Artificial neural network for enhancing signal-to-noise ratio and contrast in photothermal optical coherence tomography.

Optical coherence tomography (OCT) is a medical imaging method that generates micron-resolution 3D volumetric images of tissues in-vivo. Photothermal (PT)-OCT is a functional extension of OCT with the potential to provide depth-resolved molecular information complementary to the OCT structural images. PT-OCT typically requires long acquisition times to measure small fluctuations in the OCT phase signal. Here, we use machine learning with a neural network to infer the amplitude of the photothermal phase modulation from a short signal trace, trained in a supervised fashion with the ground truth signal obtained by conventional reconstruction of the PT-OCT signal from a longer acquisition trace. Results from phantom and tissue studies show that the developed network improves signal to noise ratio (SNR) and contrast, enabling PT-OCT imaging with short acquisition times and without any hardware modification to the PT-OCT system. The developed network removes one of the key barriers in translation of PT-OCT (i.e., long acquisition time) to the clinic.

Dual modality intravascular catheter system combining pulse-sampling fluorescence lifetime imaging and polarization-sensitive optical coherence tomography.

The clinical management of coronary artery disease and the prevention of acute coronary syndromes require knowledge of the underlying atherosclerotic plaque pathobiology. Hybrid imaging modalities capable of comprehensive assessment of biochemical and morphological plaques features can address this need. Here we report the first implementation of an intravascular catheter system combining fluorescence lifetime imaging (FLIm) with polarization-sensitive optical coherence tomography (PSOCT). This system provides multi-scale assessment of plaque structure and composition via high spatial resolution morphology from OCT, polarimetry-derived tissue microstructure, and biochemical composition from FLIm, without requiring any molecular contrast agent. This result was achieved with a low profile (2.7 Fr) double-clad fiber (DCF) catheter and high speed (100 fps B-scan rate, 40 mm/s pullback speed) console. Use of a DCF and broadband rotary junction required extensive optimization to mitigate the reduction in OCT performance originating from additional reflections and multipath artifacts. This challenge was addressed by the development of a broad-band (UV-visible-IR), high return loss (47 dB) rotary junction. We demonstrate in phantoms, ex vivo swine coronary specimens and in vivo swine heart (percutaneous coronary access) that the FLIm-PSOCT catheter system can simultaneously acquire co-registered FLIm data over four distinct spectral bands (380/20 nm, 400/20 nm, 452/45 nm, 540/45 nm) and PSOCT backscattered intensity, birefringence, and depolarization. The unique ability to collect complementary information from tissue (e.g., morphology, extracellular matrix composition, inflammation) with a device suitable for percutaneous coronary intervention offers new opportunities for cardiovascular research and clinical diagnosis.

Segmentation of anatomical layers and imaging artifacts in intravascular polarization sensitive optical coherence tomography using attending physician and boundary cardinality losses.

Intravascular ultrasound and optical coherence tomography are widely available for assessing coronary stenoses and provide critical information to optimize percutaneous coronary intervention. Intravascular polarization-sensitive optical coherence tomography (PS-OCT) measures the polarization state of the light scattered by the vessel wall in addition to conventional cross-sectional images of subsurface microstructure. This affords reconstruction of tissue polarization properties and reveals improved contrast between the layers of the vessel wall along with insight into collagen and smooth muscle content. Here, we propose a convolutional neural network model, optimized using two new loss terms (Boundary Cardinality and Attending Physician), that takes advantage of the additional polarization contrast and classifies the lumen, intima, and media layers in addition to guidewire and plaque shadows. Our model segments the media boundaries through fibrotic plaques and continues to estimate the outer media boundary behind shadows of lipid-rich plaques. We demonstrate that our multi-class classification model outperforms existing methods that exclusively use conventional OCT data, predominantly segment the lumen, and consider subsurface layers at most in regions of minimal disease. Segmentation of all anatomical layers throughout diseased vessels may facilitate stent sizing and will enable automated characterization of plaque polarization properties for investigation of the natural history and significance of coronary atheromas.

Probabilistic volumetric speckle suppression in OCT using deep learning.

We present a deep learning framework for volumetric speckle reduction in optical coherence tomography (OCT) based on a conditional generative adversarial network (cGAN) that leverages the volumetric nature of OCT data. In order to utilize the volumetric nature of OCT data, our network takes partial OCT volumes as input, resulting in artifact-free despeckled volumes that exhibit excellent speckle reduction and resolution preservation in all three dimensions. Furthermore, we address the ongoing challenge of generating ground truth data for supervised speckle suppression deep learning frameworks by using volumetric non-local means despeckling-TNode to generate training data. We show that, while TNode processing is computationally demanding, it serves as a convenient, accessible gold-standard source for training data; our cGAN replicates efficient suppression of speckle while preserving tissue structures with dimensions approaching the system resolution of non-local means despeckling while being two orders of magnitude faster than TNode. We demonstrate fast, effective, and high-quality despeckling of the proposed network in different tissue types acquired with three different OCT systems compared to existing deep learning methods. The open-source nature of our work facilitates re-training and deployment in any OCT system with an all-software implementation, working around the challenge of generating high-quality, speckle-free training data.

Quantitative imaging of three-dimensional fiber orientation in the human brain via two illumination angles using polarization-sensitive optical coherence tomography.

The accurate measurement of three-dimensional (3D) fiber orientation in the brain is crucial for reconstructing fiber pathways and studying their involvement in neurological diseases. Optical imaging methods such as polarization-sensitive optical coherence tomography (PS-OCT) provide important tools to directly quantify fiber orientation at micrometer resolution. However, brain imaging based on the optic axis by PS-OCT so far has been limited to two-dimensional in-plane orientation, preventing the comprehensive study of connectivity in 3D. In this work, we present a novel method to obtain the 3D fiber orientation in full angular space with only two illumination angles. We measure the optic axis orientation and the apparent birefringence by PS-OCT from a normal and a 15 deg tilted illumination, and then apply a computational method yielding the 3D optic axis orientation and true birefringence. We verify that our method accurately recovers a large range of through-plane orientations from -85 deg to 85 deg with a high angular precision. We further present 3D fiber orientation maps of entire coronal sections of human cerebrum and brainstem with 10 µm in-plane resolution, revealing unprecedented details of fiber configurations. We envision that further development of our method will open a promising avenue towards large-scale 3D fiber axis mapping in the human brain and other complex fibrous tissues at microscopic level.

Single-input polarization-sensitive optical coherence tomography through a catheter.

Intravascular polarimetry with catheter-based polarization-sensitive optical coherence tomography (PS-OCT) complements the high-resolution structural tomograms of OCT with morphological contrast available through polarimetry. Its clinical translation has been complicated by the need for modification of conventional OCT hardware to enable polarimetric measurements. Here, we present a signal processing method to reconstruct the polarization properties of tissue from measurements with a single input polarization state, bypassing the need for modulation or multiplexing of input states. Our method relies on a polarization symmetry intrinsic to round-trip measurements and uses the residual spectral variation of the polarization states incident on the tissue to avoid measurement ambiguities. We demonstrate depth-resolved birefringence and optic axis orientation maps reconstructed from in-vivo data of human coronary arteries. We validate our method through comparison with conventional dual-input state measurements and find a mean cumulative retardance error of 13.2deg without observable bias. The 95% limit of agreement between depth-resolved birefringence is 2.80 · 10-4, which is less than the agreement between two repeat pullbacks of conventional PS-OCT (3.14 · 10-4), indicating that the two methods can be used interchangeably. The hardware simplification arising from using a single input state may be decisive in realizing the potential of polarimetric measurements for assessing coronary atherosclerosis in clinical practice.

Computational refocusing in phase-unstable polarization-sensitive optical coherence tomography.

We present computational refocusing in polarization-sensitive optical coherence tomography (PS-OCT) to improve spatial resolution in the calculated polarimetric parameters and extend the depth-of-field in phase-unstable, fiber-based PS-OCT systems. To achieve this, we successfully adapted short A-line range phase-stability adaptive optics (SHARP), a computational aberration correction technique compatible with phase-unstable systems, into a Stokes-based PS-OCT system with inter-A-line polarization modulation. Together with the spectral binning technique to mitigate system-induced chromatic polarization effects, we show that computational refocusing improves image quality in tissue polarimetry of swine eye anterior segment ex vivo with PS-OCT. The benefits, drawbacks, and potential applications of computational refocusing in anterior segment imaging are discussed.

Posterior scleral birefringence measured by triple-input polarization-sensitive imaging as a biomarker of myopia progression.

In myopic eyes, pathological remodelling of collagen in the posterior sclera has mostly been observed ex vivo. Here we report the development of triple-input polarization-sensitive optical coherence tomography (OCT) for measuring posterior scleral birefringence. In guinea pigs and humans, the technique offers superior imaging sensitivities and accuracies than dual-input polarization-sensitive OCT. In 8-week-long studies with young guinea pigs, scleral birefringence was positively correlated with spherical equivalent refractive errors and predicted the onset of myopia. In a cross-sectional study involving adult individuals, scleral birefringence was associated with myopia status and negatively correlated with refractive errors. Triple-input polarization-sensitive OCT may help establish posterior scleral birefringence as a non-invasive biomarker for assessing the progression of myopia.

Efficient dispersion modeling in optical multimode fiber.

Dispersion remains an enduring challenge for the characterization of wavelength-dependent transmission through optical multimode fiber (MMF). Beyond a small spectral correlation width, a change in wavelength elicits a seemingly independent distribution of the transmitted field. Here we report on a parametric dispersion model that describes mode mixing in MMF as an exponential map and extends the concept of principal modes to describe the fiber's spectrally resolved transmission matrix (TM). We present computational methods to fit the model to measurements at only a few, judiciously selected, discrete wavelengths. We validate the model in various MMF and demonstrate an accurate estimation of the full TM across a broad spectral bandwidth, approaching the bandwidth of the best-performing principal modes, and exceeding the original spectral correlation width by more than two orders of magnitude. The model allows us to conveniently study the spectral behavior of principal modes, and obviates the need for dense spectral measurements, enabling highly efficient reconstruction of the multispectral TM of MMF.

Endoscopic imaging of white matter fiber tracts using polarization-sensitive optical coherence tomography.

Polarization sensitive optical coherence tomography (PSOCT) has been shown to image and delineate white matter fibers in a label-free manner by revealing optical birefringence within the myelin sheath using a microscope setup. In this proof-of-concept study, we adapt recent advancements in endoscopic PSOCT to perform depth-resolved imaging of white matter structures deep inside intact porcine brain tissue ex-vivo, through a small, rotational fiber probe. The probe geometry is comparable to microelectrodes currently used in neurosurgical interventions. The presented imaging system is mobile, robust, and uses biologically safe levels of optical radiation making it well suited for clinical translation. In neurosurgery, where accuracy is imperative, endoscopic PSOCT through a narrow-gauge fiber probe could provide intra-operative feedback on the location of critical white matter structures.

Three-dimensional opto-thermo-mechanical model for predicting photo-thermal optical coherence tomography responses in multilayer geometries.

Photothermal optical coherence tomography (PT-OCT) is a functional extension of OCT with the ability to generate qualitative maps of molecular absorptions co-registered with the micron-resolution structural tomograms of OCT. Obtaining refined insight into chemical information from PT-OCT images, however, requires solid understanding of the multifactorial physics behind generation of PT-OCT signals and their dependence on system and sample parameters. Such understanding is needed to decouple the various physical effects involved in the PT-OCT signal to obtain more accurate insight into sample composition. In this work, we propose an analytical model that considers the opto-thermo-mechanical properties of multi-layered samples in 3-D space, eliminating several assumptions that have been limiting previous PT-OCT models. In parametric studies, the model results are compared with experimental signals to investigate the effect of sample and system parameters on the acquired signals. The proposed model and the presented findings open the door for: 1) better understanding of the effects of system parameters and tissue opto-thermo-mechanical properties on experimental signals; 2) informed optimization of experimentation strategies based on sample and system parameters; 3) guidance of downstream signal processing for predicting tissue molecular composition.

Measuring collagen injury depth for burn severity determination using polarization sensitive optical coherence tomography.

Determining the optimal treatment course for a dermatologic burn wound requires knowledge of the wound's severity, as quantified by the depth of thermal damage. In current clinical practice, burn depth is inferred based exclusively on superficial visual assessment, a method which is subject to substantial error rates in the classification of partial thickness (second degree) burns. Here, we present methods for direct, quantitative determination of the depth extent of injury to the dermal collagen matrix using polarization-sensitive optical coherence tomography (PS-OCT). By visualizing the depth-dependence of the degree of polarization of light in the tissue, rather than cumulative retardation, we enable direct and volumetric assessment of local collagen status. We further augment our PS-OCT measurements by visualizing adnexal structures such as hair follicles to relay overall dermal viability in the wounded region. Our methods, which we have validated ex vivo with matched histology, offer an information-rich tool for precise interrogation of burn wound severity and healing potential in both research and clinical settings.

Confocal 3D reflectance imaging through multimode fiber without wavefront shaping.

Imaging through optical multimode fiber (MMF) has the potential to enable hair-thin endoscopes that reduce the invasiveness of imaging deep inside tissues and organs. Active wavefront shaping and fluorescent labeling have recently been exploited to overcome modal scrambling and enable MMF imaging. Here, we present a computational approach that circumvents the need for active wavefront control and exogenous fluorophores. We demonstrate the reconstruction of depth-gated confocal images through MMF using a raster-scanned, focused input illumination at the fiber proximal end. We show the compatibility of this approach with quantitative phase, dark-field, and polarimetric imaging. Computational imaging through MMF opens a new pathway for minimally invasive imaging in medical diagnosis and biological investigations.

Transient-mode photothermal optical coherence tomography.

Photothermal optical coherence tomography (PT-OCT) is an emerging extension of OCT, which forms images based on both scattering and absorption of light. The speed of PT-OCT, however, has been limited by the necessity for lock-in detection with extensive temporal sampling of the sample's PT response. Here, we demonstrate transient-mode PT-OCT (TM-PT-OCT), which increases the effective A-line rate by orders of magnitude from 10-100 Hz to 1.5-7.5 kHz, by interrogating the sample's transient thermal response to a single diode laser pulse. Functional imaging of moving samples with TM-PT-OCT at video rate is also presented. This significant improvement in imaging speed is expected to open the door for downstream integration of PT-OCT in clinical systems for in vivo imaging.

Rapid non-destructive volumetric tumor yield assessment in fresh lung core needle biopsies using polarization sensitive optical coherence tomography.

Adequate tumor yield in core-needle biopsy (CNB) specimens is essential in lung cancer for accurate histological diagnosis, molecular testing for therapeutic decision-making, and tumor biobanking for research. Insufficient tumor sampling in CNB is common, primarily due to inadvertent sampling of tumor-associated fibrosis or atelectatic lung, leading to repeat procedures and delayed diagnosis. Currently, there is no method for rapid, non-destructive intraprocedural assessment of CNBs. Polarization-sensitive optical coherence tomography (PS-OCT) is a high-resolution, volumetric imaging technique that has the potential to meet this clinical need. PS-OCT detects endogenous tissue properties, including birefringence from collagen, and degree of polarization uniformity (DOPU) indicative of tissue depolarization. Here, PS-OCT birefringence and DOPU measurements were used to quantify the amount of tumor, fibrosis, and normal lung parenchyma in 42 fresh, intact lung CNB specimens. PS-OCT results were compared to and validated against matched histology in a blinded assessment. Linear regression analysis showed strong correlations between PS-OCT and matched histology for quantification of tumors, fibrosis, and normal lung parenchyma in CNBs. PS-OCT distinguished CNBs with low tumor content from those with higher tumor content with high sensitivity and specificity. This study demonstrates the potential of PS-OCT as a method for rapid, non-destructive, label-free intra-procedural tumor yield assessment.

Spectral- and Polarization-Dependent Scattering of Gold Nanobipyramids for Exogenous Contrast in Optical Coherence Tomography.

Polarization-sensitive optical coherence tomography (PS-OCT) reveals the subsurface microstructure of biological tissue and provides information regarding the polarization state of light backscattered from tissue. Complementing OCT's structural signal with molecular imaging requires strategies to simultaneously detect multiple exogenous contrast agents with high specificity in tissue. Specific detection of molecular probes enables the parallel visualization of physiological, cellular, and molecular processes. Here we demonstrate that, by combining PS-OCT and spectral contrast (SC)-OCT measurements, we can distinguish signatures of different gold nanobipyramids (GNBPs) in lymphatic vessels from the surrounding tissue and blood vessels in live mouse models. This technique could well be extended to other anisotropic nanoparticle-based OCT contrast agents and presents significant progress toward enabling OCT molecular imaging.

Polarimetric Signatures of Coronary Thrombus in Patients With Acute Coronary Syndrome.

BACKGROUND: Intravascular polarization-sensitive optical frequency domain imaging (PS-OFDI) offers a novel approach to measure tissue birefringence, which is elevated in collagen and smooth muscle cells, that in turn plays a critical role in healing coronary thrombus (HCT). This study aimed to quantitatively assess polarization properties of coronary fresh and organizing thrombus with PS-OFDI in patients with acute coronary syndrome (ACS).Methods and Results:The POLARIS-I prospective registry enrolled 32 patients with ACS. Pre-procedural PS-OFDI pullbacks using conventional imaging catheters revealed 26 thrombus-regions in 21 patients. Thrombus was manually delineated in conventional OFDI cross-sections separated by 0.5 mm and categorized into fresh thrombus caused by plaque rupture, stent thrombosis, or erosion in 18 thrombus-regions (182 frames) or into HCT for 8 thrombus-regions (141 frames). Birefringence of coronary thrombus was compared between the 2 categories. Birefringence in HCTs was significantly higher than in fresh thrombus (∆n=0.47 (0.37-0.72) vs. ∆n=0.25 (0.17-0.29), P=0.007). In a subgroup analysis, when only using thrombus-regions from culprit lesions, ischemic time was a significant predictor for birefringence (ß (∆n)=0.001 per hour, 95% CI [0.0002-0.002], P=0.023). CONCLUSIONS: Intravascular PS-OFDI offers the opportunity to quantitatively assess the polarimetric properties of fresh and organizing coronary thrombus, providing new insights into vascular healing and plaque stability.

Effects of lipid composition on photothermal optical coherence tomography signals.

SIGNIFICANCE: Photothermal optical coherence tomography (PT-OCT) has the promise to offer structural images coregistered with chemical composition information, which can offer a significant impact in early detection of diseases such as atherosclerosis. AIM: We take the first step in understanding the relation between PT-OCT signals and the endogenous tissue composition by considering the interplay between the opto-thermo-physical properties of tissue as a function of its lipid composition and the ensuing effects on the PT-OCT signals. APPROACH: Multiparameter theoretical estimates for PT-OCT signal as a function of composition in a two-component lipid-water model are derived and discussed. Experimental data from various concentrations of lipid in the form of droplets and injections under bovine cardiac muscle align with theoretical predictions. RESULTS: Theoretical and experimental results suggest that the variations of heat capacity and mass density with tissue composition significantly contribute to the amount of optical path length difference measured by OCT phase. CONCLUSION: PT-OCT has the potential to offer key insights into the chemical composition of the subsurface lipid pools in tissue; however, the interpretation of results needs to be carried out by keeping the nonlinear interplay between the tissue of opto-thermo-physical properties and PT-OCT signals in mind.