Spatially confined quantification of bilirubin concentrations by spectroscopic visible-light optical coherence tomography.

Spatially confined measurements of bilirubin in tissue can be of great value for noninvasive bilirubin estimations during neonatal jaundice, as well as our understanding of the physiology behind bilirubin extravasation. This work shows the potential of spectroscopic visible-light optical coherence tomography (sOCT) for this purpose. At the bilirubin absorption peak around 460 nm, sOCT suffers from a strong signal decay with depth, which we overcome by optimizing our system sensitivity through a combination of zero-delay acquisition and focus tracking. In a phantom study, we demonstrate the quantification of bilirubin concentrations between 0 and 650 µM with only a 10% difference to the expected value, thereby covering the entire clinical pathophysiological range.

Visible-light optical coherence tomography oximetry based on circumpapillary scan and graph-search segmentation.

Visible-light optical coherence tomography (vis-OCT) enables retinal oximetry by measuring the oxygen saturation of hemoglobin (sO2) from within individual retinal blood vessels. The sO2 calculation requires reliable estimation of the true spectrum of backscattered light from the posterior vessel wall. Unfortunately, subject motion and image noise make averaging from multiple A-lines at the same depth position challenging, and lead to inaccurate sO2 estimation. In this study, we developed an algorithm to reliably extract the backscattered light's spectrum. We used circumpapillary scanning to sample the vessels repeatedly at the same location. A combination of cross-correlation and graph-search based segmentation extracted the posterior wall locations. Using measurements from 100 B-scans as a gold standard, we demonstrated that our method achieved highly accurate measures of sO2 with minimal bias. In addition, we also investigated how the number of repeated measurements affects the accuracy of sO2 measurement. Our method sets the stage for large-scale studies of retinal oxygenation in animals and humans.

Finite-difference time-domain analysis of increased penetration depth in optical coherence tomography by wavefront shaping.

Multiple scattering in turbid media inhibits optimal light focusing and thus limits the penetration depth in optical coherence tomography (OCT). However, the effects of multiple scattering in a turbid medium can be systematically controlled by shaping the incident wavefront. The authors utilize the reciprocity of Maxwell's equations and finite-difference time-domain numerical analysis to investigate the ultimate performance bounds of wavefront shaping-OCT under ideal and realistic configurations and compare them with the conventional method. The results reveal that the optimized impinging wavefront significantly enhances the penetration depth of OCT.

Automatic analysis of bioresorbable vascular scaffolds in intravascular optical coherence tomography images.

The bioresorbable vascular scaffold (BVS) is a new generation of bioresorbable scaffold (BRS) for the treatment of coronary artery disease. A potential challenge of BVS is malapposition, which may possibly lead to late stent thrombosis. It is therefore important to conduct malapposition analysis right after stenting. Since an intravascular optical coherence tomography (IVOCT) image sequence contains thousands of BVS struts, manual analysis is labor intensive and time consuming. Computer-based automatic analysis is an alternative, but faces some difficulties due to the interference of blood artifacts and the uncertainty of the struts number, position and size. In this paper, we propose a novel framework for a struts malapposition analysis that breaks down the problem into two steps. Firstly, struts are detected by a cascade classifier trained by AdaBoost and a region of interest (ROI) is determined for each strut to completely contain it. Then, strut boundaries are segmented within ROIs through dynamic programming. Based on the segmentation result, malapposition analysis is conducted automatically. Tested on 7 pullbacks labeled by an expert, our method correctly detected 91.5% of 5821 BVS struts with 12.1% false positives. The average segmentation Dice coefficient for correctly detected struts was 0.81. The time consumption for a pullback is 15 sec on average. We conclude that our method is accurate and efficient for BVS strut detection and segmentation, and enables automatic BVS malapposition analysis in IVOCT images.

Real-time visualization and interaction with static and live optical coherence tomography volumes in immersive virtual reality.

Virtual reality (VR) head-mounted displays are an attractive technology for viewing intrasurgical optical coherence tomography (OCT) volumes because they liberate surgeons from microscope oculars. We demonstrate real-time, interactive viewing of OCT volumes in a commercial HTC Vive immersive VR system using previously reported ray casting techniques. Furthermore, we show interactive manipulation and sectioning of volumes using handheld controllers and guidance of mock surgical procedures in porcine eyes exclusively within VR. To the best of our knowledge, we report the first immersive VR-OCT viewer with stereo ray casting volumetric renders, arbitrary sectioning planes, and live acquisition support. We believe VR-OCT volume displays will advance ophthalmic surgery towards VR-integrated surgery.

Pixel-wise segmentation of severely pathologic retinal pigment epithelium and choroidal stroma using multi-contrast Jones matrix optical coherence tomography.

Tissue segmentation of retinal optical coherence tomography (OCT) is widely used in ophthalmic diagnosis. However, its performance in severe pathologic cases is still insufficient. We propose a pixel-wise segmentation method that uses the multi-contrast measurement capability of Jones matrix OCT (JM-OCT). This method is applicable to both normal and pathologic retinal pigment epithelium (RPE) and choroidal stroma. In this method, "features," which are sensitive to specific tissues of interest, are synthesized by combining the multi-contrast images of JM-OCT, including attenuation coefficient, degree-of-polarization-uniformity, and OCT angiography. The tissue segmentation is done by simple thresholding of the feature. Compared with conventional segmentation methods for pathologic maculae, the proposed method is less computationally intensive. The segmentation method was validated by applying it to images from normal and severely pathologic cases. The segmentation results enabled the development of several types of en face visualizations, including melano-layer thickness maps, RPE elevation maps, choroidal thickness maps, and choroidal stromal attenuation coefficient maps. These facilitate close examination of macular pathology. The melano-layer thickness map is very similar to a near infrared fundus autofluorescence image, so the map can be used to identify the source of a hyper-autofluorescent signal.

Deep learning for the segmentation of preserved photoreceptors on en face optical coherence tomography in two inherited retinal diseases.

The objective quantification of photoreceptor loss in inherited retinal degenerations (IRD) is essential for measuring disease progression, and is now especially important with the growing number of clinical trials. Optical coherence tomography (OCT) is a non-invasive imaging technology widely used to recognize and quantify such anomalies. Here, we implement a versatile method based on a convolutional neural network to segment the regions of preserved photoreceptors in two different IRDs (choroideremia and retinitis pigmentosa) from OCT images. An excellent segmentation accuracy (~90%) was achieved for both IRDs. Due to the flexibility of this technique, it has potential to be extended to additional IRDs in the future.

Volumetric optical coherence microscopy with a high space-bandwidth-time product enabled by hybrid adaptive optics.

Optical coherence microscopy (OCM) is a promising modality for high resolution imaging, but has limited ability to capture large-scale volumetric information about dynamic biological processes with cellular resolution. To enhance the throughput of OCM, we implemented a hybrid adaptive optics (hyAO) approach that combines computational adaptive optics with an intentionally aberrated imaging beam generated via hardware adaptive optics. Using hyAO, we demonstrate the depth-equalized illumination and collection ability of an astigmatic beam compared to a Gaussian beam for cellular-resolution imaging. With this advantage, we achieved volumetric OCM with a higher space-bandwidth-time product compared to Gaussian-beam acquisition that employed focus-scanning across depth. HyAO was also used to perform volumetric time-lapse OCM imaging of cellular dynamics over a 1mm × 1mm × 1mm field-of-view with 2 µm isotropic spatial resolution and 3-minute temporal resolution. As hyAO is compatible with both spectral-domain and swept-source beam-scanning OCM systems, significant further improvements in absolute volumetric throughput are possible by use of ultrahigh-speed swept sources.

Automatic quantification of choroidal neovascularization lesion area on OCT angiography based on density cell-like P systems with active membranes.

Detecting and quantifying the size of choroidal neovascularization (CNV) is important for the diagnosis and assessment of neovascular age-related macular degeneration. Depth-resolved imaging of the retinal and choroidal vasculature by optical coherence tomography angiography (OCTA) has enabled the visualization of CNV. However, due to the prevalence of artifacts, it is difficult to segment and quantify the CNV lesion area automatically. We have previously described a saliency algorithm for CNV detection that could identify a CNV lesion area with 83% accuracy. However, this method works under the assumption that the CNV region is the most salient area for visual attention in the whole image and consequently, errors occur when this requirement is not met (e.g. when the lesion occupies a large portion of the image). Moreover, saliency image processing methods cannot extract the edges of the salient object very accurately. In this paper, we propose a novel and automatic CNV segmentation method based on an unsupervised and parallel machine learning technique named density cell-like P systems (DEC P systems). DEC P systems integrate the idea of a modified clustering algorithm into cell-like P systems. This method improved the accuracy of detection to 87.2% on 22 subjects and obtained clear boundaries of the CNV lesions.

Machine-learning based segmentation of the optic nerve head using multi-contrast Jones matrix optical coherence tomography with semi-automatic training dataset generation.

A pixel-by-pixel tissue classification framework using multiple contrasts obtained by Jones matrix optical coherence tomography (JM-OCT) is demonstrated. The JM-OCT is an extension of OCT that provides OCT, OCT angiography, birefringence tomography, degree-of-polarization uniformity tomography, and attenuation coefficient tomography, simultaneously. The classification framework consists of feature engineering, k-means clustering that generates a training dataset, training of a tissue classifier using the generated training dataset, and tissue classification by the trained classifier. The feature engineering process generates synthetic features from the primary optical contrasts obtained by JM-OCT. The tissue classification is performed in the feature space of the engineered features. We applied this framework to the in vivo analysis of optic nerve heads of posterior eyes. This classified each JM-OCT pixel into prelamina, lamina cribrosa (lamina beam), and retrolamina tissues. The lamina beam segmentation results were further utilized for birefringence and attenuation coefficient analysis of lamina beam.

Selective retina therapy enhanced with optical coherence tomography for dosimetry control and monitoring: a proof of concept study.

Selective treatment of the retinal pigment epithelium (RPE) by using short-pulse lasers leads to a less destructive treatment for certain retinal diseases in contrast to conventional photocoagulation. The introduction of selective retina therapy (SRT) to clinical routine is still precluded by the challenges to reliably monitor treatment success and to automatically adjust dose within the locally varying therapeutic window. Combining micrometer-scale depth resolving capabilities of optical coherence tomography (OCT) with SRT can yield real-time information on the laser-induced changes within the RPE after a laser pulse or even during treatment with a laser pulse train. In the present study, SRT and OCT were combined to treat ex-vivo porcine eyes demonstrating closed-loop dose-control. We found a reliable correlation of specific signal changes in time resolved OCT images and physiological lesions in the RPE. First experiments, including 23 porcine eyes, prove the feasibility of the novel treatment concept.

Temporally and spatially adaptive Doppler analysis for robust handheld optical coherence elastography.

Optical coherence elastography (OCE), a functional extension of optical coherence tomography (OCT), can be used to characterize the mechanical properties of biological tissue. A handheld fiber-optic OCE instrument will allow the clinician to conveniently interrogate the localized mechanical properties of in vivo tissue, leading to better informed clinical decision making. During handheld OCE characterization, the handheld probe is used to compress the sample and the displacement of the sample is quantified by analyzing the OCT signals acquired. However, the motion within the sample inevitably varies in time due to varying hand motion. Moreover, the motion speed depends on spatial location due to the sample deformation. Hence, there is a need for a robust motion tracking method for manual OCE measurement. In this study, we investigate a temporally and spatially adaptive Doppler analysis method. The method described here strategically chooses the time interval (δt) between signals involved in Doppler analysis to track the motion speed v(z,t) that varies temporally and spatially in a deformed sample volume under manual compression. Enabled by temporally and spatially adaptive Doppler analysis, we report the first demonstration of real-time manual OCE characterization of in vivo tissue to the best of our knowledge.

The value of ultrahigh resolution OCT in dermatology - delineating the dermo-epidermal junction, capillaries in the dermal papillae and vellus hairs.

Optical coherence tomography (OCT) imaging of the skin is gaining recognition and is increasingly applied to dermatological research. A key dermatological parameter inferred from an OCT image is the epidermal (Ep) thickness as a thickened Ep can be an indicator of a skin disease. Agreement in the literature on the signal characters of Ep and the subjacent skin layer, the dermis (D), is evident. Ambiguities of the OCT signal interpretation in the literature is however seen for the transition region between the Ep and D, which from histology is known as the dermo-epidermal junction (DEJ); a distinct junction comprised of the lower surface of a single cell layer in epidermis (the stratum basale) connected to an even thinner membrane (the basement membrane). The basement membrane is attached to the underlying dermis. In this work we investigate the impact of an improved axial and lateral resolution on the applicability of OCT for imaging of the skin. To this goal, OCT images are compared produced by a commercial OCT system (Vivosight from Michaelson Diagnostics) and by an in-house built ultrahigh resolution (UHR-) OCT system for dermatology. In 11 healthy volunteers, we investigate the DEJ signal characteristics. We perform a detailed analysis of the dark (low) signal band clearly seen for UHR-OCT in the DEJ region where we, by using a transition function, find the signal transition of axial sub-resolution character, which can be directly attributed to the exact location of DEJ, both in normal (thin/hairy) and glabrous (thick) skin. To our knowledge no detailed delineating of the DEJ in the UHR-OCT image has previously been reported, despite many publications within this field. For selected healthy volunteers, we investigate the dermal papillae and the vellus hairs and identify distinct features that only UHR-OCT can resolve. Differences are seen in tracing hairs of diameter below 20 µm, and in imaging the dermal papillae where, when utilising the UHR-OCT, capillary structures are identified in the hand palm, not previously reported in OCT studies and specifically for glabrous skin not reported in any other in vivo optical imaging studies.

Effective bidirectional scanning pattern for optical coherence tomography angiography.

We demonstrate the utility of a novel scanning method for optical coherence tomography angiography (OCTA). Although raster scanning is commonly used for OCTA imaging, a bidirectional approach would lessen the distortion caused by galvanometer-based scanners as sources continue to increase sweep rates. As shown, a unidirectional raster scan approach has a lower effective scanning time than bidirectional approaches; however, a strictly bidirectional approach causes contrast variation along the B-scan direction due to the non-uniform time interval between B-scans. Therefore, a stepped bidirectional approach is introduced and successfully applied to retinal imaging in normal controls and in a pathological subject with diabetic retinopathy.

Quantifying optical properties with visible and near-infrared optical coherence tomography to visualize esophageal microwave ablation zones.

Microwave ablation is a minimally invasive image guided thermal therapy for cancer that can be adapted to endoscope use in the gastrointestinal (GI) tract. Microwave ablation in the GI tract requires precise control over the ablation zone that could be guided by high resolution imaging with quantitative contrast. Optical coherence tomography (OCT) provides ideal imaging resolution and allows for the quantification of tissue scattering properties to characterize ablated tissue. Visible and near-infrared OCT image analysis demonstrated increased scattering coefficients (µs ) in ablated versus normal tissues (Vis: 347.8%, NIR: 415.0%) and shows the potential for both wavelength ranges to provide quantitative contrast. These data suggest OCT could provide quantitative image guidance and valuable information about antenna performance in vivo.

Multispectral analog-mean-delay fluorescence lifetime imaging combined with optical coherence tomography.

The pathophysiological progression of chronic diseases, including atherosclerosis and cancer, is closely related to compositional changes in biological tissues containing endogenous fluorophores such as collagen, elastin, and NADH, which exhibit strong autofluorescence under ultraviolet excitation. Fluorescence lifetime imaging (FLIm) provides robust detection of the compositional changes by measuring fluorescence lifetime, which is an inherent property of a fluorophore. In this paper, we present a dual-modality system combining a multispectral analog-mean-delay (AMD) FLIm and a high-speed swept-source optical coherence tomography (OCT) to simultaneously visualize the cross-sectional morphology and biochemical compositional information of a biological tissue. Experiments using standard fluorescent solutions showed that the fluorescence lifetime could be measured with a precision of less than 40 psec using the multispectral AMD-FLIm without averaging. In addition, we performed ex vivo imaging on rabbit iliac normal-looking and atherosclerotic specimens to demonstrate the feasibility of the combined FLIm-OCT system for atherosclerosis imaging. We expect that the combined FLIm-OCT will be a promising next-generation imaging technique for diagnosing atherosclerosis and cancer due to the advantages of the proposed label-free high-precision multispectral lifetime measurement.

Cycloid scanning for wide field optical coherence tomography endomicroscopy and angiography in vivo.

Devices that perform wide field-of-view (FOV) precision optical scanning are important for endoscopic assessment and diagnosis of luminal organ disease such as in gastroenterology. Optical scanning for in vivo endoscopic imaging has traditionally relied on one or more proximal mechanical actuators, limiting scan accuracy and imaging speed. There is a need for rapid and precise two-dimensional (2D) microscanning technologies to enable the translation of benchtop scanning microscopies to in vivo endoscopic imaging. We demonstrate a new cycloid scanner in a tethered capsule for ultrahigh speed, side-viewing optical coherence tomography (OCT) endomicroscopy in vivo. The cycloid capsule incorporates two scanners: a piezoelectrically actuated resonant fiber scanner to perform a precision, small FOV, fast scan and a micromotor scanner to perform a wide FOV, slow scan. Together these scanners distally scan the beam circumferentially in a 2D cycloid pattern, generating an unwrapped 1 mm × 38 mm strip FOV. Sequential strip volumes can be acquired with proximal pullback to image centimeter-long regions. Using ultrahigh speed 1.3 µm wavelength swept-source OCT at a 1.17 MHz axial scan rate, we imaged the human rectum at 3 volumes/s. Each OCT strip volume had 166 × 2322 axial scans with 8.5 µm axial and 30 µm transverse resolution. We further demonstrate OCT angiography at 0.5 volumes/s, producing volumetric images of vasculature. In addition to OCT applications, cycloid scanning promises to enable precision 2D optical scanning for other imaging modalities, including fluorescence confocal and nonlinear microscopy.

Shared-hole graph search with adaptive constraints for 3D optic nerve head optical coherence tomography image segmentation.

Optic nerve head (ONH) is a crucial region for glaucoma detection and tracking based on spectral domain optical coherence tomography (SD-OCT) images. In this region, the existence of a "hole" structure makes retinal layer segmentation and analysis very challenging. To improve retinal layer segmentation, we propose a 3D method for ONH centered SD-OCT image segmentation, which is based on a modified graph search algorithm with a shared-hole and locally adaptive constraints. With the proposed method, both the optic disc boundary and nine retinal surfaces can be accurately segmented in SD-OCT images. An overall mean unsigned border positioning error of 7.27 ± 5.40 µm was achieved for layer segmentation, and a mean Dice coefficient of 0.925 ± 0.03 was achieved for optic disc region detection.

Phase-stable Doppler OCT at 19 MHz using a stretched-pulse mode-locked laser.

We present a swept-wavelength optical coherence tomography (OCT) system with a 19 MHz laser source and electronic phase-locking of the source, acquisition clock, and beam scanning mirrors. The laser is based on stretched-pulse active mode-locking using an electro-optic modulator. Beam scanning in the fast axis uses a resonant micro-electromechanical systems (MEMS) -based mirror at ~23.8 kHz. Acquisition is performed at 1.78 Gigasamples per second using an external fixed clock. Phase sensitive imaging without need for k-clocking, A-line triggers, or phase-calibration methods is demonstrated. The system was used to demonstrate inter-frame and inter-volume Doppler imaging in the mouse ear and brain at 4D acquisition rates of 1, 30, 60 and 100 volumes/sec (V-scans/s). Angiography based on inter-frame and inter-volume methods are presented. The platform offers extremely fast and phase-stable measurements that can be used in preclinical angiographic and Doppler investigations of perfusion dynamics.

Eye-motion-corrected optical coherence tomography angiography using Lissajous scanning.

To correct eye motion artifacts in en face optical coherence tomography angiography (OCT-A) images, a Lissajous scanning method with subsequent software-based motion correction is proposed. The standard Lissajous scanning pattern is modified to be compatible with OCT-A and a corresponding motion correction algorithm is designed. The effectiveness of our method was demonstrated by comparing en face OCT-A images with and without motion correction. The method was further validated by comparing motion-corrected images with scanning laser ophthalmoscopy images, and the repeatability of the method was evaluated using a checkerboard image. A motion-corrected en face OCT-A image from a blinking case is presented to demonstrate the ability of the method to deal with eye blinking. Results show that the method can produce accurate motion-free en face OCT-A images of the posterior segment of the eye in vivo.