Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Review

Late gadolinium enhancement magnetic resonance imaging (LGE MRI) is commonly used to visualize and quantify left atrial (LA) scars. The position and extent of scars provide important information of the pathophysiology and progression of atrial fibrillation (AF). Hence, LA scar segmentation and quantification from LGE MRI can be useful in computer-assisted diagnosis and treatment stratification of AF patients. Since manual delineation can be time-consuming and subject to intra- and inter-expert variability, automating this computing is highly desired, which nevertheless is still challenging and under-researched. This paper aims to provide a systematic review on computing methods for LA cavity, wall, scar and ablation gap segmentation and quantification from LGE MRI, and the related literature for AF studies. Specifically, we first summarize AF-related imaging techniques, particularly LGE MRI. Then, we review the methodologies of the four computing tasks in detail, and summarize the validation strategies applied in each task. Finally, the possible future developments are outlined, with a brief survey on the potential clinical applications of the aforementioned methods. The review shows that the research into this topic is still in early stages. Although several methods have been proposed, especially for LA segmentation, there is still large scope for further algorithmic developments due to performance issues related to the high variability of enhancement appearance and differences in image acquisition.Comment: 23 page

Automated analysis of atrial late gadolinium enhancement imaging that correlates with endocardial voltage and clinical outcomes: A 2-center study

This work was supported by the British Heart Foundation PG/10/37/28347, RG/10/11/28457, NIHR Biomedical Research Centre funding, and the ElectroCardioMaths Programme of the Imperial BHF Centre of Research Excellence

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

Automated Method for the Volumetric Evaluation of Myocardial Scar from Cardiac Magnetic Resonance Images

In most western countries cardiovascular diseases are the leading cause of death, and for the survivors of ischemic attack an accurate quantification of the extent of the damage is required to correctly assess its impact and for risk stratification, and to select the best treatment for the patient. Moreover, a fast and reliable tool for the assessment of the cardiac function and the measurement of clinical indexes is highly desirable. The aim of this thesis is to provide computational approaches to better detect and assess the presence of myocardial fibrosis in the heart, particularly but not only in the left ventricle, by performing a fusion of the information from different magnetic resonance imaging sequences. We also developed and provided a semiautomatic tool useful for the fast evaluation and quantification of clinical indexes derived from heart chambers volumes. The thesis is composed by five chapters. The first chapter introduces the most common cardiac diseases such as ischemic cardiomyopathy and describes in detail the cellular and structural remodelling phenomena stemming from heart failure. The second chapter regards the detection of the left ventricle through the development of a semi-automated approach for both endocardial and epicardial surfaces, and myocardial mask extraction. In the third chapter the workflow for scar assessment is presented, in which the previously described approach is used to obtain the 3D left ventricle patient-specific geometry; a registration algorithm is then used to superimpose the fibrosis information derived from the late gadolinium enhancement magnetic resonance imaging to obtain a patientspecific 3D map of fibrosis extension and location on the left ventricle myocardium. Focus of the fourth chapter is on the left atrium, and fibrotic tissue detection for gaining insight on atrial fibrillation. In the fifth chapter some conclusive remarks are presented with possible future developments of the presented work

Clinical Conditions And Cardiac Function: Correlations With Left Atrial Fibrosis By Mri In Subjects With And Without Atrial Fibrillation

The purpose of this study was to evaluate the clinical conditions and cardiac functions associated with left atrial (LA) fibrosis by late gadolinium enhancement (LGE). LA LGE has been found to be associated with various measures of cardiac functions, procedural outcomes, and adverse events in patients who already have atrial fibrillation (AF). Assessment of LA fibrosis by LGE in patients without AF has largely been unexamined and comparison of these patients to those with AF could prove useful. This study was a retrospective chart and imaging review of 137 consecutive subjects imaged with a 3D LGE sequence at one institution from 2012-2014. Fibrosis by LA LGE is elevated in subjects with congestive heart failure (CHF), AF, hypertrophic cardiomyopathy (HCM), and mitral regurgitation when compared to a set of reference subjects (all p \u3c 0.05). In multivariate analysis, HCM (p = 0.01) and CHF (p \u3c 0.01) were independently associated with elevated LGE. Across all subjects, LA LGE was moderately correlated with minimum LA volume (r = 0.41, p \u3c 0.01) and LA ejection fraction (r = -0.43, p \u3c 0.01) but weakly correlated with maximum LA volume (r = 0.197, p = 0.02); these relationships were similar in subgroups with and without AF. In a subset of subjects without AF, there was a lower active atrial ejection fraction with increasing LA LGE (r = -0.438, p \u3c 0.01). Also, after multivariate adjustment for ventricular filling measures, there was an independent association of increased LA LGE with decreased passive LA emptying (p = 0.02). Subjects with heart failure but ventricular ejection fraction \u3e45% had greater LA LGE than those with whose ejection fraction was We found that extent of LGE correlates with the presence of CHF, AF, HCM, mitral regurgitation, and some cardiac anatomic and functional measurements. This study lays the groundwork for further evaluation of the utility of measuring LA LGE in patients without AF

Rapid automatic segmentation of abnormal tissue in late gadolinium enhancement cardiovascular magnetic resonance images for improved management of long-standing persistent atrial fibrillation

Background: Atrial fibrillation (AF) is the most common heart rhythm disorder. In order for late Gd enhancement cardiovascular magnetic resonance (LGE CMR) to ameliorate the AF management, the ready availability of the accurate enhancement segmentation is required. However, the computer-aided segmentation of enhancement in LGE CMR of AF is still an open question. Additionally, the number of centres that have reported successful application of LGE CMR to guide clinical AF strategies remains low, while the debate on LGE CMR’s diagnostic ability for AF still holds. The aim of this study is to propose a method that reliably distinguishes enhanced (abnormal) from non-enhanced (healthy) tissue within the left atrial wall of (pre-ablation and 3 months post-ablation) LGE CMR data-sets from long-standing persistent AF patients studied at our centre. Methods: Enhancement segmentation was achieved by employing thresholds benchmarked against the statistics of the whole left atrial blood-pool (LABP). The test-set cross-validation mechanism was applied to determine the input feature representation and algorithm that best predict enhancement threshold levels. Results: Global normalized intensity threshold levels T PRE = 1 1/4 and T POST = 1 5/8 were found to segment enhancement in data-sets acquired pre-ablation and at 3 months post-ablation, respectively. The segmentation results were corroborated by using visual inspection of LGE CMR brightness levels and one endocardial bipolar voltage map. The measured extent of pre-ablation fibrosis fell within the normal range for the specific arrhythmia phenotype. 3D volume renderings of segmented post-ablation enhancement emulated the expected ablation lesion patterns. By comparing our technique with other related approaches that proposed different threshold levels (although they also relied on reference regions from within the LABP) for segmenting enhancement in LGE CMR data-sets of AF patients, we illustrated that the cut-off levels employed by other centres may not be usable for clinical studies performed in our centre. Conclusions: The proposed technique has great potential for successful employment in the AF management within our centre. It provides a highly desirable validation of the LGE CMR technique for AF studies. Inter-centre differences in the CMR acquisition protocol and image analysis strategy inevitably impede the selection of a universally optimal algorithm for segmentation of enhancement in AF studies