Factors influencing lesion formation during radiofrequency catheter ablation

In radiofrequency (RF) ablation, the heating of cardiac tissue is mainly resistive. RF current heats cardiac tissue and in turn the catheter electrode is being heated. Consequently, the catheter tip temperature is always lower--or ideally equal--than the superficial tissue temperature. The lesion size is influenced by many parameters such as delivered RF power, electrode length, electrode orientation, blood flow and tissue contact. This review describes the influence of these different parameters on lesion formation and provides recommendations for different catheter types on selectable parameters such as target temperatures, power limits and RF durations.     

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.      

Noninvasive multimodal imaging by integrating optical coherence tomography with autofluorescence imaging for dental applications

We report the development of an integrated multifunctional imaging system capable of providing anatomical (optical coherence tomography, OCT), functional (OCT angiography, OCTA) and molecular imaging (light‐induced autofluorescence, LIAF) for in vivo dental applications. Blue excitation light (405 nm) was used for LIAF imaging, while the OCT was powered by a 1310 nm swept laser source. A red‐green‐blue digital camera, with a 450 nm cut‐on broadband optical filter, was used for LIAF detection. The exciting light source and camera were integrated directly with the OCT scanning probe. The integrated system used two noninvasive imaging modalities to improve the speed of in vivo OCT data collection and to better target the regions of interest. The newly designed system maintained the ability to detect differences between healthy and hypomineralized teeth, identify dental biofilm and visualize the microvasculature of gingival tissue. The development of the integrated OCT‐LIAF system provides an opportunity to conduct clinical studies more efficiently, examining changes in oral conditions over time.     

Toward optical spectroscopy-guided lung biopsy: Demonstration of tissue-type classification

The diagnostic yield of standard tissue-sampling modalities of suspected lung cancers, whether by bronchoscopy or interventional radiology, can be nonoptimal, varying with the size and location of lesions. What is needed is an insitu sensor, integrated in the biopsy tool, to objectively distinguish among tissue types in real time, not to replace biopsy with an optical diagnostic, but to verify that the sampling tool is properly located within the target lesion. We investigated the feasibility of elastic scattering spectroscopy (ESS), coupled with machine learning, to distinguish lung lesions from the various nearby tissue types, in a study with freshly-excised lung tissues from surgical resections. Optical spectra were recorded with an ESS fiberoptic probe in different areas of the resected pulmonary tissues, including benign-margin tissue sites as well as the periphery and core of the lesion. An artificial-intelligence model was used to analyze, retrospectively, 2032 measurements from excised tissues of 35 patients. With high accuracy, ESS was able to distinguish alveolar tissue from bronchi, alveolar tissue from lesions, and bronchi from lesions. This ex vivo study indicates promise for ESS fiberoptic probes to be integrated with surgical intervention tools, to improve reliability of pulmonary lesion targeting.     

Preclinical mouse model of optical coherence tomography for subcortical brain imaging without dissection

The purpose of this study was to investigate the feasibility of using optical coherence tomography (OCT) to identify internal brain lesions, specifically intracerebral hemorrhage, without dissection. Mice with artificially injected brain hematomas were used to test the OCT system, and the recorded images were compared with microscopic images of the same mouse brains after hematoxylin and eosin staining. The intracranial structures surrounding the hematomas were clearly visualized by the OCT system without dissection. These images reflect the ability of OCT to determine the extent of a lesion in several planes. OCT is a useful technology, and these findings could be used as a starting point for future research in intraoperative imaging.     

Detecting mouse squamous cell carcinoma from submicron full-field optical coherence tomography images by deep learning

The standard medical practice for cancer diagnosis requires histopathology, which is an invasive and time-consuming procedure. Optical coherence tomography (OCT) is an alternative that is relatively fast, noninvasive, and able to capture three-dimensional structures of epithelial tissue. Unlike most previous OCT systems, which cannot capture crucial cellular-level information for squamous cell carcinoma (SCC) diagnosis, the full-field OCT (FF-OCT) technology used in this paper is able to produce images at sub-micron resolution and thereby facilitates the development of a deep learning algorithm for SCC detection. Experimental results show that the SCC detection algorithm can achieve a classification accuracy of 80% for mouse skin. Using the sub-micron FF-OCT imaging system, the proposed SCC detection algorithm has the potential for in-vivo applications.     

Investigation of the influence of blood flow rate on large vessel cooling in hepatic radiofrequency ablation.

Radiofrequency (RF) ablation using high-frequency current has become an important treatment method for patients with non-resectable liver tumors. Tumor recurrence is associated with tissue cooling in the proximity of large blood vessels. This study investigated the influence of blood flow rate on tissue temperature and lesion size during monopolar RF ablation at a distance of 10 mm from single 4- and 6-mm vessels using two different approaches: 1) an ex vivo blood perfusion circuit including an artificial vessel inserted into porcine liver tissue was developed; and 2) a finite element method (FEM) model was created using a novel simplified modeling technique for large blood vessels. Blood temperatures at the inflow/outflow of the vessel and tissue temperatures at 10 and 20 mm from the electrode tip were measured in the ex vivo set-up. Tissue temperature, blood temperature and lesion size were analyzed under physiological, increased and reduced blood-flow conditions. The results show that changes in blood flow rate in large vessels do not significantly affect tissue temperature and lesion size far away from the vessel. Monopolar ablation could not produce lesions surrounding the vessel due to the strong heat-sink effect. Simulated tissue temperatures correlated well with ex vivo measurements, supporting the FEM model.     

An automatic diagnostic system of coronary artery lesions in Kawasaki disease using intravascular optical coherence tomography imaging

Intravascular optical coherence tomography (IV‐OCT) is a light‐based imaging modality with high resolution, which employs near‐infrared light to provide tomographic intracoronary images. Morbidity caused by coronary heart disease is a substantial cause of acute coronary syndrome and sudden cardiac death. The most common intracoronay complications caused by coronary artery disease are intimal hyperplasia, calcification, fibrosis, neovascularization and macrophage accumulation, which require efficient prevention strategies. OCT can provide discriminative information of the intracoronary tissues, which can be used to train a robust fully automatic tissue characterization model based on deep learning. In this study, we aimed to design a diagnostic model of coronary artery lesions. Particularly, we trained a random forest using convolutional neural network features to distinguish between normal and diseased arterial wall structure. Then, based on the arterial wall structure, fully convolutional network is designed to extract the tissue layers in normal cases, and pathological tissues regardless of lesion type in pathological cases. Then, the type of the lesions can be characterized with high precision using our previous model. The results demonstrate the robustness of the model with the approximate overall accuracy up to 90%.      

External irrigation of a non-irrigated ablation catheter for effective AV node ablation during conduction system pacing

Ablation using non-irrigated catheter can lead to rapid rise in temperature of electrode tissue interface from tissue desiccation, steam and coagulum formation and this may limit power delivery and lesion size. We present a novel technique of external irrigation through the long sheath while using a non-irrigated ablation catheter during AV Node ablation and conduction system pacing. By bringing the long sheath closer to the tip of non-irrigated catheter and injecting cold normal saline allows cooling of electrode tissue interface leading to increase in power delivery resulting in a deeper lesion.     

Automatic termination of radiofrequency energy upon catheter dislocation.

Since 1987 radiofrequency (RF) catheter ablation has proven to be an effective treatment for many cardiac arrhythmias. However, catheter dislocation during RF delivery may result in an unintentional heating of healthy non-arrhythmogenic tissue. Therefore, a device was developed (15 cm x 9 cm x 3 cm) consisting of a microprocessor, powered by a 9 V battery and to be connected between the indifferent cable of the RF generator and the patient's back electrode that continuously reads the electrode position information using a 3 dimensional electrode visualization system (LocaLisa). A red light indicates a sudden change in electrode position and an electronic switch is activated by the software to interrupt the connection between the indifferent electrode and the RF generator resulting in a high impedance shutdown and termination of RF energy delivery. Four different sensitivity settings (10 is most and 100 is least sensitive) can be selected and were tested in an in vitro tank setup during electrode dragging speeds of 0.5 to 20 cm/sec. For the sensitivity levels 10, 20, 50 and 100, an immediate termination of RF (Atakr II, Medtronic, 25 W) was demonstrated for an electrode dragging speed of greater or equal than 1, 2, 5 and 10 cm/sec, respectively. We conclude that the developed device may improve safety during ablation procedures of cardiac arrhythmias.     

Use of 2D images of depth and integrated reflectivity to represent the severity of demineralization in cross‐polarization optical coherence tomography

Several studies have demonstrated the potential of cross‐polarization optical coherence tomography (CP‐OCT) to quantify the severity of early caries lesions (tooth decay) on tooth surfaces. The purpose of this study is to show that 2D images of the lesion depth and the integrated reflectivity can be used to accurately represent the severity of early lesions. Simulated early lesions of varying severity were produced on tooth samples using simulated lesion models. Methods were developed to convert the 3D CP‐OCT images of the samples to 2D images of the lesion depth and lesion integrated reflectivity. Calculated lesion depths from OCT were compared with lesion depths measured from histological sections examined using polarized light microscopy. The 2D images of the lesion depth and integrated reflectivity are well suited for visualization of early demineralization. (© 2013 WILEY‐VCH Verlag GmbH &Co. KGaA, Weinheim)     

Mechanical compliance of the endocardium

Radio-frequency (RF) ablation is an accepted treatment for cardiac arrhythmias related to abnormal focal cardiac substrate. The penetration depth of the electrode into the endocardium affects lesion size, a critical determinant of success of RF ablation. We measured the relation between the mechanical compliance and the penetration depth of RF ablation catheter electrode at frequently ablated areas of the endocardium and examined the influence of time after death on mechanical properties of the tissue. We measured force versus time for eight insertion depths of the catheter electrode into full-thickness endocardial samples derived from the mitral valve annulus, the left ventricular free wall and the tricuspid valve annulus. We varied the time after death at 15, 40 min, 3, 8, and 18 h and repeated our measurements. At 15 min after death, the first 0.5 mm penetration depth caused the fastest relaxation at 55 s. Force decay decreased dramatically at 15 min after death as the penetration depth increased from 0.5 to 4 mm. We used the force data sampled at 60 s after insertion to approximate the elasticity. We observed the relations between the force versus the insertion depth. The force increased by a factor of 5 for the mitral valve annulus and 8 for the left free wall from 15 min to 18 h. We derived coefficients of a second-order polynomial equation relating the force data to insertion depth with R²>0.99.     

Determination of lesion size by ultrasound during radiofrequency catheter ablation.

The catheter tip temperature that is used to control the radiofrequency generator output poorly correlates to lesion size. We, therefore, evaluated lesions created in vitro using a B-mode ultrasound imaging device as a potential means to assess lesion generation during RF applications non-invasively. Porcine ventricular tissue was immersed in saline solution at 37 degrees C. The catheter was fixed in a holder and positioned in a parallel orientation to the tissue with an array transducer (7.5 MHz) app. 3 cm above the tissue. Lesions were produced either in a temperature controlled mode with a 4-mm tip catheter with different target temperatures (50, 60, 70 and 80 degrees C, 80 W maximum output) or in a power controlled mode (25, 50 and 75 W, 20 ml/min irrigation flow) using an irrigated tip catheter. Different contact forces (0.5 N, 1.0 N) were tested, and RF was delivered for 60 s. A total of 138 lesions was produced. Out of these, 128 could be identified on the ultrasound image. The lesion depth and volume was on average 4.1 +/- 1.6 mm and 52 +/- 53 mm3 as determined by ultrasound and 3.9 +/- 1.7 mm and 52 +/- 55 mm3 as measured thereafter, respectively. A linear correlation between the lesion size determined by ultrasound and that measured thereafter was demonstrated with a correlation coefficient of r = 0.87 for lesion depth and r = 0.93 for lesion volume. We conclude that lesions can be assessed by B-mode ultrasound imaging.     

Three‐dimensional mapping of the attenuation coefficient in optical coherence tomography to enhance breast tissue microarchitecture contrast

Effective intraoperative tumor margin assessment is needed to reduce re‐excision rates in breast‐conserving surgery (BCS). Mapping the attenuation coefficient in optical coherence tomography (OCT) throughout a sample to create an image (attenuation imaging) is one promising approach. For the first time, three‐dimensional OCT attenuation imaging of human breast tissue microarchitecture using a wide‐field (up to ~45 × 45 × 3.5 mm) imaging system is demonstrated. Representative results from three mastectomy and one BCS specimen (from 31 specimens) are presented with co‐registered postoperative histology. Attenuation imaging is shown to provide substantially improved contrast over OCT, delineating nuanced features within tumors (including necrosis and variations in tumor cell density and growth patterns) and benign features (such as sclerosing adenosis). Additionally, quantitative micro‐elastography (QME) images presented alongside OCT and attenuation images show that these techniques provide complementary contrast, suggesting that multimodal imaging could increase tissue identification accuracy and potentially improve tumor margin assessment.     

Joint time-frequency analysis of visible laser reflections in a sheep heart

Limited methods exist to confirm the position of cardiovascular devices in the superior vena cava or right atrium of the heart. The aim of this study was to design, test and validate the feasibility of whether an optical fiber-based instrument could accurately distinguish when a cardiovascular catheter was located in the superior vena cava vs in the right atrium. An optical fiber was placed in a cardiovascular catheter which was inserted into a living sheep and guided to the vicinity of the heart where diode laser-based reflection intensity data were simultaneously gathered from two visible wavelengths of light reflected from the venous and atrial tissue surfaces near the cavoatrial junction. The time series data were postoperatively analyzed using methods of joint time-frequency analysis and validated against catheter positions determined with fluoroscopy and ECG. The system was successful in distinguishing the location of the superior vena cava from the right atrium.     

A novel automatic 3D stitching algorithm for optical coherence tomography angiography and its application in dermatology

Optical coherence tomography (OCT) and OCT angiography (OCTA) techniques offer numerous advantages in clinical skin applications but the field of view (FOV) of current commercial systems are relatively limited to cover the entire skin lesion. The typical method to expand the FOV is to apply wide field objective lens. However, lateral resolution is often sacrificed when scanning with these lenses. To overcome this drawback, we developed an automated 3D stitching method for creating high-resolution skin structure and vascular volumes with large field of view, which was realized by montaging multiple adjacent OCT and OCTA volumes. The proposed stitching method is demonstrated by montaging 3 × 3 OCT and OCTA volumes (nine OCT/OCTA volumes as one data set with each volume covers 2.5 cm × 2.5 cm area) of healthy thin and thick skin from six volunteers. The proposed stitching protocol achieves high flexibility and repeatable for all the participants. Moreover, according to evaluation of structural similarity index and feature similarity index, our proposed stitched result has a superior similarity to single scanning protocol in large-scaled. We had also verified its improved performance through assessing metrics of vessel contrast-noise-ratio (CNR) from 2.07 ± 0.44 (single large-scaled scanning protocol) to 3.05 ± 0.51 (proposed 3 × 3 sub-volume stitching method).     

Imaging sebaceous gland using optical coherence tomography with deep learning assisted automatic identification

Imaging sebaceous glands and evaluating morphometric parameters are important for diagnosis and treatment of serum problems. In this article, we investigate the feasibility of high-resolution optical coherence tomography (OCT) in combination with deep learning assisted automatic identification for these purposes. Specifically, with a spatial resolution of 2.3 μm × 6.2 μm (axial × lateral, in air), OCT is capable of clearly differentiating sebaceous gland from other skin structures and resolving the sebocyte layer. In order to achieve efficient and timely imaging analysis, a deep learning approach built upon ResNet18 is developed to automatically classify OCT images (with/without sebaceous gland), with a classification accuracy of 97.9%. Based on the result of automatic identification, we further demonstrate the possibility to measure gland size, sebocyte layer thickness and gland density.     

The use of optical coherence tomography and convolutional neural networks to distinguish normal and abnormal oral mucosa

Incomplete surgical resection of head and neck squamous cell carcinoma (HNSCC) is the most common cause of local HNSCC recurrence. Currently, surgeons rely on preoperative imaging, direct visualization, palpation and frozen section to determine the extent of tissue resection. It has been demonstrated that optical coherence tomography (OCT), a minimally invasive, nonionizing near infrared mesoscopic imaging modality can resolve subsurface differences between normal and abnormal head and neck mucosa. Previous work has utilized two‐dimensional OCT imaging which is limited to the evaluation of small regions of interest generated frame by frame. OCT technology is capable of performing rapid volumetric imaging, but the capacity and expertise to analyze this massive amount of image data is lacking. In this study, we evaluate the ability of a retrained convolutional neural network to classify three‐dimensional OCT images of head and neck mucosa to differentiate normal and abnormal tissues with sensitivity and specificity of 100% and 70%, respectively. This method has the potential to serve as a real‐time analytic tool in the assessment of surgical margins.     

Delineating papillary dermis around basal cell carcinomas by high and ultrahigh resolution optical coherence tomography—A pilot study

Bedside diagnosis of skin cancer remains a challenging task. The real-time noninvasive technology of optical coherence tomography (OCT) masters a high diagnostic accuracy in basal cell carcinoma (BCC) but a lower specificity in recognizing imitators and other carcinomas. We investigate the delicate signal of papillary dermis using an in-house developed ultrahigh resolution OCT (UHR-OCT) system with shadow compensation and a commercial multi-focus high resolution OCT (HR-OCT) system for clinical BCC imaging. We find that the HR-OCT system struggled to resolve the dark band signal of papillary dermis where the UHR-OCT located this in all cases and detected changes in signal width. UHR-OCT is able to monitor extension and position of papillary dermis suggesting a novel feature for delineating superficial BCCs in pursuit of a fast accurate diagnosis. Comprehensive studies involving more patients are imperative in order to corroborate results.     

Diffuse reflectance spectroscopy as a monitoring tool for gastric mucosal devitalization treatments with argon plasma coagulation

Electrosurgery with argon plasma coagulation is a widespread technique used in various medical fields for applications which range from hemostasis to devitalization processes. Developing tools which provide feedback concerning tissue condition during these surgeries is fundamental for improving the safety and success of this treatment. We present here a method based on diffuse reflectance spectroscopy to monitor gastric mucosal devitalization treatments. The analysis of the diffusely reflected spectra of the tissue allows us to differentiate between ablation states by using linear discriminant analysis (LDA) as a classification algorithm. An ex vivo pilot study on several swine stomachs showed promising results, with 97.8% of correctly classified ablation states on a new unseen stomach, encouraging further tests with human tissue.