Journal of Cardiovascular Magnetic Resonance最新文献

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: Patients with diabetes mellitus (DM) and heart failure (HF) have worse outcomes than normoglycemic HF patients. Cardiovascular magnetic resonance (CMR) can identify ischemic heart disease (IHD) and quantify coronary microvascular dysfunction (CMD) using myocardial perfusion reserve (MPR). We aimed to quantify the extent of silent IHD and CMD in patients with DM presenting with HF.

Methods: Prospectively recruited outpatients undergoing assessment into the etiology of HF underwent in-line quantitative perfusion CMR for calculation of stress and rest myocardial blood flow (MBF) and MPR. Exclusions included angina or history of IHD. Patients were followed up (median 3.0 years) for major adverse cardiovascular events (MACE).

Results: Final analysis included 343 patients (176 normoglycemic, 84 with pre-diabetes, and 83 with DM). Prevalence of silent IHD was highest in DM 31% ( 26/83), then pre-diabetes 20% (17/84) then normoglycemia 17%, ( 30/176). Stress MBF was lowest in DM (1.53 ± 0.52), then pre-diabetes (1.59 ± 0.54) then normoglycemia (1.83 ± 0.62). MPR was lowest in DM (2.37 ± 0.85) then pre-diabetes (2.41 ± 0.88) then normoglycemia (2.61 ± 0.90). During follow-up, 45 patients experienced at least one MACE. On univariate Cox regression analysis, MPR and presence of silent IHD were both associated with MACE. However, after correction for HbA1c, age, and left ventricular ejection fraction, the associations were no longer significant.

Conclusion: Patients with DM and HF had higher prevalence of silent IHD, more evidence of CMD, and worse cardiovascular outcomes than their non-diabetic counterparts. These findings highlight the potential value of CMR for the assessment of silent IHD and CMD in patients with DM presenting with HF.

Background: Quantitative stress cardiac magnetic resonance (CMR) can be performed using the dual-sequence (DS) technique or dual-bolus (DB) method. It is unknown if DS and DB produce similar results for myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). The study objective is to investigate if there are any differences between DB- and DS-derived MBF and MPR.

Methods: Retrospective observational study with 168 patients who underwent stress CMR. DB and DS methods were simultaneously performed on each patient on the same day. Global and segmental stress MBF and rest MBF values were collected.

Results: Using Bland-Altman analysis, segmental and global stress MBF values were higher in DB than DS (0.22 ± 0.60 mL/g/min, p < 0.001 and 0.20 ± 0.48 mL/g/min, p = 0.005, respectively) with strong correlation (r = 0.81, p < 0.001 for segmental and r = 0.82, p < 0.001 for global). In rest MBF, segmental and global DB values were higher than by DS (0.15 ± 0.51 mL/g/min, p < 0.001 and 0.14 ± 0.36 mL/g/min, p = 0.011, respectively) with strong correlation (r = 0.81, p < 0.001 and r = 0.77, p < 0.001). Mean difference between MPR by DB and DS was -0.02 ± 0.68 mL/g/min (p = 0.758) for segmental values and -0.01 ± 0.49 mL/g/min (p = 0.773) for global values. MPR values correlated strongly as well in both segmental and global, both (r = 0.74, p < 0.001) and (r = 0.75, p < 0.001), respectively.

Conclusion: There is a very good correlation between DB- and DS-derived MBF and MPR values. However, there are significant differences between DB- and DS-derived global stress and rest MBF. While MPR values did not show statistically significant differences between DB and DS methods.

Background: Fully automatic analysis of myocardial perfusion cardiovascular magnetic resonance imaging datasets enables rapid and objective reporting of stress/rest studies in patients with suspected ischemic heart disease. Developing deep learning techniques that can analyze multi-center datasets despite limited training data and variations in software (pulse sequence) and hardware (scanner vendor) is an ongoing challenge.

Methods: Datasets from three medical centers acquired at 3T (n = 150 subjects; 21,150 first-pass images) were included: an internal dataset (inD; n = 95) and two external datasets (exDs; n = 55) used for evaluating the robustness of the trained deep neural network (DNN) models against differences in pulse sequence (exD-1) and scanner vendor (exD-2). A subset of inD (n = 85) was used for training/validation of a pool of DNNs for segmentation, all using the same spatiotemporal U-Net architecture and hyperparameters but with different parameter initializations. We employed a space-time sliding-patch analysis approach that automatically yields a pixel-wise "uncertainty map" as a byproduct of the segmentation process. In our approach, dubbed data-adaptive uncertainty-guided space-time (DAUGS) analysis, a given test case is segmented by all members of the DNN pool and the resulting uncertainty maps are leveraged to automatically select the "best" one among the pool of solutions. For comparison, we also trained a DNN using the established approach with the same settings (hyperparameters, data augmentation, etc.).

Results: The proposed DAUGS analysis approach performed similarly to the established approach on the inD (Dice score for the testing subset of inD: 0.896 ± 0.050 vs 0.890 ± 0.049; p = n.s.) whereas it significantly outperformed on the exDs (Dice for exD-1: 0.885 ± 0.040 vs 0.849 ± 0.065, p < 0.005; Dice for exD-2: 0.811 ± 0.070 vs 0.728 ± 0.149, p < 0.005). Moreover, the number of image series with "failed" segmentation (defined as having myocardial contours that include bloodpool or are noncontiguous in ≥1 segment) was significantly lower for the proposed vs the established approach (4.3% vs 17.1%, p < 0.0005).

Conclusion: The proposed DAUGS analysis approach has the potential to improve the robustness of deep learning methods for segmentation of multi-center stress perfusion datasets with variations in the choice of pulse sequence, site location, or scanner vendor.

Purpose: To apply a free-running three-dimensional (3D) cine balanced steady state free precession (bSSFP) cardiovascular magnetic resonance (CMR) framework in combination with artificial intelligence (AI) segmentations to quantify time-resolved aortic displacement, diameter and diameter change.

Methods: In this prospective study, we implemented a free-running 3D cine bSSFP sequence with scan time of approximately 4 min facilitated by pseudo-spiral Cartesian undersampling and compressed-sensing reconstruction. Automated segmentation of the aorta in all cardiac timeframes was applied through the use of nnU-Net. Dynamic 3D motion maps were created for three repeated scans per volunteer, leading to the detailed quantification of aortic motion, as well as the measurement and change in diameter of the ascending aorta.

Results: A total of 14 adult healthy volunteers (median age, 28 years (interquartile range [IQR]: 26.0-31.3), 6 females) were included. Automated segmentation compared to manual segmentation of the aorta test set showed a Dice score of 0.93 ± 0.02. The median (IQR) over all volunteers for the largest maximum and mean ascending aorta (AAo) displacement in the first scan was 13.0 (4.4) mm and 5.6 (2.4) mm, respectively. Peak mean diameter in the AAo was 25.9 (2.2) mm and peak mean diameter change was 1.4 (0.5) mm. The maximum individual variability over the three repeated scans of maximum and mean AAo displacement was 3.9 (1.6) mm and 2.2 (0.8) mm, respectively. The maximum individual variability of mean diameter and diameter change were 1.2 (0.5) mm and 0.9 (0.4) mm.

Conclusion: A free-running 3D cine bSSFP CMR scan with a scan time of four minutes combined with an automated nnU-net segmentation consistently captured the aorta's cardiac motion-related 4D displacement, diameter, and diameter change.

Background: The diagnosis of myocarditis by cardiovascular magnetic resonance (CMR) requires the use of T2 and T1 weighted imaging, ideally incorporating parametric mapping. Current two-dimensional (2D) mapping sequences are acquired sequentially and involve multiple breath-holds resulting in prolonged scan times and anisotropic image resolution. We developed an isotropic free-breathing three-dimensional (3D) whole-heart sequence that allows simultaneous T1 and T2 mapping and validated it in patients with suspected myocarditis.

Methods: Eighteen healthy volunteers and 28 patients with suspected myocarditis underwent conventional 2D T1 and T2 mapping with whole-heart coverage and 3D joint T1/T2 mapping on a 1.5T scanner. Acquisition time, image quality, and diagnostic performance were compared. Qualitative analysis was performed using a 4-point Likert scale. Bland-Altman plots were used to assess the quantitative agreement between 2D and 3D sequences.

Results: The 3D T1/T2 sequence was acquired in 8 min 26 s under free breathing, whereas 2D T1 and T2 sequences were acquired with breath-holds in 11 min 44 s (p = 0.0001). All 2D images were diagnostic. For 3D images, 89% (25/28) of T1 and 96% (27/28) of T2 images were diagnostic with no significant difference in the proportion of diagnostic images for the 3D and 2D T1 (p = 0.2482) and T2 maps (p = 1.0000). Systematic bias in T1 was noted with biases of 102, 115, and 152 ms for basal-apical segments, with a larger bias for higher T1 values. Good agreement between T2 values for 3D and 2D techniques was found (bias of 1.8, 3.9, and 3.6 ms for basal-apical segments). The sensitivity and specificity of the 3D sequence for diagnosing acute myocarditis were 74% (95% confidence interval [CI] 49%-91%) and 83% (36%-100%), respectively, with a c-statistic (95% CI) of 0.85 (0.79-0.91) and no statistically significant difference between the 2D and 3D sequences for the detection of acute myocarditis for T1 (p = 0.2207) or T2 (p = 1.0000).

Conclusion: Free-breathing whole-heart 3D joint T1/T2 mapping was comparable to 2D mapping sequences with respect to diagnostic performance, but with the added advantages of free breathing and shorter scan times. Further work is required to address the bias noted at high T1 values, but this did not significantly impact diagnostic accuracy.

Background: Cardiovascular magnetic resonance (CMR) is an emerging imaging modality for assessing the anatomy and function of the fetal heart in congenital heart disease (CHD). This study aimed to evaluate myocardial strain using fetal CMR feature tracking (FT) in different subtypes of CHD.

Methods: Fetal CMR FT analysis was retrospectively performed on four-chamber cine images acquired with Doppler ultrasound gating at 3T. Left ventricular (LV) global longitudinal strain (GLS), LV global radial strain (GRS), LV global longitudinal systolic strain rate, and right ventricular (RV) GLS were quantified using dedicated software optimized for fetal strain analysis. Analysis was performed in normal fetuses and different CHD subtypes (d-transposition of the great arteries [dTGA], hypoplastic left heart syndrome [HLHS], coarctation of the aorta [CoA], tetralogy of Fallot [TOF], RV-dominant atrioventricular septal defect [AVSD], and critical pulmonary stenosis or atresia [PS/PA]). Analysis of variance with Tukey post-hoc test was used for group comparisons.

Results: A total of 60 fetuses were analyzed (8/60 (13%) without CHD, 52/60 (87%) with CHD). Myocardial strain was successfully assessed in 113/120 ventricles (94%). Compared to controls, LV GLS was significantly reduced in fetuses with HLHS (-18.6±2.7% vs -6.2±5.6%; p<0.001) and RV-dominant AVSD (-18.6±2.7% vs -7.7±5.0%; p = 0.003) and higher in fetuses with CoA (-18.6±2.7% vs -25.0±4.3%; p = 0.038). LV GRS was significantly reduced in fetuses with HLHS (25.7±7.5% vs 11.4±9.7%; p = 0.024). Compared to controls, RV GRS was significantly reduced in fetuses with PS/PA (-16.1±2.8% vs -8.3±4.2%; p = 0.007). Across all strain parameters, no significant differences were present between controls and fetuses diagnosed with dTGA and TOF.

Conclusion: Fetal myocardial strain assessment with CMR FT in CHD is feasible. Distinct differences are present between various types of CHD, suggesting potential implications for clinical decision-making and prognostication in fetal CHD.

Background: Ultra-high field strength magnetic resonance has been proven to offer improved visualization of the distal intracranial vessels and branches, but its effectiveness for visualization of the peripheral vasculature has not been investigated. We aimed to assess the visualization of distal lower-extremity vessels using three-dimensional phase-contrast magnetic resonance angiography (3D PC-MRA) at 5T field strength in combination with warm water immersion (WWI).

Methods: Participants were prospectively recruited and underwent 3T, and 5T 3D PC-MRA of the feet with and without WWI (water temperature between 40°C and 45°C for a duration of 10 minutes). Patients with suspected lower-extremity peripheral arterial disease underwent computed tomography angiography for lesion identification. Signal-to-noise ratio (SNR), subjective scoring, quantitative vessel segmentation, and flow velocity were performed to assess vessel visualization before and after WWI. Friedman's test was conducted to determine statistical significance.

Results: Out of 30 participants (mean age, 46.2 ± 5.9; males, 20; lower-extremity vessel disease, 10), 900 vessel segments were available for evaluation. 5T images showed significantly higher scores for image quality and foot vessel visualization than 3T (all P < 0.05). WWI further improved the visualizing scores (percentage of score 3: 40.2% (193/480), 66.2% (318/480)), SNR (44.27 vs 67.78, P < 0.001), total branch count (151.92 ± 29.17 vs 225.63 ± 16.76; P < 0.001), and the flow velocity (0.72 ± 0.03 vs 0.48 ± 0.11 cm/s; P < 0.001).

Conclusion: 3D PC-MRA at 5T effectively visualizes foot vessels in patients with lower-extremity disease. Furthermore, WWI can significantly enhance the depiction of distal and small vessels.

Background: Although quantitative myocardial T1 and T2 mappings are clinically used to evaluate myocardial diseases, their application needs a minimum of six breath-holds to cover three short-axis slices. The purpose of this work is to simultaneously quantify multislice myocardial T1 and T2 across three short-axis slices in one breath-hold by combining simultaneous multislice (SMS) with multimapping.

Methods: An SMS-Multimapping sequence with multiband radiofrequency (RF) excitations and Cartesian fast low-angle shot readouts was developed for data acquisition. When 3 slices are simultaneously acquired, the acceleration rate is around 12-fold, causing a highly ill-conditioned reconstruction problem. To mitigate image artifacts and noise caused by the ill-conditioning, a reconstruction algorithm based on locally low-rank and sparsity (LLRS) constraints was developed. Validation was performed in phantoms and in vivo imaging, with 20 healthy subjects and 4 patients, regarding regional mean, precision, and scan-rescan reproducibility.

Results: The phantom imaging shows that SMS-Multimapping with locally low-rank (LLRS) accurately reconstructed multislice T1 and T2 maps despite a six-fold acceleration of scan time. Healthy subject imaging shows that the proposed LLRS algorithm substantially improved image quality relative to split slice-generalized autocalibrating partially parallel acquisition. Compared with modified look-locker inversion recovery (MOLLI), SMS-Multimapping exhibited higher T1 mean (1118 ± 43 ms vs 1190 ± 49 ms, P < 0.01), lower precision (67 ± 17 ms vs 90 ± 17 ms, P < 0.01), and acceptable scan-rescan reproducibility measured by 2 scans 10-min apart (bias = 1.4 ms for MOLLI and 9.0 ms for SMS-Multimapping). Compared with balanced steady-state free precession (bSSFP) T2 mapping, SMS-Multimapping exhibited similar T2 mean (43.5 ± 3.3 ms vs 43.0 ± 3.5 ms, P = 0.64), similar precision (4.9 ± 2.1 ms vs 5.1 ± 1.0 ms, P = 0.93), and acceptable scan-rescan reproducibility (bias = 0.13 ms for bSSFP T2 mapping and 0.55 ms for SMS-Multimapping). In patients, SMS-Multimapping clearly showed the abnormality in a similar fashion as the reference methods despite using only one breath-hold.

Conclusion: SMS-Multimapping with the proposed LLRS reconstruction can measure multislice T1 and T2 maps in one breath-hold with good accuracy, reasonable precision, and acceptable reproducibility, achieving a six-fold reduction of scan time and an improvement of patient comfort.