Autofluorescence hyperspectral imaging of radiofrequency ablation lesions in porcine cardiac tissue

Advancing laser ablation assessment in hyperspectral imaging through machine learning

Hyperspectral imaging (HSI) is gaining increasing relevance in medicine, with an innovative application being the intraoperative assessment of the outcome of laser ablation treatment used for minimally invasive tumor removal. However, the high dimensionality and complexity of HSI data create a need for end-to-end image processing workflows specifically tailored to handle these data. This study addresses this challenge by proposing a multi-stage workflow for the analysis of hyperspectral data and allows investigating the performance of different components and modalities for ablation detection and segmentation. To address dimensionality reduction, we integrated principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) to capture dominant variations and reveal intricate structures, respectively. Additionally, we employed the Faster Region-based Convolutional Neural Network (Faster R-CNN) to accurately localize ablation areas. The two-stage detection process of Faster R-CNN, along with the choice of dimensionality reduction technique and data modality, significantly influenced the performance in detecting ablation areas. The evaluation of the ablation detection on an independent test set demonstrated a mean average precision of approximately 0.74, which validates the generalization ability of the models. In the segmentation component, the Mean Shift algorithm showed high quality segmentation without manual cluster definition. Our results prove that the integration of PCA, t-SNE, and Faster R-CNN enables improved interpretation of hyperspectral data, leading to the development of reliable ablation detection and segmentation systems.

Label-Free Assessment of Key Biological Autofluorophores: Material Characteristics and Opportunities for Clinical Applications

Autofluorophores are endogenous fluorescent compounds that naturally occur in the intra and extracellular spaces of all tissues and organs. Most have vital biological functions - like the metabolic cofactors NAD(P)H and FAD+, as well as the structural protein collagen. Others are considered to be waste products - like lipofuscin and advanced glycation end products - which accumulate with age and are associated with cellular dysfunction. Due to their natural fluorescence, these materials have great utility for enabling non-invasive, label-free assays with direct ties to biological function. Numerous technologies, with different advantages and drawbacks, are applied to their assessment, including fluorescence lifetime imaging microscopy, hyperspectral microscopy, and flow cytometry. Here, the applications of label-free autofluorophore assessment are reviewed for clinical and health-research applications, with specific attention to biomaterials, disease detection, surgical guidance, treatment monitoring, and tissue assessment - fields that greatly benefit from non-invasive methodologies capable of continuous, in vivo characterization.

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

Significance

Radiofrequency 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.

Aim

Catheter-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.

Approach

Porcine 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.

Results

NIRS 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.

Conclusions

Catheter-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.

Emerging clinical applications in oncology for non-invasive multi- and hyperspectral imaging of cell and tissue autofluorescence

Hyperspectral and multispectral imaging of cell and tissue autofluorescence is an emerging technology in which fluorescence imaging is applied to biological materials across multiple spectral channels. This produces a stack of images where each matched pixel contains information about the sample's spectral properties at that location. This allows precise collection of molecularly specific data from a broad range of native fluorophores. Importantly, complex information, directly reflective of biological status, is collected without staining and tissues can be characterised in situ, without biopsy. For oncology, this can spare the collection of biopsies from sensitive regions and enable accurate tumour mapping. For in vivo tumour analysis, the greatest focus has been on oral cancer, whereas for ex vivo assessment head-and-neck cancers along with colon cancer have been the most studied, followed by oral and eye cancer. This review details the scope and progress of research undertaken towards clinical translation in oncology.

Niche preclinical and clinical applications of photoacoustic imaging with endogenous contrast

In the past decade, photoacoustic (PA) imaging has attracted a great deal of popularity as an emergent diagnostic technology owing to its successful demonstration in both preclinical and clinical arenas by various academic and industrial research groups. Such steady growth of PA imaging can mainly be attributed to its salient features, including being non-ionizing, cost-effective, easily deployable, and having sufficient axial, lateral, and temporal resolutions for resolving various tissue characteristics and assessing the therapeutic efficacy. In addition, PA imaging can easily be integrated with the ultrasound imaging systems, the combination of which confers the ability to co-register and cross-reference various features in the structural, functional, and molecular imaging regimes. PA imaging relies on either an endogenous source of contrast (e.g., hemoglobin) or those of an exogenous nature such as nano-sized tunable optical absorbers or dyes that may boost imaging contrast beyond that provided by the endogenous sources. In this review, we discuss the applications of PA imaging with endogenous contrast as they pertain to clinically relevant niches, including tissue characterization, cancer diagnostics/therapies (termed as theranostics), cardiovascular applications, and surgical applications. We believe that PA imaging's role as a facile indicator of several disease-relevant states will continue to expand and evolve as it is adopted by an increasing number of research laboratories and clinics worldwide.

Clinical applications of non-invasive multi and hyperspectral imaging of cell and tissue autofluorescence beyond oncology

Hyperspectral and multispectral imaging of cell and tissue autofluorescence employs fluorescence imaging, without exogenous fluorophores, across multiple excitation/emission combinations (spectral channels). This produces an image stack where each pixel (matched by location) contains unique information about the sample's spectral properties. Analysis of this data enables access to a rich, molecularly specific data set from a broad range of cell-native fluorophores (autofluorophores) directly reflective of biochemical status, without use of fixation or stains. This non-invasive, non-destructive technology has great potential to spare the collection of biopsies from sensitive regions. As both staining and biopsy may be impossible, or undesirable, depending on the context, this technology great diagnostic potential for clinical decision making. The main research focus has been on the identification of neoplastic tissues. However, advances have been made in diverse applications-including ophthalmology, cardiovascular health, neurology, infection, assisted reproduction technology and organ transplantation.

Monitoring of irrigated lesion formation with single fiber based multispectral system using machine learning

In radiofrequency ablation (RFA) treatment of cardiac arrhythmias, intraprocedural assessment of treatment efficacy relies on indirect measures of adequate tissue destruction. Direct sensing of diffuse reflectance spectral changes at the ablation site using optically integrated RFA catheters has been shown to enable accurate prediction of lesion dimensions, ex vivo. Challenges of optical guidance can be due to obtaining reliable measurements under various catheter-tissue contact orientations. In this work, addressed this limitation by assessing the feasibility of monitoring lesion progression using single-fiber reflectance spectroscopy (SFRS). A total of 110 endocardial lesions of various sizes were generated in freshly excised swine right ventricular tissue using a custom-built, irrigated SFRS-RFA catheter. Models were developed for assessing catheter-tissue contact, the presence of nontransmural or transmural lesions and lesion depth percentage. These results support the use of SFRS-based catheters for irrigated lesion assessment and motivate further exploration of using multi-SFRS catheters for omnidirectionality.

Cardiac endocardial left atrial substrate and lesion depth mapping using near-infrared spectroscopy

Atrial fibrillation (AF) is a rapid irregular electrical activity in the upper chamber and the most common sustained cardiac arrhythmia. Many patients require radiofrequency ablation (RFA) therapy to restore sinus rhythm. Pulmonary vein isolation requires distinguishing normal atrial wall from the pulmonary vein tissue, and atrial substrate ablation requires differentiating scar tissue, fibrosis, and adipose tissue. However, current anatomical mapping methods for strategically locating ablation sites by identifying structural substrates in real-time are limited. An intraoperative tool that accurately provides detailed structural information and classifies endocardial substrates could help improve RF guidance during RF ablation therapy. In this work, we propose a 7F NIRS integrated ablation catheter and demonstrate endocardial mapping on ex vivo swine (n = 12) and human (n = 5) left atrium (LA). First, pulmonary vein (PV) sleeve, fibrosis and ablation lesions were identified with NIRS-derived contrast indices. Based on these key spectral features, classification algorithms identified endocardial substrates with high accuracy (<11% error). Then, a predictive model for lesion depth was evaluated on classified lesions. Model predictions correlated well with histological measurements of lesion dimensions (R = 0.984). Classified endocardial substrates and lesion depth were represented in 2D spatial maps. These results suggest NIRS integrated mapping catheters can serve as a complementary tool to the current electroanatomical mapping system to improve treatment efficacy.

Prediction of In Vivo Laser-Induced Thermal Damage with Hyperspectral Imaging Using Deep Learning

Thermal ablation is an acceptable alternative treatment for primary liver cancer, of which laser ablation (LA) is one of the least invasive approaches, especially for tumors in high-risk locations. Precise control of the LA effect is required to safely destroy the tumor. Although temperature imaging techniques provide an indirect measurement of the thermal damage, a degree of uncertainty remains about the treatment effect. Optical techniques are currently emerging as tools to directly assess tissue thermal damage. Among them, hyperspectral imaging (HSI) has shown promising results in image-guided surgery and in the thermal ablation field. The highly informative data provided by HSI, associated with deep learning, enable the implementation of non-invasive prediction models to be used intraoperatively. Here we show a novel paradigm “peak temperature prediction model” (PTPM), convolutional neural network (CNN)-based, trained with HSI and infrared imaging to predict LA-induced damage in the liver. The PTPM demonstrated an optimal agreement with tissue damage classification providing a consistent threshold (50.6 ± 1.5 °C) for the damage margins with high accuracy (~0.90). The high correlation with the histology score (r = 0.9085) and the comparison with the measured peak temperature confirmed that PTPM preserves temperature information accordingly with the histopathological assessment.

Hyperspectral Imagery for Assessing Laser-Induced Thermal State Change in Liver

This work presents the potential of hyperspectral imaging (HSI) to monitor the thermal outcome of laser ablation therapy used for minimally invasive tumor removal. Our main goal is the establishment of indicators of the thermal damage of living tissues, which can be used to assess the effect of the procedure. These indicators rely on the spectral variation of temperature-dependent tissue chromophores, i.e., oxyhemoglobin, deoxyhemoglobin, methemoglobin, and water. Laser treatment was performed at specific temperature thresholds (from 60 to 110 °C) on in-vivo animal liver and was assessed with a hyperspectral camera (500-995 nm) during and after the treatment. The indicators were extracted from the hyperspectral images after the following processing steps: the breathing motion compensation and the spectral and spatial filtering, the selection of spectral bands corresponding to specific tissue chromophores, and the analysis of the areas under the curves for each spectral band. Results show that properly combining spectral information related to deoxyhemoglobin, methemoglobin, lipids, and water allows for the segmenting of different zones of the laser-induced thermal damage. This preliminary investigation provides indicators for describing the thermal state of the liver, which can be employed in the future as clinical endpoints of the procedure outcome.

A Percutaneous Catheter for In Vivo Hyperspectral Imaging of Cardiac Tissue: Challenges, Solutions and Future Directions

PURPOSE

Multiple studies have shown that spectral analysis of tissue autofluorescence can be used as a live indicator for various pathophysiological states of cardiac tissue, including ischemia, ablation-induced damage, or scar formation. Yet today there are no percutaneous devices that can detect autofluorescence signals from inside a beating heart. Our aim was to develop a prototype catheter to demonstrate the feasibility of doing so.

METHODS AND RESULTS

Here we summarize technical solutions leading to the development of a percutaneous catheter capable of multispectral imaging of intracardiac surfaces. The process included several iterations of light sources, optical filtering, and image acquisition techniques. The developed system included a compliant balloon, 355 nm laser irradiance, a high-sensitivity CCD, bandpass filtering, and image acquisition synchronized with the cardiac cycle. It enabled us to capture autofluorescence images from multiple spectral bands within the visible range while illuminating the endocardial surface with ultraviolet light. Principal component analysis and other spectral unmixing post-processing algorithms were then used to reveal target tissue.

CONCLUSION

Based on the success of our prototype system, we are confident that the development of ever more sensitive cameras, recent advances in tunable filters, fiber bundles, and other optical and computational components makes it possible to create percutaneous catheters capable of acquiring hyper or multispectral hypercubes, including those based on autofluorescence, in real-time. This opens the door for widespread use of this methodology for high-resolution intraoperative imaging of internal tissues and organs-including cardiovascular applications.

Autofluorescence properties of balloon polymers used in medical applications

SIGNIFICANCE

For use in medical balloons and related clinical applications, polymers are usually designed for transparency under illumination with white-light sources. However, when illuminated with ultraviolet (UV) or blue light, most of these materials autofluoresce in the visible range, which can be a concern for modalities that rely on tissue autofluorescence for diagnostic or therapeutic purposes.

AIM

A search for published information on spectral properties of polymers that can be used for medical balloon manufacturing revealed a scarcity of published information on this subject. The aim of these studies was to address this gap.

APPROACH

The autofluorescence properties of polymers used in medical balloon manufacturing were examined for their suitability for hyperspectral imaging and related applications. Excitation-emission matrices of different balloon materials were acquired within the 320- to 620-nm spectral range. In parallel, autofluorescence profiles from the 420- to 620-nm range were extracted from hyperspectral datasets of the same samples illuminated with UV light. The list of tested polymers included polyurethanes, nylon, polyethylene terephthalate (PET), polyether block amide (PEBAX), vulcanized silicone, thermoplastic elastomers with and without talc, and cyclic olefin copolymers, known by their trade name TOPAS.

RESULTS

Each type of polymer exhibited a specific pattern of autofluorescence. Polyurethanes, PET, and thermoplastic elastomers containing talc had the highest autofluorescence values, while sheets made of nylon, PEBAX, and TOPAS exhibited negligible autofluorescence. Hyperspectral imaging was used to illustrate how the choice of specific balloon material can impact the ability of principal component analysis to reveal the ablated cardiac tissue.

CONCLUSIONS

The data revealed significant differences between autofluorescence profiles of the polymers and pointed to the most promising balloon materials for clinical implementation of approaches that depend on tissue autofluorescence.

Key factors behind autofluorescence changes caused by ablation of cardiac tissue

Radiofrequency ablation is a commonly used clinical procedure that destroys arrhythmogenic sources in patients suffering from atrial fibrillation and other types of cardiac arrhythmias. To improve the success of this procedure, new approaches for real-time visualization of ablation sites are being developed. One of these promising methods is hyperspectral imaging, an approach that detects lesions based on changes in the endogenous tissue autofluorescence profile. To facilitate the clinical implementation of this approach, we examined the key variables that can influence ablation-induced spectral changes, including the drop in myocardial NADH levels, the release of lipofuscin-like pigments, and the increase in diffuse reflectance of the cardiac muscle beneath the endocardial layer. Insights from these experiments suggested simpler algorithms that can be used to acquire and post-process the spectral information required to reveal the lesion sites. Our study is relevant to a growing number of multilayered clinical targets to which spectral approaches are being applied.

Real-time photoacoustic assessment of radiofrequency ablation lesion formation in the left atrium

In interventional electrophysiology, catheter-based radiofrequency (RF) ablation procedures restore cardiac heart rhythm by interrupting aberrant conduction paths. Real-time feedback on lesion formation and post-treatment lesion assessment could overcome procedural challenges related to ablation of underlying structures and lesion gaps. This study aims to evaluate real-time visualization of lesion progression and continuity during intra-atrial ablation with photoacoustic (PA) imaging, using clinically deployable technology. A PA-enabled RF ablation catheter was used to ablate and illuminate porcine left atrium, both excised and intact in a passive beating heart ex-vivo, for photoacoustic signal generation. PA signals were received with an intracardiac echography catheter. Using the ratio of PA images acquired with excitation wavelengths of 790 nm and 930 nm, ablation lesions were successfully imaged through circulating saline and/or blood, and lesion gaps were identified in real-time. PA-based assessment of RF-ablation lesions was successful in a realistic preclinical model of atrial intervention.

Hyperspectral imaging for thermal effect monitoring in in vivo liver during laser ablation

Thermal ablation is a minimally invasive technique used to induce a controlled necrosis of malignant cells by increasing the temperature in localized areas. This procedure needs an accurate and real-time monitoring of thermal effects to evaluate and control treatment outcome. In this work, a hyperspectral imaging (HSI) technique is proposed as a new and non-invasive method to monitor ablative therapy. HSI provides images of the target object in several spectral bands, hence the reflectance/absorbance spectrum for each pixel. This paper presents a preliminary and original HSI-based analysis of the thermal state in the in vivo porcine liver undergoing laser ablation. In order to compare the spectral response between treated and untreated areas of the organ, proper Regions of Interest (ROIs) were chosen on the hyperspectral images; for each ROI, the absorbance variation for the selected wavelengths (i.e., 630, 760, and 960nm, for deoxyhemoglobin, methemoglobin, and water respectively) was assessed. Results obtained during and after laser ablation show that the absorbance of the methemoglobin peaks increases up to 40% in the burned region with respect to the non-ablated one. Conversely, the relative change of deoxyhemoglobin and water peaks is less marked. Based on these results, absorbance threshold values were retrieved and used to visualize the ablation zone on the images. This preliminary analysis suggests that a combination of the absorbance information is essential to achieve a more accurate identification of the ablation region. The results encourage further studies on the correlation between thermal effects and the spectral response of biological tissues undergoing thermal ablation, for final clinical use.

Towards real-time multispectral endoscopic imaging for cardiac lesion quality assessment

Atrial fibrillation (Afib) can lead to life threatening conditions such as heart failure and stroke. During Afib treatment, clinicians aim to repress unusual electrical activity by electrically isolating the pulmonary veins (PV) from the left atrium (LA) using radiofrequency ablation. However, current clinical tools are limited in reliably assessing transmurality of the ablation lesions and detecting the presence of gaps within ablation lines, which can warrant repeat procedures. In this study, we developed an endoscopic multispectral reflectance imaging (eMSI) system for enhanced discrimination of tissue treatment at the PV junction. The system enables direct visualization of cardiac lesions through an endoscope at acquisition rates up to 25 Hz. Five narrowband, high-power LEDs were used to illuminate the sample (450, 530, 625, 810 and 940nm) and combinatory parameters were calculated based on their relative reflectance. A stitching algorithm was employed to generate large field-of-view, multispectral mosaics of the ablated PV junction from individual eMSI images. A total of 79 lesions from 15 swine hearts were imaged, ex vivo. Statistical analysis of the acquired five spectral data sets and ratiometric maps revealed significant differences between transmural lesions, non-transmural lesions around the venoatrial junctions, unablated posterior wall of left atrium tissue, and pulmonary vein (p < 0.0001). A pixel-based quadratic discriminant analysis classifier was applied to distinguish four tissue types: PV, untreated LA, non-transmural and transmural lesions. We demonstrate tissue type classification accuracies of 80.2% and 92.1% for non-transmural and transmural lesions, and 95.0% and 92.8% for PV and untreated LA sites, respectively. These findings showcase the potential of eMSI for lesion validation and may help to improve AFib treatment efficacy.

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.

Balloon catheter-based radiofrequency ablation monitoring in porcine esophagus using optical coherence tomography

We present a microscopic image guidance platform for radiofrequency ablation (RFA) using a clinical balloon-catheter-based optical coherence tomography (OCT) system, currently used in the surveillance of Barrett's esophagus patients. Our integrated thermal therapy delivery and monitoring platform consists of a flexible, customized bipolar RFA electrode array designed for use with a clinical balloon OCT catheter and a processing algorithm to accurately map the thermal coagulation process. Non-uniform rotation distortion was corrected using a feature tracking-based technique, which enables robust, frame-to-frame analysis of the temporal fluctuation of the complex OCT signal. With proper noise calibration, precise delineation of the thermal therapy zone was demonstrated using cumulative complex differential variance in porcine esophagus ex vivo with the integrated OCT-RFA system, as validated by nitroblue tetrazolium chloride (NBTC) histology. The ability to directly and accurately visualize the thermal coagulation process at high resolution is critical to the precise delivery of thermal energy to a wide range of epithelial lesions.

Application of unsupervised learning to hyperspectral imaging of cardiac ablation lesions

Atrial fibrillation is the most common cardiac arrhythmia. It is being effectively treated using the radiofrequency ablation (RFA) procedure, which destroys culprit tissue and creates scars that prevent the spread of abnormal electrical activity. Long-term success of RFA could be improved further if ablation lesions can be directly visualized during the surgery. We have shown that autofluorescence-based hyperspectral imaging (aHSI) can help to identify lesions based on spectral unmixing. We show that use of k -means clustering, an unsupervised learning method, is capable of detecting RFA lesions without a priori knowledge of the lesions' spectral characteristics. We also show that the number of spectral bands required for successful lesion identification can be significantly reduced, enabling the use of increased spectral bandwidth. Together, these findings can help with clinical implementation of a percutaneous aHSI catheter, since by reducing the number of spectral bands one can reduce hypercube acquisition and processing times, and by increasing the spectral width of individual bands one can collect more photons. The latter is of critical importance in low-light applications such as intracardiac aHSI. The ultimate goal of our studies is to help improve clinical outcomes for atrial fibrillation patients.

Optimization of wavelength selection for multispectral image acquisition: a case study of atrial ablation lesions

In vivo autofluorescence hyperspectral imaging of moving objects can be challenging due to motion artifacts and to the limited amount of acquired photons. To address both limitations, we selectively reduced the number of spectral bands while maintaining accurate target identification. Several downsampling approaches were applied to data obtained from the atrial tissue of adult pigs with sites of radiofrequency ablation lesions. Standard image qualifiers such as the mean square error, the peak signal-to-noise ratio, the structural similarity index map, and an accuracy index of lesion component images were used to quantify the effects of spectral binning, an increased spectral distance between individual bands, as well as random combinations of spectral bands. Results point to several quantitative strategies for deriving combinations of a small number of spectral bands that can successfully detect target tissue. Insights from our studies can be applied to a wide range of applications.

Spectroscopic photoacoustic imaging of radiofrequency ablation in the left atrium

Catheter-based radiofrequency ablation for atrial fibrillation has long-term success in 60-70% of cases. A better assessment of lesion quality, depth, and continuity could improve the procedure's outcome. We investigate here photoacoustic contrast between ablated and healthy atrial-wall tissue in vitro in wavelengths spanning from 410 nm to 1000 nm. We studied single- and multi-wavelength imaging of ablation lesions and we demonstrate that a two-wavelength technique yields precise detection of lesions, achieving a diagnostic accuracy of 97%. We compare this with a best single-wavelength (640 nm) analysis that correctly identifies 82% of lesions. We discuss the origin of relevant spectroscopic features and perspectives for translation to clinical imaging.

Hyperspectral imaging for label-free in vivo identification of myocardial scars and sites of radiofrequency ablation lesions

BACKGROUND

Treatment of cardiac arrhythmias often involves ablating viable muscle tissue within or near islands of scarred myocardium. Yet, today there are limited means by which the boundaries of such scars can be visualized during surgery and distinguished from the sites of acute injury caused by radiofrequency (RF) ablation.

OBJECTIVE

We sought to explore a hyperspectral imaging (HSI) methodology to delineate and distinguish scar tissue from tissue injury caused by RF ablation.

METHODS

RF ablation of the ventricular surface of live rats that underwent thoracotomy was followed by a 2-month animal recovery period. During a second surgery, new RF lesions were placed next to the scarred tissue from the previous ablation procedure. The myocardial infarction model was used as an alternative way to create scar tissue.

RESULTS

Excitation-emission matrices acquired from the sites of RF lesions, scar region, and the surrounding unablated tissue revealed multiple spectral changes. These findings justified HSI of the heart surface using illumination with 365 nm UV light while acquiring spectral images within the visible range. Autofluorescence-based HSI enabled to distinguish sites of RF lesions from scar or unablated myocardium in open-chest rats. A pilot version of a percutaneous HSI catheter was used to demonstrate the feasibility of RF lesion visualization in atrial tissue of live pigs.

CONCLUSION

HSI based on changes in tissue autofluorescence is a highly effective tool for revealing-in vivo and with high spatial resolution-surface boundaries of myocardial scar and discriminating it from areas of acute necrosis caused by RF ablation.

Catheter Ablation of Atrial Fibrillation: A Review of the Current Status and Future Directions

Atrial fibrillation (AF) is one of the most common arrhythmias encountered in clinical practice today. Over the last 20 years, the frequency of use of catheter ablation to treat AF has grown, commensurate with the rise in arrhythmia burden and via a number of technical advancements. These developments can be divided into new techniques for myocardial ablation, improvements in the understanding of AF trigger mechanisms, and advancements in atrial mapping. Progress in these fields has led to a fundamental change in daily practice, and has contributed to a rise, for ablation, from a procedure performed infrequently at select centers to one that is commonplace worldwide. In this article, the data and methods leading to this fundamental change will be presented and discussed.

Anatomical and Optical Properties of Atrial Tissue: Search for a Suitable Animal Model

The purpose of this study was to evaluate structural and optical properties of atrial tissue from common animal models and to compare it with human atria. We aimed to do this in a format that will be useful for development of better ablation tools and/or new means for visualizing atrial lesions. Human atrial tissue from clinically relevant age group was compared and contrasted with atrial tissue of large animal models commonly available for research purposes. These included pigs, sheep, dogs and cows. The presented data include area measurements of smooth atrial surface available for ablation and estimates of thickness of collagen and muscle for five different species. We also described methods to quantify presence of collagen and overall thickness of atrial wall. Provided information enables placement of atrial lesions to locations with clinically relevant atrial wall thickness and macroscopic structure ultimately helping investigators to develop better ablation and imaging tools. It also highlights the impact of collagen thickness on optical measurements and lesion visualization.

Seeing the Invisible: Revealing Atrial Ablation Lesions Using Hyperspectral Imaging Approach

Background

Currently, there are limited means for high-resolution monitoring of tissue injury during radiofrequency ablation procedures.

Objective

To develop the next generation of visualization catheters that can reveal irreversible atrial muscle damage caused by ablation and identify viability gaps between the lesions.

Methods

Radiofrequency lesions were placed on the endocardial surfaces of excised human and bovine atria and left ventricles of blood perfused rat hearts. Tissue was illuminated with 365nm light and a series of images were acquired from individual spectral bands within 420-720nm range. By extracting spectral profiles of individual pixels and spectral unmixing, the relative contribution of ablated and unablated spectra to each pixel was then displayed. Results of spectral unmixing were compared to lesion pathology.

Results

RF ablation caused significant changes in the tissue autofluorescence profile. The magnitude of these spectral changes in human left atrium was relatively small (< 10% of peak fluorescence value), yet highly significant. Spectral unmixing of hyperspectral datasets enabled high spatial resolution, in-situ delineation of radiofrequency lesion boundaries without the need for exogenous markers. Lesion dimensions derived from hyperspectral imaging approach strongly correlated with histological outcomes. Presence of blood within the myocardium decreased the amplitude of the autofluorescence spectra while having minimal effect on their overall shapes. As a result, the ability of hyperspectral imaging to delineate ablation lesions in vivo was not affected.

Conclusions

Hyperspectral imaging greatly increases the contrast between ablated and unablated tissue enabling visualization of viability gaps at clinically relevant locations. Data supports the possibility for developing percutaneous hyperspectral catheters for high-resolution ablation guidance.