Tissue-Specific Optical Mapping Models of Swine Atria Informed by Optical Coherence Tomography

Predictive coding compressive sensing optical coherence tomography hardware implementation

Compressed sensing (CS) is an approach that enables comprehensive imaging by reducing both imaging time and data density, and is a theory that enables undersampling far below the Nyquist sampling rate and guarantees high-accuracy image recovery. Prior efforts in the literature have focused on demonstrations of synthetic undersampling and reconstructions enabled by compressed sensing. In this paper, we demonstrate the first physical, hardware-based sub-Nyquist sampling with a galvanometer-based OCT system with subsequent reconstruction enabled by compressed sensing. Acquired images of a variety of samples, with volume scanning time reduced by 89% (12.5% compression rate), were successfully reconstructed with relative error (RE) of less than 20% and mean square error (MSE) of around 1%.

Optical mapping and optogenetics in cardiac electrophysiology research and therapy: a state-of-the-art review

State-of-the-art innovations in optical cardiac electrophysiology are significantly enhancing cardiac research. A potential leap into patient care is now on the horizon. Optical mapping, using fluorescent probes and high-speed cameras, offers detailed insights into cardiac activity and arrhythmias by analysing electrical signals, calcium dynamics, and metabolism. Optogenetics utilizes light-sensitive ion channels and pumps to realize contactless, cell-selective cardiac actuation for modelling arrhythmia, restoring sinus rhythm, and probing complex cell-cell interactions. The merging of optogenetics and optical mapping techniques for 'all-optical' electrophysiology marks a significant step forward. This combination allows for the contactless actuation and sensing of cardiac electrophysiology, offering unprecedented spatial-temporal resolution and control. Recent studies have performed all-optical imaging ex vivo and achieved reliable optogenetic pacing in vivo, narrowing the gap for clinical use. Progress in optical electrophysiology continues at pace. Advances in motion tracking methods are removing the necessity of motion uncoupling, a key limitation of optical mapping. Innovations in optoelectronics, including miniaturized, biocompatible illumination and circuitry, are enabling the creation of implantable cardiac pacemakers and defibrillators with optoelectrical closed-loop systems. Computational modelling and machine learning are emerging as pivotal tools in enhancing optical techniques, offering new avenues for analysing complex data and optimizing therapeutic strategies. However, key challenges remain including opsin delivery, real-time data processing, longevity, and chronic effects of optoelectronic devices. This review provides a comprehensive overview of recent advances in optical mapping and optogenetics and outlines the promising future of optics in reshaping cardiac electrophysiology and therapeutic strategies.

3-D compressed sensing optical coherence tomography using predictive coding

We present a compressed sensing (CS) algorithm and sampling strategy for reconstructing 3-D Optical Coherence Tomography (OCT) image volumes from as little as 10% of the original data. Reconstruction using the proposed method, Denoising Predictive Coding (DN-PC), is demonstrated for five clinically relevant tissue types including human heart, retina, uterus, breast, and bovine ligament. DN-PC reconstructs the difference between adjacent b-scans in a volume and iteratively applies Gaussian filtering to improve image sparsity. An a-line sampling strategy was developed that can be easily implemented in existing Spectral-Domain OCT systems and reduce scan time by up to 90%.

Three-dimensional collagen fiber mapping and tractography of human uterine tissue using OCT

Automatic quantification and visualization of 3-D collagen fiber architecture using Optical Coherence Tomography (OCT) has previously relied on polarization information and/or prior knowledge of tissue-specific fiber architecture. This study explores image processing, enhancement, segmentation, and detection algorithms to map 3-D collagen fiber architecture from OCT images alone. 3-D fiber mapping, histogram analysis, and 3-D tractography revealed fiber groupings and macro-organization previously unseen in uterine tissue samples. We applied our method on centimeter-scale mosaic OCT volumes of uterine tissue blocks from pregnant and non-pregnant specimens revealing a complex, patient-specific network of fibrous collagen and myocyte bundles.

Monitoring the dynamics of acute radiofrequency ablation lesion formation in thin-walled atria - a simultaneous optical and electrical mapping study

Background Radiofrequency ablation (RFA) is a common approach to treat cardiac arrhythmias. During this intervention, numerous strategies are applied to indirectly estimate lesion formation. However, the assessment of the spatial extent of these acute injuries needs to be improved in order to create well-defined and durable ablation lesions. Methods We investigated the electrophysiological characteristics of rat atrial myocardium during an ex vivo RFA procedure with fluorescence-optical and electrical mapping. By analyzing optical data, the temporal growth of punctiform ablation lesions was reconstructed after stepwise RFA sequences. Unipolar electrograms (EGMs) were simultaneously recorded by a multielectrode array (MEA) before and after each RFA sequence. Based on the optical results, we searched for electrical features to delineate these lesions from healthy myocardium. Results Several unipolar EGM parameters were monotonically decreasing when distances between the electrode and lesion boundary were smaller than 2 mm. The negative component of the unipolar EGM [negative peak amplitude (Aneg)] vanished for distances lesser than 0.4 mm to the lesion boundary. Median peak-to-peak amplitude (Vpp) was decreased by 75% compared to baseline. Conclusion Aneg and Vpp are excellent parameters to discriminate the growing lesion area from healthy myocardium. The experimental setup opens new opportunities to investigate EGM characteristics of more complex ablation lesions.

Characterization of the human myocardium by optical coherence tomography

Imaging of cardiac tissue structure plays a critical role in the treatment and understanding of cardiovascular disease. Optical coherence tomography (OCT) offers the potential to provide valuable, high-resolution imaging of cardiac tissue. However, there is a lack of comprehensive OCT imaging data of the human heart, which could improve identification of structural substrates underlying cardiac abnormalities. The objective of this study was to provide qualitative and quantitative analysis of OCT image features throughout the human heart. Fifty human hearts were acquired, and tissues from all chambers were imaged with OCT. Histology was obtained to verify tissue composition. Statistical differences between OCT image features corresponding to different tissue types and chambers were estimated using analysis of variance. OCT imaging provided features that were able to distinguish structures such as thickened collagen, as well as adipose tissue and fibrotic myocardium. Statistically significant differences were found between atria and ventricles in attenuation coefficient, and between adipose and all other tissue types. This study provides an overview of OCT image features throughout the human heart, which can be used for guiding future applications such as OCT-integrated catheter-based treatments or ex vivo investigation of structural substrates.

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

Background

Optical coherence tomography (OCT) has the potential to provide real‐time imaging guidance for atrial fibrillation ablation, with promising results for lesion monitoring. OCT can also offer high‐resolution imaging of tissue composition, but there is insufficient cardiac OCT data to inform the use of OCT to reveal important tissue architecture of the human left atrium. Thus, the objective of this study was to define OCT imaging data throughout the human left atrium, focusing on the distribution of adipose tissue and fiber orientation as seen from the endocardium.

Methods and Results

Human hearts (n = 7) were acquired for imaging the left atrium with OCT. A spectral‐domain OCT system with 1325 nm center wavelength, 6.5 μm axial resolution, 15 μm lateral resolution, and a maximum imaging depth of 2.51 mm in the air was used. Large‐scale OCT image maps of human left atrial tissue were developed, with adipose thickness and fiber orientation extracted from the imaging data. OCT imaging showed scattered distributions of adipose tissue around the septal and pulmonary vein regions, up to a depth of about 0.43 mm from the endocardial surface. The total volume of adipose tissue detected by OCT over one left atrium ranged from 1.42 to 28.74 mm³. Limited fiber orientation information primarily around the pulmonary veins and the septum could be identified.

Conclusion

OCT imaging could provide adjunctive information on the distribution of subendocardial adipose tissue, particularly around thin areas around the pulmonary veins and septal regions. Variations in OCT‐detected tissue composition could potentially assist ablation guidance.

High-speed collagen fiber modeling and orientation quantification for optical coherence tomography imaging

Quantifying collagen fiber architecture has clinical and scientific relevance across a variety of tissue types and adds functionality to otherwise largely qualitative imaging modalities. Optical coherence tomography (OCT) is uniquely suited for this task due to its ability to capture the collagen microstructure over larger fields of view than traditional microscopy. Existing image processing techniques for quantifying fiber architecture, while accurate and effective, are very slow for processing large datasets and tend to lack structural specificity. We describe here a computationally efficient method for quantifying and visualizing collagen fiber organization. The algorithm is demonstrated on swine atria, bovine anterior cruciate ligament, and human cervical tissue samples. Additionally, we show an improved performance for images with crimped fiber textures and low signal to noise when compared to similar methods.

Optical coherence tomography imaging of cardiac substrates

Cardiovascular disease is the leading cause of morbidity and mortality in the United States. Knowledge of a patient's heart structure will help to plan procedures, potentially identifying arrhythmia substrates, critical structures to avoid, detect transplant rejection, and reduce ambiguity when interpreting electrograms and functional measurements. Similarly, basic research of numerous cardiac diseases would greatly benefit from structural imaging at cellular scale. For both applications imaging on the scale of a myocyte is needed, which is approximately 100 µm × 10 µm. The use of optical coherence tomography (OCT) as a tool for characterizing cardiac tissue structure and function has been growing in the past two decades. We briefly review OCT principles and highlight important considerations when imaging cardiac muscle. In particular, image penetration, tissue birefringence, and light absorption by blood during in vivo imaging are important factors when imaging the heart with OCT. Within the article, we highlight applications of cardiac OCT imaging including imaging heart tissue structure in small animal models, quantification of myofiber organization, monitoring of radiofrequency ablation (RFA) lesion formation, structure-function analysis enabled by functional extensions of OCT and multimodal analysis and characterizing important substrates within the human heart. The review concludes with a summary and future outlook of OCT imaging the heart, which is promising with progress in optical catheter development, functional extensions of OCT, and real time image processing to enable dynamic imaging and real time tracking during therapeutic procedures.

Real-time optical spectroscopic monitoring of nonirrigated lesion progression within atrial and ventricular tissues

Despite considerable advances in guidance of radiofrequency ablation (RFA) therapy for the treatment of cardiac arrhythmias, success rates have been hampered by a lack of tools for precise intraoperative evaluation of lesion extent. Near-infrared spectroscopic (NIRS) techniques are sensitive to tissue structural and biomolecular properties, characteristics that are directly altered by radiofrequency (RF) treatment. In this work, a combined NIRS-RFA catheter is developed for real-time monitoring of tissue reflectance during RF energy delivery. An algorithm is proposed for processing NIR spectra to approximate nonirrigated lesion depth in both atrial and ventricular tissues. The probe optical geometry was designed to bias measurement influence toward absorption enabling enhanced sensitivity to changes in tissue composition. A set of parameters termed "lesion optical indices" are defined encapsulating spectral differences between ablated and unablated tissue. Utilizing these features, a model for real-time tissue spectra classification and lesion size estimation is presented. Experimental validation conducted within freshly excised porcine cardiac specimens showed strong concordance between algorithm estimates and post-hoc tissue assessment.

Mapping the human pulmonary venoatrial junction with optical coherence tomography

Imaging guidance provided by optical coherence tomography (OCT) could improve the outcomes of atrial fibrillation (AF) ablation by providing detailed structural information of the pulmonary veins, which are critical targets during ablation. In this study, stitched volumetric OCT images of venoatrial junctions from post-mortem human hearts were acquired and compared to histology. Image features corresponding to venous media and myocardial sleeves, as well as fiber orientation and fibrosis, were identified and found to vary between veins. Imaging of detailed tissue architecture could improve understanding of the AF structural substrate within the pulmonary veins and assist the guidance of ablation procedures.

The role of personalized atrial modeling in understanding atrial fibrillation mechanisms and improving treatment

Atrial fibrillation is the most common arrhythmia in humans and is associated with high morbidity, mortality and health-related expenses. Computational approaches have been increasingly utilized in atrial electrophysiology. In this review we summarize the recent advancements in atrial fibrillation modeling at the organ scale. Multi-scale atrial models now incorporate high level detail of atrial anatomy, tissue ultrastructure and fibrosis distribution. We provide the state-of-the art methodologies in developing personalized atrial fibrillation models with realistic geometry and tissue properties. We then focus on the use of multi-scale atrial models to gain mechanistic insights in AF. Simulations using atrial models have provided important insight in the mechanisms underlying AF, showing the importance of the atrial fibrotic substrate and altered atrial electrophysiology in initiation and maintenance of AF. Last, we summarize the translational evidence that supports incorporation of computational modeling in clinical practice for development of personalized treatment strategies for patients with AF. In early-stages clinical studies, AF models successfully identify patients where pulmonary vein isolation alone is not adequate for treatment of AF and suggest novel targets for ablation. We conclude with a summary of the future developments envisioned for the field of atrial computational electrophysiology.