Integration of electro-anatomical and imaging data of the left ventricle: An evaluation framework

A transferable in-silico augmented ischemic model for virtual myocardial perfusion imaging and myocardial infarction detection

This paper proposes an innovative approach to generate a generalized myocardial ischemia database by modeling the virtual electrophysiology of the heart and the 12-lead electrocardiography projected by the in-silico model can serve as a ready-to-use database for automatic myocardial infarction/ischemia (MI) localization and classification. Although the virtual heart can be created by an established technique combining the cell model with personalized heart geometry to observe the spatial propagation of depolarization and repolarization waves, we developed a strategy based on the clinical pathophysiology of MI to generate a heterogeneous database with a generic heart while maintaining clinical relevance and reduced computational complexity. First, the virtual heart is simplified into 11 regions that match the types and locations, which can be diagnosed by 12-lead ECG; the major arteries were divided into 3-5 segments from the upstream to the downstream based on the general anatomy. Second, the stenosis or infarction of the major or minor coronary artery branches can cause different perfusion drops and infarct sizes. We simulated the ischemic sites in different branches of the arteries by meandering the infarction location to elaborate on possible ECG representations, which alters the infraction's size and changes the transmembrane potential (TMP) of the myocytes associated with different levels of perfusion drop. A total of 8190 different case combinations of cardiac potentials with ischemia and MI were simulated, and the corresponding ECGs were generated by forward calculations. Finally, we trained and validated our in-silico database with a sparse representation classification (SRC) and tested the transferability of the model on the real-world Physikalisch Technische Bundesanstalt (PTB) database. The overall accuracies for localizing the MI region on the PTB data achieved 0.86, which is only 2% drop compared to that derived from the simulated database (0.88). In summary, we have shown a proof-of-concept for transferring an in-silico model to real-world database to compensate for insufficient data.

Marfan Syndrome beyond Aortic Root-Phenotyping Using Cardiovascular Magnetic Resonance Imaging and Clinical Implications

Marfan syndrome (MFS) is an inherited autosomal-dominant connective tissue disorder with multiorgan involvement including musculoskeletal, respiratory, cardiovascular, ocular, and skin manifestations. Life expectancy in patients with MFS is primarily determined by the degree of cardiovascular involvement. Aortic disease is the major cardiovascular manifestation of MFS. However, non-aortic cardiac diseases, such as impaired myocardial function and arrhythmia, have been increasingly acknowledged as additional causes of morbidity and mortality. We present two cases demonstrating the phenotypical variation in patients with MFS and how CMR (Cardiovascular Magnetic Resonance) could serve as a "one stop shop" to retrieveS all the necessary information regarding aortic/vascular pathology as well as any potential underlying arrhythmogenic substrate or cardiomyopathic process.

Quality assessment of cardiac magnetic resonance myocardial scar imaging prior to ventricular arrhythmia ablation

High-resolution scar characterization using late gadolinium enhancement cardiac magnetic resonance imaging (LGE-CMR) is useful for guiding ventricular arrhythmia (VA) treatment. However, imaging study quality may be degraded by breath-holding difficulties, arrhythmias, and implantable cardioverter-defibrillators (ICDs). We evaluated the effect of image quality on left ventricle (LV) base to apex scar interpretation in pre-VA ablation LGE-CMR. 43 consecutive patients referred for VA ablation underwent gradient-recalled-echo LGE-CMR. In ICD patients (n = 24), wide-bandwidth inversion-recovery suppressed ICD artifacts. In non-ICD patients, single-shot steady-state free-precession LGE-CMR could also be performed to reduce respiratory motion/arrhythmia artifacts. Study quality was assessed for adequate/limited scar interpretation due to cardiac/respiratory motion artifacts, ICD-related artifacts, and image contrast. 28% of non-ICD patients had studies where image quality limited scar interpretation in at least one image compared to 71% of ICD patient studies (p = 0.012). A median of five image slices had limited quality per ICD patient study, compared to 0 images per non-ICD patient study. Poorer quality in ICD patients was largely due to motion-related artifacts (54% ICD vs 6% non-ICD studies, p = 0.001) as well as ICD-related image artifacts (25% of studies). In VA ablation patients with ICDs, conventional CMR protocols frequently have image slices with limited scar interpretation, which can limit whole-heart scar assessment. Motion artifacts contribute to suboptimal image quality, particularly in ICD patients. Improved methods for motion and ICD artifact suppression may better delineate high-resolution LGE scar features of interest for guiding VA ablation.

Electrophysiological effects of adipose graft transposition procedure (AGTP) on the post-myocardial infarction scar: A multimodal characterization of arrhythmogenic substrate

Objective

To assess the arrhythmic safety profile of the adipose graft transposition procedure (AGTP) and its electrophysiological effects on post-myocardial infarction (MI) scar.

Background

Myocardial repair is a promising treatment for patients with MI. The AGTP is a cardiac reparative therapy that reduces infarct size and improves cardiac function. The impact of AGTP on arrhythmogenesis has not been addressed.

Methods

MI was induced in 20 swine. Contrast-enhanced magnetic resonance (ce-MRI), electrophysiological study (EPS), and left-ventricular endocardial high-density mapping were performed 15 days post-MI. Animals were randomized 1:1 to AGTP or sham-surgery group and monitored with ECG-Holter. Repeat EPS, endocardial mapping, and ce-MRI were performed 30 days post-intervention. Myocardial SERCA2, Connexin-43 (Cx43), Ryanodine receptor-2 (RyR2), and cardiac troponin-I (cTnI) gene and protein expression were evaluated.

Results

The AGTP group showed a significant reduction of the total infarct scar, border zone and dense scar mass by ce-MRI (p = 0.04), and a decreased total scar and border zone area in bipolar voltage mapping (p < 0.001). AGTP treatment significantly reduced the area of very-slow conduction velocity (<0.2 m/s) (p = 0.002), the number of deceleration zones (p = 0.029), and the area of fractionated electrograms (p = 0.005). No differences were detected in number of induced or spontaneous ventricular arrhythmias at EPS and Holter-monitoring. SERCA2, Cx43, and RyR2 gene expression were decreased in the infarct core of AGTP-treated animals (p = 0.021, p = 0.018, p = 0.051, respectively).

Conclusion

AGTP is a safe reparative therapy in terms of arrhythmic risk and provides additional protective effect against adverse electrophysiological remodeling in ischemic heart disease.

Accuracy of left atrial fibrosis detection with cardiac magnetic resonance: correlation of late gadolinium enhancement with endocardial voltage and conduction velocity

AIMS

Myocardial fibrosis is a hallmark of atrial fibrillation (AF) and its characterization could be used to guide ablation procedures. Late gadolinium enhanced-magnetic resonance imaging (LGE-MRI) detects areas of atrial fibrosis. However, its accuracy remains controversial. We aimed to analyse the accuracy of LGE-MRI to identify left atrial (LA) arrhythmogenic substrate by analysing voltage and conduction velocity at the areas of LGE.

METHODS AND RESULTS

Late gadolinium enhanced-magnetic resonance imaging was performed before ablation in 16 patients. Atrial wall intensity was normalized to blood pool and classified as healthy, interstitial fibrosis, and dense scar tissue depending of the resulting image intensity ratio. Bipolar voltage and local conduction velocity were measured in LA with high-density electroanatomic maps recorded in sinus rhythm and subsequently projected into the LGE-MRI. A semi-automatic, point-by-point correlation was made between LGE-MRI and electroanatomical mapping. Mean bipolar voltage and local velocity progressively decreased from healthy to interstitial fibrosis to scar. There was a significant negative correlation between LGE with voltage (r = -0.39, P < 0.001) and conduction velocity (r = -0.25, P < 0.001). In patients showing dilated atria (LA diameter ≥45 mm) the conduction velocity predictive capacity of LGE-MRI was weaker (r = -0.40 ± 0.09 vs. -0.20 ± 0.13, P = 0.02).

CONCLUSIONS

Areas with higher LGE show lower voltage and slower conduction in sinus rhythm. The enhancement intensity correlates with bipolar voltage and conduction velocity in a point-by-point analysis. The performance of LGE-MRI in assessing local velocity might be reduced in patients with dilated atria (LA diameter ≥45).

Proximity to the descending aorta predicts regional fibrosis in the adjacent left atrial wall: aetiopathogenic and prognostic implications

AIMS

Left atrial (LA) fibrosis is present in patients with atrial fibrillation (AF) and can be visualized by magnetic resonance imaging with late gadolinium enhancement (LGE-MRI). Previous studies have shown that LA fibrosis is not randomly distributed, being more frequent in the area adjacent to the descending aorta (DAo). The objective of this study is to analyse the relationship between fibrosis in the atrial area adjacent to the DAo and the distance to it, as well as the prognostic implications of this fibrosis.

METHODS AND RESULTS

Magnetic resonance imaging with late gadolinium enhancement was obtained in 108 patients before AF ablation to analyse the extent of LA fibrosis and the distance DAo-to-LA. A high-density electroanatomic map was performed in a subgroup of 16 patients to exclude the possibility of an MRI artifact. Recurrences after ablation were analysed at 1 year of follow-up. The extent of atrial fibrosis in the area adjacent to the DAo was inversely correlated with the distance DAo-to-LA (r = -0.34, P < 0.001). This area had the greatest intensity of LGE [image intensity ratio (IIR) 1.14 ± 0.15 vs. 0.99 ± 0.16; P < 0.001] and also the lowest voltage (1.07 ± 0.86 vs. 1.54 ± 1.07 mV; P < 0.001) and conduction velocity (0.65 ± 0.06 vs. 0.96 ± 0.57 mm/ms; P < 0.001). The extent of this regional fibrosis predicted recurrence after AF ablation [hazard ratio (HR) 1.02, 95% CI 1.01-1.03; P = 0.01], however total fibrosis did not (HR = 1.01, 95% CI 0.97-1.06, P = 0.54).

CONCLUSIONS

Atrial fibrosis was predominantly located in the area adjacent to the DAo, and increased with the proximity between the two structures. Furthermore, this regional fibrosis better predicted recurrence after AF ablation than total atrial fibrosis.

Fast Quasi-Conformal Regional Flattening of the Left Atrium

Two-dimensional representation of 3D anatomical structures is a simple and intuitive way for analysing patient information across populations and image modalities. While cardiac ventricles, especially the left ventricle, have an established standard representation (bull's eye plot), the 2D depiction of the left atrium (LA) remains challenging due to its sub-structural complexity including the pulmonary veins (PV) and the left atrial appendage (LAA). Quasi-conformal flattening techniques, successfully applied to cardiac ventricles, require additional constraints in the case of the LA to place the PV and LAA in the same geometrical 2D location for different cases. Some registration-based methods have been proposed but surface registration is time-consuming and prone to errors when the geometries are very different. We propose a novel atrial flattening methodology where a 2D standardised map of the LA is obtained quickly and without errors related to registration. The LA is divided into five regions which are then mapped to their analogue two-dimensional regions. 67 human left atria from magnetic resonance images (MRI) were studied to derive a population-based template representing the averaged relative locations of the PVs and LAA. The clinical application of our methodology is illustrated on different use cases including the integration of MRI and electroanatomical data.

Personalized Cardiac Computational Models: From Clinical Data to Simulation of Infarct-Related Ventricular Tachycardia

In the chronic stage of myocardial infarction, a significant number of patients develop life-threatening ventricular tachycardias (VT) due to the arrhythmogenic nature of the remodeled myocardium. Radiofrequency ablation (RFA) is a common procedure to isolate reentry pathways across the infarct scar that are responsible for VT. Unfortunately, this strategy show relatively low success rates; up to 50% of patients experience recurrent VT after the procedure. In the last decade, intensive research in the field of computational cardiac electrophysiology (EP) has demonstrated the ability of three-dimensional (3D) cardiac computational models to perform in-silico EP studies. However, the personalization and modeling of certain key components remain challenging, particularly in the case of the infarct border zone (BZ). In this study, we used a clinical dataset from a patient with a history of infarct-related VT to build an image-based 3D ventricular model aimed at computational simulation of cardiac EP, including detailed patient-specific cardiac anatomy and infarct scar geometry. We modeled the BZ in eight different ways by combining the presence or absence of electrical remodeling with four different levels of image-based patchy fibrosis (0, 10, 20, and 30%). A 3D torso model was also constructed to compute the ECG. Patient-specific sinus activation patterns were simulated and validated against the patient's ECG. Subsequently, the pacing protocol used to induce reentrant VTs in the EP laboratory was reproduced in-silico. The clinical VT was induced with different versions of the model and from different pacing points, thus identifying the slow conducting channel responsible for such VT. Finally, the real patient's ECG recorded during VT episodes was used to validate our simulation results and to assess different strategies to model the BZ. Our study showed that reduced conduction velocities and heterogeneity in action potential duration in the BZ are the main factors in promoting reentrant activity. Either electrical remodeling or fibrosis in a degree of at least 30% in the BZ were required to initiate VT. Moreover, this proof-of-concept study confirms the feasibility of developing 3D computational models for cardiac EP able to reproduce cardiac activation in sinus rhythm and during VT, using exclusively non-invasive clinical data.

Assessing the Effectiveness of Direct Data Merging Strategy in Long-Term and Large-Scale Pharmacometabonomics

Because of the extended period of clinic data collection and huge size of analyzed samples, the long-term and large-scale pharmacometabonomics profiling is frequently encountered in the discovery of drug/target and the guidance of personalized medicine. So far, integration of the results (ReIn) from multiple experiments in a large-scale metabolomic profiling has become a widely used strategy for enhancing the reliability and robustness of analytical results, and the strategy of direct data merging (DiMe) among experiments is also proposed to increase statistical power, reduce experimental bias, enhance reproducibility and improve overall biological understanding. However, compared with the ReIn, the DiMe has not yet been widely adopted in current metabolomics studies, due to the difficulty in removing unwanted variations and the inexistence of prior knowledges on the performance of the available merging methods. It is therefore urgently needed to clarify whether DiMe can enhance the performance of metabolic profiling or not. Herein, the performance of DiMe on 4 pairs of benchmark datasets was comprehensively assessed by multiple criteria (classification capacity, robustness and false discovery rate). As a result, integration/merging-based strategies (ReIn and DiMe) were found to perform better under all criteria than those strategies based on single experiment. Moreover, DiMe was discovered to outperform ReIn in classification capacity and robustness, while the ReIn showed superior capacity in controlling false discovery rate. In conclusion, these findings provided valuable guidance to the selection of suitable analytical strategy for current metabolomics.

Transfer Learning From Simulations on a Reference Anatomy for ECGI in Personalized Cardiac Resynchronization Therapy

GOAL

Noninvasive cardiac electrophysiology (EP) model personalisation has raised interest for instance in the scope of predicting EP cardiac resynchronization therapy (CRT) response. However, the restricted clinical applicability of current methods is due in particular to the limitation to simple situations and the important computational cost.

METHODS

We propose in this manuscript an approach to tackle these two issues. First, we analyze more complex propagation patterns (multiple onsets and scar tissue) using relevance vector regression and shape dimensionality reduction on a large simulated database. Second, this learning is performed offline on a reference anatomy and transferred onto patient-specific anatomies in order to achieve fast personalized predictions online.

RESULTS

We evaluated our method on a dataset composed of 20 dyssynchrony patients with a total of 120 different cardiac cycles. The comparison with a commercially available electrocardiographic imaging (ECGI) method shows a good identification of the cardiac activation pattern. From the cardiac parameters estimated in sinus rhythm, we predicted five different paced patterns for each patient. The comparison with the body surface potential mappings (BSPM) measured during pacing and the ECGI method indicates a good predictive power.

CONCLUSION

We showed that learning offline from a large simulated database on a reference anatomy was able to capture the main cardiac EP characteristics from noninvasive measurements for fast patient-specific predictions.

SIGNIFICANCE

The fast CRT pacing predictions are a step forward to a noninvasive CRT patient selection and therapy optimisation, to help clinicians in these difficult tasks.

Image-based criteria to identify the presence of epicardial arrhythmogenic substrate in patients with transmural myocardial infarction

BACKGROUND

Patients with transmural myocardial infarction (MI) who undergo endocardial-only substrate ablation are at increased risk for ventricular tachycardia recurrence. Late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) can be used to assess infarct transmurality (IT). However, the degree of IT associated with an epicardial arrhythmogenic substrate (AS) has not been determined.

OBJECTIVE

The purpose of this study was to determine the degree of IT observed by LGE-CMR and multidetector computed tomography (MDCT) that predicts the presence of epicardial AS.

METHODS

The study included 38 post-MI patients. Ten patients with a subendocardial infarction underwent endocardial-only mapping, and 28 with a classic transmural MI (C-TMI), defined as hyperenhancement ≥75% of myocardial wall thickness (WT), underwent endo-epicardial mapping. LGE-CMR/MDCT data were registered to high-density endocardial or epicardial maps to be analyzed for the presence of AS.

RESULTS

Of the 28 post-MI patients with C-TMI, 18 had epicardial AS (64%) and 10 (36%) did not. An epicardial scar area ≥14 cm² on LGE-CMR identified patients with epicardial AS (sensitivity 1, specificity 1). Mean WT in the epicardial scar area in these patients was lower than in patients without epicardial AS (3.14 ± 1.16 mm vs 5.54 ± 1.78 mm; P = .008). A mean WT cutoff value ≤3.59 mm identified patients with epicardial AS (sensitivity 0.91, specificity 0.93).

CONCLUSION

An epicardial scar area ≥14 cm² on LGE-CMR and mean CT-WT ≤3.59 mm predict epicardial AS in post-MI patients.

Quantitative Analysis of Electro-Anatomical Maps: Application to an Experimental Model of Left Bundle Branch Block/Cardiac Resynchronization Therapy

Electro-anatomical maps (EAMs) are commonly acquired in clinical routine for guiding ablation therapies. They provide voltage and activation time information on a 3-D anatomical mesh representation, making them useful for analyzing the electrical activation patterns in specific pathologies. However, the variability between the different acquisitions and anatomies hampers the comparison between different maps. This paper presents two contributions for the analysis of electrical patterns in EAM data from biventricular surfaces of cardiac chambers. The first contribution is an integrated automatic 2-D disk representation (2-D bull’s eye plot) of the left ventricle (LV) and right ventricle (RV) obtained with a quasi-conformal mapping from the 3-D EAM meshes, that allows an analysis of cardiac resynchronization therapy (CRT) lead positioning, interpretation of global (total activation time), and local indices (local activation time (LAT), surrogates of conduction velocity, inter-ventricular, and transmural delays) that characterize changes in the electrical activation pattern. The second contribution is a set of indices derived from the electrical activation: speed maps, computed from LAT values, to study the electrical wave propagation, and histograms of isochrones to analyze regional electrical heterogeneities in the ventricles. We have applied the proposed methods to look for the underlying physiological mechanisms of left bundle branch block (LBBB) and CRT, with the goal of optimizing the therapy by improving CRT response. To better illustrate the benefits of the proposed tools, we created a set of synthetically generated and fully controlled activation patterns, where the proposed representation and indices were validated. Then, the proposed analysis tools are used to analyze EAM data from an experimental swine model of induced LBBB with an implanted CRT device. We have analyzed and compared the electrical activation patterns at baseline, LBBB, and CRT stages in four animals: two without any structural disease and two with an induced infarction. By relating the CRT lead location with electrical dyssynchrony, we evaluated current hypotheses about lead placement in CRT and showed that optimal pacing sites should target the RV lead close to the apex and the LV one distant from it.