Imaging of subendocardial adipose tissue and fiber orientation distributions in the human left atrium using optical coherence tomography

Lye, Theresa H.; Marboe, Charles C.; Hendon, Christine P.

doi:10.1111/jce.14255

Cited by 12 publications

(5 citation statements)

References 38 publications

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“…In [42], segmentation was obtained from the variance map through compressive sensing reconstruction. In [38], the distributions of adipose tissues and fiber orientations were retracted and mapped throughout human left atrium, while in [6], the visualization of cardiac fibers in the atrium, ventricle, atrioventricular node, and sinoatrial node were presented. Overall, conventional cardiac OCT image analysis relies on handcrafted features for tissue characterization or fiber orientation-based methods to focus on myofibers.…”

Section: Related Workmentioning

confidence: 99%

“…Recent advances have demonstrated the capability of OCT on capturing myocardial structures such as Purkinje network [55], atrial ventricular nodes [20], sinoatrial nodes [5], and myofiber organization [18]. In addition, it can be used to resolve critical tissue substrates of arrhythmias, such as fibrosis and adipose tissues [38]. With the development of OCT-integrated catheters [14], OCT can image the heart wall in real time through percutaneous access [51], which holds promise to aid catheter ablation.…”

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confidence: 99%

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Cardiac Adipose Tissue Segmentation via Image-Level Annotations

Huang

Gan

Lye

et al. 2023

IEEE J. Biomed. Health Inform.

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Automatically identifying the structural substrates underlying cardiac abnormalities can potentially provide real-time guidance for interventional procedures. With the knowledge of cardiac tissue substrates, the treatment of complex arrhythmias such as atrial fibrillation and ventricular tachycardia can be further optimized by detecting arrhythmia substrates to target for treatment (i.e., adipose) and identifying critical structures to avoid. Optical coherence tomography (OCT) is a real-time imaging modality that aids in addressing this need. Existing approaches for cardiac image analysis mainly rely on fully supervised learning techniques, which suffer from the drawback of workload on labor-intensive annotation process of pixelwise labeling. To lessen the need for pixel-wise labeling, we develop a two-stage deep learning framework for cardiac adipose tissue segmentation using image-level annotations on OCT images of human cardiac substrates. In particular, we integrate class activation mapping with superpixel segmentation to solve the sparse tissue seed challenge raised in cardiac tissue segmentation. Our study bridges the gap between the demand on automatic tissue analysis and the lack of high-quality pixel-wise annotations. To the best of our knowledge, this is the first study that attempts to address cardiac tissue segmentation on OCT images via weakly supervised learning techniques. Within an invitro human cardiac OCT dataset, we demonstrate that our weakly supervised approach on image-level annotations achieves comparable performance as fully supervised methods trained on pixel-wise annotations.

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Section: Related Workmentioning

confidence: 99%

mentioning

confidence: 99%

Cardiac Adipose Tissue Segmentation via Image-Level Annotations

Huang

Gan

Lye

et al. 2023

IEEE J. Biomed. Health Inform.

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“…One specific study utilizing OCT in the left human atria identified adipose tissue near the venous media, within the myocardial sleeves, in the adventitia of the pulmonary veins (PVs), and around the septum. The localization of epicardial fat by OCT‐integrated catheters might thus be helpful for improving the success of AF ablation 44 . However, quality, rather than volume or thickness of the epicardial fat, was found to be an independent risk factor for AF after the first catheter ablation.…”

Section: Obesity Eat and Afmentioning

confidence: 99%

Updates on epicardial adipose tissue mechanisms on atrial fibrillation

et al. 2021

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Summary Obesity is a well‐known risk factor for atrial fibrillation (AF). Local epi‐myocardial or intra‐myocardial adiposity caused by aging, obesity, or cardiovascular disease (CVD) is considered to be a better predictor of the risk of AF than general adiposity. Some of the described mechanisms suggest that epicardial adipose tissue (EAT) participates in structural remodeling owing to its endocrine activity or its infiltration between cardiomyocytes. Epicardial fat also wraps up the ganglionated plexi that reach the myocardium. Although the increment of volume/thickness and activity of EAT might modify autonomic activity, autonomic system dysfunction might also change the endocrine activity of epicardial fat in a feedback response. As a result, new preventive therapeutic strategies are focused on reducing adiposity and weight loss before AF ablation or inhibiting autonomic neurotransmitter secretion on fat pads during open‐heart surgery to reduce the recurrence or postoperative risk of AF. In this manuscript, we review some of the novel findings regarding the pathophysiology and associated risk factors of AF, with special emphasis on the role of EAT in the electrical, structural, and molecular mechanisms of AF initiation and maintenance. In addition, we have included a brief note provided on epicardial fat preclinical models that could be useful for identifying new therapeutic targets.

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“… 17 , 18 Recently, optical imaging techniques have been applied to the challenge of RFA lesion characterization. Hyperspectral autofluorescence imaging has shown promise in localizing and characterizing RFA lesions, but the complexity of this technique (requiring a hyperspectral camera, UV illumination, and additional optics) renders it less compatible with endovascular access 19 – 21 Optical coherence tomography has also proven capable of identifying diverse structural substrates, including fibrotic and adipose tissue, 22 – 27 but tissue penetration depth is limited to 1 to 2 mm.…”

Section: Introductionmentioning

confidence: 99%

Robust, high-density lesion mapping in the left atrium with near-infrared spectroscopy

Yang,

Majumder,

Huang

et al. 2024

J. Biomed. Opt.

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.SignificanceRadiofrequency ablation (RFA) procedures for atrial fibrillation frequently fail to prevent recurrence, partially due to limitations in assessing extent of ablation. Optical spectroscopy shows promise in assessing RFA lesion formation but has not been validated in conditions resembling those in vivo.AimCatheter-based near-infrared spectroscopy (NIRS) was applied to porcine hearts to demonstrate that spectrally derived optical indices remain accurate in blood and at oblique incidence angles.ApproachPorcine left atria were ablated and mapped using a custom-fabricated NIRS catheter. Each atrium was mapped first in phosphate-buffered saline (PBS) then in porcine blood.ResultsNIRS measurements showed little angle dependence up to 60 deg. A trained random forest model predicted lesions with a sensitivity of 81.7%, a specificity of 86.1%, and a receiver operating characteristic curve area of 0.921. Predicted lesion maps achieved a mean structural similarity index of 0.749 and a mean normalized inner product of 0.867 when comparing maps obtained in PBS and blood.ConclusionsCatheter-based NIRS can precisely detect RFA lesions on left atria submerged in blood. Optical parameters are reliable in blood and without perpendicular contact, confirming their ability to provide useful feedback during in vivo RFA procedures.

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Imaging of subendocardial adipose tissue and fiber orientation distributions in the human left atrium using optical coherence tomography

Cited by 12 publications

References 38 publications

Cardiac Adipose Tissue Segmentation via Image-Level Annotations

Cardiac Adipose Tissue Segmentation via Image-Level Annotations

Updates on epicardial adipose tissue mechanisms on atrial fibrillation

Robust, high-density lesion mapping in the left atrium with near-infrared spectroscopy

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