Use of delayed-enhancement magnetic resonance imaging for fibrosis detection in the atria: a review

Characterization of patients with extensive left atrial myopathy referred for atrial fibrillation ablation: incidence, predictors, and outcomes

BACKGROUND

Although atrial fibrosis has a relevant impact on ablation success rate, experimental studies have reported that extensive fibrosis may be accompanied by a reduced burden secondary to a prominent depression of atrial excitability.

OBJECTIVES

We aimed to identify clinical and echocardiographic factors associated with extensive left atrial myopathy (ELAM), to analyze the predictive ability of established scores (AF score, APPLE, and DR-FLASH) and assess outcomes in terms of AF recurrence, left atrial flutter, and post-procedural heart failure admissions.

METHODS

A total of 950 consecutive patients undergoing the first AF ablation were included. A 3D electroanatomical mapping system (CARTO3, Biosense Webster) was created using a multipolar mapping catheter (PentaRay, Biosense Webster). ELAM was defined as ≥ 50% low voltage area. A subanalysis with four groups was also created (< 10%; 10-20%; 10-20%; and > 30%). Logistic regressions, Cox proportional hazards models, and log-rank test were used to test the predictors independently associated with the presence of ELAM and AF recurrence. The model was prospectively validated in a cohort of 150 patients obtaining an excellent ability for prediction AUC 0.90 (CI 95% 0.84-0.96).

RESULTS

Overall, 78 (8.42%) presented ELAM. Age, female sex, persistent AF, first-degree AV block, and E/e' were significant predictors. The model incorporating these factors outperformed the existing scores (AUC = 0.87). During a mean follow-up of 20 months (IQR 9 to 36), patients with ELAM presented a higher rate of AF recurrence (42.02% vs 26.01%, p = 0.030), left atrial flutter (26.03% vs 8.02%, p < 0.001), and post-procedural heart failure admissions (12.01% vs 0.61%, p < 0.001) than non-ELAM patients.

CONCLUSIONS

This study reveals the incidence and clinical factors associated with ELAM in AF, highlighting age, female, persistent AF, first-degree AV block, and E/e'. Importantly, the presence of ELAM is associated with poorer outcomes in terms of recurrence and HF admission.

Atrial cardiomyopathy in patients with ischaemic stroke: a cross-sectional and prospective cohort study-the COAST study

INTRODUCTION

Despite workup for the aetiology of ischaemic stroke, about 25% of cases remain unexplained. Paroxysmal atrial fibrillation is typically suspected but often not detected. Even if atrial fibrillation (AF) is detected, the quantitative threshold of clinically relevant AF remains unclear. Emerging evidence suggests that left atrial (LA) functional and structural abnormalities may convey a risk of ischaemic stroke in which AF is only one of several features. These abnormalities have been termed 'atrial cardiomyopathy'. This study uses cardiac magnetic resonance (CMR) to evaluate atrial cardiomyopathy among patients with stroke of undetermined aetiology compared with those with an attributable mechanism and controls without established cardiovascular disease.

METHODS AND ANALYSIS

This cross-sectional and prospective cohort study included 100 patients with recent ischaemic stroke and 50 controls with no established cardiovascular disease. The study will assess LA structural and functional abnormalities with CMR. Inclusion began in March 2019, and follow-up is planned to be complete in January 2023. There are two scheduled follow-ups: (1) 18 months after individual inclusion, counting from the index diagnostic MRI of the brain, (2) end of study follow-up at 18 months after inclusion of the last patient, assessing the incidence of recurrent ischaemic stroke, AF and cardiovascular death. The primary endpoint is the extent of CMR-assessed atrial fibrosis in the LA at baseline. The study is powered to detect a difference of 6% fibrosis between stroke of undetermined aetiology and stroke of known mechanism with a SD of 9%, a significance level of 0.05, and power of 80%.

ETHICS AND DISSEMINATION

This study has been approved by the Danish National Committee on Health Research Ethics (H-18055313). All participants in the study signed informed consent. Results from the study will be published in peer-reviewed journals regardless of the outcome.

TRIAL REGISTRATION NUMBER

NCT03830983.

Ablation Lesion Assessment with MRI

Late gadolinium enhancement (LGE) MRI is capable of detecting not only native cardiac fibrosis, but also ablation-induced scarring. Thus, it offers the unique opportunity to assess ablation lesions non-invasively. In the atrium, LGE-MRI has been shown to accurately detect and localise gaps in ablation lines. With a negative predictive value close to 100% it can reliably rule out pulmonary vein reconnection non-invasively and thus may avoid unnecessary invasive repeat procedures where a pulmonary vein isolation only approach is pursued. Even LGE-MRI-guided repeat pulmonary vein isolation has been demonstrated to be feasible as a standalone approach. LGE-MRI-based lesion assessment may also be of value to evaluate the efficacy of ventricular ablation. In this respect, the elimination of LGE-MRI-detected arrhythmogenic substrate may serve as a potential endpoint, but validation in clinical studies is lacking. Despite holding great promise, the widespread use of LGE-MRI is still limited by the absence of standardised protocols for image acquisition and post-processing. In particular, reproducibility across different centres is impeded by inconsistent thresholds and internal references to define fibrosis. Thus, uniform methodological and analytical standards are warranted to foster a broader implementation in clinical practice.

Epicardial adipose tissue is associated with left atrial volume and fibrosis in patients with atrial fibrillation

Background

Obesity is a risk factor for atrial fibrillation (AF) and strongly influences the response to treatment. Atrial fibrosis shows similar associations. Epicardial adipose tissue (EAT) may be a link between these associations. We sought to assess whether EAT is associated with body mass index (BMI), left atrial (LA) fibrosis and volume.

Methods

LA fibrosis and EAT were assessed using late gadolinium enhancement, and Dixon MRI sequences, respectively. We derived 3D models incorporating fibrosis and EAT, then measured the distance of fibrotic and non-fibrotic areas to the nearest EAT to assess spatial colocalization.

Results

One hundred and three AF patients (64% paroxysmal, 27% female) were analyzed. LA volume index was 54.9 (41.2, 69.7) mL/m², LA EAT index was 17.4 (12.7, 22.9) mL/m², and LA fibrosis was 17.1 (12.4, 23.1)%. LA EAT was significantly correlated with BMI (R = 0.557, p < 0.001); as well as with LA volume and LA fibrosis after BSA adjustment (R = 0.579 and R = 0.432, respectively, p < 0.001 for both). Multivariable analysis showed LA EAT to be independently associated with LA volume and fibrosis. 3D registration of fat and fibrosis around the LA showed no clear spatial overlap between EAT and fibrotic LA regions.

Conclusion

LA EAT is associated with obesity (BMI) as well as LA volume and fibrosis. Regions of LA EAT did not colocalize with fibrotic areas, suggesting a systemic or paracrine mechanism rather than EAT infiltration of fibrotic areas.

Impaired left atrial reservoir and conduit strain in patients with atrial fibrillation and extensive left atrial fibrosis

BACKGROUND

Atrial fibrillation (AF) is associated with profound structural and functional changes in the atria. In the present study, we investigated the association between left atrial (LA) phasic function and the extent of LA fibrosis using advanced cardiovascular magnetic resonance (CMR) imaging techniques, including 3-dimensional (3D) late gadolinium enhancement (LGE) and feature tracking.

METHODS

Patients with paroxysmal and persistent AF (n = 105) underwent CMR in sinus rhythm. LA global reservoir strain, conduit strain and contractile strain were derived from cine CMR images using CMR feature tracking. The extent of LA fibrosis was assessed from 3D LGE images. Healthy subjects underwent CMR and served as controls (n = 19).

RESULTS

Significantly lower LA reservoir strain, conduit strain and contractile strain were found in AF patients, as compared to healthy controls (- 15.9 ± 3.8% vs. - 21.1 ± 3.6% P < 0.001, - 8.7 ± 2.7% vs. - 12.6 ± 2.5% P < 0.001 and - 7.2 ± 2.3% vs. - 8.6 ± 2.2% P = 0.02, respectively). Patients with a high degree of LA fibrosis (dichotomized by the median value) had lower reservoir strain and conduit strain compared to patients with a low degree of LA fibrosis (- 15.0 ± 3.9% vs. - 16.9 ± 3.3%, P = 0.02 and - 7.9 ± 2.7% vs. - 9.5 ± 2.6%, P = 0.01, respectively). In contrast, no difference was found for LA contractile strain (- 7.1 ± 2.4% vs. - 7.4 ± 2.3%, P = 0.55).

CONCLUSIONS

Impaired LA reservoir and conduit strain are present in AF patients with extensive atrial fibrosis. Future studies are needed to examine the biologic nature of this association and possible therapeutic implications.

Current progress of computational modeling for guiding clinical atrial fibrillation ablation

Atrial fibrillation (AF) is one of the most common arrhythmias, associated with high morbidity, mortality, and healthcare costs, and it places a significant burden on both individuals and society. Anti-arrhythmic drugs are the most commonly used strategy for treating AF. However, drug therapy faces challenges because of its limited efficacy and potential side effects. Catheter ablation is widely used as an alternative treatment for AF. Nevertheless, because the mechanism of AF is not fully understood, the recurrence rate after ablation remains high. In addition, the outcomes of ablation can vary significantly between medical institutions and patients, especially for persistent AF. Therefore, the issue of which ablation strategy is optimal is still far from settled. Computational modeling has the advantages of repeatable operation, low cost, freedom from risk, and complete control, and is a useful tool for not only predicting the results of different ablation strategies on the same model but also finding optimal personalized ablation targets for clinical reference and even guidance. This review summarizes three-dimensional computational modeling simulations of catheter ablation for AF, from the early-stage attempts such as Maze III or circumferential pulmonary vein isolation to the latest advances based on personalized substrate-guided ablation. Finally, we summarize current developments and challenges and provide our perspectives and suggestions for future directions.

SGLT2 promotes cardiac fibrosis following myocardial infarction and is regulated by miR-141

Cardiac fibrosis is a primary event during myocardial infarction (MI) progression, which impairs cardiac function. The present study aimed to investigate the effect of SGLT2 on cardiac fibrosis following MI. To validate the role of SGLT2 in the regulation of cardiac fibrosis in vivo, an MI rat model was established. Echocardiography was performed to determine cardiac function at 4 weeks post-MI. MI model rats were transfected with short hairpin RNA (sh)-SGLT2 or sh-negative control lentiviruses to investigate the effect of SGLT2 on rat heart function post-MI. Subsequently, the effects of SGLT2 on the cardiac fibrosis of infarcted hearts were assessed by performing Masson's trichrome staining. To further clarify the effect of SGLT2 on cardiac fibroblast proliferation, TGFβ was used to stimulate primary cardiac fibroblasts in vitro. The results demonstrated that SGLT2 served a key role in cardiac fibrosis. SGLT2 expression levels in infarct tissues were significantly increased at week 1 post-MI compared with the sham group. Compared with the control group, SGLT2 knockdown attenuated cardiac fibrosis by inhibiting the expression of collagen I and collagen III in cardiac fibroblasts in vitro and in vivo. Furthermore, the results indicated that SGLT2 expression was modulated by miR-141 in cardiac fibroblasts. In summary, the present study indicated that upregulated SGLT2 expression in cardiac fibrosis following MI was regulated by miR-141 and SGLT2 that knockdown reduced cardiac fibrosis and improved cardiac function after MI.

Novel Approaches in Cardiac Imaging for Non-invasive Assessment of Left Heart Myocardial Fibrosis

In the past, the identification of myocardial fibrosis was only possible through invasive histologic assessment. Although endomyocardial biopsy remains the gold standard, recent advances in cardiac imaging techniques have enabled non-invasive tissue characterization of the myocardium, which has also provided valuable insights into specific disease processes. The diagnostic accuracy, incremental yield and prognostic value of speckle tracking echocardiography, late gadolinium enhancement and parametric mapping modules by cardiac magnetic resonance and cardiac computed tomography have been validated against tissue samples and tested in broad patient populations, overall providing relevant clinical information to the cardiologist. This review describes the patterns of left ventricular and left atrial fibrosis, and their characterization by advanced echocardiography, cardiac magnetic resonance and cardiac computed tomography, allowing for clinical applications in sudden cardiac death and management of atrial fibrillation.

Left Atrial Enhancement Correlates With Myocardial Conduction Velocity in Patients With Persistent Atrial Fibrillation

BACKGROUND

Conduction velocity (CV) heterogeneity and myocardial fibrosis both promote re-entry, but the relationship between fibrosis as determined by left atrial (LA) late-gadolinium enhanced cardiac magnetic resonance imaging (LGE-CMRI) and CV remains uncertain.

OBJECTIVE

Although average CV has been shown to correlate with regional LGE-CMRI in patients with persistent AF, we test the hypothesis that a localized relationship exists to underpin LGE-CMRI as a minimally invasive tool to map myocardial conduction properties for risk stratification and treatment guidance.

METHOD

3D LA electroanatomic maps during LA pacing were acquired from eight patients with persistent AF following electrical cardioversion. Local CVs were computed using triads of concurrently acquired electrograms and were co-registered to allow correlation with LA wall intensities obtained from LGE-CMRI, quantified using normalized intensity (NI) and image intensity ratio (IIR). Association was evaluated using multilevel linear regression.

RESULTS

An association between CV and LGE-CMRI intensity was observed at scales comparable to the size of a mapping electrode: -0.11 m/s per unit increase in NI (P < 0.001) and -0.96 m/s per unit increase in IIR (P < 0.001). The magnitude of this change decreased with larger measurement area. Reproducibility of the association was observed with NI, but not with IIR.

CONCLUSION

At clinically relevant spatial scales, comparable to area of a mapping catheter electrode, LGE-CMRI correlates with CV. Measurement scale is important in accurately quantifying the association of CV and LGE-CMRI intensity. Importantly, NI, but not IIR, accounts for changes in the dynamic range of CMRI and enables quantitative reproducibility of the association.

Accelerated 3D Left Atrial Late Gadolinium Enhancement in Patients with Atrial Fibrillation at 1.5 T: Technical Development

PURPOSE

To develop an accelerated three-dimensional (3D) late gadolinium enhancement (LGE) pulse sequence using balanced steady-state free precession readout with stack-of-stars k-space sampling and extra motion-state golden-angle radial sparse parallel (XD-GRASP) reconstruction and test the performance for detecting atrial scar and fibrosis in patients with atrial fibrillation (AF).

MATERIALS AND METHODS

Twenty-five patients with AF (20 paroxysmal and five persistent; 65 years ± 7 [standard deviation]; 18 men) were imaged at 1.5 T using the proposed LGE sequence with 1.3 mm × 1.3 mm × 2-mm spatial resolution and predictable imaging time. The resulting images were compared with historic images of 25 patients with AF (18 paroxysmal and seven persistent; 67 years ± 10; 14 men) obtained using a reference 3D left atrial (LA) LGE sequence with 1.3 mm × 1.3 mm × 2.5-mm spatial resolution. Two readers visually graded the 3D LGE images (conspicuity, artifact, noise) on a five-point Likert scale (1 = worst, 3 = acceptable, 5 = best), in which the summed visual score (SVS) of 9 or greater was defined as clinically acceptable. Appropriate statistical analyses (Cohen κ coefficient, Mann-Whitney U test, t tests, and intraclass correlation) were performed, where a P value < .05 was considered significant.

RESULTS

Mean imaging time was significantly shorter (P < .01) for the proposed pulse sequence (5.9 minutes ± 1.3) than for the reference pulse sequence (10.6 minutes ± 2). Median SVS was significantly higher (P < .01) for the proposed (SVS = 11) than reference (SVS = 9.5) 3D LA LGE images. Interrater reproducibility in visual scores was higher for the proposed (κ = 0.78-1) than reference 3D LA LGE (κ = 0.44-0.75). Intrareader repeatability in fibrosis quantification was higher for the reference cohort (intraclass correlation coefficient [ICC] = 0.94) than the prospective cohort (ICC = 0.79).

CONCLUSION

The proposed 3D LA LGE method produced clinically acceptable image quality with 1.5 mm × 1.5 mm × 2-mm nominal spatial resolution and 6-minute predictable imaging time for quantification of LA scar and fibrosis in patients with AF. Supplemental material is available for this article. © RSNA, 2020.

The Value of Voltage Histogram Analysis Derived Right Atrial Scar Burden in the Prediction of Left Atrial Scar Burden

Introduction

Growing evidence suggests that fibrotic changes can be observed in atrial fibrillation (AF) in both atria. Quantification of the scar burden during electroanatomical mapping might have important therapeutic and prognostic consequences. However, as the current invasive treatment of AF is focused on the left atrium (LA), the role of the right atrium (RA) is less well understood. We aimed to characterize the clinical determinates of the RA low-voltage burden and its relation to the LA scaring.

Methods

We have included 36 patients who underwent catheter ablation for AF in a prospective observational study. In addition to LA mapping and ablation, high-density RA bipolar voltage maps (HD-EAM) were also reconstructed. The extent of the diseased RA tissue (≤0.5 mV) was quantified using the voltage histogram analysis tool (CARTO^®3, Biosense Webster).

Results

The percentage of RA diseased tissue burden was significantly higher in patients with a CHA₂DS₂-VASc score ≥ 2 (p = 0.0305), higher indexed LA volume on the CTA scan and on the HD‐EAM (p = 0.0223 and p = 0.0064, respectively), or higher indexed RA volume on the HD‐EAM (p = 0.0026). High RA diseased tissue burden predicted the presence of high LA diseased tissue burden (OR = 7.1, CI (95%): 1.3–38.9, p = 0.0145), and there was a significant correlation of the same (r = 0.6461, p < 0.0001).

Conclusions

Determining the extent of the right atrial low-voltage burden might give useful clinical information. According to our results, the diseased tissue burden correlates well between the two atria: the right atrium mirrors the left atrium.

Verification of threshold for image intensity ratio analyses of late gadolinium enhancement magnetic resonance imaging of left atrial fibrosis in 1.5T scans

The use of cardiovascular magnetic resonance imaging left atrial late gadolinium enhancement (LA LGE) is increasing for fibrosis evaluation though the use is still limited to specialized centres due to complex image acquisition and lack of consensus on image analyses. Analysis of LA LGE with image intensity ratio (IIR) (pixel intensity of atrial wall normalized by blood pool intensity) provides an objective method to obtain quantitative data on atrial fibrosis. A threshold between healthy myocardium and fibrosis of 1.2 has previously been established in 3T scans. The aim of the study was to reaffirm this threshold in 1.5T scans. LA LGE was performed using a 1.5T magnetic resonance scanner on: 11 lone-AF patients, 11 age-matched healthy volunteers (aged 27-44) and 11 elderly patients without known history of AF but varying degrees of comorbidities. Mean values of IIR for all healthy volunteers +2SD were set as upper limit of normality and was reproduced to 1.21 and the original IIR-threshold of 1.20 was maintained. The degree of fibrosis in lone-AF patients [median 9.0% (IQR 3.9-12.0)] was higher than in healthy volunteers [2.8% (1.3-8.3)] and even higher in elderly non-AF [20.1% (10.2-35.8), p = 0.001]. The previously established IIR-threshold of 1.2 was reaffirmed in 1.5T LA LGE scans. Patients with lone AF presented with increased degrees of atrial fibrosis compared to healthy volunteers in the same age-range. Elderly patients with no history of AF showed significantly higher degrees of fibrosis compared to both groups with younger individuals.

Atrial scar quantification via multi-scale CNN in the graph-cuts framework

•

Propose a fully automatic method for left atrial scar quantification, with promising performance.

•

Formulate a new framework of scar quantification based on surface projection and graph-cuts framework.

•

Propose the multi-scale learning CNN, combined with the random shift training strategy, to learn and predict the graph potentials, which significantly improves the performance of the proposed method, and enables the full automation of the framework.

•

Provide thorough validation and parameter studies for the proposed techniques using fifty-eight clinical images.

Late gadolinium enhancement magnetic resonance imaging (LGE MRI) appears to be a promising alternative for scar assessment in patients with atrial fibrillation (AF). Automating the quantification and analysis of atrial scars can be challenging due to the low image quality. In this work, we propose a fully automated method based on the graph-cuts framework, where the potentials of the graph are learned on a surface mesh of the left atrium (LA) using a multi-scale convolutional neural network (MS-CNN). For validation, we have included fifty-eight images with manual delineations. MS-CNN, which can efficiently incorporate both the local and global texture information of the images, has been shown to evidently improve the segmentation accuracy of the proposed graph-cuts based method. The segmentation could be further improved when the contribution between the t-link and n-link weights of the graph is balanced. The proposed method achieves a mean accuracy of 0.856 ± 0.033 and mean Dice score of 0.702 ± 0.071 for LA scar quantification. Compared to the conventional methods, which are based on the manual delineation of LA for initialization, our method is fully automatic and has demonstrated significantly better Dice score and accuracy (p < 0.01). The method is promising and can be potentially useful in diagnosis and prognosis of AF.

Mapping and Imaging in Non-paroxysmal AF

Despite intense research efforts, maintenance of sinus rhythm in patients with non-paroxysmal AF remains challenging with suboptimal outcomes. A major limitation to the success of current ablation-based treatments is that our understanding of AF pathophysiology is incomplete. Advances in imaging and mapping tools have been reported to improve ablation outcomes. However, the role of these new approaches on the clinical care of patients with AF remains to be validated and better understood before wide adoption can occur. This article reviews the current techniques of imaging and mapping that can be applied in the management of patients with non-paroxysmal AF with a focus on their relevance to catheter ablation. Future applications and opportunities for new knowledge are also discussed.

Targeting the Substrate in Ablation of Persistent Atrial Fibrillation: Recent Lessons and Future Directions

While isolation of the pulmonary veins is firmly established as effective treatment for the majority of paroxysmal atrial fibrillation (AF) patients, there is recognition that patients with persistent AF have substrate for perpetuation of arrhythmia existing outside of the pulmonary veins. Various computational approaches have been used to identify targets for effective ablation of persistent AF. This paper aims to discuss the clinical aspects of computational approaches that aim to identify critical sites for treatment. Various analyses of electrogram characteristics have been performed with this aim. Leading techniques for electrogram analysis are Complex Fractionated Atrial Electrograms (CFAE) and Dominant Frequency (DF). These techniques have been the subject of clinical trials of which the results are discussed. Evaluation of the activation patterns of atria in AF has been another avenue of research. Focal Impulse and Rotor Modulation (FIRM) mapping and forms of Body Surface Mapping aim to characterize multiple atrial wavelets, macro-reentry and focal sources which have been proposed as basic mechanisms perpetuating AF. Both invasive and non-invasive activation mapping techniques are reviewed. The presence of atrial fibrosis causes non-uniform anisotropic impulse propagation. Therefore, identification of fibrosis by imaging techniques is an avenue of potential research. The leading contender for imaging-based techniques is Cardiac Magnetic Resonance (CMR). As this technology advances, improvements in resolution and scar identification have positioned CMR as the mode of choice for analysis of atrial structure. AF has been demonstrated to be associated with obesity, inactivity and diseases of modern life. An opportunity exists for detailed computational analysis of the impact of risk factor modification on atrial substrate. This ranges from microstructural investigation through to examination at a population level via registries and public health interventions. Computational analysis of atrial substrate has moved from basic science toward clinical application. Future directions and potential limitations of such analyses are examined in this review.

Bayés' syndrome: Time to consider early anticoagulation?

In the past few decades, extensive research has been conducted on atrial conduction disorders and their clinical relevance. An association between interatrial block (IAB) and supraventricular arrhythmias [most commonly atrial fibrillation (AF)] has been discovered and extensively investigated. We coined the term "Bayés Syndrome" to describe this association, and the medical community has accepted the eponym in recognition to the scientist who discovered most of the aspects associated with it. In this non-systematic review, we will focus on the association between IAB and AF, with special emphasis on the value of the surface 12-lead ECG as a valid tool to predict AF.

Three-dimensional Integrated Functional, Structural, and Computational Mapping to Define the Structural "Fingerprints" of Heart-Specific Atrial Fibrillation Drivers in Human Heart Ex Vivo

BACKGROUND

Structural remodeling of human atria plays a key role in sustaining atrial fibrillation (AF), but insufficient quantitative analysis of human atrial structure impedes the treatment of AF. We aimed to develop a novel 3-dimensional (3D) structural and computational simulation analysis tool that could reveal the structural contributors to human reentrant AF drivers.

METHODS AND RESULTS

High-resolution panoramic epicardial optical mapping of the coronary-perfused explanted intact human atria (63-year-old woman, chronic hypertension, heart weight 608 g) was conducted during sinus rhythm and sustained AF maintained by spatially stable reentrant AF drivers in the left and right atrium. The whole atria (107×61×85 mm³) were then imaged with contrast-enhancement MRI (9.4 T, 180×180×360-μm³ resolution). The entire 3D human atria were analyzed for wall thickness (0.4-11.7 mm), myofiber orientations, and transmural fibrosis (36.9% subendocardium; 14.2% midwall; 3.4% subepicardium). The 3D computational analysis revealed that a specific combination of wall thickness and fibrosis ranges were primarily present in the optically defined AF driver regions versus nondriver tissue. Finally, a 3D human heart-specific atrial computer model was developed by integrating 3D structural and functional mapping data to test AF induction, maintenance, and ablation strategies. This 3D model reproduced the optically defined reentrant AF drivers, which were uninducible when fibrosis and myofiber anisotropy were removed from the model.

CONCLUSIONS

Our novel 3D computational high-resolution framework may be used to quantitatively analyze structural substrates, such as wall thickness, myofiber orientation, and fibrosis, underlying localized AF drivers, and aid the development of new patient-specific treatments.

How to detect atrial fibrosis

In the last twenty years, new imaging techniques to assess atrial function and to predict the risk of recurrence of atrial fibrillation after treatment have been developed. The present review deals with the role of these techniques in the detection of structural and functional changes of the atrium and diagnosis of atrial remodeling, particularly atrial fibrosis. Echocardiography allows the detection of anatomical, functional changes and deformation of the atrial wall during the phases of the cardiac cycle. For this, adequate acquisition of atrial images is necessary using speckle tracking imaging and interpretation of the resulting strain and strain rate curves. This allows to predict new-onset atrial fibrillation and recurrences. Its main limitations are inter-observer variability, the existence of different software manufacturers, and the fact that the software used were originally developed for the evaluation of the ventricular function and are now applied to the atria. Cardiac magnetic resonance, using contrast enhancement with gadolinium, plays a key role in the visualization and quantification of atrial fibrosis. This is the established method for in vivo visualization of myocardial fibrotic tissue. The non-invasive evaluation of atrial fibrosis is associated with the risk of recurrence of atrial fibrillation and with electro-anatomical endocardial mapping. We discuss the limitations of these techniques, derived from the difficulty of demonstrating the correlation between fibrosis imaging and histology, and poor intra- and inter-observer reproducibility. The sources of discordance are described, mainly due to image acquisition and processing, and the challenges ahead in an attempt to eliminate differences between operators.