Balanced Steady-state Free Precession Research Articles

Flexible and cost-effective deep learning for accelerated multi-parametric relaxometry using phase-cycled bSSFP

Abstract To accelerate the clinical adoption of quantitative magnetic resonance imaging (qMRI), frameworks are needed that not only allow for rapid acquisition, but also flexibility, cost efficiency, and high accuracy in parameter mapping. In this study, feed-forward deep neural network (DNN)- and iterative fitting-based frameworks are compared for multi-parametric (MP) relaxometry based on phase-cycled balanced steady-state free precession (pc-bSSFP) imaging. The performance of supervised DNNs (SVNN), self-supervised physics-informed DNNs (PINN), and an iterative fitting framework termed motion-insensitive rapid configuration relaxometry (MIRACLE) was evaluated in silico and in vivo in brain tissue of healthy subjects, including Monte Carlo sampling to simulate noise. DNNs were trained on three distinct in silico parameter distributions and at different signal-to-noise-ratios. The PINN framework, which incorporates physical knowledge into the training process, ensured more consistent inference and increased robustness to training data distribution compared to the SVNN. Furthermore, DNNs utilizing the full information of the underlying complex-valued MR data demonstrated ability to accelerate the data acquisition by a factor of 3. Whole-brain relaxometry using DNNs proved to be effective and adaptive, suggesting the potential for low-cost DNN retraining. This work emphasizes the advantages of in silico DNN MP-qMRI pipelines for rapid data generation and DNN training without extensive dictionary generation, long parameter inference times, or prolonged data acquisition, highlighting the flexible and rapid nature of lightweight machine learning applications for MP-qMRI.

Improving Image Quality and Decreasing SAR With High Dielectric Constant Pads in 3 T Fetal MRI.

At high magnetic fields, degraded image quality due to dielectric artifacts and elevated specific absorption rate (SAR) are two technical challenges in fetal MRI. To assess the potential of high dielectric constant (HDC) pad in increasing image quality and decreasing SAR for 3 T fetal MRI. Prospective. 3 T. Balanced steady-state free precession (bSSFP) and single-shot fast spin-echo (SSFSE). One hundred twenty-eight participants (maternal-age 29.0 ± 3.6, range 20-40; gestational-age 30.3 ± 3.5 weeks, range 22-37 weeks) undertook bSSFP and 40 participants (maternal-age 29.5 ± 3.8, range 19-40; gestational-age 30.4 ± 3.5 weeks, range 23-37 weeks) undertook SSFSE. Patient clinical characteristics were recorded, such as gestational-age, amniotic-fluid-index, abdominal-circumference, body-mass-index, and fetal-presentation. Quantitative Image-quality analysis included signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative analysis was performed by three radiologists with four-point scale to evaluate overall image quality, dielectric artifact, and diagnostic confidence. Whole-body total SAR was obtained from the vendor workstation. Paired rank sum test was used to analyze the differences in SNR, CNR, overall image quality, dielectric artifact, diagnostic confidence, and SAR with and without HDC pad. Spearman correlation test was used to detect correlations between image quality variable changes and patient clinical characteristics. P values <0.05 were set as statistical significance. With HDC pad, SNR and CNR was significantly higher (41.45% increase in SNR, 54.05% increase in CNR on bSSFP; 258.76% increase in SNR, 459.55% increase in CNR on SSFSE). Overall qualitative image quality, dielectric artifact and diagnostic confidence improved significantly. Adding HDC pad significantly reduced Whole-body total SAR (32.60% on bSSFP; 15.40% on SSFSE). There was no significant correlation between image quality variable changes and participant clinical characteristics (P-values ranging from 0.072 to 0.992). In the clinical setting, adding a HDC pad might increase image quality while reducing dielectric artifact and SAR. Dielectric artifacts and elevated SAR are two technical problems in 3T fetal MRI. In a prospective analysis of 168 pregnant participants undertaking 3.0T fetal MRI scanning, high dielectric constant (HDC) pad increased SNR by 41.45%, CNR by 54.05% on bSSFP, and SNR by 258.76%, CNR by 459.55% on SSFSE. Overall image quality, dielectric artifact reduction, and diagnostic confidence assessed by three radiologists was improved. Whole-body total SAR decreased by 32.60% on bSSFP and by 15.40% on SSFSE. These findings suggested that the HDC pad can enhance fetal MRI safety and quality, making it a promising tool for clinical practice. 2 TECHNICAL EFFICACY: Stage 5.

Relaxometry and contrast-free cerebral microvascular quantification using balanced steady-state free precession MR fingerprinting.

This study proposes a novel, contrast-free Magnetic Resonance Fingerprinting (MRF) method using balanced Steady-State Free Precession (bSSFP) sequences for the quantification of cerebral blood volume (CBV), vessel radius (R), and relaxometry parameters (T , T , T *) in the brain. The technique leverages the sensitivity of bSSFP sequences to intra-voxel frequency distributions in both transient and steady-state regimes. A dictionary-matching process is employed, using simulations of realistic mouse microvascular networks to generate the MRF dictionary. The method is validated through in silico and in vivo experiments on six healthy subjects, comparing results with standard MRF methods and literature values. The proposed method shows strong correlation and agreement with standard MRF methods for T and T values. High-resolution maps provide detailed visualizations of CBV and microvascular structures, highlighting differences in white matter (WM) and gray matter (GM) regions. The measured GM/WM ratio for CBV is 1.91, consistent with literature values. This contrast-free bSSFP-based MRF method offers an new approach for quantifying CBV, vessel radius, and relaxometry parameters. Further validation against DSC imaging and clinical studies in pathological conditions is warranted to confirm its clinical utility.

Ultra-high-resolution brain MRI at 0.55T: bSTAR and its application to magnetization transfer ratio imaging.

This study aims to evaluate the feasibility of structural sub-millimeter isotropic brain MRI at 0.55 T using a 3D half-radial dual-echo balanced steady-state free precession sequence, termed bSTAR and to assess its potential for high-resolution magnetization transfer imaging. Phantom and in-vivo imaging of three healthy volunteers was performed on a low-field 0.55 T MR-system with isotropic bSTAR resolution settings of 0.87 × 0.87 × 0.87 mm3 and 0.69 × 0.69 × 0.69 mm3. Furthermore, off-resonance mapping was performed using 3D double-echo spoiled gradient imaging. For magnetization transfer (MT) MRI, the RF pulse duration of the 0.87 mm bSTAR scan was modified. Data were reconstructed using a GPU-accelerated compressed sensing algorithm. Magnetization transfer ratio (MTR) maps were calculated from two bSTAR scans with and without RF pulse prolongation. The MTR scan took 5 minutes and the reproducibility was assessed through repeated scans. Off-resonance mapping revealed that bSSFP brain imaging with TR < 5ms is essentially free of off-resonance-related artifacts even near the nasal cavities. Phantom and in-vivo scans demonstrated the feasibility of sub-millimeter isotropic bSTAR imaging. MTR maps obtained with high isotropic resolution bSTAR showed contrast between white and gray matter in agreement with expectations from high-field studies. The MTR measurements were highly reproducible with an average inter-scan MTR peak value of 43.3 ± 0.3 percent units. This study demonstrated the potential of sub-millimeter and artifact-free morphologic brain imaging at 0.55 T using bSTAR leveraging the advantages of low-field MRI, such as reduced susceptibility artifacts and improved radio-frequency field homogeneity. Furthermore, MT-sensitized bSTAR brain MRI enabled whole-brain MTR assessment within clinically feasible times and with high reproducibility.

Accelerated deep-learning reconstructed cine balanced steady-state free precession cine imaging: Potential for workflow improvement.

Accelerated deep-learning reconstructed cine balanced steady-state free precession cine imaging: Potential for workflow improvement.

ORACLE: An analytical approach for T1, T2, proton density, and off-resonance mapping with phase-cycled balanced steady-state free precession.

To develop and validate a novel analytical approach simplifying , , proton density (PD), and off-resonance quantifications from phase-cycled balanced steady-state free precession (bSSFP) data. Additionally, to introduce a method to correct aliasing effects in undersampled bSSFP profiles. Off-resonant-encoded analytical parameter quantification using complex linearized equations (ORACLE) provides analytical solutions for bSSFP profiles. which instantaneously quantify , , proton density (PD), and . An aliasing correction formalism was derived to allow undersampling of bSSFP profiles. ORACLE was used to quantify , , PD, / , and based on fully sampled ( ) bSSFP profiles from numerical simulations and 3T MRI experiments in phantom and 10 healthy subjects' brains. Obtained values were compared with reference scans in the same scan session. Aliasing correction was validated in subsampled ( ) bSSFP profiles in numerical simulations and human brains. ORACLE quantifications agreed well with input values from simulations and phantom reference values (R2 = 0.99). In human brains, and quantifications when compared with reference methods showed coefficients of variation below 2.9% and 3.9%, biases of 182 and 16.6 ms, and mean white-matter values of 642 and 51 ms using ORACLE. The quantification differed less than 3 Hz between both methods. PD and maps had comparable histograms. The maps effectively identified cerebrospinal fluid. Aliasing correction removed aliasing-related quantification errors in undersampled bSSFP profiles, significantly reducing scan time. ORACLE enables simplified and rapid quantification of , , PD, and from phase-cycled bSSFP profiles, reducing acquisition time and eliminating biomarker maps' coregistration issues.

Macrovascular contributions to resting-state fMRI signals: A comparison between EPI and bSSFP at 9.4 Tesla

Abstract The draining-vein bias of T2*-weighted sequences, like gradient echo echo-planar imaging (GRE-EPI), can limit the spatial specificity of functional MRI (fMRI). The underlying extravascular signal changes increase with field strength (B0) and the perpendicularity of draining veins to the main axis of B0, and are therefore particularly problematic at ultra-high field (UHF). In contrast, simulations showed that T2-weighted sequences are less affected by the draining-vein bias, depending on the amount of rephasing of extravascular signal. As large pial veins on the cortical surface follow the cortical folding tightly, their orientation can be approximated by the cortical orientation to B→0. In our work, we compare the influence of the cortical orientation to B→0 on the resting-state fMRI signal of three sequences aiming to understand their macrovascular contribution. While 2D GRE-EPI and 3D GRE-EPI (both T2*-weighted) showed a high dependence on the cortical orientation to B→0, especially on the cortical surface, this was not the case for 3D balanced steady-state free precession (bSSFP) (T2/T1-weighted). Here, a slight increase of orientation dependence was shown in depths closest to WM. And while orientation dependence decreased with increased distance to the veins for both EPI sequences, no change in orientationdependence was observed in bSSFP. This indicates the low macrovascular contribution to the bSSFP signal, making it a promising sequence for layer fMRI at UHF.

Ferumoxytol-Enhanced Cardiac Cine MRI Reconstruction Using a Variable-Splitting Spatiotemporal Network.

Balanced steady-state free precession (bSSFP) imaging is commonly used in cardiac cine MRI but prone to image artifacts. Ferumoxytol-enhanced (FE) gradient echo (GRE) has been proposed as an alternative. Utilizing the abundance of bSSFP images to develop a computationally efficient network that is applicable to FE GRE cine would benefit future network development. To develop a variable-splitting spatiotemporal network (VSNet) for image reconstruction, trained on bSSFP cine images and applicable to FE GRE cine images. Retrospective and prospective. 41 patients (26 female, 53 ± 19 y/o) for network training, 31 patients (19 female, 49 ± 17 y/o) and 5 healthy subjects (5 female, 30 ± 7 y/o) for testing. 1.5T and 3T, bSSFP and GRE. VSNet was compared to VSNet with total variation loss, compressed sensing and low rank methods for 14× accelerated data. The GRAPPA×2/×3 images served as the reference. Peak signal-to-noise-ratio (PSNR), structural similarity index (SSIM), left ventricular (LV) and right ventricular (RV) end-diastolic volume (EDV), end-systolic volume (ESV), and ejection fraction (EF) were measured. Qualitative image ranking and scoring were independently performed by three readers. Latent scores were calculated based on scores of each method relative to the reference. Linear mixed-effects regression, Tukey method, Fleiss' Kappa, Bland-Altman analysis, and Bayesian categorical cumulative probit model. A P-value <0.05 was considered statistically significant. VSNet achieved significantly higher PSNR (32.7 ± 0.2), SSIM (0.880 ± 0.004), rank (2.14 ± 0.06), and latent scores (-1.72 ± 0.22) compared to other methods (rank >2.90, latent score < -2.63). Fleiss' Kappa was 0.52 for scoring and 0.61 for ranking. VSNet showed no significantly different LV and RV ESV (P = 0.938) and EF (P = 0.143) measurements, but statistically significant different (2.62 mL) EDV measurements compared to the reference. VSNet produced the highest image quality and the most accurate functional measurements for FE GRE cine images among the tested 14× accelerated reconstruction methods. 3 TECHNICAL EFFICACY: Stage 1.

Cardiac compressed sensing real-time cine for the assessment of left ventricular function: a large sample size analysis.

Segmented cine imaging using a balanced steady-state free precession sequence is the gold standard for accurately quantifying cardiac function and myocardial mass. However, this method suffers from inefficient K-space sampling, resulting in long scan times, and requires multiple breath holds that can be difficult for some patients. Real-time compressed sensing (CS) cine reduces image acquisition time through K-space undersampling and iterative reconstruction, enabling rapid magnetic resonance (MR) imaging. Further large-scale studies need to be conducted to validate its effectiveness. In this study, we assessed image quality and left ventricular (LV) function during the routine clinical use of CS imaging in cardiovascular MR (CMR) to determine the feasibility of using CS cine. From April 2022 to March 2023, 242 patients with various heart diseases, including arrhythmia, at outpatient, inpatient, and health examination centers, were consecutively enrolled in this prospective, cross-sectional study and underwent CMR. Two methods [real-time CS cine with free breathing (RTCSCineFB) and conventional breath-hold segmented cine (SegBH)] were used to acquire long- and short-axis cine images of the heart. The total scan time, image quality (Likert score; range, 1-5), LV function parameters, and image fidelity were evaluated for each method. The study cohort comprised 149 men and 75 women with a mean age of 56.2±15.1 years. The mean ± standard deviation (SD) total scan time was significantly shorter for RTCSCineFB than for SegBH (86.44±31.74 vs. 289.81±88.41 s, P<0.001). The overall image quality was slightly lower for RTCSCineFB than for SegBH (P<0.001). The correlations between cardiac function parameters were excellent (0.913-0.984), demonstrating good consistency between the two methods. Both methods were considered equivalent in evaluating LV function and image quality, and showed strong agreement in their diagnostic gradings of ejection fraction (EF) (κ=0.759) and high accuracy. CS cine assessed LV function with high diagnostic accuracy and enhanced image stability for individuals with arrhythmia while maintaining strong consistency in two methods for EF grading condition.

Feasibility of fetal cardiac function and anatomy assessment by real-time spiral bSSFP MRI at 0.55T

BackgroundContemporary 0.55T MRI is promising for fetal MRI, due to the larger bore, reduced safety concerns, lower acoustic noise, and improved fast imaging capability. In this work, we explore improved fetal cardiac MRI (CMR) without relying on any synchronizing devices, prospective, or retrospective gating. PurposeTo determine the feasibility of real-time MRI evaluation of fetal cardiac function as well as cardiac and great vessel anatomies by using spiral balanced steady-state free precession (bSSFP) at 0.55T. MethodsA real-time spiral bSSFP pulse sequence for fetal CMR was implemented and optimized on a 0.55T whole-body MRI. Fetal CMR was prospectively performed between May 2022 and August 2023. The protocol included: 1) real-time images at standard cardiac views, for 10-20seconds/view and 40 to 43.6 ms/frame and 2) 4-9 stacks of slices at standard cardiac views that each cover the whole heart, with 15-30 slices/stack, and 2-5seconds/slice, at 320 to 349 ms/frame. Images were evaluated by a fetal cardiologist. Quantitative measurements of cardiothoracic area ratio and cardiac axis were compared with previous reports. Diagnostic accuracy was compared against postnatal echocardiographic findings. ResultsTwenty-nine participants were enrolled for 32 CMR exams, with mean maternal age 33.6±5.8 year (range 22-44 year) and mean gestational age 32.8±3.9 weeks (range 23-38 weeks). The proposed sequence enabled evaluation of the fetal heart in <30minutes in all cases (average 22minutes). Real-time MRI allowed easy adjustment of scan plan, automatic whole-heart volumetric sweeping, and flexible choice of reconstruction temporal resolution. For key cardiac anatomic features 60% were delineated well. Mean cardiothoracic area ratio and cardiac axis were 0.27±0.04 and 45.8±7.8. Diagnostic agreement with postnatal echocardiographic findings was 84%. ConclusionA spiral real-time bSSFP pulse sequence at 0.55T can provide both low framerate and high framerate fetal heart images without relying on maternal breath-hold, specialized gating devices, or cardiac gating. The low framerate images offer high diagnostic quality structural evaluations of the fetal heart, while the high framerate images capture fetal heart motion and may enable functional assessments.

Late Gadolinium Enhancement CMR with Generative AI

BackgroundLate gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging enables imaging of scar/fibrosis and is a cornerstone of most CMR imaging protocols. CMR imaging can benefit from image acceleration; however, image acceleration in LGE remains challenging due to its limited signal-to-noise ratio. In this study, we sought to evaluate a rapid 2D LGE imaging protocol using a generative artificial intelligence (AI) algorithm with inline reconstruction. MethodsA generative AI-based image enhancement was used to improve the sharpness of 2D LGE images acquired with low spatial resolution in the phase-encode direction. The generative AI model is an image enhancement technique built on the enhanced super-resolution generative adversarial network. The model was trained using balanced steady-state free-precession cine images, readily used for LGE without additional training. The model was implemented inline, allowing the reconstruction of images on the scanner console. We prospectively enrolled 100 patients (55 ± 14 years, 72 males) referred for clinical CMR at 3T. We collected three sets of LGE images in each subject, with in-plane spatial resolutions of 1.5×1.5-3-6 mm2. The generative AI model enhanced in-plane resolution to 1.5×1.5 mm2 from the low-resolution counterparts. Images were compared using a blur metric, quantifying the perceived image sharpness (0 = sharpest, 1=blurriest). LGE image sharpness (using a 5-point scale) was assessed by three independent readers. ResultsThe scan times for the three imaging sets were 15±3, 9±2, and 6±1seconds, with inline generative AI-based images reconstructed time of ~37 ms. The generative-AI-based model improved visual image sharpness, resulting in lower blur metric than low-resolution counterparts (AI-enhanced from 1.5×3 mm2 resolution: 0.3±0.03 vs. 0.35±0.03, P<0.01). Meanwhile, AI-enhanced images from 1.5×3 mm2 resolution and original LGE images showed similar blur metric (0.30±0.03 vs. 0.31±0.03, P=1.0) Additionally, there was an overall 18% improvement in image sharpness between AI-enhanced images from 1.5×3 mm2 resolution and original LGE images in the subjective blurriness score (P<0.01). ConclusionsGenerative AI-based model enhances the image quality of 2D LGE images while reducing the scan time and preserving imaging sharpness. Further evaluation in a large cohort is needed to assess the clinical utility of AI-enhanced LGE images for scar evaluation, as this proof-of-concept study does not provide evidence of an impact on diagnosis.

Repeatability, Reproducibility, and Observer Variability of Cortical T1 Mapping for Renal Tissue Characterization.

The global rise in kidney diseases underscores the need for reliable, noninvasive imaging biomarkers. Among these, renal cortical T1 has shown promise but further technical validation is still required. To evaluate the repeatability, reproducibility, and observer variability of kidney cortical T1 mapping in human volunteers without known renal disease. Prospective. Three cohorts without renal disease: 1) 25 volunteers (median age 38 [interquartile range, IQR: 28-42] years, female N = 11) for scan-rescan assessments on GE 1.5 T and Siemens 1.5 T; 2) 29 volunteers (median age 29 [IQR: 24-40] years, female N = 15) for scan-rescan assessments on Siemens 3 T; and 3) 16 volunteers (median age 34 [IQR: 31-42] years, female N = 8) for cross-scanner reproducibility. 1.5 T and 3 T, a modified Look-Locker imaging (MOLLI) sequence with a balanced steady-state free precession (bSSFP) readout. Kidney cortical T1 data was acquired on GE 1.5 T scanner, Siemens 1.5 T and 3 T scanners. Within-scanner repeatability and inter/intra-observer variability: GE 1.5 T and Siemens 1.5 T, and cross-scanner manufacturer reproducibility: Siemens 1.5 T-GE 1.5 T. Bland Altman analysis, coefficient of variation (CoV), intra-class coefficient (ICC), and repeatability coefficient (RC). Renal cortical T1 mapping showed high repeatability and reliability across scanner field strengths and manufacturers (repeatability: CoV 1.9%-2.8%, ICC 0.79-0.88, pooled RC 73 msec; reproducibility: CoV 3.0%, ICC 0.75, RC 90 msec). The method also showed robust observer variability (CoV 0.6%-1.4%, ICC 0.93-0.98, RC 22-48 msec). Kidney cortical T1 mapping is a highly repeatable and reproducible method across MRI manufacturers, field strengths, and observer conditions. 2 TECHNICAL EFFICACY: Stage 2.

3D Vortex-Energetics in the Left Pulmonary Artery for Differentiating Pulmonary Arterial Hypertension and Pulmonary Venous Hypertension Groups Using 4D Flow MRI.

Pulmonary hypertension (PH) is a life-threatening. Differentiation pulmonary arterial hypertension (PAH) from pulmonary venous hypertension (PVH) is important due to distinct treatment protocols. Invasive right heart catheterization (RHC) remains the reference standard but noninvasive alternatives are needed. To evaluate 4D Flow MRI-derived 3D vortex energetics in the left pulmonary artery (LPA) for distinguishing PAH from PVH. Prospective case-control. Fourteen PAH patients (11 female) and 18 PVH patients (9 female) diagnosed from RHC, 23 healthy controls (9 female). 1.5 T; gradient recalled echo 4D flow and balanced steady-state free precession (bSSFP) cardiac cine sequences. LPA 3D vortex cores were identified using the lambda2 method. Peak vortex-contained kinetic energy (vortex-KE) and viscous energy loss (vortex-EL) were computed from 4D flow MRI. Left and right ventricular (LV, RV) stroke volume (LVSV, RVSV) and ejection fraction (LVEF, RVEF) were computed from bSSFP. In PH patients, mean pulmonary artery pressure (mPAP), pulmonary capillary wedge pressure (PCWR) and pulmonary vascular resistance (PVR) were determined from RHC. Mann-Whitney U test for group comparisons, Spearman's rho for correlations, logistic regression for identifying predictors of PAH vs. PVH and develop models, area under the receiver operating characteristic curve (AUC) for model performance. Significance was set at P < 0.05. PAH patients showed significantly lower vortex-KE (37.14 [14.68-78.52] vs. 76.48 [51.07-120.51]) and vortex-EL (9.93 [5.69-25.70] vs. 24.22 [12.20-32.01]) than PVH patients. The combined vortex-KE and LVEF model achieved an AUC of 0.89 for differentiating PAH from PVH. Vortex-EL showed significant negative correlations with mPAP (rho = -0.43), PCWP (rho = 0.37), PVR (rho = -0.64). In the PAH group, PVR was significantly negatively correlated with LPA vortex-KE (rho = -0.73) and vortex-EL (rho = -0.71), and vortex-KE significantly correlated with RVEF (rho = 0.69), RVSV, (rho = 0.70). In the PVH group, vortex-KE (rho = 0.52), vortex-EL significantly correlated with RVSV (rho = 0.58). These preliminary findings suggest that 4D flow MRI-derived LPA vortex energetics have potential to noninvasively differentiate PAH from PVH and correlate with invasive hemodynamic parameters. 1 TECHNICAL EFFICACY: Stage 3.

Subclinical myocardial fibrosis is almost ubiquitous in the hearts of older British persons: 'MyoFit46' cardiovascular sub-study of the NSHD

Abstract Background Unprecedented numbers are now surviving to older age, but little is known about the burden or pattern of myocardial fibrosis in the asymptomatic elderly population. Previous 1.5 Tesla (T) cardiovascular magnetic resonance (CMR) studies found a prevalence of unexpected infarct-pattern late gadolinium enhancement (LGE) of 17-20% above 75 years but less is known about non-infarct pattern scar in this group. We investigated the prevalence, patterns, and clinical predictors of left ventricular (LV) scar in a large asymptomatic older age cohort. Methods CMR with a single 3T magnet was performed on participants all born in the same week in March 1946, as part of the longest running continued surveillance birth cohort: the National Survey of Health and Development. LV short-axis stack LGE imaging was performed using a free-breathing motion-corrected balanced steady-state free precession sequence with phase-sensitive inversion-recovery. Two blinded observers independently recorded the prevalence, extent, and pattern of LGE per participant. Logistic regression was used to study the association between clinicodemographic parameters and LGE. Results 460 participants were prospectively recruited of which 406 completed CMR with LGE imaging (77.8 ± 0.1 years, 44% male). 341 (84%) demonstrated LGE affecting a mean of 2.1±1.2 myocardial segments per participant (Figure 1). The commonest pattern of LGE was inferior right ventricular insertion point (RVIP), observed in 66.9%. Other patterns included (Figure 2): Linear mid-wall (19.6%) of which 38% were located in the inferior/lateral walls; subepicardial (12.1%); subendocardial infarct-pattern (8.8%); patchy/diffuse (1.6%); embolic LGE (0.6%). Sub-analysis was performed comparing those without significant unexpected fibrosis (LGE–) vs those with focal fibrosis (LGE+, excluding RVIP and those participants with a known history of prior myocardial infarction). LGE+ participants were more likely to be female (71.7% vs 49.1%, p&amp;lt;0.001) or diabetic (11.3% vs 5.1%, p=0.05), had a higher body surface area (BSA, 1.9 vs 1.8 m2, p&amp;lt;0.001), weight (80.1 vs 72.8 kg, p&amp;lt;0.001), LV indexed end systolic volume (24.2 vs 20.4 ml/m2, p=0.001) and LV indexed mass (59.2 vs 55.4 g/m2, p&amp;lt;0.001), and a lower LV ejection fraction (67.9 vs 71.8%, p&amp;lt;0.001) In multivariable logistic regression: BSA, LV indexed mass, LV ejection fraction and diabetic status were independently associated with LGE+ status (odds ratios [95% confidence intervals]: 9.4 [0.7–3.8]; 1.0 [0.01–0.05]; 0.9 [-0.08--0.02]; and 2.5 [0.03–1.7] respectively, p&amp;lt;0.05). Conclusion Advanced PSIR MOCO LGE imaging at 3T reveals that the majority (84%) of asymptomatic British persons above the age of 75 harbour unexpected ‘subclinical’ focal fibrosis, with a substantial proportion of these scars consistent with probable historical myocarditis events. Further work will now explore the life-course determinants of this scar burden in the older age human heart.

Deep learning super-resolution reconstruction for fast and high-quality cine cardiovascular magnetic resonance.

To compare standard-resolution balanced steady-state free precession (bSSFP) cine images with cine images acquired at low resolution but reconstructed with a deep learning (DL) super-resolution algorithm. Cine cardiovascular magnetic resonance (CMR) datasets (short-axis and 4-chamber views) were prospectively acquired in healthy volunteers and patients at normal (cineNR: 1.89 × 1.96 mm2, reconstructed at 1.04 × 1.04 mm2) and at a low-resolution (2.98 × 3.00 mm2, reconstructed at 1.04 × 1.04 mm2). Low-resolution images were reconstructed using compressed sensing DL denoising and resolution upscaling (cineDL). Left ventricular ejection fraction (LVEF), end-diastolic volume index (LVEDVi), and strain were assessed. Apparent signal-to-noise (aSNR) and contrast-to-noise ratios (aCNR) were calculated. Subjective image quality was assessed on a 5-point Likert scale. Student's paired t-test, Wilcoxon matched-pairs signed-rank-test, and intraclass correlation coefficient (ICC) were used for statistical analysis. Thirty participants were analyzed (37 ± 16 years; 20 healthy volunteers and 10 patients). Short-axis views whole-stack acquisition duration of cineDL was shorter than cineNR (57.5 ± 8.7 vs 98.7 ± 12.4 s; p < 0.0001). No differences were noted for: LVEF (59 ± 7 vs 59 ± 7%; ICC: 0.95 [95% confidence interval: 0.94, 0.99]; p = 0.17), LVEDVi (85.0 ± 13.5 vs 84.4 ± 13.7 mL/m2; ICC: 0.99 [0.98, 0.99]; p = 0.12), longitudinal strain (-19.5 ± 4.3 vs -19.8 ± 3.9%; ICC: 0.94 [0.88, 0.97]; p = 0.52), short-axis aSNR (81 ± 49 vs 69 ± 38; p = 0.32), aCNR (53 ± 31 vs 45 ± 27; p = 0.33), or subjective image quality (5.0 [IQR 4.9, 5.0] vs 5.0 [IQR 4.7, 5.0]; p = 0.99). Deep-learning reconstruction of cine images acquired at a lower spatial resolution led to a decrease in acquisition times of 42% with shorter breath-holds without affecting volumetric results or image quality. Question Cine CMR acquisitions are time-intensive and vulnerable to artifacts. Findings Low-resolution upscaled reconstructions using DL super-resolution decreased acquisition times by 35-42% without a significant difference in volumetric results or subjective image quality. Clinical relevance DL super-resolution reconstructions of bSSFP cine images acquired at a lower spatial resolution reduce acquisition times while preserving diagnostic accuracy, improving the clinical feasibility of cine imaging by decreasing breath hold duration.

Lung volumes are increased in fetuses with transposition of the great arteries on intrauterine MRI.

Fetal brain size is decreased in some children with complex CHDs, and the distribution of blood and accompanying oxygen and nutrients is regionally skewed from early fetal life dependent on the CHD. In transposition of the great arteries, deoxygenated blood preferentially runs to the brain, whereas the more oxygenated blood is directed towards the lungs and the abdomen. Knowledge of whether this impactsintrauterine organ development is limited. We investigated lung, liver, and total intracranial volume in fetuses with transposition of the great arteries using MRI.Eight fetuses with dextro-transposition and without concomitant disease or chromosomal abnormalities and 42 fetuses without CHD or other known diseases were scanned once or twice at gestational age 30 through 39 weeks. The MRI scans were conducted on a 1.5T system, using a 2D balanced steady-state free precession sequence. Slices acquired covered the entire fetus, slice thickness was 10 mm, pixel size 1.5 × 1.5 mm, and scan duration was 30 sec.The mean lung z score was significantly larger in fetuses with transposition compared with those without a CHD; mean difference is 1.24, 95% CI:(0.59;1.89), p < 0.001. The lung size, corrected for estimated fetal weight, was larger than in the fetuses without transposition; mean difference is 8.1 cm3/kg, 95% CI:(2.5;13.7 cm3/kg), p = 0.004.In summary, fetuses with dextro-transposition of the great arteries had both absolute and relatively larger lung volumes than those without CHD. No differences were seen in liver and total intracranial volume. Despite the small number of cases, the results are interesting and warrant further investigation.

Evaluation of the impact of cardiac implantable electronic devices on cine MRI for real-time adaptive cardiac radioablation on a 1.5 T MR-linac.

Stereotactic arrhythmia radioablation (STAR) is a novel treatment approach for refractory ventricular tachycardia (VT). The risk of treatment-induced toxicity and geographic miss can be reduced with online MRI-guidance on an MR-linac. However, most VT patients carry cardiac implantable electronic devices (CIED), which compromise MRimages. Robust MR-linac imaging sequences are required for cardiac visualization and accurate motion monitoring in presence of a CIED during MRI-guided STAR. We optimized two clinically available cine sequences for cardiorespiratory motion estimation in presence of a CIED on a 1.5 T MR-linac. The image quality, motion estimation accuracy, and geometric fidelity using these cine sequences wereevaluated. Clinically available 2D balanced steady-state free precession (bSSFP, voxel size = 3.0 3.0 10 mm3, Tscan = 96 ms, bandwidth (BW) = 1884 Hz/px) and -spoiled gradient echo ( -GRE, voxel size = 4.0 4.0 10 mm3, Tscan = 97 ms, BW = 500 Hz/px) sequences were adjusted for real-time cardiac visualization and cardiorespiratory motion estimation on a 1.5 T Unity MR-linac (Elekta AB, Stockholm, Sweden), while complying with safety guidelines for MRI in presence of CIEDs (specific absorption rate 2 W/kg and 80 mT/s). Cine acquisitions were performed in five healthy volunteers, with and without an implantable cardioverter- defibrillator (ICD) placed on the clavicle, and a VT patient. Generalized divergence-curl (GDC) deformable image registration (DIR) was used for automated landmark motion estimation in the left ventricle (LV). Gaussian processes (GP), a machine-learning technique, was trained using GDC landmarks and deployed for real-time cardiorespiratory motion prediction. -mapping was performed to assess geometric image fidelity in the presence ofCIEDs. CIEDs introduced banding artifacts partially obscuring cardiac structures in bSSFP acquisitions. In contrast, the -GRE was more robust to CIED-induced artifacts at the expense of a lower signal-to-noise ratio. In presence of an ICD, image-based cardiorespiratory motion estimation was possible for 85% (100%) of the volunteers using the bSSFP ( -GRE) sequence. The in-plane 2D root-mean-squared deviation (RMSD) range between GDC-derived landmarks and manual annotations using the bSSFP (T1-GRE) sequence was 3.1-3.3 (3.3-4.1) mm without ICD and 4.6-4.6 (3.2-3.3) mm with ICD. Without ICD, the RMSD between the GP-predictions and GDC-derived landmarks ranged between 0.9 and 2.2 mm (1.3-3.0 mm) for the bSSFP (T1-GRE) sequence. With ICD, the RMSD between the GP-predictions and GDC-derived landmarks ranged between 1.3 and 2.2 mm (1.2-3.2 mm) using the bSSFP (T1-GRE) sequence resulting in an RMSD-increase of 42%-143% (bSSFP) and -61%-142% (T1-GRE). Lead-induced spatial distortions ranged between -0.2 and 0.2 mm (-0.7-1.2 mm) using the bSSFP ( -GRE) sequence. The 98th percentile range of the spatial distortions in the gross target volume of the patient was between 0.0 and 0.4 mm (0.0-1.8 mm) when using bSSFP ( -GRE). Tailored bSSFP and -GRE sequences can facilitate real-time cardiorespiratory estimation using GP trained with GDC-derived landmarks in the majority of landmark locations in the LV despite the presence of CIEDs. The need for high temporal resolution noticeably reduced achievable spatial resolution of the cine MRIs. However, the effect of the CIED-induced artifacts is device, patient and sequence dependent and requires specific assessment percase.

Deep-Learning-Based Disease Classification in Patients Undergoing Cine Cardiac MRI.

Automated approaches may allow for fast, reproducible clinical assessment of cardiovascular diseases from MRI. To develop an MRI-based deep learning (DL) disease classification algorithm to distinguish among normal subjects (NORM), patients with dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), and ischemic heart disease (IHD). Retrospective. A total of 1337 subjects (55% female), comprising normal subjects (N = 568), and patients with DCM (N = 151), HCM (N = 177), and IHD (N = 441). Balanced steady-state free precession cine sequence at 1.5/3.0 T. Bi-ventricular morphological and functional features and global and segmental left ventricular strain features were automatically extracted from short- and long-axis cine images. Variational autoencoder models were trained on the extracted features and compared against consensus disease label provided by two expert readers (13 and 14 years of experience). Adding unlabeled, normal data to the training was explored to increase specificity of NORM class. Tenfold cross-validation for model development; mean, standard deviation (SD) for measurements; classification metrics: area under the curve (AUC), confusion matrix, accuracy, specificity, precision, recall; 95% confidence intervals; Mann-Whitney U test for significance. AUCs of 0.952 for NORM, 0.881 for DCM, 0.908 for HCM, and 0.856 for IHD and overall accuracy of 0.778 were obtained, with specificity of 0.908 for the NORM class using both SAX and LAX features. Longitudinal strain features slightly improved classification metrics by 0.001 to 0.03 points, except for HCM-AUC. Differences in accuracy, metrics for NORM class and HCM-AUC were statistically significant. Cotraining using unlabeled data increased the specificity for the NORM class to 0.961. Cardiac function features automatically extracted from cine MRI have potential to be used for disease classification, especially for normal-abnormal classification. Feature analyses showed that strain features were important for disease labeling. Cotraining using unlabeled data may help to increase specificity for normal-abnormal classification. 3 TECHNICAL EFFICACY: Stage 1.

Accelerated Cartesian cardiac T2 mapping based on a calibrationless locally low-rank tensor constraint.

Cardiac T2 mapping is a valuable tool for diagnosing myocardial edema, inflammation, and infiltration, yet its spatial resolution is limited by the single-shot balanced steady-state free precession acquisition and duration of the cardiac quiescent period, which may reduce sensitivity in detecting focal lesions in the myocardium. To improve spatial resolution without extending the acquisition window, this study examined a novel accelerated Cartesian cardiac T2 mapping technique. We introduce a novel improved-resolution cardiac T2 mapping approach leveraging a calibrationless space-contrast-coil locally low-rank tensor (SCC-LLRT)-constrained reconstruction algorithm in conjunction with Cartesian undersampling trajectory. The method was validated with phantom imaging and in vivo imaging that involved 13 healthy participants and 20 patients. The SCC-LLRT algorithm was compared with a conventional locally low-rank (LLR)-constrained algorithm and a nonlinear inversion (NLINV) reconstruction algorithm. The improved-resolution T2 mapping (1.4 mm × 1.4 mm) was compared globally and regionally with the regular-resolution T2 mapping (2.3 mm × 1.9 mm) according to the 16-segment model of the American Heart Association. The agreement between the improved-resolution and regular-resolution T2 mappings was evaluated by linear regression and Bland-Altman analyses. Image quality was scored by two experienced reviewers on a five-point scale (1, worst; 5, best). In healthy participants, SCC-LLRT significantly reduced artifacts (4.50±0.39) compared with LLR (2.31±0.60; P<0.001) and NLINV (3.65±0.56; P<0.01), suppressed noise (4.12±0.35) compared with NLINV (2.65±0.50; P<0.001), and improved the overall image quality (4.38±0.40) compared with LLR (2.54±0.41; P<0.001) and NLINV (3.04±0.50; P<0.001). Compared with the regular-resolution T2 mapping, the proposed method significantly improved the sharpness of myocardial boundaries (4.46±0.60 vs. 3.04±0.50; P<0.001) and the conspicuity of papillary muscles and fine structures (4.46±0.63 vs. 2.65±0.30; P<0.001). Myocardial T2 values obtained with the proposed method correlated significantly with those from regular-resolution T2 mapping in both healthy participants (r=0.79; P<0.01) and patients (r=0.94; P<0.001). The proposed SCC-LLRT-constrained reconstruction algorithm in conjunction with Cartesian undersampling pattern achieved improved-resolution cardiac T2 mapping of comparable accuracy, precision, and scan-rescan reproducibility compared with the regular-resolution T2 mapping. The higher resolution improved the sharpness of myocardial borders and the conspicuity of image fine details, which may increase diagnostic confidence in cardiac T2 mapping for detecting small lesions.

Enhancing organ and vascular contrast in preclinical ultra-low field MRI using superparamagnetic iron oxide nanoparticles

Superparamagnetic iron oxide nanoparticles (SPIONs) are characterized by their exceptional susceptibility and relaxivity at ultra-low field (ULF) regimes, make them a promising contrast agent (CA) for ULF MRI. Despite their distinct advantages, the translation of these properties into clinically valuable image contrast in ULF MRI remains underexplored. In this study, we investigate the use of SPIONs to generate in vivo MRI contrast at 6.5 mT within the organs and vascular system of rodents. This investigation includes comprehensive SPION characterization and phantom imaging experiments to validate the utility of SPIONs to produce positive image contrast and to facilitate phase-sensitive imaging at ULF. Optimized balanced steady-state free precession (bSSFP) and spoiled gradient echo (SPGR) MRI sequences are used to generate in vivo contrast by leveraging the distinctive properties of SPIONs at ULF. Imaging studies in rodents reveal positive organ contrast attainable in magnitude images, and MRI phase maps can be used to visualize the vascular system. This work demonstrates the effectiveness of SPIONs in enhancing preclinical organ and vascular imaging at ULF; it bridges the gap between the study of the distinctive physical properties of SPIONs and the demonstration of in vivo image contrast.