Virtual Hall sensor triggered multi-MHz endoscopic OCT imaging for stable real-time visualization.

Optical Coherence Tomography (OCT) is widely used for endoscopic imaging in endoluminal organs because of its high imaging accuracy and resolution. However, OCT endoscopic imaging suffers from Non-Uniform Rotational Distortion (NURD), which can be caused by many factors, such as irregular motor rotation and changes in friction between the probe and the sheath. Correcting this distortion is essential to obtaining high-quality Optical Coherence Tomography Angiography (OCTA) images. There are two main approaches for correcting NURD: hardware-based methods and algorithm-based methods. Hardware-based methods can be costly, challenging to implement, and may not eliminate NURD. Algorithm-based methods, such as image registration, can be effective for correcting NURD but can also be prone to the problem of NURD propagation. To address this issue, we process frames by coarse and fine registration, respectively. The new reference frame is generated by filtering out the A-scan that may have the NURD problem by coarse registration. And the fine registration uses this frame to achieve the final NURD correction. In addition, we have improved the Features from Accelerated Segment Test (FAST) algorithm and put it into coarse and fine registration process. Four evaluation functions were used for the experimental results, including signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), mean squared error (MSE), and structural similarity index measure (SSIM). By comparing with Scale-invariant feature transform (SIFT), Speeded up robust features (SURF), Oriented FAST and Rotated BRIEF (ORB), intensity-based (Cross-correlation), and Optical Flow algorithms, our algorithm has a higher similarity between the corrected frames. Moreover, the noise in the OCTA data is better suppressed, and the vascular information is well preserved. Our image registration-based algorithm reduces the problem of NURD propagation between B-scan frames and improves the imaging quality of OCT endoscopic images.

Comparison of nonuniform rotational distortion between mechanical IVUS and OCT using a phantom model

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.

In Vivo Imaging of the Biliary (BD) and Pancreatic Duct (PD) with Optical Coherence Tomography (OCT) During ERCP

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.

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.

Acquired subglottic stenosis is a narrowing of the airway caused by prolonged endotracheal intubation. Currently, there are no non-invasive means to diagnose the disease. A previous study by this same group introduced optical coherence tomography (OCT) as a means of monitoring the progression of stenosis. The aim of the current study was to qualitatively and quantitatively analyze OCT images obtained from a subglottic stenosis model of the rabbit airway. 15 rabbits were used throughout the study, and a MEMs based OCT probe was utilized. The OCT images obtained were analyzed using a free software program, 3D Slicer. The region of scarred tissue was grown out and measured quantitatively. This study demonstrated the feasibility of using a program to quantify the progression of scarring in OCT images, in addition to qualitatively correlating between histology, endoscopic, and OCT images. Future works may include utilization of a long-range probe and use of a pressure necrosis model to better emulate the actual onset of neonatal subglottic stenosis.

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.

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.

Optical coherence tomography (OCT) is a noninvasive diagnostic imaging modality that has become increasingly important in ophthalmology because it produces detailed high-resolution tomographic images of the retina and other posterior segment structures. This chapter describes the instrument developed by Podoleanu, Jackson, and colleagues, called the OCT ophthalmoscope. The OCT ophthalmoscope produces images based upon the optical principle of Michaelson interferometry, named after the physicist who first described it in 1881. The novel and unique application of the OCT ophthalmoscope is in its simultaneous generation of C-scan OCT and scanning laser ophthalmoscopy images. The OCT ophthalmoscope produces both highly accurate cross-sectional OCT images and C-scan OCT images in the ophthalmoscopic plane. The OCT ophthalmoscope can be useful in cases of central serous chorioretinopathy. Ophthalmologists have come to rely on OCT imaging as an important diagnostic tool in the evaluation, diagnosis, and management of patients.

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

Retinal drawings are a valuable tool allowing for easy visual communication of ophthalmoscopic findings despite less frequent use today in the era of digital medical records and abundance of imaging options (Schachat et al. 2018). For rhegmatogenous retinal detachments (RRD), drawings of retinal breaks and degree of detachment can aid patient management. In a RRD with an intact fovea, the distance of a detachment from the fovea indicates the distance that ensures central visual acuity, as fovea-off RRD are at risk of a worse visual outcome (Salicone et al. 2006; Hajari et al. 2014; Rezar et al. 2016). Communicating the distance from the RRD border to the fovea to the patient as well as other healthcare personnel can likely improve outcomes especially since patient movement has shown to cause retinal detachment progression (de Jong et al. 2017). This study examines the subjective/objective discrepancy or whether the degree of detachment is communicated accurately by comparing the user-dependent slit-lamp and/or indirect ophthalmoscopy findings to optical coherence tomography (OCT) images taken immediately after diagnosis. For this study, we solely view the degree of detachment as distance from the RRD border to the fovea. Retinal drawings were obtained from fovea-on RRD patients participating in a prospective study (ClinicalTrials.gov Identifier: NCT03655652) at the Department of Ophthalmology, at Rigshospitalet – Glostrup, Denmark. The retinal drawings were either drawn digitally or on paper by ophthalmology residents. The shortest distance from the retinal detachment border on a drawing to the fovea was measured with Fiji imagej software (v. 1.52 g) (https://fiji.sc). For each retinal drawing, we measured the corresponding distance on OCT images (Heidelberg Spectralis, Heidelberg Engineering, Heidelberg, Germany) taken immediately after examination and retinal drawing. The shortest distance on OCT between fovea and the RRD border was measured with built-in software (heidelberg eye explorer, v. 1.9.10.0, Heidelberg Engineering, Heidelberg, Germany). Patients with an RRD > 10 mm from the fovea were excluded as our digital template for retinal drawings only allows the RRD border to be within 10 mm of the fovea. r (v. 3.3.2, R Foundation for Statistical Computing, Vienna, Austria) was used for statistical analysis. From 59 patients, 45 retinal drawings were available – 43 drawn digitally and two drawn on paper. Two patients were excluded for exceeding the 10 mm RRD border distance to the fovea. Figure 1 A depicts the correlation between the retinal drawings and the objective OCT distance taken immediately after examination. Retinal drawings deviated significantly from the ideal no difference between drawing and objectively measured RRD border distance from the fovea (p < 0.0001). A split-fovea patient would on average be drawn 3.31 mm from the fovea, whereas an RRD border 6.0 mm from the fovea would be drawn 4.32 mm from the fovea. Almost half of the patients (20/43, 46.5%) had routine OCT performed prior to examination (TOPCON OCT 3D 2000 – 6 × 6 mm macular scan) (Topcon Corporation, Tokyo, Japan) with the RRD border visible in 13 of these scans. The fovea threatening RRDs visualized on OCT were somewhat more accurately identified; a split fovea would on average be drawn 2.05 mm from the fovea if OCT was available. Although OCT seemed to aid in more accurate retinal drawings, it did not represent a significant improvement over no OCT visualization of the RRD (p = 0.175). Thus, with retinal drawings it is worth noting that RRDs close to the fovea are at risk of being labelled as far away and vice versa. We suspect that the bullous components of the RRD draw attention while flatter components are easier to miss. We suggest that the OCT be used more actively in RRD diagnosis to accurately communicate the RRD status to the patient and other healthcare personnel as well as aid ophthalmology residents in accurately interpreting ophthalmoscopic findings.

To train generative adversarial network (GAN) models to generate predictive optical coherence tomography (OCT) images of central serous chorioretinopathy (CSC) at 3months after observation using multi-modal OCT images. Four hundred forty CSC eyes of 440 patients who underwent Cirrus OCT imaging were included. Baseline OCT B-scan images through the foveal center, en face choroid, and en face ellipsoid zone were collected from each patient. The datasets were divided into training and validation (n = 390) and test (n = 50) sets. The input images for each model comprised either baseline B-scan alone or a combination of en face choroid and ellipsoid zones. Predictive post-treatment OCT B-scan images were generated using GAN models and compared with real 3-month images. Of 50 generated OCT images, there were 48, 47, and 48 acceptable images for UNIT, CycleGAN, and RegGAN, respectively. In comparison with real 3-month images, the generated images showed sensitivity, specificity, and positive predictive values (PPV) for residual fluid in the ranges of 0.762-1.000, 0.483-0.724, and 0.583-0.704; for pigment epithelial detachment (PED) of 0.917-1.000, 0.974-1.000, and 0.917-1.000; and for subretinal hyperreflective material (SHRM) of 0.667-0.778, 0.925-0.950 and 0.700-0.750, respectively. RegGAN exhibited the highest values except for sensitivity. GAN models could generate prognostic OCT images with good performance for prediction of residual fluid, PED, and SHRM presence in CSC. Implementation of the models may help predict disease activity in CSC, facilitating the establishment of a proper treatment plan.