Journal of Cardiovascular Magnetic Resonance最新文献

Background: Ferumoxytol-enhanced dynamic whole-heart MRI is a promising technique for imaging patients with congenital heart disease (CHD). However, lesions that cause flow turbulence can result in artifacts that obscure the images and affect their diagnostic quality. The goal of this work is to develop and test an approach for dynamic whole-heart MRI in CHD patients with preserved image quality in the presence of turbulent flow.

Methods: A 3D radial ultra-short echo time (UTE) acquisition was integrated within the free-running framework for cardiac and respiratory motion-resolved (5D) whole-heart MRI. We prospectively validated our approach in a cohort of 21 CHD patients (age 11.9±9.2 years; 14 male) between July 2021 and February 2023. We compared UTE images to a previously established gradient recalled echo (GRE) approach. Quantitative (contrast, sharpness) and qualitative (expert grading) comparisons of images were performed. The severity of flow artifacts was also quantitatively (signal loss) and qualitatively (expert grading) compared. Statistical significance was tested using the paired t-test or the Wilcoxon signed rank test.

Results: UTE and GRE images were not significantly different in terms of sharpness (0.54±0.10 versus 0.57±0.12, p=.09), and image quality grading (OBS1: 2.5 [1] versus 2.5 [1], p =.10; OBS2: 3 [0.75] versus 3 [1.5], p=.74; OBS3: 4 [0] versus 4 [0], p =.5). Blood-to-myocardium contrast was significantly higher in UTE images (4.92±0.79 versus 3.89±0.37) while blood-to-fat contrast was significantly lower (1.74±0.42 versus 2.03±0.54). UTE images had significantly fewer flow artifacts than GRE images as attested by both signal loss (8.1% [3.2] versus 47.4% [17.6]) and flow artifact grade (OBS1:0 [1] versus 2 [1]; OBS2: 0[0] versus 1 [2]; OBS3: 0 [0] versus 1 [1.25]). Prominent systolic flow artifacts in GRE images were absent in the corresponding UTE images, even at locations of lesions with a propensity for flow turbulences.

Conclusion: Free-running 3D radial UTE imaging enabled the acquisition of dynamic whole-heart images with consistent visualization of cardiovascular structures throughout the cardiac cycle despite the presence of flow turbulences.

Background: Three-dimensional (3D) speckle-tracking echocardiography (STE) and cardiac magnetic resonance (CMR) feature tracking (FT) have been reported to correlate with the extent of left ventricular myocardial fibrosis (LVMF), but the value of 3D-STE in predicting LVMF compared with CMR-FT has not been investigated in patients with end-stage heart failure (HF).

Materials and methods: A total of 155 patients who underwent CMR, two-dimensional (2D) and 3D echocardiographic examinations before heart transplantation were enrolled. Left ventricular global radial strain (GRS), global circumferential strain (GCS) and global longitudinal strain (GLS) were obtained from CMR-FT, 3D-STE and 2D-STE. The degree of LVMF was quantified using Masson's trichrome staining in left ventricular myocardial samples from the explanted hearts, and patients were divided into three groups according to tertiles of histologic LVMF.

Results: 3D-GLS, 2D-GLS, CMR-GLS and CMR-GCS were lower in patients with severe LVMF than in those with mild and moderate LVMF. LVMF was strongly correlated with CMR-GLS and 3D-GLS (r = 0.74, 0.73, respectively; both P < 0.001), moderately correlated with 2D-GLS (r = 0.63, P < 0.001). CMR-GLS and 3D-GLS demonstrated similar diagnostic performance in identifying severe LVMF (area under the curve: 0.88 vs. 0.86, P > 0.05). The model with CMR-GLS (R² = 0.550, P < 0.001) had a similar predictive value for the degree of LVMF as the model with 3D-GLS (R² = 0.528, P < 0.001), and outperformed the model with 2D-GLS (R² = 0.383, P < 0.001).

Conclusions: Both CMR-GLS and 3D-GLS are strongly correlated with LVMF, and are promising non-invasive imaging parameters for the assessment of LVMF in patients with end-stage HF.

Background: Cardiac diffusion tensor imaging (cDTI) has traditionally relied on inefficient stimulated echo techniques to robustly assess microstructural changes over the cardiac cycle. Ultrahigh gradient strength systems (>80mT/m) allow shorter motion compensated diffusion encoding. This study compares the ability of high and ultrahigh strength gradient systems to provide systolic and diastolic motion compensated spin echo (MCSE) cDTI.

Methods: Second order MCSE sequences were developed for a research-only Siemens 3T Connectom (300mT/m maximum gradient amplitude per axis) and breath hold cDTI was acquired at peak systole and end diastole. Acquisitions used the maximum achievable gradient strength (G_UH, 116mT/m) and also limited to typical high gradient strengths (G_H, 66mT/m based on 80mT/m maximum allowable), giving TE=48ms and 58ms respectively. Data were acquired at 2.8×2.8x8mm³, b=500s/mm² (8 averages) and b=150s/mm² (2 averages) in 6 encoding directions.

Results: 22 healthy subjects were recruited. 20/21 and 21/22 systolic acquisitions at G_UH and G_H respectively met the >50% criteria of the circumferential myocardium showing the expected transmural variation in helix angle. For G_UH and G_H (16/20) 80% and (16/22) 73% of diastolic acquisitions were successful respectively. SNR was increased using G_UH compared to G_H (median [IQR]: 112.9 [3.8] vs. 9.6 [2.9], p=0.0002 diastole, 15.6 [5.9] vs. 12.5 [6.7], p=0.006 systole). Using G_UH fractional anisotropy was lower in systole (0.349 [0.040] vs. 0.373 [0.019], p=0.002) and G_UH transmural helix angle gradient (HAG) was steeper in diastole (-0.70 [0.17] vs. -0.55 [0.12] ˚/%, p=0.04). At both G_UH and G_H, sheetlet angle (|E2A|) was higher in systole than in diastole (30.7 [7.3] vs. 21.3 [6.7]˚ p=10^-4 and 32.6 [10.9] vs. 26.0 [7.4]˚, p=0.03 respectively). Differences in HAG between phases were only apparent with G_H (-0.88 [0.23] vs. -0.55 [0.15], p=10^-4) and differences in the mean diffusivity only with G_UH (1.64 [0.11] vs. 1.52 [0.24] x10^-3mm²/s, p=0.00²).

Conclusion: Ultrahigh strength gradient systems deliver higher SNR for MCSE and more robust imaging in diastole. While further work is required to further improve the reliability in diastole, at ultrahigh gradient strengths, cDTI using MCSE can identify dynamic changes in the cardiac microstructure. These findings will lead to more widespread use of multiphase MCSE in cDTI clinical research.

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.