Wideband black-blood late gadolinium enhancement imaging for improved myocardial scar assessment in patients with cardiac implantable electronic devices.

PURPOSE: Wideband phase-sensitive inversion recovery (PSIR) late gadolinium enhancement (LGE) enables myocardial scar imaging in implantable cardioverter defibrillators (ICD) patients, mitigating hyperintensity artifacts. To address subendocardial scar visibility challenges, a 2D breath-hold single-shot electrocardiography-triggered black-blood (BB) LGE sequence was integrated with wideband imaging, enhancing scar-blood contrast. METHODS: Wideband BB, with increased bandwidth in the inversion pulse (0.8-3.8 kHz) and T2 preparation refocusing pulses (1.6-5.0 kHz), was compared with conventional and wideband PSIR, and conventional BB, in a phantom and sheep with and without ICD, and in six patients with cardiac devices and known myocardial injury. ICD artifact extent was quantified in the phantom and specific absorption rate (SAR) was reported for each sequence. Image contrast ratios were analyzed in both phantom and animal experiments. Expert radiologists assessed image quality, artifact severity, and scar segments in patients and sheep. Additionally, histology was performed on the sheep's heart. RESULTS: In the phantom, wideband BB reduced ICD artifacts by 62% compared to conventional BB while substantially improving scar-blood contrast, but with a SAR more than 24 times that of wideband PSIR. Similarly, the animal study demonstrated a considerable increase in scar-blood contrast with wideband BB, with superior scar detection compared with wideband PSIR, the latter confirmed by histology. In alignment with the animal study, wideband BB successfully eliminated severe ICD hyperintensity artifacts in all patients, surpassing wideband PSIR in image quality and scar detection. CONCLUSION: Wideband BB may play a crucial role in imaging ICD patients, offering images with reduced ICD artifacts and enhanced scar detection.

Fully automated contrast selection of joint bright- and black-blood late gadolinium enhancement imaging for robust myocardial scar assessment.

PURPOSE: Joint bright- and black-blood MRI techniques provide improved scar localization and contrast. Black-blood contrast is obtained after the visual selection of an optimal inversion time (TI) which often results in uncertainties, inter- and intra-observer variability and increased workload. In this work, we propose an artificial intelligence-based algorithm to enable fully automated TI selection and simplify myocardial scar imaging. METHODS: The proposed algorithm first localizes the left ventricle using a U-Net architecture. The localized left cavity centroid is extracted and a squared region of interest ("focus box") is created around the resulting pixel. The focus box is then propagated on each image and the sum of the pixel intensity inside is computed. The smallest sum corresponds to the image with the lowest intensity signal within the blood pool and healthy myocardium, which will provide an ideal scar-to-blood contrast. The image's corresponding TI is considered optimal. The U-Net was trained to segment the epicardium in 177 patients with binary cross-entropy loss. The algorithm was validated retrospectively in 152 patients, and the agreement between the algorithm and two magnetic resonance (MR) operators' prediction of TI values was calculated using the Fleiss' kappa coefficient. Thirty focus box sizes, ranging from 2.3mm2 to 20.3cm2, were tested. Processing times were measured. RESULTS: The U-Net's Dice score was 93.0 ± 0.1%. The proposed algorithm extracted TI values in 2.7 ± 0.1 s per patient (vs. 16.0 ± 8.5 s for the operator). An agreement between the algorithm's prediction and the MR operators' prediction was found in 137/152 patients (κ= 0.89), for an optimal focus box of size 2.3cm2. CONCLUSION: The proposed fully-automated algorithm has potential of reducing uncertainties, variability, and workload inherent to manual approaches with promise for future clinical implementation for joint bright- and black-blood MRI.

Assessment of myocardial injuries in ischaemic and non-ischaemic cardiomyopathies using magnetic resonance T1-rho mapping.

AIMS: To identify clinical correlates of myocardial T1ρ and to examine how myocardial T1ρ values change under various clinical scenarios. METHODS AND RESULTS: A total of 66 patients (26% female, median age 57 years [Q1-Q3, 44-65 years]) with known structural heart disease and 44 controls (50% female, median age 47 years [28-57 years]) underwent cardiac magnetic resonance imaging at 1.5 T, including T1ρ mapping, T2 mapping, native T1 mapping, late gadolinium enhancement, and extracellular volume (ECV) imaging. In controls, T1ρ positively related with T2 (P = 0.038) and increased from basal to apical levels (P < 0.001). As compared with controls and remote myocardium, T1ρ significantly increased in all patients' sub-groups and all types of myocardial injuries: acute and chronic injuries, focal and diffuse tissue abnormalities, as well as ischaemic and non-ischaemic aetiologies (P < 0.05). T1ρ was independently associated with T2 in patients with acute injuries (P = 0.004) and with native T1 and ECV in patients with chronic injuries (P < 0.05). Myocardial T1ρ mapping demonstrated good intra- and inter-observer reproducibility (intraclass correlation coefficient = 0.86 and 0.83, respectively). CONCLUSION: Myocardial T1ρ mapping appears to be reproducible and equally sensitive to acute and chronic myocardial injuries, whether of ischaemic or non-ischaemic origins. It may thus be a contrast-agent-free biomarker for gaining new and quantitative insight into myocardial structural disorders. These findings highlight the need for further studies through prospective and randomized trials.

Endogenous assessment of myocardial injury with single-shot model-based non-rigid motion-corrected T1 rho mapping.

BACKGROUND: Cardiovascular magnetic resonance T1ρ mapping may detect myocardial injuries without exogenous contrast agent. However, multiple co-registered acquisitions are required, and the lack of robust motion correction limits its clinical translation. We introduce a single breath-hold myocardial T1ρ mapping method that includes model-based non-rigid motion correction. METHODS: A single-shot electrocardiogram (ECG)-triggered balanced steady state free precession (bSSFP) 2D adiabatic T1ρ mapping sequence that collects five T1ρ-weighted (T1ρw) images with different spin lock times within a single breath-hold is proposed. To address the problem of residual respiratory motion, a unified optimization framework consisting of a joint T1ρ fitting and model-based non-rigid motion correction algorithm, insensitive to contrast change, was implemented inline for fast (~ 30 s) and direct visualization of T1ρ maps. The proposed reconstruction was optimized on an ex vivo human heart placed on a motion-controlled platform. The technique was then tested in 8 healthy subjects and validated in 30 patients with suspected myocardial injury on a 1.5T CMR scanner. The Dice similarity coefficient (DSC) and maximum perpendicular distance (MPD) were used to quantify motion and evaluate motion correction. The quality of T1ρ maps was scored. In patients, T1ρ mapping was compared to cine imaging, T2 mapping and conventional post-contrast 2D late gadolinium enhancement (LGE). T1ρ values were assessed in remote and injured areas, using LGE as reference. RESULTS: Despite breath holds, respiratory motion throughout T1ρw images was much larger in patients than in healthy subjects (5.1 ± 2.7 mm vs. 0.5 ± 0.4 mm, P < 0.01). In patients, the model-based non-rigid motion correction improved the alignment of T1ρw images, with higher DSC (87.7 ± 5.3% vs. 82.2 ± 7.5%, P < 0.01), and lower MPD (3.5 ± 1.9 mm vs. 5.1 ± 2.7 mm, P < 0.01). This resulted in significantly improved quality of the T1ρ maps (3.6 ± 0.6 vs. 2.1 ± 0.9, P < 0.01). Using this approach, T1ρ mapping could be used to identify LGE in patients with 93% sensitivity and 89% specificity. T1ρ values in injured (LGE positive) areas were significantly higher than in the remote myocardium (68.4 ± 7.9 ms vs. 48.8 ± 6.5 ms, P < 0.01). CONCLUSIONS: The proposed motion-corrected T1ρ mapping framework enables a quantitative characterization of myocardial injuries with relatively low sensitivity to respiratory motion. This technique may be a robust and contrast-free adjunct to LGE for gaining new insight into myocardial structural disorders.

High-Spatial-Resolution 3D Whole-Heart MRI T2 Mapping for Assessment of Myocarditis.

Background Clinical guidelines recommend the use of established T2 mapping sequences to detect and quantify myocarditis and edema, but T2 mapping is performed in two dimensions with limited coverage and repetitive breath holds. Purpose To assess the reproducibility of an accelerated free-breathing three-dimensional (3D) whole-heart T2 MRI mapping sequence in phantoms and participants without a history of cardiac disease and to investigate its clinical performance in participants with suspected myocarditis. Materials and Methods Eight participants (three women, mean age, 31 years ± 4 [standard deviation]; cohort 1) without a history of cardiac disease and 25 participants (nine women, mean age, 45 years ± 17; cohort 2) with clinically suspected myocarditis underwent accelerated free-breathing 3D whole-heart T2 mapping with 100% respiratory scanning efficiency at 1.5 T. The participants were enrolled from November 2018 to August 2020. Three repeated scans were performed on 2 separate days in cohort 1. Segmental variations in T2 relaxation times of the left ventricular myocardium were assessed, and intrasession and intersession reproducibility were measured. In cohort 2, segmental myocardial T2 values, detection of focal inflammation, and map quality were compared with those obtained from clinical breath-hold two-dimensional (2D) T2 mapping. Statistical differences were assessed using the nonparametric Mann-Whitney and Kruskal-Wallis tests, whereas the paired Wilcoxon signed-rank test was used to assess subjective scores. Results Whole-heart T2 maps were acquired in a mean time of 6 minutes 53 seconds ± 1 minute 5 seconds at 1.5 mm3 resolution. Breath-hold 2D and free-breathing 3D T2 mapping had similar intrasession (mean T2 change of 3.2% and 2.3% for 2D and 3D, respectively) and intersession (4.8% and 4.9%, respectively) reproducibility. The two T2 mapping sequences showed similar map quality (P = .23, cohort 2). Abnormal myocardial segments were identified with confidence (score 3) in 14 of 25 participants (56%) with 3D T2 mapping and only in 10 of 25 participants (40%) with 2D T2 mapping. Conclusion High-spatial-resolution three-dimensional (3D) whole-heart T2 mapping shows high intrasession and intersession reproducibility and helps provide T2 myocardial characterization in agreement with clinical two-dimensional reference, while enabling 3D assessment of focal disease with higher confidence. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Friedrich in this issue.

Faster 3D saturation-recovery based myocardial T1 mapping using a reduced number of saturation points and denoising.

PURPOSE: To accelerate the acquisition of free-breathing 3D saturation-recovery-based (SASHA) myocardial T1 mapping by acquiring fewer saturation points in combination with a post-processing 3D denoising technique to maintain high accuracy and precision. METHODS: 3D SASHA T1 mapping acquires nine T1-weighted images along the saturation recovery curve, resulting in long acquisition times. In this work, we propose to accelerate conventional cardiac T1 mapping by reducing the number of saturation points. High T1 accuracy and low standard deviation (as a surrogate for precision) is maintained by applying a 3D denoising technique to the T1-weighted images prior to pixel-wise T1 fitting. The proposed approach was evaluated on a T1 phantom and 20 healthy subjects, by varying the number of T1-weighted images acquired between three and nine, both prospectively and retrospectively. Following the results from the healthy subjects, three patients with suspected cardiovascular disease were acquired using five T1-weighted images. T1 accuracy and precision was determined for all the acquisitions before and after denoising. RESULTS: In the T1 phantom, no statistical difference was found in terms of accuracy and precision for the different number of T1-weighted images before or after denoising (P = 0.99 and P = 0.99 for accuracy, P = 0.64 and P = 0.42 for precision, respectively). In vivo, both prospectively and retrospectively, the precision improved considerably with the number of T1-weighted images employed before denoising (P<0.05) but was independent on the number of T1-weighted images after denoising. CONCLUSION: We demonstrate the feasibility of accelerating 3D SASHA T1 mapping by reducing the number of acquired T1-weighted images in combination with an efficient 3D denoising, without affecting accuracy and precision of T1 values.

One-millimeter isotropic breast diffusion-weighted imaging: Evaluation of a superresolution strategy in terms of signal-to-noise ratio, sharpness and apparent diffusion coefficient.

PURPOSE: To quantitatively evaluate a superresolution technique for 3D, one-millimeter isotropic diffusion-weighted imaging (DWI) of the whole breasts. METHODS: Isotropic 3D DWI datasets are obtained using a combination of (i) a readout-segmented diffusion-weighted-echo-planar imaging (DW-EPI) sequence (rs-EPI), providing high in-plane resolution, and (ii) a superresolution (SR) strategy, which consists of acquiring 3 datasets with thick slices (3 mm) and 1-mm shifts in the slice direction, and combining them into a 1 × 1 × 1-mm3 dataset using a dedicated reconstruction. Two SR reconstruction schemes were investigated, based on different regularization schemes: conventional Tikhonov or Beltrami (an edge-preserving constraint). The proposed SR strategy was compared to native 1 × 1 × 1-mm3 acquisitions (i.e. with 1-mm slice thickness) in 8 healthy subjects, in terms of signal-to-noise ratio (SNR) efficiency, using a theoretical framework, Monte Carlo simulations and region-of-interest (ROI) measurements, and image sharpness metrics. Apparent diffusion coefficient (ADC) values in normal breast tissue were also compared. RESULTS: The SR images resulted in an SNR gain above 3 compared to native 1 × 1 × 1-mm3 using the same acquisition duration (acquisition gain 3 and reconstruction gain >1). Beltrami-SR provided the best results in terms of SNR and image sharpness. The ADC values in normal breast measured from Beltrami-SR were preserved compared to low-resolution images (1.91 versus 1.97 ×10-3 mm2 /s, P = .1). CONCLUSION: A combination of rs-EPI and SR allows 3D, 1-mm isotropic breast DWI data to be obtained with better SNR than a native 1-mm isotropic acquisition. The proposed DWI protocol might be of interest for breast cancer monitoring/screening without injection.