Depth‐sensitive Raman spectroscopy combined with optical coherence tomography for layered tissue analysis

To evaluate how information from combined coronal optical coherence tomography (OCT) and confocal laser scanning ophthalmoscopy (SLO) with integrated simultaneous indocyanine green (ICG) dye angiography can be used in the diagnosis of a variety of macular diseases. A compact chin-rest-based OCT/confocal imaging system was used to produce the OCT image and excite the fluorescence in the ICG dye. The same eye fundus area can be visualized with coronal (C-scans, en face) OCT and ICG angiography simultaneously. Fast T scanning (transverse scanning, en face) was used to build B- or C-scan OCT images along with confocal SLO views, with and without ICG filtration. The OCT, confocal SLO and ICG fluorescence images were simultaneously presented in a three-screen format. A live mixing channel overlaid the ICG sequence on the coronal OCT slices in a fourth panel for immediate comparison. Thirty eyes were imaged. The pathologic conditions studied included classic and occult neovascular membranes, vascularized RPE detachments, polypoidal choroidal vasculopathy, traumatic choroidal rupture, diabetic maculopathy, central serous retinopathy, and macular drusen. Images were evaluated with special attention toward identifying novel relationships between morphology and function revealed by the superimposition of the studies. Simultaneous visualization of an en face (coronal, C-scan) OCT image and of an ICG angiogram, displayed side by side and superimposed, permits more precise correlations between late fluorescence accumulation with structures deep to the retinal surface at the retina-choroid interface. The multiplanar scanning also permits immediate B-scan OCT cross-sectional views of regions of abnormal fluorescence. The paper demonstrates the synergy between the two types of studies, functional and anatomic, in providing a more complete view of the pathologic condition.

This work investigates combination of Optical Coherence Tomography and two cameras, observing a microscopic scene. Stereo vision provides realistic images, but is limited in terms of penetration depth. Optical Coherence Tomography (OCT) enables access to subcutaneous structures, but 3D-OCT volume data do not give the surgeon a familiar view. The extension of the stereo camera setup with OCT imaging combines the benefits of both modalities. In order to provide the surgeon with a convenient integration of OCT into the vision interface, we present an automated image processing analysis of OCT and stereo camera data as well as combined imaging as augmented reality visualization. Therefore, we care about OCT image noise, perform segmentation as well as develop proper registration objects and methods. The registration between stereo camera and OCT results in a Root Mean Square error of 284 μm as average of five measurements. The presented methods are fundamental for fusion of both imaging modalities. Augmented reality is shown as application of the results. Further developments lead to fused visualization of subcutaneous structures, as information of OCT images, into stereo vision.

Three-Dimensional Optical Coherence Tomography on Endoscopic Mucosal Resection Specimens Confirms Identification of Malignant From Metaplastic Lesions in Patients With Barrett's Esophagus

Previous studies have demonstrated that optical coherence tomography (OCT) could be used to delineate alterations in the microstructure of cartilage, and have suggested that changes in the polarization state of light as detected by OCT could provide information on the birefringence properties of articular cartilage as influenced by disease. In this study we have used both OCT and polarization sensitive optical coherence tomography (PS-OCT) technologies to evaluate normal and abnormal bovine articular cartilage according to established structural, organizational, and birefringent characteristics of degenerative joint disease (DJD) in order to determine if this technology can be used to differentiate various stages of DJD as a minimally invasive imaging tool. Fresh bovine femoral-tibial joints were obtained from an abattoir, and 45 cartilage specimens were harvested from 8 tibial plateaus. Whole ex vivo specimens of normal and degenerative articular cartilage were imaged by both OCT and PS-OCT, then fixed and processed for histological evaluation. OCT/PS-OCT images and corresponding histology sections of each specimen were scored according to a modified Mankin structural grading scale and compared. OCT and PS-OCT imaging allowed structural evaluation of intact articular cartilage along a 6 mm surface length to a depth of 2 mm with a transverse resolution of 12 microm and an axial resolution of 10 microm. The OCT and PS-OCT images demonstrated characteristic alterations in the structure of articular cartilage with a high correlation to histological evaluation (kappa = 0.776). The OCT images were able to demonstrate early to advanced structural changes of articular cartilage while the optical phase retardation images obtained by PS-OCT imaging were able to discriminate areas where disorganization of the cartilage matrix was present, however, these characteristics are much different than those reported where OCT images alone were used to characterize tissue birefringence. No evidence of differences in OCT or PS-OCT images were detected between specimens of similar structural characteristics where proteoglycan was judged present or absent by safranin-O Fast Green staining. The combined use of OCT and PS-OCT technologies to obtain images from a single system is able to demonstrate and discriminate between characteristics of very early stages of surface irregularities not previously reported for OCT imaging, to deep clefts and collagen matrix disorganization for tissue at depths of up to 2 mm with good correlation to histology. PS-OCT and accumulated optical phase retardation images of articular cartilage as constructed from alterations in Stokes vector parameters appear to give a valuable but different assessment of alterations in tissue birefringence and organization than have been reported for OCT images obtained with the use of polarized or non-polarized light sources. This is the first time that alterations in the polarization state of light reflected from within the tissue have been demonstrated to be consistent with changes observed in the orientation and organization of the collagen matrix in advanced stages of DJD. The degree of phase transformation of light reflected from within the tissue as determined by PS-OCT imaging does not appear to be altered by the presence or absence of proteoglycan.

Microaneurysms (MAs) are pathognomonic signs that help clinicians to detect diabetic retinopathy (DR) in the early stages. Automatic detection of MA in retinal images is an active area of research due to its application in screening processes for DR which is one of the main reasons of blindness amongst the working-age population. The focus of these works is on the automatic detection of MAs in en face retinal images like fundus color and Fluorescein Angiography (FA). On the other hand, detection of MAs from Optical Coherence Tomography (OCT) images has 2 main advantages: first, OCT is a non-invasive imaging technique that does not require injection, therefore is safer. Secondly, because of the proven application of OCT in detection of Age-Related Macular Degeneration, Diabetic Macular Edema, and normal cases, thanks to detecting MAs in OCT, extensive information is obtained by using this imaging technique. In this research, the concentration is on the diagnosis of MAs using deep learning in the OCT images which represent in-depth structure of retinal layers. To this end, OCT B-scans should be divided into strips and MA patterns should be searched in the resulted strips. Since we need a dataset comprising OCT image strips with suitable labels and such large labelled datasets are not yet available, we have created it. For this purpose, an exact registration method is utilized to align OCT images with FA photographs. Then, with the help of corresponding FA images, OCT image strips are created from OCT B-scans in four labels, namely MA, normal, abnormal, and vessel. Once the dataset of image strips is prepared, a stacked generalization (stacking) ensemble of four fine-tuned, pre-trained convolutional neural networks is trained to classify the strips of OCT images into the mentioned classes. FA images are used once to create OCT strips for training process and they are no longer needed for subsequent steps. Once the stacking ensemble model is obtained, it will be used to classify the OCT strips in the test process. The results demonstrate that the proposed framework classifies overall OCT image strips and OCT strips containing MAs with accuracy scores of 0.982 and 0.987, respectively.

Conventional optical coherence tomography (OCT) systems generally have a limited imaging range within a depth of only 1-2 mm and suffers from unwanted noise such as speckle, ghost or mirror noise. To overcome these limitations, we developed a motorized-stage-based OCT system with an extended imaging range, using a common-path Fourier-domain optical coherence tomography (CP-FD-OCT) configuration. Using this OCT systems, OCT image was obtained from an onion, and their subsurface structure were observed. The result showed that the OCT images obtained using our motorized-stage-based system had a significantly extended imaging range due to its real-time accurate depth tracking. Consequently, the devised CP-FD-OCT systems and algorithms have good potential for the further development of endoscopic OCT for microsurgery.

The conventional optical coherence tomography (OCT) images based on enhanced scattering and the photothermal (PT) images based on enhanced absorption of the localized surface plasmon (LSP) resonance of Au nanorings (NRIs) in a bio-tissue sample are demonstrated with the scans of an OCT system (1310-nm system), in which the spectral range covers the LSP resonance peak wavelength, and another OCT system (1060-nm system), in which the spectral range is away from the LSP resonance peak wavelength. A PT image is formed by evaluating the modulation frequency (400 Hz) response of an excitation laser with its wavelength (1308 nm) close to the LSP resonance peak at 1305 nm of the Au NRI solution. With the scan of the 1310-nm OCT system, the Au NRI distribution in the bio-tissue sample can be observed in both conventional OCT and PT images. However, with the scan of the 1060-nm OCT system, the Au NRI distribution can be clearly observed only in the PT image. The diffusion process of Au NRIs in the bio-tissue sample can be traced with the scan of either OCT system. Based on phantom experiments, it is shown that the PT image can help in resolving the ambiguity of a conventional OCT image between the enhanced scattering of Au NRIs and the strong scattering of a tissue structure in the 1310-nm OCT scanning. Also, under the condition of weak intrinsic sample scattering, particularly in the scan of the 1060-nm system, the PT signal can be lower than a saturating level, which is determined by the excitation power. By increasing OCT system signal-to-noise ratio or M-mode scan time, the PT signal level can be enhanced.

Objective: Numerous ablation techniques have been developed to alleviate urethral obstruction and improve urodynamics in benign prostatic hyperplasia. Most techniques, however, rely on visual observation of surface changes for ablation end points. The feasibility of using real-time optical coherence tomography (OCT) for minimally invasive imaging to guide and monitor prostate resection is demonstrated with representative techniques of laser and radiofrequency ablation. Empiric comparisons of ablation dynamics are made, and the use of OCT as a high-resolution, subsurface modality for image guidance is evaluated.Materials and Methods: Optical coherence tomography is a high-resolution, high-speed near-infrared imaging technique analogous to ultrasound imaging, except that reflections of light are detected rather than sound. High-speed OCT is used to image the dynamic process of laser and radiofrequency ablation of in vitro human prostate tissue. OCT images of ablation sites are compared with corresponding histology.Results: Based on comparisons between OCT images and corresponding histology, OCT imaged transurethral prostate tissue morphology, including urethral sinuses and submucosal glands. Real-time OCT imaging provided rapid feedback and control of ablation dynamics. The compact and portable OCT technology is amenable to minimally invasive beam-delivery devices.Conclusions: Optical coherence tomography offers a minimally invasive means of assessing transurethral prostate morphology. Real-time OCT has the potential to provide image guidance of prostate resection for many of the existing surgical treatments directed at alleviating urethral obstruction associated with benign prostatic hyperplasia.

IMPACT: Despite its importance in systemic diseases such as diabetes, the eye is notably difficult to examine for non-specialists; this study introduces a fully automated approach for eye disease screening, coupling a deep learning algorithm with a robotically-aligned optical coherence tomography system to improve eye care in non-ophthalmology settings. OBJECTIVES/GOALS: This study aims to develop and test a deep learning (DL) method to classify images acquired from a robotically-aligned optical coherence tomography (OCT) system as normal vs. abnormal. The long-term goal of our study is to integrate artificial intelligence and robotic eye imaging to fully automate eye disease screening in diverse clinical settings. METHODS/STUDY POPULATION: Between August and October 2020, patients seen at the Duke Eye Center and healthy volunteers (age ≥18) were imaged with a custom, robotically-aligned OCT (RAOCT) system following routine eye exam. Using transfer learning, we adapted a preexisting convolutional neural network to train a DL algorithm to classify OCT images as normal vs. abnormal. The model was trained and validated on two publicly available OCT datasets and two of our own RAOCT volumes. For external testing, the top-performing model based on validation was applied to a representative averaged B-scan from each of the remaining RAOCT volumes. The model’s performance was evaluated against a reference standard of clinical diagnoses by retina specialists. Saliency maps were created to visualize the areas contributing most to the model predictions. RESULTS/ANTICIPATED RESULTS: The training and validation datasets included 87,697 OCT images, of which 59,743 were abnormal. The top-performing DL model had a training accuracy of 96% and a validation accuracy of 99%. For external testing, 43 eyes of 27 subjects were imaged with the robotically-aligned OCT system. Compared to clinical diagnoses, the model correctly labeled 18 out of 22 normal averaged B-scans and 18 out of 21 abnormal averaged B-scans. Overall, in the testing set, the model had an AUC for the detection of pathology of 0.92, an accuracy of 84%, a sensitivity of 86%, and a specificity of 82%. For the correctly predicted scans, saliency maps identified the areas contributing most to the DL algorithm’s predictions, which matched the regions of greatest clinical importance. DISCUSSION/SIGNIFICANCE OF FINDINGS: This is the first study to develop and apply a DL model to images acquired from a self-aligning OCT system, demonstrating the potential of integrating DL and robotic eye imaging to automate eye disease screening. We are working to translate this technology for use in emergency departments and primary care, where it will have the greatest impact.

We report the development of a combined dual-modal photoacoustic and optical coherence tomography (PA-OCT) system using a single near-infrared (NIR) supercontinuum laser source which can provide both optical absorption and scattering contrasts simultaneously. By using a small sized pulsed Nd:YAG microchip laser and a photonic crystal fiber, we fabricated a pulsed broadband supercontinuum source from 600 to 1700 nm. Under the same optical hardware system, intrinsically registered PA and OCT images are acquired in a single scanning. In order to demonstrate feasibility of our system, we successfully acquired the PA and OCT images of black and white hairs images at the same time. The black hair was detected in both PA and OCT images, while the white hair appeared only in the OCT image. This result suggests the potential of compact, cost-effective, and simple dual-modal PA-OCT system. Moreover, we believe that this approach will be a key point for commercialization and clinical translation.

High-Definition and 3-dimensional Imaging of Macular Pathologies with High-speed Ultrahigh-Resolution Optical Coherence Tomography

To investigate morphological variations in the macular area with optical coherence tomography (OCT) after vitrectomy for diabetic fibrovascular proliferation. We reviewed 108 cases using OCT 7-15 months after vitrectomy. Of these, 32 received OCT within 3 months postoperatively. Morphological variations were categorized and correlated with visual outcome. Only 24 cases (21.4%) had no obvious abnormalities. The most frequent findings were epiretinal membrane (52.8%), macular thickening (37.0%) and macular cysts (28.7%). Multivariate regression showed that diffuse macular thickening, loss of foveal depression and diffuse retinal thinning were significantly associated with poor visual acuity. Sequential OCT (< 3 and >or= 7 months) revealed that epiretinal membrane and oedema outside of fovea changed significantly between two examinations. OCT may identify diverse morphological changes in the macular area after diabetic vitrectomy for fibrovascular proliferation. Macular appearance may change over time, and certain types of morphological changes may be associated with poor visual function.

Aims/Purpose: The detection of subretinal fluid (SRF) and intraretinal fluid (IRF) in optical coherence tomography (OCT) images plays a crucial role in the diagnosis and treatment of certain eye diseases. In this study, we investigated the performance of a Transfer Learning artificial intelligence (AI) technique, which we used to perform the model adaptation from the domain of Heidelberg OCT images to Optopol devices.Methods: A data set of 133 Optopol OCT images. 69 images indicating subretinal or intraretinal fluid and 64 fluid‐free images, were analysed. The AI algorithm that was initially trained on OCT images from Heidelberg device was fine‐tuned to perform the biomarker segmentation in Optopol (Revo NX, SOCT Copernicus REVO, REVO FC) OCT images. Manual assessments by the medical experts were used to evaluate the algorithm's performance.Results: Our findings demonstrate the promising performance of the domain‐adapted model. in detecting SRF and IRF, when initially trained on OCT images from a different device. The algorithm achieved an accuracy of 80% while classifying the presence versus absence of the fluids on the balanced test data set.Conclusions: The study demonstrates a successful application of a transfer learning technique for detection of subretinal and intraretinal fluids in OCT images acquired with the Optopol devices, indicating its potential for enhancing eye diagnostics. Further studies utilizing larger data sets, further biomarkers and diverse OCT devices are warranted to validate the algorithm's robustness and generalizability.

Extracting optical properties of tissue [e.g., the attenuation coefficient () and the backscattering fraction] from the optical coherence tomography (OCT) images is a valuable tool for parametric imaging and related diagnostic applications. Previous attenuation estimation models depend on the assumption of the uniformity of the backscattering fraction () within layers or whole samples, which does not accurately represent real-world conditions. Our aim is to develop a robust and accurate model that calculates depth-wise values of attenuation and backscattering fractions simultaneously from OCT signals. Furthermore, we aim to develop an attenuation compensation model for OCT images that utilizes the optical properties we obtained to improve the visual representation of tissues. Using the stationary iteration method under suitable constraint conditions, we derived the approximated solutions of and on a single scattering model. During the iteration, the estimated value of can be rectified by introducing the large variations of , whereas the small ones were automatically ignored. Based on the calculation of the structure information, the OCT intensity with attenuation compensation was deduced and compared with the original OCT profiles. The preliminary validation was performed in the OCT A-line simulation and Monte Carlo modeling, and the subsequent experiment was conducted on multi-layer silicone-dye- phantoms and ex vivo cow eyes. Our method achieved robust and precise estimation of and for both simulated and experimental data. Moreover, corresponding OCT images with attenuation compensation provided an improved resolution over the entire imaging range. Our proposed method was able to correct the estimation bias induced by the variations of and provided accurate depth-resolved measurements of both and simultaneously. The method does not require prior knowledge of the morphological information of tissue and represents more real-life tissues. Thus, it has the potential to help OCT imaging based disease diagnosis of complex and multi-layer biological tissue.

Optical coherence tomography (OCT) is a noninvasive imaging modality generating cross sectional and volumetric images of translucent samples. In Fourier domain OCT (FD OCT), the depth profile is calculated by a fast Fourier transformation of the interference spectrum, providing speed and SNR advantage and thus making FD OCT well suitable in biomedical applications. The interference spectrum can be acquired spectrally resolved in spectral domain OCT or time-resolved in optical frequency domain imaging (OFDI). Since OCT images still suffer from motion artifacts, especially under in vivo conditions, increased depth scan rates are required. Therefor, the principle of Fourier domain mode locking has been presented by R. Huber et al. circumventing the speed limitations of conventional FD OCT systems. In FDML lasers, a long single mode fiber is inserted in the ring resonator of the laser resulting in an optical round trip time of a few microseconds. Sweeping the wavelength synchronously by a tunable Fabry-Perot filter can provide wavelength sweeps with repetition rates up to a few MHz used for OFDI. Imaging of subpleural lung tissue for investigation of lung dynamics and its elastic properties is a further biomedical application demanding high-speed OCT imaging techniques. For the first time, the visualization of subpleural alveolar structures of a rabbit lung is presented by the use of an FDML-based OCT system enabling repetition rates of 49.5 kHz and 122.6 kHz, respectively.