Journal of Cardiovascular Magnetic Resonance最新文献

Background: In the assessment of patients with suspected coronary artery disease (CAD), the diagnostic role of stress-perfusion cardiovascular magnetic resonance (CMR) is well established. However, its reliance on gadolinium-based contrast agents may restrict its application in certain populations. T1 mapping during vasodilatory stress has been proposed as a contrast-free alternative for detecting CAD. This study sought to compare the diagnostic accuracy of adenosine-stress T1 reactivity (ΔT1) with that of stress-perfusion CMR for identifying hemodynamically significant CAD.

Methods: Patients with suspected angina referred for diagnostic invasive coronary angiography underwent 3-Tesla CMR consisting of: (1) T1 mapping at rest and following intravenous adenosine using a modified Look-Locker inversion recovery sequence, (2) stress and rest perfusion, and (3) late gadolinium enhancement. Significant CAD was defined invasively as fractional flow reserve ≤0.80 in epicardial vessels ≥2mm diameter (or quantitative flow ratio ≤0.80 if unavailable). A ΔT1 vessel threshold (% increase in T1 from rest to stress) was derived from receiver operating characteristic analysis, using invasive coronary angiography as the reference standard. Stress-perfusion CMR was assessed qualitatively with CAD determined by the presence of ischemia and/or infarction, (A) per-vessel (as determined by two independent readers) and (B) per-patient (following consensus read).

Results: Of 121 prospectively recruited patients, 115 had paired T1 mapping and coronary angiography data (mean age 66±9 years, 72% male, CAD prevalence 51%). ΔT1 demonstrated poor diagnostic performance to detect significant CAD (AUC 0.59 [95% CI: 0.52, 0.65], p=0.011), with an optimal vessel threshold ≤4.36% giving accuracy 54.9%, sensitivity 68.3% and specificity 49.2%. Stress-perfusion CMR demonstrated superior diagnostic accuracy compared to ΔT1: (A) per-vessel (for the two independent reads, +26.2% [19.4%, 32.6%] and +26.7% [19.9%, 33.3%], both p<0.001) and (B) per-patient (for consensus read, +21.7% [10.2%, 32.6%], p<0.001).

Conclusion: In patients with suspected angina, ΔT1 demonstrates limited diagnostic accuracy for the detection of obstructive CAD. Future efforts should be directed towards alternative contrast-free methods for the reliable detection of CAD in this population.

Background: Centerline semi-automatic measurements (CSAM) of the thoracic aorta have been shown to reduce interobserver variability of diameter measurements. The purpose of this study is to demonstrate the feasibility and efficiency of non-expert CSAM using contrast enhanced magnetic resonance angiography (CE-MRA) versus double oblique (DO) multiplanar reformation (MPR) measurements obtained by experts, and to assess CSAM failure rate in subjects with and without thoracic aortic disease (TAD).

Methods: Image-based navigator (iNAV) and variable density sampling with Cartesian spiral-like trajectories (VD-CASPR) framework for non-rigid motion correction and image acceleration was utilized for inversion recovery gradient echo MRA. Thoracic MRA was obtained in 41 TAD subjects and 27 normals and independently analyzed by expert cardiologists for DO MPR measurements; one cardiovascular imaging fellow (CSAM1) obtained CSAM in all subjects; another (CSAM2) obtained CSAM in TAD patients. 9 prior MRA exams were analyzed for CSAM in 7 subjects with stable aneurysms. Post-processing efficiency, and intra/interobserver agreement were assessed at the sinus of Valsalva (SOV), sinotubular junction (STJ), and ascending aorta (AAO) using intra/interclass correlation coefficients. Contour failures were graded on a four-point scale: 1- failure of ≤25% vessel circumference; 2- 26-50% circumference failure; 3- 51-75% circumference failure; 4- >75% failure.

Results: CSAM1 failure rate was 13% and 14% in the TAD and normal cohorts respectively (p=0.78). CSAM 2 failure rate was 2% in the TAD cohort. Intraobserver agreement was excellent for both methods. SOV interobserver agreement with DO MPR performed the worst, with the lowest interclass correlation (ICC) for SOV major (vs physician 1) in the normal cohort (ICC=.69). Otherwise, agreement with DO MPR was near excellent. Major diameter interobserver agreement was excellent in the TAD cohort. Efficiency was highest for CSAM2. In stable TAD, baseline and follow-up major diameter measurements were not significantly different.

Conclusion: Non-expert MRA CSAM are feasible with excellent intraobserver and excellent to near excellent interobserver agreement at the STJ and AAO levels compared to expert DO MPR. CSAM failure rates varied significantly between non-expert readers; inter-study CSAM were overall precise.

Background: Isotropic three-dimensional (3D) cine imaging is an attractive one-stop-shop acquisition for cardiac MRI, as it can be arbitrarily resliced for the assessment of cardiac function and simplifies imaging workflows. Current free-breathing 3D cine approaches are hampered by long reconstruction times, and at lower field strengths, by relatively long acquisition times. Here, we aim to maximize acquisition efficiency at 0.55T pairing two techniques; using a spiral acquisition with an optimized sampling distribution and a reconstruction incorporating data from all respiratory phases.

Methods: We implemented a 2mm isotropic 3D cine approach on a prototype 0.55T scanner, using a 6minute stack-of-spiral balanced steady-state free precession (bSSFP) acquisition modified to use tiny-golden-angle in-plane rotations and distribute the k_z partition samples to a variable-density. The data were reconstructed with a modified iterative motion compensation reconstruction which resolved cardiac motion (denoted 4D iMoCo) and combined respiratory states using a navigator signal extracted from the acquired data. The proposed technique was compared to reference 2D free-breathing Cartesian volumetry of the left ventricle in 11 human subjects.

Results: The 4D iMoCo reconstruction required 20minutes. The proposed variable-density sampling distribution reduced image artifacts, compared to a common linear sampling approach, and improved apparent signal-to-noise with relative increase of 221±99%. Measurements had good agreement with the 2D Cartesian reference data with a left ventricular volume bias of -2.5±6.2% and 2.6±10.4% in diastole and systole, respectively, and an ejection fraction bias of -3.5±8.8%.

Conclusion: We demonstrate an efficient free-breathing technique to produce 2mm isotropic 3D cardiac images within a 6minute acquisition time and 20minute reconstruction time at 0.55T. Such a method could be a valuable clinical tool for cardiac imaging.

Background: Quantitative stress perfusion cardiovascular magnetic resonance (CMR) is a valuable tool for assessing myocardial ischemia. Motion correction is a crucial step in automated quantification pipelines, especially for high-resolution pixel-wise mapping. Established methods for motion correction, based on image registration, are computationally intensive and sensitive to changes in image acquisitions, necessitating more efficient and robust solutions.

Methods: This study developed and evaluated an unsupervised deep learning-based motion correction pipeline. Based on a previously described approach, it corrects motion in three steps while using (robust) principal component analysis to mitigate the effects of the dynamic contrast. The time-consuming iterative registration optimizations are replaced with an efficient one-shot estimation by trained deep learning models. The pipeline aligns the perfusion series and includes auxiliary images series: the low-resolution, short-saturation preparation time arterial input function series and the proton density-weighted images. The deep learning models were trained and validated on multivendor data from 201 patients, with 38 held out for independent testing. The performance was evaluated in terms of the temporal alignment of the image series and the derived quantitative perfusion values in comparison to a previously established optimization-based registration approach.

Results: The deep learning approach significantly improved temporal smoothness of time-intensity curves compared to the previously published baseline (p<0.001). Temporal alignment of the myocardium (based on automated segmentations) was similar between methods and significantly improved for both as compared to before registration (mean (standard deviation) Dice = 0.92 (0.04) and Dice = 0.91 (0.05) (respectively) vs Dice = 0.80 (0.09), both p<0.001). Quantitative perfusion maps were also smoother, indicating a reduction of motion artifacts, with a median (inter-quartile range) standard deviation of 0.52 (0.39) ml/min/g in myocardial segments, than before motion correction and improved compared to the baseline method (0.55 (0.44) ml/min/g). Processing time was reduced by a factor of 15 for a representative image series using the deep learning approach in comparison to the iterative method.

Conclusion: The deep learning approach offers faster and more robust motion correction for stress perfusion CMR, improving accuracy for the dynamic contrast-enhanced data and the auxiliary images. It was trained with multi-vendor data and different acquisition sequence implementations, so, as well as enhancing efficiency and performance, it could facilitate broader clinical use of quantitative perfusion CMR.

"Cases of SCMR" is a case series on the SCMR website (https://www.scmr.org) for the purpose of education. The cases reflect the clinical presentation, and the use of cardiovascular magnetic resonance (CMR) in the diagnosis and management of cardiovascular disease. The 2024 digital collection of cases are presented in this manuscript.

Background: In pediatric heart transplant recipients (PHTR), myocardial T1 and T2 values are elevated in the setting of acute rejection and with cardiac allograft vasculopathy. In normal, healthy children, T1 and T2 values vary with patient age. Our goal was to identify associations between T1, ECV, and T2 values and patient- and donor-characteristics in PHTR without history of significant graft pathology.

Methods: We performed a single-center, retrospective chart review of consecutive CMR studies in PHTR from 2017-2023. Exclusion criteria were a prior CMR during the study period, history of any prior antibody-mediated rejection (AMR), acute cellular rejection (ACR) >1R, or treated, biopsy negative rejection. PHTR were also excluded for any history of elevated donor-derived cell-free DNA > 0.15%, CAV, RV or LV systolic dysfunction by CMR, or presence of late gadolinium enhancement. T1 and T2 mapping were performed. A single reviewer performed parametric mapping analysis. We evaluated differences in global mapping values based on patient- and donor-characteristics in PHTR. T1 and ECV values in PHTR were compared to those of pediatric control patients.

Results: Out of the 137 PHTR meeting inclusion criteria, 28 remained in the final cohort after exclusion criteria were applied. Median age was 10.6y (5.9-14.9) with time since transplant of 4.6y (3.9-8.0). Univariate regression analysis identified significant negative associations between both patient age and donor age with native T1. By multivariate regression analysis, patient age remained negatively correlated with native T1 (β=-5.2, SE= 2.3, p=0.033), ECV (β=-0.41, SE=0.19, p=0.044), and T2 (β=-0.47, SE=0.18, p=0.018), independent of donor age. Compared to pediatric control patients > 10y of age, PHTR > 10y of age demonstrated significantly higher native T1 (1020ms (1002-1033) vs 980ms (942-995), p<0.001), and ECV values (27.7% (25.0-30.2) vs 23.8% (22.2-25.9), p=0.003).

Conclusion: In PHTR, myocardial T1, ECV, and T2 values depend on patient age. PHTR without a history of known graft pathology demonstrate higher myocardial T1 and ECV compared to healthy children.

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.