Novel systematic processing of cardiac magnetic resonance imaging identifies target regions associated with infarct-related ventricular tachycardia.

AIMS: There is lack of agreement on late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging processing for guiding ventricular tachycardia (VT) ablation. We aim at developing and validating a systematic processing approach on LGE-CMR images to identify VT corridors that contain critical VT isthmus sites. METHODS AND RESULTS: This is a translational study including 18 pigs with established myocardial infarction and inducible VT undergoing in vivo characterization of the anatomical and functional myocardial substrate associated with VT maintenance. Clinical validation was conducted in a multicentre series of 33 patients with ischaemic cardiomyopathy undergoing VT ablation. Three-dimensional LGE-CMR images were processed using systematic scanning of 15 signal intensity (SI) cut-off ranges to obtain surface visualization of all potential VT corridors. Analysis and comparisons of imaging and electrophysiological data were performed in individuals with full electrophysiological characterization of the isthmus sites of at least one VT morphology. In both the experimental pig model and patients undergoing VT ablation, all the electrophysiologically defined isthmus sites (n = 11 and n = 19, respectively) showed overlapping regions with CMR-based potential VT corridors. Such imaging-based VT corridors were less specific than electrophysiologically guided ablation lesions at critical isthmus sites. However, an optimized strategy using the 7 most relevant SI cut-off ranges among patients showed an increase in specificity compared to using 15 SI cut-off ranges (70 vs. 62%, respectively), without diminishing the capability to detect VT isthmus sites (sensitivity 100%). CONCLUSION: Systematic imaging processing of LGE-CMR sequences using several SI cut-off ranges may improve and standardize procedure planning to identify VT isthmus sites.

Histopathological Validation of Dark-Blood Late Gadolinium Enhancement MRI Without Additional Magnetization Preparation.

BACKGROUND: Conventional bright-blood late gadolinium enhancement (LGE) cardiac magnetic resonance imaging (MRI) often suffers from poor scar-to-blood contrast due to the bright blood pool adjacent to the enhanced scar tissue. Recently, a dark-blood LGE method was developed which increases scar-to-blood contrast without using additional magnetization preparation. PURPOSE: We aim to histopathologically validate this dark-blood LGE method in a porcine animal model with induced myocardial infarction (MI). STUDY TYPE: Prospective. ANIMAL MODEL: Thirteen female Yorkshire pigs. FIELD STRENGTH/SEQUENCE: 1.5 T, two-dimensional phase-sensitive inversion-recovery radiofrequency-spoiled turbo field-echo. ASSESSMENT: MI was experimentally induced by transient coronary artery occlusion. At 1-week and 7-week post-infarction, in-vivo cardiac MRI was performed including conventional bright-blood and novel dark-blood LGE. Following the second MRI examination, the animals were sacrificed, and histopathology was obtained. Matching LGE slices and histopathology samples were selected based on anatomical landmarks. Independent observers, while blinded to other data, manually delineated the endocardial, epicardial, and infarct borders on either LGE images or histopathology samples. The percentage of infarcted left-ventricular myocardium was calculated for both LGE methods on a per-slice basis, and compared with histopathology as reference standard. Contrast-to-noise ratios were calculated for both LGE methods at 1-week and 7-week post-infarction. STATISTICAL TESTS: Pearson's correlation coefficient and paired-sample t-tests were used. Significance was set at P < 0.05. RESULTS: A combined total of 24 matched LGE and histopathology slices were available for histopathological validation. Dark-blood LGE demonstrated a high level of agreement compared to histopathology with no significant bias (-0.03%, P = 0.75). In contrast, bright-blood LGE showed a significant bias of -1.57% (P = 0.03) with larger 95% limits of agreement than dark-blood LGE. Image analysis demonstrated significantly higher scar-to-blood contrast for dark-blood LGE compared to bright-blood LGE, at both 1-week and 7-weeks post-infarction. DATA CONCLUSION: Dark-blood LGE without additional magnetization preparation provides superior visualization and quantification of ischemic scar compared to the current in vivo reference standard. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

Transforming a pre-existing MRI environment into an interventional cardiac MRI suite.

AIMS: To illustrate the practical and technical challenges along with the safety aspects when performing MRI-guided electrophysiological procedures in a pre-existing diagnostic magnetic resonance imaging (MRI) environment. METHODS AND RESULTS: A dedicated, well-trained multidisciplinary interventional cardiac MRI team (iCMR team), consisting of electrophysiologists, imaging cardiologists, radiologists, anaesthesiologists, MRI physicists, electrophysiological (EP) and MRI technicians, biomedical engineers, and medical instrumentation technologists is a prerequisite for a safe and feasible implementation of CMR-guided electrophysiological procedures (iCMR) in a pre-existing MRI environment. A formal dry run "mock-up" to address the entire spectrum of technical, logistic, and safety issues was performed before obtaining final approval of the Board of Directors. With this process we showed feasibility of our workflow, safety protocol, and bailout procedures during iCMR outside the conventional EP lab. The practical aspects of performing iCMR procedures in a pre-existing MRI environment were addressed and solidified. Finally, the influence on neighbouring MRI scanners was evaluated, showing no interference. CONCLUSION: Transforming a pre-existing diagnostic MRI environment into an iCMR suite is feasible and safe. However, performing iCMR procedures outside the conventional fluoroscopic lab, poses challenges with technical, practical, and safety aspects that need to be addressed by a dedicated multi-disciplinary iCMR team.

Dark-blood late gadolinium enhancement cardiovascular magnetic resonance for improved detection of subendocardial scar: a review of current techniques.

For almost 20 years, late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) has been the reference standard for the non-invasive assessment of myocardial viability. Since the blood pool often appears equally bright as the enhanced scar regions, detection of subendocardial scar patterns can be challenging. Various novel LGE methods have been proposed that null or suppress the blood signal by employing additional magnetization preparation mechanisms. This review aims to provide a comprehensive overview of these dark-blood LGE methods, discussing the magnetization preparation schemes and findings in phantom, preclinical, and clinical studies. Finally, conclusions on the current evidence and limitations are drawn and new avenues for future research are discussed. Dark-blood LGE methods are a promising new tool for non-invasive assessment of myocardial viability. For a mainstream adoption of dark-blood LGE, however, clinical availability and ease of use are crucial.

Topical Application of Glycerol Increases Penetration Depth of Optical Coherence Tomography in Diagnosis of Basal Cell Carcinoma.

Optical coherence tomography is a non-invasive imaging technique that enables high-resolution in vivo imaging of skin. Although optical coherence tomography is promising for diagnosing basal cell carcinoma, its limited penetration depth may impede basal cell carcinoma subtyping. This study evaluated whether topical application of glycerol can increase penetration depth and improve the image quality and visibility of characteristic features of basal cell carcinoma. A total of 61 patients with a total of 72 basal cell carcinomas were included. Optical coherence tomography scans were obtained before and after application of an 85% glyce-rol solution. The mean penetration depth of each optical coherence tomography scan was acquired by automatically tracing both skin surface and the point of signal loss using a custom-made MATLAB program. Mean ± standard deviation penetration depth increased from 883 ± 108 to 904 ± 88 µm before and after glycerol application, respectively (p = 0.005). Topical application of glycerol leads to a significant 2.4% increase in penetration depth. However, no significant differences in image quality and visibility of basal cell carcinoma features were found.

Clinical value of dark-blood late gadolinium enhancement cardiovascular magnetic resonance without additional magnetization preparation.

BACKGROUND: For two decades, bright-blood late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) has been considered the reference standard for the non-invasive assessment of myocardial viability. While bright-blood LGE can clearly distinguish areas of myocardial infarction from viable myocardium, it often suffers from poor scar-to-blood contrast, making subendocardial scar difficult to detect. Recently, we proposed a novel dark-blood LGE approach that increases scar-to-blood contrast and thereby improves subendocardial scar conspicuity. In the present study we sought to assess the clinical value of this novel approach in a large patient cohort with various non-congenital ischemic and non-ischemic cardiomyopathies on both 1.5 T and 3 T CMR scanners of different vendors. METHODS: Three hundred consecutive patients referred for clinical CMR were randomly assigned to a 1.5 T or 3 T scanner. An entire short-axis stack and multiple long-axis views were acquired using conventional phase sensitive inversion recovery (PSIR) LGE with TI set to null myocardium (bright-blood) and proposed PSIR LGE with TI set to null blood (dark-blood), in a randomized order. The bright-blood LGE and dark-blood LGE images were separated, anonymized, and interpreted in a random order at different time points by one of five independent observers. Each case was analyzed for the type of scar, per-segment transmurality, papillary muscle enhancement, overall image quality, observer confidence, and presence of right ventricular scar and intraventricular thrombus. RESULTS: Dark-blood LGE detected significantly more cases with ischemic scar compared to conventional bright-blood LGE (97 vs 89, p = 0.008), on both 1.5 T and 3 T, and led to a significantly increased total scar burden (3.3 ± 2.4 vs 3.0 ± 2.3 standard AHA segments, p = 0.015). Overall image quality significantly improved using dark-blood LGE compared to bright-blood LGE (81.3% vs 74.0% of all segments were of highest diagnostic quality, p = 0.006). Furthermore, dark-blood LGE led to significantly higher observer confidence (confident in 84.2% vs 78.4%, p = 0.033). CONCLUSIONS: The improved detection of ischemic scar makes the proposed dark-blood LGE method a valuable diagnostic tool in the non-invasive assessment of myocardial scar. The applicability in routine clinical practice is further strengthened, as the present approach, in contrast to other recently proposed dark- and black-blood LGE techniques, is readily available without the need for scanner adjustments, extensive optimizations, or additional training.

Dark-blood late gadolinium enhancement without additional magnetization preparation.

BACKGROUND: This study evaluates a novel dark-blood late gadolinium enhancement (LGE) cardiovascular magnetic resonance imaging (CMR) method, without using additional magnetization preparation, and compares it to conventional bright-blood LGE, for the detection of ischaemic myocardial scar. LGE is able to clearly depict myocardial infarction and macroscopic scarring from viable myocardium. However, due to the bright signal of adjacent left ventricular blood, the apparent volume of scar tissue can be significantly reduced, or even completely obscured. In addition, blood pool signal can mimic scar tissue and lead to false positive observations. Simply nulling the blood magnetization by choosing shorter inversion times, leads to a negative viable myocardium signal that appears equally as bright as scar due to the magnitude image reconstruction. However, by combining blood magnetization nulling with the extended grayscale range of phase-sensitive inversion-recovery (PSIR), a darker blood signal can be achieved whilst a dark myocardium and bright scar signal is preserved. METHODS: LGE was performed in nine male patients (63 ± 11y) using a PSIR pulse sequence, with both conventional viable myocardium nulling and left ventricular blood nulling, in a randomized order. Regions of interest were drawn in the left ventricular blood, viable myocardium, and scar tissue, to assess contrast-to-noise ratios. Maximum scar transmurality, scar size, circumferential scar angle, and a confidence score for scar detection and maximum transmurality were also assessed. Bloch simulations were performed to simulate the magnetization levels of the left ventricular blood, viable myocardium, and scar tissue. RESULTS: Average scar-to-blood contrast was significantly (p < 0.001) increased by 99% when nulling left ventricular blood instead of viable myocardium, while scar-to-myocardium contrast was maintained. Nulling left ventricular blood also led to significantly (p = 0.038) higher expert confidence in scar detection and maximum transmurality. No significant changes were found in scar transmurality (p = 0.317), normalized scar size (p = 0.054), and circumferential scar angle (p = 0.117). CONCLUSIONS: Nulling left ventricular blood magnetization for PSIR LGE leads to improved scar-to-blood contrast and increased expert confidence in scar detection and scar transmurality. As no additional magnetization preparation is used, clinical application on current MR systems is readily available without the need for extensive optimizations, software modifications, and/or additional training.

Free-Running Cardiac and Respiratory Motion-Resolved Imaging: A Paradigm Shift for Managing Motion in Cardiac MRI?

Cardiac magnetic resonance imaging (MRI) is widely used for non-invasive assessment of cardiac morphology, function, and tissue characteristics due to its exquisite soft-tissue contrast. However, it remains time-consuming and requires proficiency, making it costly and limiting its widespread use. Traditional cardiac MRI is inefficient as signal acquisition is often limited to specific cardiac phases and requires complex view planning, parameter adjustments, and management of both respiratory and cardiac motion. Recent efforts have aimed to make cardiac MRI more efficient and accessible. Among these innovations, the free-running framework enables 5D whole-heart imaging without the need for an electrocardiogram signal, respiratory breath-holding, or complex planning. It uses a fully self-gated approach to extract cardiac and respiratory signals directly from the acquired image data, allowing for more efficient coverage in time and space without the need for electrocardiogram gating, triggering, navigators, or breath-holds. This review provides a comprehensive overview of the free-running framework, detailing its history, concepts, recent improvements, and clinical applications.

Deep Learning Synthesis of White-Blood From Dark-Blood Late Gadolinium Enhancement Cardiac Magnetic Resonance.

OBJECTIVES: Dark-blood late gadolinium enhancement (DB-LGE) cardiac magnetic resonance has been proposed as an alternative to standard white-blood LGE (WB-LGE) imaging protocols to enhance scar-to-blood contrast without compromising scar-to-myocardium contrast. In practice, both DB and WB contrasts may have clinical utility, but acquiring both has the drawback of additional acquisition time. The aim of this study was to develop and evaluate a deep learning method to generate synthetic WB-LGE images from DB-LGE, allowing the assessment of both contrasts without additional scan time. MATERIALS AND METHODS: DB-LGE and WB-LGE data from 215 patients were used to train 2 types of unpaired image-to-image translation deep learning models, cycle-consistent generative adversarial network (CycleGAN) and contrastive unpaired translation, with 5 different loss function hyperparameter settings each. Initially, the best hyperparameter setting was determined for each model type based on the Fréchet inception distance and the visual assessment of expert readers. Then, the CycleGAN and contrastive unpaired translation models with the optimal hyperparameters were directly compared. Finally, with the best model chosen, the quantification of scar based on the synthetic WB-LGE images was compared with the truly acquired WB-LGE. RESULTS: The CycleGAN architecture for unpaired image-to-image translation was found to provide the most realistic synthetic WB-LGE images from DB-LGE images. The results showed that it was difficult for visual readers to distinguish if an image was true or synthetic (55% correctly classified). In addition, scar burden quantification with the synthetic data was highly correlated with the analysis of the truly acquired images. Bland-Altman analysis found a mean bias in percentage scar burden between the quantification of the real WB and synthetic white-blood images of 0.44% with limits of agreement from -10.85% to 11.74%. The mean image quality of the real WB images (3.53/5) was scored higher than the synthetic white-blood images (3.03), P = 0.009. CONCLUSIONS: This study proposed a CycleGAN model to generate synthetic WB-LGE from DB-LGE images to allow assessment of both image contrasts without additional scan time. This work represents a clinically focused assessment of synthetic medical images generated by artificial intelligence, a topic with significant potential for a multitude of applications. However, further evaluation is warranted before clinical adoption.

Automated cardiovascular MR myocardial scar quantification with unsupervised domain adaptation.

Quantification of myocardial scar from late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) images can be facilitated by automated artificial intelligence (AI)-based analysis. However, AI models are susceptible to domain shifts in which the model performance is degraded when applied to data with different characteristics than the original training data. In this study, CycleGAN models were trained to translate local hospital data to the appearance of a public LGE CMR dataset. After domain adaptation, an AI scar quantification pipeline including myocardium segmentation, scar segmentation, and computation of scar burden, previously developed on the public dataset, was evaluated on an external test set including 44 patients clinically assessed for ischemic scar. The mean ± standard deviation Dice similarity coefficients between the manual and AI-predicted segmentations in all patients were similar to those previously reported: 0.76 ± 0.05 for myocardium and 0.75 ± 0.32 for scar, 0.41 ± 0.12 for scar in scans with pathological findings. Bland-Altman analysis showed a mean bias in scar burden percentage of -0.62% with limits of agreement from -8.4% to 7.17%. These results show the feasibility of deploying AI models, trained with public data, for LGE CMR quantification on local clinical data using unsupervised CycleGAN-based domain adaptation. RELEVANCE STATEMENT: Our study demonstrated the possibility of using AI models trained from public databases to be applied to patient data acquired at a specific institution with different acquisition settings, without additional manual labor to obtain further training labels.

Quantification of myocardial scar of different etiology using dark- and bright-blood late gadolinium enhancement cardiovascular magnetic resonance.

Dark-blood late gadolinium enhancement (LGE) has been shown to improve the visualization and quantification of areas of ischemic scar compared to standard bright-blood LGE. Recently, the performance of various semi-automated quantification methods has been evaluated for the assessment of infarct size using both dark-blood LGE and conventional bright-blood LGE with histopathology as a reference standard. However, the impact of this sequence on different quantification strategies in vivo remains uncertain. In this study, various semi-automated scar quantification methods were evaluated for a range of different ischemic and non-ischemic pathologies encountered in clinical practice. A total of 62 patients referred for clinical cardiovascular magnetic resonance (CMR) were retrospectively included. All patients had a confirmed diagnosis of either ischemic heart disease (IHD; n = 21), dilated/non-ischemic cardiomyopathy (NICM; n = 21), or hypertrophic cardiomyopathy (HCM; n = 20) and underwent CMR on a 1.5 T scanner including both bright- and dark-blood LGE using a standard PSIR sequence. Both methods used identical sequence settings as per clinical protocol, apart from the inversion time parameter, which was set differently. All short-axis LGE images with scar were manually segmented for epicardial and endocardial borders. The extent of LGE was then measured visually by manual signal thresholding, and semi-automatically by signal thresholding using the standard deviation (SD) and the full width at half maximum (FWHM) methods. For all quantification methods in the IHD group, except the 6 SD method, dark-blood LGE detected significantly more enhancement compared to bright-blood LGE (p < 0.05 for all methods). For both bright-blood and dark-blood LGE, the 6 SD method correlated best with manual thresholding (16.9% vs. 17.1% and 20.1% vs. 20.4%, respectively). For the NICM group, no significant differences between LGE methods were found. For bright-blood LGE, the 5 SD method agreed best with manual thresholding (9.3% vs. 11.0%), while for dark-blood LGE the 4 SD method agreed best (12.6% vs. 11.5%). Similarly, for the HCM group no significant differences between LGE methods were found. For bright-blood LGE, the 6 SD method agreed best with manual thresholding (10.9% vs. 12.2%), while for dark-blood LGE the 5 SD method agreed best (13.2% vs. 11.5%). Semi-automated LGE quantification using dark-blood LGE images is feasible in both patients with ischemic and non-ischemic scar patterns. Given the advantage in detecting scar in patients with ischemic heart disease and no disadvantage in patients with non-ischemic scar, dark-blood LGE can be readily and widely adopted into clinical practice without compromising on quantification.

Impact of reconstruction parameters on the accuracy of myocardial extracellular volume quantification on a first-generation, photon-counting detector CT.

BACKGROUND: The potential role of cardiac computed tomography (CT) has increasingly been demonstrated for the assessment of diffuse myocardial fibrosis through the quantification of extracellular volume (ECV). Photon-counting detector (PCD)-CT technology may deliver more accurate ECV quantification compared to energy-integrating detector CT. We evaluated the impact of reconstruction settings on the accuracy of ECV quantification using PCD-CT, with magnetic resonance imaging (MRI)-based ECV as reference. METHODS: In this post hoc analysis, 27 patients (aged 53.1 ± 17.2 years (mean ± standard deviation); 14 women) underwent same-day cardiac PCD-CT and MRI. Late iodine CT scans were reconstructed with different quantum iterative reconstruction levels (QIR 1-4), slice thicknesses (0.4-8 mm), and virtual monoenergetic imaging levels (VMI, 40-90 keV); ECV was quantified for each reconstruction setting. Repeated measures ANOVA and t-test for pairwise comparisons, Bland-Altman plots, and Lin's concordance correlation coefficient (CCC) were used. RESULTS: ECV values did not differ significantly among QIR levels (p = 1.000). A significant difference was observed throughout different slice thicknesses, with 0.4 mm yielding the highest agreement with MRI-based ECV (CCC = 0.944); 45-keV VMI reconstructions showed the lowest mean bias (0.6, 95% confidence interval 0.1-1.4) compared to MRI. Using the most optimal reconstruction settings (QIR4. slice thickness 0.4 mm, VMI 45 keV), a 63% reduction in mean bias and a 6% increase in concordance with MRI-based ECV were achieved compared to standard settings (QIR3, slice thickness 1.5 mm; VMI 65 keV). CONCLUSIONS: The selection of appropriate reconstruction parameters improved the agreement between PCD-CT and MRI-based ECV. RELEVANCE STATEMENT: Tailoring PCD-CT reconstruction parameters optimizes ECV quantification compared to MRI, potentially improving its clinical utility. KEY POINTS: • CT is increasingly promising for myocardial tissue characterization, assessing focal and diffuse fibrosis via late iodine enhancement and ECV quantification, respectively. • PCD-CT offers superior performance over conventional CT, potentially improving ECV quantification and its agreement with MRI-based ECV. • Tailoring PCD-CT reconstruction parameters optimizes ECV quantification compared to MRI, potentially improving its clinical utility.

Extended MRI-based PET motion correction for cardiac PET/MRI.

PURPOSE: A 2D image navigator (iNAV) based 3D whole-heart sequence has been used to perform MRI and PET non-rigid respiratory motion correction for hybrid PET/MRI. However, only the PET data acquired during the acquisition of the 3D whole-heart MRI is corrected for respiratory motion. This study introduces and evaluates an MRI-based respiratory motion correction method of the complete PET data. METHODS: Twelve oncology patients scheduled for an additional cardiac 18F-Fluorodeoxyglucose (18F-FDG) PET/MRI and 15 patients with coronary artery disease (CAD) scheduled for cardiac 18F-Choline (18F-FCH) PET/MRI were included. A 2D iNAV recorded the respiratory motion of the myocardium during the 3D whole-heart coronary MR angiography (CMRA) acquisition (~ 10 min). A respiratory belt was used to record the respiratory motion throughout the entire PET/MRI examination (~ 30-90 min). The simultaneously acquired iNAV and respiratory belt signal were used to divide the acquired PET data into 4 bins. The binning was then extended for the complete respiratory belt signal. Data acquired at each bin was reconstructed and combined using iNAV-based motion fields to create a respiratory motion-corrected PET image. Motion-corrected (MC) and non-motion-corrected (NMC) datasets were compared. Gating was also performed to correct cardiac motion. The SUVmax and TBRmax values were calculated for the myocardial wall or a vulnerable coronary plaque for the 18F-FDG and 18F-FCH datasets, respectively. RESULTS: A pair-wise comparison showed that the SUVmax and TBRmax values of the motion corrected (MC) datasets were significantly higher than those for the non-motion-corrected (NMC) datasets (8.2 ± 1.0 vs 7.5 ± 1.0, p < 0.01 and 1.9 ± 0.2 vs 1.2 ± 0.2, p < 0.01, respectively). In addition, the SUVmax and TBRmax of the motion corrected and gated (MC_G) reconstructions were also higher than that of the non-motion-corrected but gated (NMC_G) datasets, although for the TBRmax this difference was not statistically significant (9.6 ± 1.3 vs 9.1 ± 1.2, p = 0.02 and 2.6 ± 0.3 vs 2.4 ± 0.3, p = 0.16, respectively). The respiratory motion-correction did not lead to a change in the signal to noise ratio. CONCLUSION: The proposed respiratory motion correction method for hybrid PET/MRI improved the image quality of cardiovascular PET scans by increased SUVmax and TBRmax values while maintaining the signal-to-noise ratio. Trial registration METC162043 registered 01/03/2017.

A case report of a myocardial ischaemic attack: a novel hyperenhancement pattern on cardiac magnetic resonance in focal ischaemic injury.

Background: Delayed enhancement cardiac magnetic resonance (DE-CMR) is the reference standard for the non-invasive assessment of myocardial fibrosis. DE-CMR is able to distinguish ischaemic from non-ischaemic aetiologies based on differences in hyperenhancement distribution patterns. Hyperenhancement caused by ischaemic injury typically involves the endocardium, while hyperenhancement confined to the mid- and epicardial layers of the myocardium suggests a non-ischaemic aetiology. Case summary: This is a case of a 20-year-old male with an unremarkable medical history with an acute ST-elevation myocardial infarction. DE-CMR revealed two distinct patterns of hyperenhancement: (i) a 'normal' wavefront-ischaemic pattern, and (ii) multiple atypical mid-wall and epicardial areas of focal hyperenhancement. Invasive coronary angiography (ICA) and coronary computed tomographic angiography (CCTA) showed multiple intracoronary thrombi and distal emboli in the left anterior descending, ramus circumflexus, and in smaller branches of the LCA. All hyperenhancement patterns observed on DE-CMR perfectly matched the distribution territories of the affected coronary arteries. Discussion: This case with an acute myocardial infarction showed intracoronary thrombi and emboli on ICA and CCTA. Interestingly, DE-CMR showed two different patterns of hyperenhancement in the same territories of the coronary thrombi. This observation may challenge the concept that these non-endocardial areas of hyperenhancement on DE-CMR are always of non-ischaemic aetiology. It is hypothesized that occlusion of smaller distal branches of the coronary arteries may result in mid-wall or epicardial fibrosis as opposed to subendocardial fibrosis commonly found in patients with a large epicardial coronary occlusion. Clinicians should be aware of these atypical patterns to be able to initiate adequate medical therapy.

Dark-Blood Late Gadolinium Enhancement MRI Is Noninferior to Bright-Blood LGE in Non-Ischemic Cardiomyopathies.

(1) Background and Objectives: Dark-blood late gadolinium enhancement has been shown to be a reliable cardiac magnetic resonance (CMR) method for assessing viability and depicting myocardial scarring in ischemic cardiomyopathy. The aim of this study was to evaluate dark-blood LGE imaging compared with conventional bright-blood LGE for the detection of myocardial scarring in non-ischemic cardiomyopathies. (2) Materials and Methods: Patients with suspected non-ischemic cardiomyopathy were prospectively enrolled in this single-centre study from January 2020 to March 2023. All patients underwent 1.5 T CMR with both dark-blood and conventional bright-blood LGE imaging. Corresponding short-axis stacks of both techniques were analysed for the presence, distribution, pattern, and localisation of LGE, as well as the quantitative scar size (%). (3) Results: 343 patients (age 44 ± 17 years; 124 women) with suspected non-ischemic cardiomyopathy were examined. LGE was detected in 123 of 343 cases (36%) with excellent inter-reader agreement (κ 0.97-0.99) for both LGE techniques. Dark-blood LGE showed a sensitivity of 99% (CI 98-100), specificity of 99% (CI 98-100), and an accuracy of 99% (CI 99-100) for the detection of non-ischemic scarring. No significant difference in total scar size (%) was observed. Dark-blood imaging with mean 5.35 ± 4.32% enhanced volume of total myocardial volume, bright-blood with 5.24 ± 4.28%, p = 0.84. (4) Conclusions: Dark-blood LGE imaging is non-inferior to conventional bright-blood LGE imaging in detecting non-ischemic scarring. Therefore, dark-blood LGE imaging may become an equivalent method for the detection of both ischemic and non-ischemic scars.

Multi-modal characterization of the left atrium by a fully automated integration of pre-procedural cardiac imaging and electro-anatomical mapping.

Background: The combination of information obtained from pre-procedural cardiac imaging and electro-anatomical mapping (EAM) can potentially help to locate new ablation targets. In this study we developed and evaluated a fully automated technique to align left atrial (LA) anatomies obtained from CT- and MRI-scans with LA anatomies obtained from EAM. Methods: Twenty-one patients scheduled for a pulmonary vein (PV) isolation with a pre-procedural MRI were enrolled. Additionally, a recent computed tomography (CT) scan was available in 12 patients. LA anatomies were segmented from MRI-scans using ADAS-AF (Galgo Medical, Barcelona) and from the CT-scans using Slicer3D. MRI and CT anatomies were aligned with the EAM anatomy using an iterative closest plane-to-plane algorithm. Initially, the algorithm included the PVs, LA appendage and mitral valve anulus as they are the most distinctive landmarks. Subsequently, the algorithm was applied again, excluding these structures, with only three iterative steps to refine the alignment of the true LA surface. The result of the alignments was quantified by the Euclidian distance between the aligned anatomies after excluding PVs, LA appendage and mitral anulus. Results: Our algorithm successfully aligned 20/21 MRI anatomies and 11/12 CT anatomies with the corresponding EAM anatomies. The average median residual distances were 1.9 ± 0.6 mm and 2.5 ± 0.8 mm for MRI and CT anatomies respectively. The average LA surface with a residual distance less than 5.00 mm was 89 ± 9% and 89 ± 10% for MRI and CT anatomies respectively. Conclusion: An iterative closest plane-to-plane algorithm is a reliable method to automatically align pre-procedural cardiac images with anatomies acquired during ablation procedures.

High-resolution structural-functional substrate-trigger characterization: Future roadmap for catheter ablation of ventricular tachycardia.

Introduction: Patients with ventricular tachyarrhythmias (VT) are at high risk of sudden cardiac death. When appropriate, catheter ablation is modestly effective, with relatively high VT recurrence and complication rates. Personalized models that incorporate imaging and computational approaches have advanced VT management. However, 3D patient-specific functional electrical information is typically not considered. We hypothesize that incorporating non-invasive 3D electrical and structural characterization in a patient-specific model improves VT-substrate recognition and ablation targeting. Materials and methods: In a 53-year-old male with ischemic cardiomyopathy and recurrent monomorphic VT, we built a structural-functional model based on high-resolution 3D late-gadolinium enhancement (LGE) cardiac magnetic resonance imaging (3D-LGE CMR), multi-detector computed tomography (CT), and electrocardiographic imaging (ECGI). Invasive data from high-density contact and pace mapping obtained during endocardial VT-substrate modification were also incorporated. The integrated 3D electro-anatomic model was analyzed off-line. Results: Merging the invasive voltage maps and 3D-LGE CMR endocardial geometry led to a mean Euclidean node-to-node distance of 5 ± 2 mm. Inferolateral and apical areas of low bipolar voltage (<1.5 mV) were associated with high 3D-LGE CMR signal intensity (>0.4) and with higher transmurality of fibrosis. Areas of functional conduction delay or block (evoked delayed potentials, EDPs) were in close proximity to 3D-LGE CMR-derived heterogeneous tissue corridors. ECGI pinpointed the epicardial VT exit at ∼10 mm from the endocardial site of origin, both juxtaposed to the distal ends of two heterogeneous tissue corridors in the inferobasal left ventricle. Radiofrequency ablation at the entrances of these corridors, eliminating all EDPs, and at the VT site of origin rendered the patient non-inducible and arrhythmia-free until the present day (20 months follow-up). Off-line analysis in our model uncovered dynamic electrical instability of the LV inferolateral heterogeneous scar region which set the stage for an evolving VT circuit. Discussion and conclusion: We developed a personalized 3D model that integrates high-resolution structural and electrical information and allows the investigation of their dynamic interaction during arrhythmia formation. This model enhances our mechanistic understanding of scar-related VT and provides an advanced, non-invasive roadmap for catheter ablation.

Myocardial Scar Detection Using High-Resolution Free-Breathing 3D Dark-Blood and Standard Breath-Holding 2D Bright-Blood Late Gadolinium Enhancement MRI: A Comparison of Observer Confidence.

OBJECTIVE: To compare observer confidence for myocardial scar detection using 3 different late gadolinium enhancement (LGE) data sets by 2 observers with different levels of experience. MATERIALS AND METHODS: Forty-one consecutive patients, who were referred for 3D dark-blood LGE MRI before implantable cardioverter-defibrillator implantation or ablation therapy and who underwent 2D bright-blood LGE MRI within a time frame of 3 months, were prospectively included. From all 3D dark-blood LGE data sets, a stack of 2D short-axis slices was reconstructed. All acquired LGE data sets were anonymized and randomized and evaluated by 2 independent observers with different levels of experience in cardiovascular imaging (beginner and expert). Confidence in detection of ischemic scar, nonischemic scar, papillary muscle scar, and right ventricular scar for each LGE data set was scored using a using a 3-point Likert scale (1 = low, 2 = medium, or 3 = high). Observer confidence scores were compared using the Friedman omnibus test and Wilcoxon signed-rank post hoc test. RESULTS: For the beginner observer, a significant difference in confidence regarding ischemic scar detection was observed in favor of reconstructed 2D dark-blood LGE compared with standard 2D bright-blood LGE (p = 0.030) while for the expert observer, no significant difference was found (p = 0.166). Similarly, for right ventricular scar detection, a significant difference in confidence was observed in favor of reconstructed 2D dark-blood LGE compared with standard 2D bright-blood LGE (p = 0.006) while for the expert observer, no significant difference was found (p = 0.662). Although not significantly different for other areas of interest, 3D dark-blood LGE and its derived 2D dark-blood LGE data set showed a tendency to score higher for all areas of interest at both experience levels. CONCLUSIONS: The combination of dark-blood LGE contrast and high isotropic voxels may contribute to increased observer confidence in myocardial scar detection, independent of observer's experience level but in particular for beginner observers.

Histopathological validation of semi-automated myocardial scar quantification techniques for dark-blood late gadolinium enhancement magnetic resonance imaging.

AIMS: To evaluate the performance of various semi-automated techniques for quantification of myocardial infarct size on both conventional bright-blood and novel dark-blood late gadolinium enhancement (LGE) images using histopathology as reference standard. METHODS AND RESULTS: In 13 Yorkshire pigs, reperfused myocardial infarction was experimentally induced. At 7 weeks post-infarction, both bright-blood and dark-blood LGE imaging were performed on a 1.5 T magnetic resonance scanner. Following magnetic resonance imaging (MRI), the animals were sacrificed, and histopathology was obtained. The percentage of infarcted myocardium was assessed per slice using various semi-automated scar quantification techniques, including the signal threshold vs. reference mean (STRM, using 3 to 8 SDs as threshold) and full-width at half-maximum (FWHM) methods, as well as manual contouring, for both LGE methods. Infarct size obtained by histopathology was used as reference. In total, 24 paired LGE MRI slices and histopathology samples were available for analysis. For both bright-blood and dark-blood LGE, the STRM method with a threshold of 5 SDs led to the best agreement to histopathology without significant bias (-0.23%, 95% CI [-2.99, 2.52%], P = 0.862 and -0.20%, 95% CI [-2.12, 1.72%], P = 0.831, respectively). Manual contouring significantly underestimated infarct size on bright-blood LGE (-1.57%, 95% CI [-2.96, -0.18%], P = 0.029), while manual contouring on dark-blood LGE outperformed semi-automated quantification and demonstrated the most accurate quantification in this study (-0.03%, 95% CI [-0.22, 0.16%], P = 0.760). CONCLUSION: The signal threshold vs. reference mean method with a threshold of 5 SDs demonstrated the most accurate semi-automated quantification of infarcted myocardium, without significant bias compared to histopathology, for both conventional bright-blood and novel dark-blood LGE.

Evaluation of Microvascular Rarefaction in Vascular Cognitive Impairment and Heart Failure (CRUCIAL): Study Protocol for an Observational Study.

INTRODUCTION: Microvascular rarefaction, the functional reduction in perfused microvessels and structural reduction of microvascular density, seems to be an important mechanism in the pathophysiology of small blood vessel-related disorders including vascular cognitive impairment (VCI) due to cerebral small vessel disease and heart failure with preserved ejection fraction (HFpEF). Both diseases share common risk factors including hypertension, diabetes mellitus, obesity, and ageing; in turn, these comorbidities are associated with microvascular rarefaction. Our consortium aims to investigate novel non-invasive tools to quantify microvascular health and rarefaction in both organs, as well as surrogate biomarkers for cerebral and/or cardiac rarefaction (via sublingual capillary health, vascular density of the retina, and RNA content of circulating extracellular vesicles), and to determine whether microvascular density relates to disease severity. METHODS: The clinical research program of CRUCIAL consists of four observational cohort studies. We aim to recruit 75 VCI patients, 60 HFpEF patients, 60 patients with severe aortic stenosis (AS) undergoing surgical aortic valve replacement as a pressure overload HFpEF model, and 200 elderly participants with mixed comorbidities to serve as controls. Data collected will include medical history, physical examination, cognitive testing, advanced brain and cardiac MRI, ECG, echocardiography, sublingual capillary health, optical coherence tomography angiography (OCTa), extracellular vesicles RNA analysis, and myocardial remodelling-related serum biomarkers. The AS cohort undergoing surgery will also have myocardial biopsy for histological microvascular assessment. DISCUSSION: CRUCIAL will examine the pathophysiological role of microvascular rarefaction in VCI and HFpEF using advanced brain and cardiac MRI techniques. Furthermore, we will investigate surrogate biomarkers for non-invasive, faster, easier, and cheaper assessment of microvascular density since these are more likely to be disseminated into widespread clinical practice. If microvascular rarefaction is an early marker of developing small vessel diseases, then measuring rarefaction may allow preclinical diagnosis, with implications for screening, risk stratification, and prevention. Further knowledge of the relevance of microvascular rarefaction and its underlying mechanisms may provide new avenues for research and therapeutic targets.