacts, particularly in patients with conditions affecting ECG reliability, making it a promising alternative for cardiac MRI synchronization.