Automated prediction of isthmus areas in scar-related atrial tachycardias using artificial intelligence

INTRODUCTION

Ablation of scar-related reentrant atrial tachycardia (SRRAT) involves identification and ablation of a critical isthmus. A graph convolutional network (GCN) is a machine learning structure that is well-suited to analyze the irregularly-structured data obtained in mapping procedures and may be used to identify potential isthmuses.

METHODS

Electroanatomic maps from 29 SRRATs were collected, and custom electrogram features assessing key tissue and wavefront properties were calculated for each point. Isthmuses were labeled off-line. Training data was used to determine the optimal GCN parameters and train the final model. Putative isthmus points were predicted in the training and test populations and grouped into proposed isthmus areas based on density and distance thresholds. The primary outcome was the distance between the centroids of the true and closest proposed isthmus areas.

RESULTS

A total of 193 821 points were collected. Thirty isthmuses were detected in 29 tachycardias among 25 patients (median age 65.0, 5 women). The median (IQR) distance between true and the closest proposed isthmus area centroids was 8.2 (3.5, 14.4) mm in the training and 7.3 (2.8, 16.1) mm in the test group. The mean overlap in areas, measured by the Dice coefficient, was 11.5 ± 3.2% in the training group and 13.9 ± 4.6% in the test group.

CONCLUSION

A GCN can be trained to identify isthmus areas in SRRATs and may help identify critical ablation targets.

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.

Compressed sensing on displacement signals measured with optical coherence tomography

Optical coherence tomography (OCT) is capable of angstrom-scale vibrometry of particular interest to researchers of auditory mechanics. We develop a method for compressed sensing vibrometry using OCT that significantly reduces acquisition time for dense motion maps. Our method, based on total generalized variation with uniform subsampling, can reduce the number of samples needed to measure motion maps by a factor of ten with less than 5% normalized mean square error when tested on a diverse set of in vivo measurements from the gerbil cochlea. This opens up the possibility for more complex in vivo experiments for cochlear mechanics.

Compressed sensing of human breast optical coherence 3-D image volume data using predictive coding

There are clinical needs for optical coherence tomography (OCT) of large areas within a short period of time, such as imaging resected breast tissue for the evaluation of cancer. We report on the use of denoising predictive coding (DN-PC), a novel compressed sensing (CS) algorithm for reconstruction of OCT volumes of human normal breast and breast cancer tissue. The DN-PC algorithm has been rewritten to allow for computational parallelization and efficient memory transfer, resulting in a net reduction of computation time by a factor of 20. We compress image volumes at decreasing A-line sampling rates to evaluate a relation between reconstruction behavior and image features of breast tissue.

Automated analysis framework for in vivo cardiac ablation therapy monitoring with optical coherence tomography

Radiofrequency ablation (RFA) is a minimally invasive procedure that is commonly used for the treatment of atrial fibrillation. However, it is associated with a significant risk of arrhythmia recurrence and complications owing to the lack of direct visualization of cardiac substrates and real-time feedback on ablation lesion transmurality. Within this manuscript, we present an automated deep learning framework for in vivo intracardiac optical coherence tomography (OCT) analysis of swine left atria. Our model can accurately identify cardiac substrates, monitor catheter-tissue contact stability, and assess lesion transmurality on both OCT intensity and polarization-sensitive OCT data. To the best of our knowledge, we have developed the first automatic framework for in vivo cardiac OCT analysis, which holds promise for real-time monitoring and guidance of cardiac RFA therapy..

Optical coherence tomography holds promise to transform the diagnostic anatomic pathology gross evaluation process

SIGNIFICANCE

Real-time histology can close a variety of gaps in tissue diagnostics. Currently, gross pathology analysis of excised tissue is dependent upon visual inspection and palpation to identify regions of interest for histopathological processing. Such analysis is limited by the variable correlation between macroscopic and microscopic findings. The current standard of care is costly, burdensome, and inefficient.

AIM

We are the first to address this gap by introducing optical coherence tomography (OCT) to be integrated in real-time during the pathology grossing process.

APPROACH

This is achieved by our high-resolution, ultrahigh-speed, large field-of-view OCT device designed for this clinical application.

RESULTS

We demonstrate the feasibility of imaging tissue sections from multiple human organs (breast, prostate, lung, and pancreas) in a clinical gross pathology setting without interrupting standard workflows.

CONCLUSIONS

OCT-based real-time histology evaluation holds promise for addressing a gap that has been present for >100 years.

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.

Millimeter-scale chip-based supercontinuum generation for optical coherence tomography

Supercontinuum sources for optical coherence tomography (OCT) have raised great interest as they provide broad bandwidth to enable high resolution and high power to improve imaging sensitivity. Commercial fiber-based supercontinuum systems require high pump powers to generate broad bandwidth and customized optical filters to shape/attenuate the spectra. They also have limited sensitivity and depth performance. We introduce a supercontinuum platform based on a 1-mm² Si₃N₄ photonic chip for OCT. We directly pump and efficiently generate supercontinuum near 1300 nm without any postfiltering. With a 25-pJ pump pulse, we generate a broadband spectrum with a flat 3-dB bandwidth of 105 nm. Integrating the chip into a spectral domain OCT system, we achieve 105-dB sensitivity and 1.81-mm 6-dB sensitivity roll-off with 300-μW optical power on sample. We image breast tissue to demonstrate strong imaging performance. Our chip will pave the way toward portable OCT and incorporating integrated photonics into optical imaging technologies.

Anisotropic Mechanical Properties of the Human Uterus Measured by Spherical Indentation

The mechanical function of the uterus is critical for a successful pregnancy. During gestation, uterine tissue grows and stretches to many times its size to accommodate the growing fetus, and it is hypothesized the magnitude of uterine tissue stretch triggers the onset of contractions. To establish rigorous mechanical testing protocols for the human uterus in hopes of predicting tissue stretch during pregnancy, this study measures the anisotropic mechanical properties of the human uterus using optical coherence tomography (OCT), instrumented spherical indentation, and video extensometry. In this work, we perform spherical indentation and digital image correlation to obtain the tissue's force and deformation response to a ramp-hold loading regimen. We translate previously reported fiber architecture, measured via optical coherence tomography, into a constitutive fiber composite material model to describe the equilibrium material behavior during indentation. We use an inverse finite element method integrated with a genetic algorithm (GA) to fit the material model to our experimental data. We report the mechanical properties of human uterine specimens taken across different anatomical locations and layers from one non-pregnant (NP) and one pregnant (PG) patient; both patients had pathological uterine tissue. Compared to NP uterine tissue, PG tissue has a more dispersed fiber distribution and equivalent stiffness material parameters. In both PG and NP uterine tissue, the mechanical properties differ significantly between anatomical locations.

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.

Feasibility of near-infrared spectroscopy as a tool for anatomical mapping of the human epicardium

Epicardial ablation is necessary for the treatment of ventricular tachycardias refractory to endocardial ablation due to arrhythmic substrates involving the epicardium. The human epicardium is composed of adipose tissue and coronary vasculature embedded on the surface and within the myocardium, which can complicate electroanatomical mapping, electrogram interpretation and ablation delivery. We propose using near-infrared spectroscopy (NIRS) to decipher adipose tissue from myocardial tissue within human hearts ex vivo. Histological measurement of epicardial adipose thickness direct correlated (R = 0.884) with the adipose contrast index. These results demonstrate the potential of NIRS integrated catheters for mapping the spatial distribution of epicardial substrates and could aid in improving guidance during epicardial ablation interventions.

Fully Automated Postlumpectomy Breast Margin Assessment Utilizing Convolutional Neural Network Based Optical Coherence Tomography Image Classification Method

BACKGROUND

The purpose of this study was to develop a deep learning classification approach to distinguish cancerous from noncancerous regions within optical coherence tomography (OCT) images of breast tissue for potential use in an intraoperative setting for margin assessment.

METHODS

A custom ultrahigh-resolution OCT (UHR-OCT) system with an axial resolution of 2.7 μm and a lateral resolution of 5.5 μm was used in this study. The algorithm used an A-scan-based classification scheme and the convolutional neural network (CNN) was implemented using an 11-layer architecture consisting of serial 3 × 3 convolution kernels. Four tissue types were classified, including adipose, stroma, ductal carcinoma in situ, and invasive ductal carcinoma.

RESULTS

The binary classification of cancer versus noncancer with the proposed CNN achieved 94% accuracy, 96% sensitivity, and 92% specificity. The mean five-fold validation F1 score was highest for invasive ductal carcinoma (mean standard deviation, 0.89 ± 0.09) and adipose (0.79 ± 0.17), followed by stroma (0.74 ± 0.18), and ductal carcinoma in situ (0.65 ± 0.15).

CONCLUSION

It is feasible to use CNN based algorithm to accurately distinguish cancerous regions in OCT images. This fully automated method can overcome limitations of manual interpretation including interobserver variability and speed of interpretation and may enable real-time intraoperative margin assessment.

Anisotropic Material Characterization of Human Cervix Tissue Based on Indentation and Inverse Finite Element Analysis

The cervix is essential to a healthy pregnancy as it must bear the increasing load caused by the growing fetus. Preterm birth is suspected to be caused by the premature softening and mechanical failure of the cervix. The objective of this paper is to measure the anisotropic mechanical properties of human cervical tissue using indentation and video extensometry. The human cervix is a layered structure, where its thick stromal core contains preferentially aligned collagen fibers embedded in a soft ground substance. The fiber composite nature of the tissue provides resistance to the complex three-dimensional loading environment of pregnancy. In this work, we detail an indentation mechanical test to obtain the force and deformation response during loading which closely matches in vivo conditions. We postulate a constitutive material model to describe the equilibrium material behavior to ramp-hold indentation, and we use an inverse finite element method based on genetic algorithm (GA) optimization to determine best-fit material parameters. We report the material properties of human cervical slices taken at different anatomical locations from women of different obstetric backgrounds. In this cohort of patients, the anterior internal os (the area where the cervix meets the uterus) of the cervix is stiffer than the anterior external os (the area closest to the vagina). The anatomic anterior and posterior quadrants of cervical tissue are more anisotropic than the left and right quadrants. There is no significant difference in material properties between samples of different parities (number of pregnancies reaching viable gestation age).

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.

Chip-based frequency comb sources for optical coherence tomography

Optical coherence tomography (OCT) is a powerful interferometric imaging technique widely used in medical fields such as ophthalmology, cardiology and dermatology. Superluminescent diodes (SLDs) are widely used as light sources in OCT. Recently integrated chip-based frequency combs have been demonstrated in numerous platforms and the possibility of using these broadband chip-scale combs for OCT has been raised extensively over the past few years. However, the use of these chip-based frequency combs as light sources for OCT requires bandwidth and power compatibility with current OCT systems and have not been shown to date. Here we generate frequency combs based on chip-scale lithographically-defined microresonators and demonstrate its capability as a novel light source for OCT. The combs are designed with a small spectral line spacing of 0.21 nm which ensure imaging range comparable to commercial system and operated at non-phase locked regime which provide conversion efficiency of 30%. The comb source is shown to be compatible with a standard commercial spectral domain (SD) OCT system and enables imaging of human tissue with image quality comparable to the one achieved with tabletop commercial sources. The comb source also provides a path towards fully integrated OCT systems.

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.

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.

Real-time assessment of catheter contact and orientation using an integrated optical coherence tomography cardiac ablation catheter

The efficacy of catheter ablation treatment for atrial fibrillation is directly impacted by the quality of lesion formation. Two parameters that are critical for maximizing energy delivery are sustained catheter contact and orientation. Currently, these parameters must be inferred indirectly through tactile feedback or measurements of bioelectrical impedance and tip force. In this work, we propose a method for discerning contact and orientation based on direct endomyocardial imaging mediated by optical coherence tomography (OCT)-integrated ablation catheters. A two-stage classifier is developed to deduce contact parameters from M-mode images. Experimental validation within swine left-atrial specimens demonstrate accuracies of 99.96% and 92.88% for contact and orientation stages, respectively. These results highlight the potential of OCT M-mode imaging for guiding catheter placement during radiofrequency ablation interventions.

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.

Scanning optical coherence tomography probe for in vivo imaging and displacement measurements in the cochlea

We developed a spectral domain optical coherence tomography (SDOCT) fiber optic probe for imaging and sub-nanometer displacement measurements inside the mammalian cochlea. The probe, 140 μm in diameter, can scan laterally up to 400 μm by means of a piezoelectric bender. Two different sampling rates are used, 10 kHz for high-resolution B-scan imaging, and 100 kHz for displacement measurements in order to span the auditory frequency range of gerbil (~50 kHz). Once the cochlear structures are recognized, the scanning range is gradually decreased and ultimately stopped with the probe pointing at the selected angle to measure the simultaneous displacements of multiple structures inside the organ of Corti (OC). The displacement measurement is based on spectral domain phase microscopy. The displacement noise level depends on the A-scan signal of the structure within the OC and we have attained levels as low as ~0.02 nm in in vivo measurements. The system's broadband infrared light source allows for an imaging depth of ~2.7 mm, and axial resolution of ~3 μm. In future development, the probe can be coupled with an electrode for time-locked voltage and displacement measurements in order to explore the electro-mechanical feedback loop that is key to cochlear processing. Here, we describe the fabrication of the laterally-scanning optical probe, and demonstrate its functionality with in vivo experiments.

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.

Compressed sensing-enabled phase-sensitive swept-source optical coherence tomography

Here we present a novel phase-sensitive swept-source optical coherence tomography (PhS-SS-OCT) system. The simultaneously recorded calibration signal, which is commonly used in SS-OCT to stabilize the phase, is randomly sub-sampled during the acquisition, and it is later reconstructed based on the Compressed Sensing (CS) theory. We first mathematically investigated the method, and verified it through computer simulations. We then conducted a vibrational frequency test and a flow velocity measurement in phantoms to demonstrate the system's capability of handling phase-sensitive tasks. The proposed scheme shows excellent phase stability with greatly discounted data bandwidth compared with conventional procedures. We further showcased the usefulness of the system in biological samples by detecting the blood flow in ex vivo swine left marginal artery. The proposed system is compatible with most of the existing SS-OCT systems and could be a preferred solution for future high-speed phase-sensitive applications.

Introduction to the Biophotonics Congress 2018 feature issue

The guest editors introduce a feature issue containing papers based on research presented at the OSA Biophotonics Congress (the former BIOMED) held in Hollywood, FL, 2-6 April, 2018.

Multicontrast endomyocardial imaging by single-channel high-resolution cross-polarization optical coherence tomography

A single-channel high-resolution cross-polarization (CP) optical coherence tomography (OCT) system is presented for multicontrast imaging of human myocardium in one-shot measurement. The intensity and functional contrasts, including the ratio between the cross- and co-polarization channels as well as the cumulative retardation, are reconstructed from the CP-OCT readout. By comparing the CP-OCT results with histological analysis, it is shown that the system can successfully delineate microstructures in the myocardium and differentiate the fibrotic myocardium from normal or ablated myocardium based on the functional contrasts provided by the CP-OCT system. The feasibility of using A-line profiles from the 2 orthogonal polarization channels to identify fibrotic myocardium, normal myocardium and ablated lesion is also discussed.

Frequency-constrained robust principal component analysis: a sparse representation approach to segmentation of dynamic features in optical coherence tomography imaging

Sparse representation theory is an exciting area of research with recent applications in medical imaging and detection, segmentation, and quantitative analysis of biological processes. We present a variant on the robust-principal component analysis (RPCA) algorithm, called frequency constrained RPCA (FC-RPCA), for selectively segmenting dynamic phenomena that exhibit spectra within a user-defined range of frequencies. The algorithm lacks subjective parameter tuning and demonstrates robust segmentation in datasets containing multiple motion sources and high amplitude noise. When tested on 17 ex-vivo, time lapse optical coherence tomography (OCT) B-scans of human ciliated epithelium, segmentation accuracies ranged between 91-99% and consistently out-performed traditional RPCA.

Highly phase-stable 200 kHz swept-source optical coherence tomography based on KTN electro-optic deflector

The rapid advance in swept-source optical coherence tomography (SS-OCT) technology has enabled exciting new applications in elastography, angiography, and vibrometry, where both high temporal resolution and phase stability are highly sought-after. In this paper, we present a 200 kHz SS-OCT system centered at 1321 nm by using an electro-optically tuned swept source. The proposed system's performance was fully characterized, and it possesses superior phase stability (0.0012% scanning variability and <1 ns timing jitter) that is promising for many phase-sensitive imaging applications. Biological experiments were demonstrated within ex vivo human tracheobronchial ciliated epithelium where both the ciliary motion and ciliary beat frequency were successfully extracted.

Comparative study of texture features in OCT images at different scales for human breast tissue classification

Breast cancer is the second leading cause of death in women in the United States due to cancer. Early detection of breast cancerous regions will aid the diagnosis, staging, and treatment of breast cancer. Optical coherence tomography (OCT), a non-invasive imaging modality with high resolution, has been widely used to visualize various tissue types within the human breast and has demonstrated great potential for assessing tumor margins. Imaging large resected samples with a fast imaging speed can be accomplished by under-sampling in the spatial domain, resulting in a large image scale. However, it is unclear whether there is an impact on the ability to classify tissue types based on the selected imaging scale. Our objective is to evaluate how the scale at which the images are acquired impacts texture features and the accuracy of an automated classification algorithm. To this end, we present a comparative study of texture features in OCT images at two image scales for human breast tissue classification. Texture features and attenuation coefficients were inputs to a statistical classification model, relevance vector machine. The automated classification results from the two image scales were compared. We found that more informative tissue features are preserved in small image scale and accordingly, small image scale leads to more accurate tissue type classification.

Phase-noise analysis of swept-source optical coherence tomography systems

We propose a new model to characterize the phase noise in swept-source optical coherence tomography (SS-OCT). The new model explicitly incorporates scanning variability, timing jitter, and sample location in addition to intensity noise (shot noise). The model was analyzed and validated by using both Monte Carlo methods and experiments. We suggest that the proposed model can be used as a guideline for future SS-OCT experimental designs.

Ex vivo visualization of human ciliated epithelium and quantitative analysis of induced flow dynamics by using optical coherence tomography

BACKGROUND AND OBJECTIVE

Cilia-driven mucociliary clearance is an important self-defense mechanism of great clinical importance in pulmonary research. Conventional light microscopy possesses the capability to visualize individual cilia and its beating pattern but lacks the throughput to assess the global ciliary activities and flow dynamics. Optical coherence tomography (OCT), which provides depth-resolved cross-sectional images, was recently introduced to this area.

MATERIALS AND METHODS

Fourteen de-identified human tracheobronchial tissues are directly imaged by two OCT systems: one system centered at 1,300 nm with 6.5 μm axial resolution and 15 μm lateral resolution, and the other centered at 800 nm with 2.72 μm axial resolution and 5.52 μm lateral resolution. Speckle variance images are obtained in both cross-sectional and volumetric modes. After imaging, sample blocks are sliced along the registered OCT imaging plane and processed with hematoxylin and eosin (H&E) stain for comparison. Quantitative flow analysis is performed by tracking the path-lines of microspheres in a fixed cross-section. Both the flow rate and flow direction are characterized.

RESULTS

The speckle variance images successfully segment the ciliated epithelial tissue from its cilia-denuded counterpart, and the results are validated by corresponding H&E stained sections. A further temporal frequency analysis is performed to extract the ciliary beat frequency (CBF) at cilia cites. By adding polyester microspheres as contrast agents, we demonstrate ex vivo imaging of the flow induced by cilia activities of human tracheobronchial samples.

CONCLUSION

This manuscript presents an ex vivo study on human tracheobronchial ciliated epithelium and its induced mucous flow by using OCT. Within OCT images, intact ciliated epithelium is effectively distinguished from cilia-denuded counterpart, which serves as a negative control, by examining the speckle variance images. The cilia beat frequency is extracted by temporal frequency analysis. The flow rate, flow direction, and particle throughput are obtained through particle tracking. The availability of these quantitative parameters provides us with a powerful tool that will be useful for studying the physiology, pathophysiology and the effectiveness of therapies on epithelial cilia function, as well as serve as a diagnostic tool for diseases associated with ciliary dysmotility. Lasers Surg. Med. 49:270-279, 2017. © 2017 Wiley Periodicals, Inc.

Signal competition in optical coherence tomography and its relevance for cochlear vibrometry

The usual technique for measuring vibration within the cochlear partition is heterodyne interferometry. Recently, spectral domain phase microscopy (SDPM) was introduced and offers improvements over standard heterodyne interferometry. In particular, it has a penetration depth of several mm due to working in the infrared range, has narrow and steep optical sectioning due to using a wideband light source, and is able to measure from several cochlear layers simultaneously. However, SDPM is susceptible to systematic error due to "phase leakage," in which the signal from one layer competes with the signal from other layers. Here, phase leakage is explored in vibration measurements in the cochlea and a model structure. The similarity between phase leakage and signal competition in heterodyne interferometry is demonstrated both experimentally and theoretically. Due to phase leakage, erroneous vibration amplitudes can be reported in regions of low reflectivity that are near structures of high reflectivity. When vibration amplitudes are greater than ∼0.1 of the light source wavelength, phase leakage can cause reported vibration waveforms to be distorted. To aid in the screening of phase leakage in experimental results, the error is plotted and discussed as a function of the important parameters of signal strength and vibration amplitude.

Micro- and Ultrastructural Characterization of Age-Related Changes at the Anterior Cruciate Ligament-to-Bone Insertion

There remains a lack of understanding of the structural changes that occur across the complex, multitissue anterior cruciate ligament (ACL)-to-bone insertion as a function of aging. The objective of this study is to provide a multiscale comparison of matrix properties across the skeletally immature and mature ACL-to-bone insertion. Using complementary imaging methods, micro- and ultrastructural analysis of the insertion revealed that collagen fiber orientation at the interface changes with age, though the degree of collagen organization is maintained over time. These changes are accompanied by a decrease in collagen fibril density and are likely driven by physiological loading. Mineral crystal structure and crystallinity are conserved over time, despite regional differences in crystallinity between the interface and bone. This suggests that mineral chemistry is established early in development and underscores its important functional role. Collectively, these findings provide new insights into interface development and set critical design benchmarks for integrative soft tissue repair.

Collagen Fiber Orientation and Dispersion in the Upper Cervix of Non-Pregnant and Pregnant Women

The structural integrity of the cervix in pregnancy is necessary for carrying a pregnancy until term, and the organization of human cervical tissue collagen likely plays an important role in the tissue's structural function. Collagen fibers in the cervical extracellular matrix exhibit preferential directionality, and this collagen network ultrastructure is hypothesized to reorient and remodel during cervical softening and dilation at time of parturition. Within the cervix, the upper half is substantially loaded during pregnancy and is where the premature funneling starts to happen. To characterize the cervical collagen ultrastructure for the upper half of the human cervix, we imaged whole axial tissue slices from non-pregnant and pregnant women undergoing hysterectomy or cesarean hysterectomy respectively using optical coherence tomography (OCT) and implemented a pixel-wise fiber orientation tracking method to measure the distribution of fiber orientation. The collagen fiber orientation maps show that there are two radial zones and the preferential fiber direction is circumferential in a dominant outer radial zone. The OCT data also reveal that there are two anatomic regions with distinct fiber orientation and dispersion properties. These regions are labeled: Region 1-the posterior and anterior quadrants in the outer radial zone and Region 2-the left and right quadrants in the outer radial zone and all quadrants in the inner radial zone. When comparing samples from nulliparous vs multiparous women, no differences in these fiber properties were noted. Pregnant tissue samples exhibit an overall higher fiber dispersion and more heterogeneous fiber properties within the sample than non-pregnant tissue. Collectively, these OCT data suggest that collagen fiber dispersion and directionality may play a role in cervical remodeling during pregnancy, where distinct remodeling properties exist according to anatomical quadrant.

Automated classification of optical coherence tomography images of human atrial tissue

Tissue composition of the atria plays a critical role in the pathology of cardiovascular disease, tissue remodeling, and arrhythmogenic substrates. Optical coherence tomography (OCT) has the ability to capture the tissue composition information of the human atria. In this study, we developed a region-based automated method to classify tissue compositions within human atria samples within OCT images. We segmented regional information without prior information about the tissue architecture and subsequently extracted features within each segmented region. A relevance vector machine model was used to perform automated classification. Segmentation of human atrial ex vivo datasets was correlated with trichrome histology and our classification algorithm had an average accuracy of 80.41% for identifying adipose, myocardium, fibrotic myocardium, and collagen tissue compositions.

Myocardial imaging using ultrahigh-resolution spectral domain optical coherence tomography

We present an ultrahigh-resolution spectral domain optical coherence tomography (OCT) system in 800 nm with a low-noise supercontinuum source (SC) optimized for myocardial imaging. The system was demonstrated to have an axial resolution of 2.72  μm with a large imaging depth of 1.78 mm and a 6-dB falloff range of 0.89 mm. The lateral resolution (5.52  μm) was compromised to enhance the image penetration required for myocardial imaging. The noise of the SC source was analyzed extensively and an imaging protocol was proposed for SC-based OCT imaging with appreciable contrast. Three-dimensional datasets were acquired ex vivo on the endocardium side of tissue specimens from different chambers of fresh human and swine hearts. With the increased resolution and contrast, features such as elastic fibers, Purkinje fibers, and collagen fiber bundles were observed. The correlation between the structural information revealed in the OCT images and tissue pathology was discussed as well.

An automated 3D registration method for optical coherence tomography volumes

Optical coherence tomography (OCT) is able to provide high resolution volumetric data for biological tissues. However, the field of view (FOV) of OCT is sometimes smaller than the field of interest, which limits the clinical application of OCT. One way to overcome the drawback is to stitch multiple 3D volumes. In this paper, we propose a novel method to register multiple overlapped volumetric OCT data into a single volume. The relative positions of overlapped volumes were estimated on en face plane and at depth. On en face plane, scale invariant feature transform (SIFT) was implemented to extract the keypoints in each volume. Based on the invariant features, volumes were paired through keypoint matching. Then, we formulated the relationship between paired offsets and absolute positions as a linear model and estimated the centroid of each volume using least square method. Moreover, we calibrated the depth displacement in each paired volume and aligned the z coordinates of volumes globally. The algorithm was validated through stitching multiple volumetric OCT datasets of human cervix tissue and of swine heart. The experimental results demonstrated that our method is capable of visualizing biological samples over a wider FOV, which enhances the investigation of tissue structure such as fiber orientation.

Near-infrared spectroscopy integrated catheter for characterization of myocardial tissues: preliminary demonstrations to radiofrequency ablation therapy for atrial fibrillation

Effects of radiofrequency ablation (RFA) treatment of atrial fibrillation can be limited by the ability to characterize the tissue in contact. Parameters obtained by conventional catheters, such as impedance and temperature can be insufficient in providing physiological information pertaining to effective treatment. In this report, we present a near-infrared spectroscopy (NIRS)-integrated catheter capable of extracting tissue optical properties. Validation experiments were first performed in tissue phantoms with known optical properties. We then apply the technique for characterization of myocardial tissues in swine and human hearts, ex vivo. Additionally, we demonstrate the recovery of critical parameters relevant to RFA therapy including contact verification, and lesion transmurality. These findings support the application of NIRS for improved guidance in RFA therapeutic interventions.

Analyzing three-dimensional ultrastructure of human cervical tissue using optical coherence tomography

During pregnancy, the uterine cervix is the mechanical barrier that prevents delivery of a fetus. The underlying cervical collagen ultrastructure, which influences the overall mechanical properties of the cervix, plays a role in maintaining a successful pregnancy until term. Yet, not much is known about this collagen ultrastructure in pregnant and nonpregnant human tissue. We used optical coherence tomography to investigate the directionality and dispersion of collagen fiber bundles in the human cervix. An image analysis tool has been developed, combining a stitching method with a fiber orientation measurement, to study axially sliced cervix samples. This tool was used to analyze the ultrastructure of ex-vivo pregnant and non-pregnant hysterectomy tissue samples taken at the internal os, which is the region of the cervix adjacent to the uterus. With this tool, directionality maps of collagen fiber bundles and dispersion of collagen fiber orientation were analyzed. It was found that that the overall preferred directionality of the collagen fibers for both the nonpregnant and pregnant samples were circling around the inner cervical canal. Pregnant samples showed greater dispersion than non-pregnant samples. Lastly, we observed regional differences in collagen fiber dispersion. Fibers closer to the inner canal showed more dispersion than the fibers on the radial edges.

A continuous fiber distribution material model for human cervical tissue

The uterine cervix during pregnancy is the vital mechanical barrier which resists compressive and tensile loads generated from a growing fetus. Premature cervical remodeling and softening is hypothesized to result in the shortening of the cervix, which is known to increase a woman׳s risk of preterm birth. To understand the role of cervical material properties in preventing preterm birth, we derive a cervical material model based on previous mechanical, biochemical and histological experiments conducted on nonpregnant and pregnant human hysterectomy cervical tissue samples. In this study we present a three-dimensional fiber composite model that captures the equilibrium material behavior of the tissue in tension and compression. Cervical tissue is modeled as a fibrous composite material, where a single family of preferentially aligned and continuously distributed collagen fibers are embedded in a compressible neo-Hookean ground substance. The total stress in the collagen solid network is calculated by integrating the fiber stresses. The shape of the fiber distribution is described by an ellipsoid where semi-principal axis lengths are fit to optical coherence tomography measurements. The composite material model is fit to averaged mechanical testing data from uni-axial compression and tension experiments, and averaged material parameters are reported for nonpregnant and term pregnant human cervical tissue. The model is then evaluated by investigating the stress and strain state of a uniform thick-walled cylinder under a compressive stress with collagen fibers preferentially aligned in the circumferential direction. This material modeling framework for the equilibrium behavior of human cervical tissue serves as a basis to determine the role of preferentially-aligned cervical collagen fibers in preventing cervical deformation during pregnancy.