Journal of Cardiovascular Magnetic Resonance最新文献

Background: Individuals with a Fontan circulation encompass a heterogeneous group with adverse outcomes linked to ventricular dilation, dysfunction, and dyssynchrony. The purpose of this study was to assess if unsupervised machine learning cluster analysis of cardiovascular magnetic resonance (CMR)-derived dyssynchrony metrics can separate ventricles in the Fontan circulation from normal control left ventricles and identify prognostically distinct subgroups within the Fontan cohort.

Methods: This single-center, retrospective study used 503 CMR studies from Fontan patients (median age 15 y) and 42 from age-matched controls from January 2005 to May 2011. Feature tracking on short-axis cine stacks assessed radial and circumferential strain, strain rate, and displacement. Unsupervised K-means clustering was applied to 24 mechanical dyssynchrony metrics derived from these deformation measurements. Clusters were compared for demographic, anatomical, and composite outcomes of death, or heart transplantation.

Results: Four distinct phenotypic clusters were identified. Over a median follow-up of 4.2 y (interquartile ranges 1.7-8.8 y), 58 (11.5%) patients met the composite outcome. The highest-risk cluster (largely comprised of right or mixed ventricular morphology and dilated, dyssynchronous ventricles) exhibited a higher hazard for the composite outcome compared to the lowest-risk cluster while controlling for ventricular morphology (hazard ratio [HR] 6.4; 95% confidence interval [CI] 2.1-19.3; P value 0.001) and higher indexed end-diastolic volume (HR 3.2; 95% CI 1.04-10.0; P value 0.043) per 10 mL/m².

Conclusion: Unsupervised machine learning using CMR-derived dyssynchrony metrics identified four distinct clusters of patients with Fontan circulation and healthy controls with varying clinical characteristics and risk profiles. This technique can be used to guide future studies and identify more homogeneous subsets of patients from an overall heterogeneous population.

Background: Clinical guidelines and scientific data increasingly support the appropriate use of cardiovascular magnetic resonance (CMR) . The extent of CMR adoption across the United States (US) remains unclear. This observational analysis aims to capture CMR practice patterns in the US.

Methods: Commissioned reports from the Society for Cardiovascular Magnetic Resonance (SCMR), pre-existing survey data from CMR centers, and socioeconomic and coronary heart disease data from the Centers for Disease Control and Prevention were used. The location of imaging centers performing CMR was based on 2018 Medicare claims. Secondary analysis was performed on center-specific survey data from 2017-2019, which were collected by members of the SCMR US Advocacy Subcommittee for quality improvement purposes. The correlation between the number of imaging centers billing for CMR services per million persons, socioeconomic determinants, and coronary heart disease epidemiology was determined.

Results: A total of 591 imaging centers billed the Center for Medicare & Medicaid Services for CMR services in 2018 and 112 (of 155) unique CMR centers responded to the survey. In 2018, CMR services were available in almost all 50 states. Minnesota was the state with the highest number of CMR centers per million Medicare beneficiaries (52.6 centers per million), and Maine had the lowest (4.4 per million). The total density of CMR centers was 16 per million for US Medicare beneficiaries. Sixty-eight percent (83 of 112) of survey responders were cardiologists, and 28% (31/112) were radiologists. In 72% (71/112) of centers, academic health care systems performed 81%-100% of CMR exams. The number of high-volume centers (>500 scans per year) increased by seven between 2017 and 2019. In 2019, 53% (59/112) of centers were considered high-volume centers and had an average of 19 years of experience. Centers performing <50 scans had on average 3.5 years of experience. Approximate patient wait time for a CMR exam was 2 weeks to 1 month.

Conclusion: Despite increasing volume and availability in almost all 50 states, CMR access remains geographically variable. Advocacy efforts to improve access and innovations that reduce imaging time and exam complexity have the potential to increase the adoption of CMR technology.

Background: While late gadolinium enhancement (LGE) is proposed as a diagnostic criterion for arrhythmogenic right ventricular cardiomyopathy (ARVC), the potential of LGE to distinguish ARVC from differentials remains unknown. We aimed to assess the diagnostic value of LGE for ARVC diagnosis.

Methods: We included 132 subjects (60% male, 47 ± 11 years) who had undergone cardiac magnetic resonance imaging with LGE assessment for ARVC or ARVC differentials. ARVC was diagnosed as per 2010 Task Force Criteria (n = 55). ARVC differentials consisted of familial/genetic dilated cardiomyopathy (n = 25), myocarditis (n = 13), sarcoidosis (n = 20), and amyloidosis (n = 19). The diagnosis of all differentials was based on the most current standard of reference. The presence of LGE was evaluated using a 7-segment right ventricle (RV) and 17-segment left ventricle (LV) model. Subsequently, we assessed LGE patterns for every patient individually for fulfilling LV- and/or RV-LGE per Padua criteria, independent of their clinical diagnosis (i.e. phenotype). Diagnostic values were analyzed using sensitivity and specificity for any RV-LGE, any LV-LGE, RV-LGE per Padua criteria, and prevalence graphs for LV-LGE per Padua criteria. The optimal integration of LGE for ARVC diagnosis was determined using classification and regression tree analysis.

Results: One-third (38%) of ARVC patients had RV-LGE, while half (51%) had LV-LGE. RV-LGE was less frequently observed in ARVC vs non-ARVC patients (38% vs 58%, p = 0.034) leading to a poor discriminatory potential (any RV-LGE: sensitivity 38%, specificity 42%; RV-LGE per Padua criteria: sensitivity 36%, specificity 44%). Compared to ARVC patients, non-ARVC patients more often had LV-LGE (91% vs 51%, p < 0.001) which was also more globally distributed (median 9 [interquartile range (IQR): 3-13] vs 0 [IQR: 0-3] segments, p < 0.001). The absence of anteroseptal and absence of extensive (≥5 segments) mid-myocardial LV-LGE, and absence of moderate (≥2 segments) mid-myocardial LV-LGE predicted ARVC with good diagnostic performance (sensitivity 93%, specificity 78%).

Conclusion: LGE is often present in ARVC differentials and may lead to false positive diagnoses when used without knowledge of LGE patterns. Moderate RV-LGE without anteroseptal and mid-myocardial LV-LGE is typically observed in ARVC.

Background: Cardiovascular magnetic resonance (CMR) is increasingly utilized to evaluate expanding cardiovascular conditions. The Society for Cardiovascular Magnetic Resonance (SCMR) Registry is a central repository for real-world clinical data to support cardiovascular research, including those relating to outcomes, quality improvement, and machine learning. The SCMR Registry is built on a regulatory-compliant, cloud-based infrastructure that houses searchable content and Digital Imaging and Communications in Medicine images. The goal of this study is to summarize the status of the SCMR Registry at 150,000 exams.

Methods: The processes for data security, data submission, and research access are outlined. We interrogated the Registry and presented a summary of its contents.

Results: Data were compiled from 154,458 CMR scans across 20 United States sites, containing 299,622,066 total images (∼100 terabytes of storage). Across reported values, the human subjects had an average age of 58 years (range 1 month to >90 years old), were 44% (63,070/145,275) female, 72% (69,766/98,008) Caucasian, and had a mortality rate of 8% (9,962/132,979). The most common indication was cardiomyopathy (35,369/131,581, 27%), and most frequently used current procedural terminology code was 75561 (57,195/162,901, 35%). Macrocyclic gadolinium-based contrast agents represented 89% (83,089/93,884) of contrast utilization after 2015. Short-axis cines were performed in 99% (76,859/77,871) of tagged scans, short-axis late gadolinium enhancement (LGE) in 66% (51,591/77,871), and stress perfusion sequences in 30% (23,241/77,871). Mortality data demonstrated increased mortality in patients with left ventricular ejection fraction <35%, the presence of wall motion abnormalities, stress perfusion defects, and infarct LGE, compared to those without these markers. There were 456,678 patient-years of all-cause mortality follow-up, with a median follow-up time of 3.6 years.

Conclusion: The vision of the SCMR Registry is to promote evidence-based utilization of CMR through a collaborative effort by providing a web mechanism for centers to securely upload de-identified data and images for research, education, and quality control. The Registry quantifies changing practice over time and supports large-scale real-world multicenter observational studies of prognostic utility.

Background: Myocardial strain is a more sensitive parameter for cardiac function evaluation than left ventricular ejection fraction (LVEF). This study aimed to assess the predictive value of left ventricular global longitudinal strain (LV-GLS) by feature tracking-cardiac magnetic resonance (FT-CMR) imaging in patients with known or suspected coronary artery disease (CAD) with preserved left ventricular systolic function.

Methods: This retrospective cohort analysis enrolled patients with known or suspected CAD who underwent cardiac magnetic resonance imaging from September 2017 to December 2019. LV-GLS was analyzed via feature-tracking analysis. Patients with LVEF <50% were excluded. The composite outcome comprised all-cause death, non-fatal myocardial infarction, and heart failure.

Results: There was a total of 2613 patients. Mean follow-up duration was 39.7 ± 13.9 months. During follow-up, 194 patients (7.4%) experienced a composite outcome. The best cutoff of LV-GLS in the prediction of composite outcome from receiver operating characteristics was -14.4%. Patients were classified into 2 groups according to the LV-GLS; 1489 (57.0%) had LV-GLS <-14.4% and 1124 (43.0%) had LV-GLS ≥-14.4%. Patients with LV-GLS ≥-14.4% had a significantly higher rate of composite outcome than LV-GLS <-14.4% patients (3.59 vs. 1.39 per 100 person-years, respectively; p < 0.001). Multivariable analysis showed that patients with LV-GLS ≥-14.4% had a significantly higher risk of experiencing a composite outcome event compared to global longitudinal strain <-14.4% patients (adjusted hazard ratio: 1.83, 95% confidence interval: 1.28-2.61; p = 0.001).

Conclusion: LV-GLS by FT-CMR was shown to be useful for predicting the prognosis of patients with known or suspected CAD with preserved left ventricular systolic function. LV-GLS -14.4% was the identified cutoff for prognostic determination.

Background: The presence of mitral annulus disjunction (MAD) has been considered a high-risk feature for sudden cardiac death based on selected study populations. We aimed to assess the prevalence of MAD in consecutive patients undergoing clinically indicated cardiovascular magnetic resonance (CMR), its association with ventricular arrhythmias, mitral valve prolapse (MVP), and other CMR features.

Methods: This single-center retrospective study included consecutive patients referred to CMR at our institution between June 2021 and November 2021. MAD was defined as a ≥1 mm displacement between the left atrial wall-mitral valve leaflet junction and the left ventricular wall during end-systole. MAD extent was defined as the maximum longitudinal displacement. Associates of MAD were evaluated at univariable and multivariable regression analysis. The study endpoint, a composite of (aborted) sudden cardiac death, unexplained syncope, and sustained ventricular tachycardia, was evaluated at a 12-month follow-up.

Results: Four hundred and forty-one patients 55 ± 18 years, 267/441 (61%) males) were included, and 29/441 (7%) had MVP. The prevalence of MAD ≥1 mm, 4 mm, and 6 mm was 214/441 (49%), 63/441 (14%), and 15/441 (3%), respectively. Patients with MVP showed a higher prevalence of MAD greater than 1 mm (26/29 (90%) vs 118/412 (46%)); p < 0.001), 4 mm (14/29 (48%) vs 49/412 (12%)); p < 0.001), and 6 mm (3/29 (10%) vs 12/412 (3%)); p = 0.03), and a greater MAD extent (4.2 mm, 3.0-5.7 mm vs 2.8 mm, 1.9-4.0 mm; p < 0.001) compared to patients without MVP. MVP was the only morpho-functional abnormality associated with MAD at multivariable analysis (p < 0.001). A high burden of ventricular ectopic beats at baseline Holter-electrocardiogram was associated with MAD ≥4 mm and MAD extent (p < 0.05). The presence of MAD ≥1 mm (0.9% vs 1.8%; p = 0.46), MAD ≥4 mm (1.6% vs 1.3%; p = 0.87), or MVP (3.5% vs 1.2%; p = 0.32) were not associated with the study endpoint, whereas patients with MAD ≥6 mm showed a trend toward a higher likelihood of the study endpoint (6.7% vs 1.2%; p = 0.07).

Conclusion: MAD of limited severity was common in consecutive patients undergoing CMR. Patients with MVP showed higher prevalence and greater extent of MAD. Extended MAD was rarer and showed association with ventricular arrhythmias at baseline. The mid-term prognosis of MAD seems benign; however, prospective studies are warranted to search for potential "malignant MAD extents" to improve patients' risk stratification.

Background: In double aortic arch (DAA), one of the arches can demonstrate atretic portions postnatally, leading to diagnostic uncertainty due to overlap with isolated right aortic arch (RAA) variants. The main objective of this study is to demonstrate the morphological evolution of different DAA phenotypes from prenatal to postnatal life using three-dimensional (3D) fetal cardiac magnetic resonance (CMR) imaging and postnatal computed tomography (CT)/CMR imaging.

Methods: Three-dimensional fetal CMR was undertaken in fetuses with suspected DAA over a 6-year period (January 2016-January 2022). All cases with surgical confirmation of DAA were retrospectively studied and morphology on fetal CMR was compared to postnatal CT/CMR and surgical findings.

Results: Thirty-four fetuses with surgically confirmed DAA underwent fetal CMR. The RAA was dominant in 32/34 (94%). Postnatal CT/CMR was undertaken at a median age of 3.3 months (interquartile range 2.0-3.9) demonstrating DAA with patency of both arches in 10/34 (29%), with 7 showing signs of coarctation of the left aortic arch (LAA). The LAA isthmus was not present on CT/CMR in 22/34 (65%), and the transverse arch between left carotid and left subclavian artery was not present in 2 cases.

Conclusion: Fetal CMR provides novel insights into perinatal evolution of DAA. The smaller LAA can develop coarctation or atresia related to postnatal constriction of the arterial duct, making diagnosis of DAA challenging with contrast-enhanced CT/CMR. This highlights the potentially important role for prenatal 3D vascular imaging and might improve the interpretation of postnatal imaging.

Background: The prognostic value of myocardial deformation parameters in adults with repaired tetralogy of Fallot (rTOF) has not been well-elucidated. We therefore aimed to explore myocardial deformation parameters for outcome prediction in adults with rTOF using cardiovascular magnetic resonance imaging (CMR).

Methods: Adults with rTOF and at least moderate pulmonary regurgitation were identified from an institutional prospective CMR registry. Left ventricular (LV) and right ventricular (RV) global strains were recorded in longitudinal (GLS), circumferential (GCS), and radial (GRS) directions. Major adverse cardiovascular events (MACE) were defined as a composite of mortality, resuscitated sudden death, sustained ventricular tachycardia (>30 seconds), or heart failure (hospital admission >24 hours). In patients with pulmonary valve replacement (PVR), pre- and post-PVR CMR studies were analyzed to assess for predictors of complete RV reverse remodeling, defined as indexed RV end-diastolic volume (RVEDVi) <110 mL/m². Logistic regression models were used to estimate the odds ratio (OR) per unit change in absolute strain value associated with clinical outcomes and receiver operator characteristic curves were constructed with area under the curve (AUC) for select CMR variables.

Results: We included 307 patients (age 35 ± 13 years, 59% (180/307) male). During 6.1 years (3.3-8.8) of follow-up, PVR was performed in 142 (46%) and MACE occurred in 31 (10%). On univariate analysis, baseline biventricular ejection fraction (EF), mass, and all strain parameters were associated with MACE. After adjustment for LVEF, only LV-GLS remained independently predictive of MACE (OR 0.822 [0.693-0.976] p = 0.025). Receiver operator curves identified an absolute LV-GLS value less than 15 and LVEF less than 51% as thresholds for MACE prediction (AUC 0.759 [0.655-0.840] and 0.720 [0.608-0.810]). After adjusting for baseline RVEDVi, RV-GCS (OR 1.323 [1.094-1.600] p = 0.004), LV-GCS (OR 1.276 [1.029-1.582] p = 0.027) and LV-GRS (OR 1.101 [1.0210-1.200], p = 0.028) were independent predictors of complete remodeling post-PVR remodeling.

Conclusion: Biventricular strain parameters predict clinical outcomes and post-PVR remodeling in rTOF. Further study will be necessary to establish the role of myocardial deformation parameters in clinical practice.

Background: In-vivo diffusion tensor cardiovascular magnetic resonance (DT-CMR) is an emerging technique for microstructural tissue characterization in the myocardium. Most studies are performed at 3T, where higher signal-to-noise ratio (SNR) should benefit this signal-starved method. However, a few studies have suggested that DT-CMR is possible at 1.5T, where echo planar imaging artifacts may be less severe and 1.5T hardware is more widely available.

Methods: We recruited 20 healthy volunteers and performed mid-ventricular short-axis DT-CMR at 1.5T and 3T. Acquisitions were performed at peak systole and end-diastole using both stimulated echo acquisition mode (STEAM) and motion-compensated spin-echo (MCSE) sequences at matched spatial resolutions. DT-CMR parameters were averaged over the left ventricle and compared between 1.5T and 3T sequences using both datasets with and without the b_low reference data included.

Results: Eleven (1.5T) and 12 (3T) diastolic MCSE acquisitions were rejected as the helix angle (HA) demonstrated <50% normal appearance circumferentially or the acquisition was abandoned due to poor image quality; a maximum of one acquisition was rejected for other datasets. Subjective HA map quality was significantly better at 3T than 1.5T for STEAM (p < 0.05), but not for MCSE and other DT-CMR quality measures were consistent with improvements in STEAM at 3T over 1.5T. When b_low data were excluded, no significant differences in mean diffusivity were observed between field strengths, but fractional anisotropy was significantly higher at 1.5T than 3T for STEAM systole (p < 0.05). Absolute second eigenvector orientation (E2A, sheetlet angle) was significantly higher at 1.5T than 3T for MCSE systole and STEAM diastole, but significantly lower for STEAM systole (all p < 0.05). Transmural HA distribution was less steep at 1.5T than 3T for STEAM diastole data (p < 0.05). SNR was higher at 3T than 1.5T for all acquisitions (p < 0.05).

Conclusion: While 3T provides benefits in terms of SNR, both STEAM and MCSE can be performed at 1.5T. However, MCSE is unreliable in diastole at both field strengths and STEAM benefits from the improved SNR at 3T over 1.5T. Future clinical research studies may be able to leverage the wider availability of 1.5T CMR hardware where MCSE acquisitions are desirable.

Background: Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment of heart disease; however, limitations of CMR include long exam times and high complexity compared to other cardiac imaging modalities. Recently advancements in artificial intelligence (AI) technology have shown great potential to address many CMR limitations. While the developments are remarkable, translation of AI-based methods into real-world CMR clinical practice remains at a nascent stage and much work lies ahead to realize the full potential of AI for CMR.

Methods: Herein we review recent cutting-edge and representative examples demonstrating how AI can advance CMR in areas such as exam planning, accelerated image reconstruction, post-processing, quality control, classification and diagnosis.

Results: These advances can be applied to speed up and simplify essentially every application including cine, strain, late gadolinium enhancement, parametric mapping, 3D whole heart, flow, perfusion and others. AI is a unique technology based on training models using data. Beyond reviewing the literature, this paper discusses important AI-specific issues in the context of CMR, including (1) properties and characteristics of datasets for training and validation, (2) previously published guidelines for reporting CMR AI research, (3) considerations around clinical deployment, (4) responsibilities of clinicians and the need for multi-disciplinary teams in the development and deployment of AI in CMR, (5) industry considerations, and (6) regulatory perspectives.

Conclusions: Understanding and consideration of all these factors will contribute to the effective and ethical deployment of AI to improve clinical CMR.