Intravascular polarimetry with optical coherence tomography measures polarization effects arising from tissue anisotropy. This affords insight into the microstructure and physical orientation of collagen or smooth muscle cells and provides metrics to quantify scattering properties of lipid-rich plaques. We present insights from clinical pilot studies with intravascular polarimetry, discuss its prospects for improving our mechanistic understanding of plaque progression and help patient management, and explain our progress with alleviating the hardware requirements to enable intravascular polarimetry.

We report the use of our multimodal near-infrared fluorescence (NIRF) and OCT imaging system and catheter to perform the first imaging of LUM015 inflammatory activity in rabbit models of atherosclerosis in vivo. Using co-injection and multi-channel intravascular NIRF-OCT, we compared LUM015 (6.2 mg/kg) and preclinical ProSense (VM110, 3.5 mg/kg) fluorescence in the same subject. We found that co-registered fluorescence carpet maps were remarkably similar with a PCC of 0.51 and a Mander’s overlap coefficient of 0.79. Results suggest that LUM015 will be a viable clinical option for intracoronary imaging of plaque inflammatory activity in patients.

Intravascular polarization-sensitive optical coherence tomography (IV-PSOCT) provides depth-resolved tissue birefringence which can be used to evaluate the mechanical stability of a plaque. Here, we demonstrate a very simple method of constructing an intravascular polarization-sensitive optical coherence tomography (IV-PSOCT) system. A conventional intravascular OCT system can be modified for IV-PSOCT by applying a 12-m polarization-maintaining fiber based imaging probe. Its two polarization modes separately produce OCT images of polarization detection channels spatially distinguished by an image separation of 2.7 mm. We experimentally validated our IV-PSOCT with chicken tendon, chicken breast, and coronary artery for the image samples. We found that the birefringent properties can be successfully visualized by our endoscopic imaging tool.

We report a novel multispectral FLIm/ swept-source OCT intravascular imaging catheter system including three key innovative features: 1) UV/NIR beam focusing is achieved with a free-form reflective distal optics that outperforms both ball and GRIN-based catheter optics, 2) stable optical coupling (single mode transmission: 75.7+-0.5% at 100 rps) by way of an air bearing rotary collimator, and 3) improvements in FLIm SNR obtained by integrating solid-state FLIm detection within the motor drive. Validation in excised human coronary artery specimens demonstrates the capabilities of FLIm to detect and quantify inflammation and characterize the extracellular matrix of atherosclerotic lesions.

Radiofrequency ablation (RFA) procedures require detailed mapping of atrial structure for patients with atrial fibrillation (AF). Identifying the spatial distribution and transmural properties of lesions in left atrium (LA) can provide helpful guidance to RFA treatment. We implement anatomical mapping by tracking sample-sites and capturing spectral signatures from near-infrared spectroscopy (NIRS) with an optical catheter. Using interpolation algorithm, we reconstruct atrial lesion maps of ex-vivo swine and human atriums, and evaluate the capability of NIRS to recognize spatial discontinuity of lesions.

Atrial fibrosis is an important cause of atrial fibrillation (AF) and is often targeted for radiofrequency ablation (RFA) treatment. However, fibrosis identification during an RFA procedure is indirect and not well established. Polarization-sensitive optical coherence tomography (PSOCT) provides high-resolution in-depth noninvasive structural and tissue birefringence images, which can be effective for detecting fibrosis. In this work, combining histology and optical mapping of atrial action potential activity, we demonstrated the identification of atrial fibrosis that caused abnormal impulse propagation in a pig model of AF with PSOCT. Results indicate that PSOCT may provide effective guidance for RFA procedures in the future.

Low Cardiac Output Syndrome (LCOS) is a common complication of congenital heart disease corrective cardiopulmonary bypass surgery. Providing clinicians with realtime assessment of LCOS will facilitate early detection for implementation of more timely and effective interventions to reduce fatalities and improve infant outcomes. We demonstrate the realtime capture of relative temperature changes via an optical and thermographic imaging-based system that serve as an accurate measure of dynamic changes in peripheral blood perfusion. The results of this study show promise for the application of a realtime noninvasive optical and thermographic imaging-based system for LCOS detection.

An intraoperative tool that accurately provides detailed structural information and classifies endocardial substrates could help improve guidance during ablation therapy. With our custom near infrared spectroscopy-integrated radiofrequency catheter, here we demonstrate atrial substrate mapping on ex vivo swine and human left atria. Optical contrast indices and classification algorithms were developed, which classified pulmonary vein, lesion, and fibrosis using optically derived parameters based on endogenous tissue spectral signatures with high accuracy. Predicted lesion depth percentage linearly corresponded with ground truth measurements from trichrome histology. These results suggest near infrared-integrated mapping catheters can serve as a complementary tool to currently-available electroanatomical mapping systems to improve treatment efficacy.

Advances in tissue clearing and three-dimensional microscopy require new tools to analyze the resulting large volumes with single-cell resolution. Many existing nuclei detection approaches fail when applied to the developing heart, with its high cell density, and elongated myocytes. We propose a new regression-based convolutional neural network that detect nuclei centroids in whole DAPI-stained embryonic quail hearts. High nuclei detection accuracy was obtained in two different hearts where our algorithm outperformed other deep learning approaches. Once nuclei were identified we were also able to extract properties such as orientation and size, which enables future studies of heart development and disease.

The mouse embryo is an established model for investigation of regulatory mechanisms controlling cardiac development and congenital heart defects in humans. Optogenetics, originally developed for neuroscience research, has recently been shown to control embryonic mouse heartbeat with pulsed light in a range of stimulation frequencies. The aim of this study was to explore continuous wave optogenetic light stimulation for activation of contractions through regions of the heart. This study suggests a potential to use continuous wave optogenetic stimulation for quick identification and investigation of developmental origin of cardiac cell populations in addition to previously established manipulation of embryo cardiodynamics.

Coronary heart disease has the highest rate of death and morbidity in the Western world. Lipid-laden plaques containing a necrotic core may eventually rupture causing heart attack and stroke. Intravascular Optical Coherence Tomography (IV-OCT) imaging has been used for plaque assessment. However, the IV-OCT images are visually interpreted, which is burdensome and require highly trained physicians. This study aims to provide high throughput lipid-laden plaque identification that can assist in vivo imaging by offering faster screening and guided decision-making during percutaneous coronary interventions. An A-line wise classification methodology based on time-series deep learning is presented to fulfill this aim.

In this project, we propose a deep learning-based method to detect calcified tissue within coronary optical coherence tomography (OCT) images. Conventionally, diseased tissue was manually checked on a frame (Bscan)-by-frame (Bscan) basis. Based on faster region-based convolutional neural network, our proposed method can automatically detect the calcified regions from diseased coronary artery. Our method achieves promising result of mean average precision (0.74) and recall (0.79) in detecting calcified regions. The proposed method could provide valuable information for locating calcified tissue within a large volume of OCT images. It has great potential to aid the treatment of coronary artery disease.

Optical coherence tomography has been employed to expose and map micron-level cardiac tissue structures. Previous studies have characterized structural substrates like collagen fibers, adipose tissue, scar tissue, and the pulmonary vein region. Cardiac fiber orientation plays a critical role in the electromechanics of the human atria but it has yet to be quantitatively evaluated. Therefore, personalized fiber orientation atlases produced by algorithmic mapping of atrial fiber geometry can serve as models for studying the mechanisms behind AF and cardiac arrhythmias overall. Integration of this algorithm may eventually provide important insights for the guidance of RFA procedures as well.