Purpose: The purpose of this study was to introduce and evaluate a novel 2D wideband black-blood (BB) LGE sequence, incorporating wideband inversion recovery, wideband T2 preparation, and non-rigid motion correction (MOCO) reconstruction, to improve myocardial scar detection and address artifacts associated with implantable cardioverter defibrillators (ICDs). Materials and methods: The wideband MOCO free-breathing BB-LGE sequence was tested on a sheep with ischemic scar and in 22 patients with cardiac disease, including 15 with cardiac implants, at 1.5T. Wideband MOCO free-breathing BB-LGE sequence was compared with conventional and wideband breath-held PSIR-LGE and conventional and wideband breath-held BB-LGE techniques. Image sharpness, entropy, and scar-to-blood, scar-to-myocardium, and blood-to-myocardium contrast were analyzed and reconstruction times were measured. Two expert readers assessed the image quality, ICD artifact severity, and the diagnostic confidence with scar extent. Finally, for the animal study, a histology of the heart was performed to confirm the presence and localization of scar tissue. Results: In the animal, wideband MOCO free-breathing BB-LGE were reconstructed in 0.6 s and demonstrated a 200 % improvement in scar-to-blood contrast compared to wideband breath-held PSIR-LGE, with significant improvement in image sharpness and reduction in entropy. It also effectively minimized ICD artifacts and accurately detected scars. In patients, wideband MOCO free-breathing BB-LGE were reconstructed in 1.5 +/- 0.4 (standard deviation) s per slice. Seventeen patients (17/22; 77%) with myocardial scars were confidently diagnosed with wideband MOCO free-breathing BB-LGE, compared to 11 (11/22; 50 %) with wideband breath-held PSIR-LGE (P < 0.01). Conclusion: Free-breathing wideband T2-prepared black-blood LGE imaging, combined with motion-corrected reconstruction, offers a promising diagnostic approach for the evaluation of myocardial lesions in patients with ICDs.

Motivation: Bright-blood sequences are used to retrieve information about cardiac anatomy and function, while black-blood sequences have been exploited for focal scar detection. Moreover, contrast agent-free T1-rho (T1ρ) mapping has shown promise for scar quantification, particularly of diffuse nature. Goal(s): We propose SPOT1ρ, a single-click joint bright-blood, black-blood, and T1ρ mapping sequence providing improved scar localization, detection, and quantification. Approach: The proposed SPOT1ρ was compared to reference sequences in phantom and patients (three myocardial infarctions, one cardiac amyloidosis and one healthy control). Results: Excellent correlation was observed between SPOT1ρ and reference T1ρ values, along with co-registered bright- and black-blood images in phantom and patients. Impact: The proposed single-click SPOT1ρ permits easier and faster planning for MR technicians, more comfort for the patient, promoted by fewer breath-holds, and a simplified interpretation for the radiologists, through co-registered, qualitative, and quantitative images.

BACKGROUND:5D, free-running imaging resolves sets of 3D whole-heart images in both cardiac and respiratory dimensions. In an application such as coronary imaging when a single, static image is of interest, computationally expensive offline iterative reconstruction is still needed to compute the multiple 3D datasets. PURPOSE:Evaluate how the number of physiologic bins included in the reconstruction affects the computational cost and resulting image quality of a single, static volume reconstruction. STUDY TYPE:Retrospective. SUBJECTS:15 pediatric patients following Ferumoxytol infusion (4 mg/kg). FIELD STRENGTH/SEQUENCE:1.5 T/Ungated 5D free-running GRE sequence. ASSESSMENT:The raw data of each subject were binned and reconstructed into a 5D (x-y-z-cardiac-respiratory) images. 1, 3, 5, 7, and 9 bins adjacent to both sides of the retrospectively determined cardiac resting phase and 1, 3 bins adjacent to the end-expiration phase are used for limited frame reconstructions. The static volume within each limited reconstruction was compared with the corresponding full 5D reconstruction using the structural similarity index measure (SSIM). A non-linear regression model was used to fit SSIM with the percentage of data used compared to full reconstruction (% data). A linear regression model was used to fit computation time with % raw data used. Coronary artery sharpness is measured on each limited reconstructed images to determine the minimal number of cardiac and respiratory bins needed to preserve image quality. STATISTICAL TESTS:The coefficient of determination (R2) is computed for each regression model. RESULTS:The % of data used in the reconstruction was linearly related to the computational time (R2 = 0.99). The SSIM of the static image from the limited reconstructions is non-linearly related with the % of data used (R2 = 0.80). Over the 15 patients, the model showed SSIM of 0.9 with 18% of data, and SSIM of 0.96 with 30% of data. The coronary artery sharpness of images reconstructed using no less than 5 cardiac and all respiratory phases is not significantly different from the full reconstructed images using all cardiac and respiratory bins. DATA CONCLUSION:Reconstruction using only a limited number of acquired physiological states can linearly reduce the computational cost while preserving similarity to the full reconstruction image. It is suggested to use no less than 5 cardiac and all respiratory phases in the limited reconstruction to best preserve the original quality seen on the full reconstructed images.

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.

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.

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.

Conventional LGE PSIR provides very good contrast between healthy and scar tissue, but scar patterns may be confused with blood signal. Joint LGE bright- and black-blood imaging allows for improved scar contrast and detailed cardiac anatomy. However, many patients with cardiac implantable electronic device (CIED) do not undergo cardiac imaging due to severe hyperintensity artefacts. Here we propose a technology to image myocardial scars with unprecedent scar contrast in patients with CIED by combining bright- and black-blood SPOT imaging with wideband MRI. We showed that wideband SPOT can suppress CIED-related hyperintensity artefacts, while maintaining improved scar contrast and localization.

Background: Free-running cardiac and respiratory motion-resolved whole-heart five-dimensional (5D) cardiovascular magnetic resonance (CMR) can reduce scan planning and provide a means of evaluating respiratory- driven changes in clinical parameters of interest. However, respiratory-resolved imaging can be limited by user- defined parameters which create trade-offs between residual artifact and motion blur. In this work, we develop and validate strategies for both correction of intra-bin and compensation of inter-bin respiratory motion to improve the quality of 5D CMR. Methods: Each component of the reconstruction framework was systematically validated and compared to the previously established 5D approach using simulated free-running data (N = 50) and a cohort of 32 patients with congenital heart disease. The impact of intra-bin respiratory motion correction was evaluated in terms of image sharpness while inter-bin respiratory motion compensation was evaluated in terms of reconstruction error, compression of respiratory motion, and image sharpness. The full reconstruction framework (intra-acquisition correction and inter-acquisition compensation of respiratory motion [IIMC] 5D) was evaluated in terms of image sharpness and scoring of image quality by expert reviewers. Results: Intra-bin motion correction provides significantly (p < 0.001) sharper images for both simulated and patient data. Inter-bin motion compensation results in significant (p < 0.001) lower reconstruction error, lower motion compression, and higher sharpness in both simulated (10/11) and patient (9/11) data. The combined framework resulted in significantly (p < 0.001) sharper IIMC 5D reconstructions (End-expiration (End-Exp): 0.45 +/- 0.09, End-inspiration (End-Ins): 0.46 +/- 0.10) relative to the previously established 5D implementation (End-Exp: 0.43 +/- 0.08, End-Ins: 0.39 +/- 0.09). Similarly, image scoring by three expert reviewers was significantly (p < 0.001) higher using IIMC 5D(End-Exp: 3.39 +/- 0.44, End-Ins: 3.32 +/- 0.45) relative to 5D images (End-Exp: 3.02 +/- 0.54, End-Ins: 2.45 +/- 0.52). Conclusion: The proposed IIMC reconstruction significantly improves the quality of 5D whole-heart MRI. This may be exploited for higher resolution or abbreviated scanning. Further investigation of the diagnostic impact of this framework and comparison to gold standards is needed to understand its full clinical utility, including exploration of respiratory-driven changes in physiological measurements of interest.

A similarity-driven multi-dimensional binning algorithm (SIMBA) reconstruction of free-running cardiac magnetic resonance imaging data was previously proposed. While very efficient and fast, the original SIMBA focused only on the reconstruction of a single motion-consistent cluster, discarding the remaining data acquired. However, the redundant data clustered by similarity may be exploited to further improve image quality. In this work, we propose a novel compressed sensing (CS) reconstruction that performs an effective regularization over the clustering dimension, thanks to the integration of inter-cluster motion compensation (XD-MC-SIMBA). This reconstruction was applied to free-running ferumoxytol-enhanced datasets from 24 patients with congenital heart disease, and compared to the original SIMBA, the same XD-MC-SIMBA reconstruction but without motion compensation (XD-SIMBA), and a 5D motion-resolved CS reconstruction using the free-running framework (FRF). The resulting images were compared in terms of lung-liver and blood-myocardium sharpness, blood-myocardium contrast ratio, and visible length and sharpness of the coronary arteries. Moreover, an automated image quality score (IQS) was assigned using a pretrained deep neural network. The lung-liver sharpness and blood-myocardium sharpness were significantly higher in XD-MC-SIMBA and FRF. Consistent with these findings, the IQS analysis revealed that image quality for XD-MC-SIMBA was improved in 18 of 24 cases, compared to SIMBA. We successfully tested the hypothesis that multiple motion-consistent SIMBA clusters can be exploited to improve the quality of ferumoxytol-enhanced cardiac MRI when inter-cluster motion-compensation is integrated as part of a CS reconstruction.

Cardiovascular magnetic resonance imaging (MRI) in patients with cardiac implants, such as pacemakers and defibrillators, has gained importance in recent years with the development of modern cardiac implantable electronic devices. The increasing clinical need to perform MRI examinations in patients with cardiac implants has driven the development of new advanced MRI sequences to mitigate image artifacts associated with cardiac implants. More specifically, advances in imaging techniques, such as wideband late gadolinium enhancement imaging, wideband T1 mapping, and wideband perfusion, have been designed to improve image quality and examinations in patients with cardiac implants, enabling a comprehensive and more reliable diagnosis, which was previously unattainable in these patients. This review article explores recent developments and applications of wideband techniques in the field of cardiovascular MRI, offering insights into their transformative potential. Clinical applications of wideband cardiovascular MRI are highlighted, particularly in assessing myocardial viability, guiding ventricular tachycardia ablation, and characterizing myocardial tissue.

Free-running cardiac and respiratory motion-resolved whole-heart 5D MRI can reduce scan planning and provide a means of evaluating respiratory-driven changes in clinical parameters of interest. However, respiratory-resolved imaging can be limited by user-defined parameters which create trade-offs between residual artifact and motion blur. In this work, we develop and validate strategies for both correction of intra-bin and compensation of inter-bin respiratory motion to improve the quality of 5D MRI. Each component of the reconstruction framework was systematically validated and compared to the previously established 5D approach using simulated free-running data (N=50) and a cohort of 32 patients with congenital heart disease. The impact of intra-bin respiratory motion correction was evaluated in terms of image sharpness while inter-bin respiratory motion compensation was evaluated in terms of reconstruction error, compression of respiratory motion, and image sharpness. The full reconstruction framework (IIMC 5D) was evaluated in terms of image sharpness and scoring of image quality by expert reviewers. Intra-bin motion correction provides significantly (p < 10-3) sharper images for both simulated and patient data. Inter-bin motion compensation results in significant (p < 10-3) lower reconstruction error, lower motion compression, and higher sharpness in both simulated (10/11) and patient (9/11) data. The combined framework resulted in significantly (p < 10-3) sharper IIMC 5D reconstructions (End-Exp: 0.45±0.09, End-Ins: 0.46±0.10) relative to the previously established 5D implementation (End-Exp: 0.43±0.08, End-Ins: 0.39±0.09). Similarly, image scoring by three expert reviewers was significantly (p < 10-3) higher using IIMC 5D (End-Exp: 3.39±0.44, End-Ins: 3.32±0.45) relative to 5D images (End-Exp: 3.02±0.54, End-Ins: 2.45±0.52). The proposed IIMC reconstruction significantly improves the quality of 5D whole-heart MRI. This may be exploited for higher resolution or abbreviated scan. Further investigation of the diagnostic impact of this framework and comparison to gold-standards is needed to understand its full clinical utility including exploration of respiratory-driven changes in physiological measurements of interest.

Unveiling the unseen: next-generation cardiac magnetic resonance imaging Cardiovascular disease (CVD) claims over 1.8 million European lives yearly, surpassing cancer, chronic respiratory disease and diabetes fatalities. Cardiac magnetic resonance imaging (CMR) is crucial for understanding and treating CVD, offering radiation-free comprehensive heart assessment. However, current CMR systems are slow, complex and require specialised expertise, limiting widespread adoption. SMHEART aims to revolutionise CMR with a one-click approach, creating a unique 3D whole-heart volume for automated cardiology diagnosis, prognosis and therapy selection. This project streamlines CMR, facilitating broader acceptance and optimising its impact on personalised patient care, including diagnosis, risk stratification, therapy selection, monitoring and image-guided interventions.

BackgroundMyocardial T1‐rho (T1ρ) mapping is a promising method for identifying and quantifying myocardial injuries without contrast agents, but its clinical use is hindered by the lack of dedicated analysis tools.PurposeTo explore the feasibility of clinically integrated artificial intelligence‐driven analysis for efficient and automated myocardial T1ρ mapping.Study TypeRetrospective.PopulationFive hundred seventy‐three patients divided into a training (N = 500) and a test set (N = 73) including ischemic and nonischemic cases.Field Strength/SequenceSingle‐shot bSSFP T1ρ mapping sequence at 1.5 T.AssessmentThe automated process included: left ventricular (LV) wall segmentation, right ventricular insertion point detection and creation of a 16‐segment model for segmental T1ρ value analysis. Two radiologists (20 and 7 years of MRI experience) provided ground truth annotations. Interobserver variability and segmentation quality were assessed using the Dice coefficient with manual segmentation as reference standard. Global and segmental T1ρ values were compared. Processing times were measured.Statistical TestsIntraclass correlation coefficients (ICCs) and Bland–Altman analysis (bias ±2SD); Paired Student's t‐tests and one‐way ANOVA. A P value <0.05 was considered significant.ResultsThe automated approach significantly reduced processing time (3 seconds vs. 1 minute 51 seconds ± 22 seconds). In the test set, automated LV wall segmentation closely matched manual results (Dice 81.9% ± 9.0) and closely aligned with interobserver segmentation (Dice 82.2% ± 6.5). Excellent ICCs were achieved on a patient basis (0.94 [95% CI: 0.91 to 0.96]) with bias of −0.93 cm2 ± 6.60. There was no significant difference in global T1ρ values between manual (54.9 msec ± 4.6; 95% CI: 53.8 to 56.0 msec, range: 46.6–70.9 msec) and automated processing (55.4 msec ± 5.1; 95% CI: 54.2 to 56.6 msec; range: 46.4–75.1 msec; P = 0.099). The pipeline demonstrated a high level of agreement with manual‐derived T1ρ values at the patient level (ICC = 0.85; bias +0.52 msec ± 5.18). No significant differences in myocardial T1ρ values were found between methods across the 16 segments (P = 0.75).Data ConclusionAutomated myocardial T1ρ mapping shows promise for the rapid and noninvasive assessment of heart disease.Evidence Level3Technical EfficacyStage 1

Ferumoxytol-enhanced free-running whole-heart MRI allows for a comprehensive evaluation of the cardiovascular anatomy in 3D. A similarity-driven multi-dimensional binning algorithm (SIMBA) has been proposed as a fast and efficient reconstruction of such data, by clustering and selecting motion-consistent information. In this work, we extend the SIMBA reconstruction to make use of the inherent redundancy of motion-consistent information using a compressed-sensing reconstruction, in which sparsity is maximized by the integration of inter-cluster non-rigid 3D motion-fields. With this new framework we demonstrate improved image quality, increased coronary sharpness and vessel conspicuity.

Artificial intelligence (AI) integration in cardiac magnetic resonance imaging presents new and exciting avenues for advancing patient care, automating post-processing tasks, and enhancing diagnostic precision and outcomes. The use of AI significantly streamlines the examination workflow through the reduction of acquisition and postprocessing durations, coupled with the automation of scan planning and acquisition parameters selection. This has led to a notable improvement in examination workflow efficiency, a reduction in operator variability, and an enhancement in overall image quality. Importantly, AI unlocks new possibilities to achieve spatial resolutions that were previously unattainable in patients. Furthermore, the potential for low-dose and contrast-agent-free imaging represents a stride toward safer and more patient-friendly diagnostic procedures. Beyond these benefits, AI facilitates precise risk stratification and prognosis evaluation by adeptly analysing extensive datasets. This comprehensive review article explores recent applications of AI in the realm of cardiac magnetic resonance imaging, offering insights into its transformative potential in the field.

PURPOSE OF REVIEW:Imaging plays a crucial role in the therapy of ventricular tachycardia (VT). We offer an overview of the different methods and provide information on their use in a clinical setting.RECENT FINDINGS:The use of imaging in VT has progressed recently. Intracardiac echography facilitates catheter navigation and the targeting of moving intracardiac structures. Integration of pre-procedural CT or MRI allows for targeting the VT substrate, with major expected impact on VT ablation efficacy and efficiency. Advances in computational modeling may further enhance the performance of imaging, giving access to pre-operative simulation of VT. These advances in non-invasive diagnosis are increasingly being coupled with non-invasive approaches for therapy delivery. This review highlights the latest research on the use of imaging in VT procedures. Image-based strategies are progressively shifting from using images as an adjunct tool to electrophysiological techniques, to an integration of imaging as a central element of the treatment strategy.

The potential of cardiac magnetic resonance to improve cardiovascular care and patient management is considerable. Myocardial T1-rho (T1ρ) mapping, in particular, has emerged as a promising biomarker for quantifying myocardial injuries without exogenous contrast agents. Its potential as a contrast-agent-free ("needle-free") and cost-effective diagnostic marker promises high impact both in terms of clinical outcomes and patient comfort. However, myocardial T1ρ mapping is still at a nascent stage of development and the evidence supporting its diagnostic performance and clinical effectiveness is scant, though likely to change with technological improvements. The present review aims at providing a primer on the essentials of myocardial T1ρ mapping, and to describe the current range of clinical applications of the technique to detect and quantify myocardial injuries. We also delineate the important limitations and challenges for clinical deployment, including the urgent need for standardization, the evaluation of bias, and the critical importance of clinical testing. We conclude by outlining technical developments to be expected in the future. If needle-free myocardial T1ρ mapping is shown to improve patient diagnosis and prognosis, and can be effectively integrated in cardiovascular practice, it will fulfill its potential as an essential component of a cardiac magnetic resonance examination.

The advent of invasive and non-invasive imaging tools in early phenotyp-ing of disease, risk assessment