Optical Coherence Tomography Signal Research Articles

Optical Assessment of Photoreceptor Function Over the Macula.

The purpose of this study was to develop next-generation functional photoreceptor imaging using ultrahigh-speed swept-source optical coherence tomography (UHS-SS-OCT) and split-spectrum amplitude-decorrelation optoretinography (SSADOR) algorithm. The advancement enables rapid surveying of large retinal areas, promising non-contact, objective, and quantifiable measurements of macular visual function. We designed and built a UHS-SS-OCT prototype instrument using a wavelength tunable laser with 1 MHz A-scan rate. The functional scanning protocol records 5 repeated volumes in 3 seconds. A flash pattern selectively exposes the imaged retina area. SSADOR quantifies photoreceptor light response by extracting optical coherence tomography (OCT) signal changes within the photoreceptor outer segment before and after the flash. The study prospectively enrolled 16 eyes from 8 subjects, demonstrating the ability to measure photoreceptor light response over a record field of view (3 × 3mm2) with high topographical resolution (approximately 100 µm). The measured SSADOR signal corresponds to the flashed pattern, whose amplitude also correlates with flash strength, showing consistency and reproducibility across subjects. The integration of high-performance UHS-SS-OCT and SSADOR enables characterizing photoreceptor function over a clinically meaningful field of view, while maintaining a workflow that can be integrated into routine clinical tests and trials. The new approach allows detecting changes in photoreceptor light response with high sensitivity and can detect small focal impairments. This innovative advance can enable us to detect early photoreceptor abnormalities, as well as help to stage and monitor degenerative retinal diseases, potentially providing a surrogate visual function marker for retinal diseases and accelerating therapeutic development through a safe and efficient outcome endpoint.

Polarization-resolved analysis of outer retinal bands: investigating ballistic and multiply scattered photons using full-field swept-source optical coherence tomography

Precise interpretation of the anatomical origins of outer retinal optical coherence tomography (OCT) presents technical challenges owing to the delicate nature of the retina. To address this challenge, our study introduces a novel polarization-sensitive full-field swept-source OCT (FF-SS-OCT) that provides parallel-polarization and cross-polarization OCT measurements, predominantly capturing ballistically reflected photons and multiply scattered photons, respectively. Notably, parallel-polarization OCT unveils layer-like structures more effectively, including the inner plexiform layer (IPL) sub-layers, outer plexiform layer (OPL) sub-layers (in rod-dominant regions), and rod/cone outer segment (OS) tips, compared to cross-polarization OCT, where such sub-layers are not visible. Through a comparative analysis of parallel-polarization and cross-polarization OCT images of the outer retina, we discovered that the 2nd outer retinal OCT band results from contributions from both the ellipsoid zone (EZ) and the inner segment/outer segment (IS/OS) junction. Similarly, the 3rd outer retinal OCT band appears to reflect contributions from both the interdigitation zone (IZ) and photoreceptor OS tips. This polarization-sensitive approach advances our understanding of the origins of outer retinal OCT signals and proposes potential new biomarkers for assessing retinal health and diseases.

Computationally efficient adaptive optimization of vector-method parameters for phase-sensitive strain estimation in optical coherence elastography

A new method for automatic adaptive optimization of strain estimation in phase-sensitive optical coherence tomography (OCT) is introduced. More specifically, this paper focuses on optimizing the estimation of strain using the vector method, in which OCT signals are treated as vectors in the complex plane. In phase-sensitive optical coherence elastography, the tissue strain is extracted from the interframe phase variation between the complex-valued scans acquired for the initial and deformed tissue. This phase variation is proportional to interframe displacements of scatterers and corresponds to the argument of the pixel-by-pixel product of the initial OCT scan and complex-conjugate deformed scan. Measurement noises and the so-called ‘speckle noise’ that are intrinsic to OCT scans cause degradation of the derived scan obtained by such multiplication. To mitigate the noise influence, complex-valued pixel amplitudes in the derived scan are usually averaged over a certain window. The interframe strain is found by estimating the gradient of the interframe phase difference. The noise influence on the strain estimation can also be reduced by increasing the scale over which the phase-variation gradient is estimated. However, choosing a too large window for preliminary averaging may significantly distort the reconstructed strain distribution. Similarly, a too large scale for gradient estimation may also cause errors in the estimated-strain magnitude and even its sign (because of possible phase wrapping). Therefore, appropriately performed adaptive choice of the strain-estimation parameters can greatly improve the quality of strain estimation. Here, we present a unified approach for adaptive choice of both the averaging-window size and gradient-estimation scale that were initially considered separately. The new method is computationally simplified but enables approximately the same strain-estimation quality, as demonstrated using both simulated and experimental OCT data.

Ergodic speckle contrast optical coherence tomography velocimetry of rapid blood flow.

Visualizing a 3D blood flow velocity field through noninvasive imaging is crucial for analyzing hemodynamic mechanisms in areas prone to disorders. However, traditional correlation-based optical coherence tomography (OCT) velocimetry techniques have a maximum measurable flow velocity depending on the A-line rate. We presented the ergodic speckle contrast OCT (ESCOCT) to break the bottleneck in measuring the rapid blood flow velocity. It achieved a measurement of blood flow velocity ranging from 9.5 to 280 mm/s using a 100 kHz swept-source (SS) OCT based on 100 A-repeats scanning mode. Addressing the non-ergodic problem of temporal OCT signals by integrating more consecutive A-scans, ESCOCT can enable the estimation for lower velocity flows by increasing A-repeats. ESCOCT provided a wide dynamic range with no upper limit on measuring blood flow velocity with an adequate signal-to-noise ratio and improved the sensitivity and accuracy of the hemodynamic assessment.

Calcified Drusen Prevent the Detection of Underlying Choriocapillaris Using Swept-Source Optical Coherence Tomography Angiography.

In age-related macular degeneration (AMD), choriocapillaris flow deficits (CCFDs) under soft drusen can be measured using established compensation strategies. This study investigated whether CCFDs can be quantified under calcified drusen (CaD). CCFDs were measured in normal eyes (n = 30) and AMD eyes with soft drusen (n = 30) or CaD (n = 30). CCFD density masks were generated to highlight regions with higher CCFDs. Masks were also generated for soft drusen and CaD based on both structural en face OCT images and corresponding B-scans. Dice similarity coefficients were calculated between the CCFD density masks and both the soft drusen and CaD masks. A phantom experiment was conducted to simulate the impact of light scattering that arises from CaD. Area measurements of CCFDs were highly correlated with those of CaD but not soft drusen, suggesting an association between CaD and underlying CCFDs. However, unlike soft drusen, the detected optical coherence tomography (OCT) signals underlying CaD did not arise from the defined CC layer but were artifacts caused by the multiple scattering property of CaD. Phantom experiments showed that the presence of highly scattering material similar to the contents of CaD caused an artifactual scattering tail that falsely generated a signal in the CC structural layer but the underlying flow could not be detected. Similarly, CaD also caused an artifactual scattering tail and prevented the penetration of light into the choroid, resulting in en face hypotransmission defects and an inability to detect blood flow within the choriocapillaris. Upon resolution of the CaD, the CC perfusion became detectable. The high scattering property of CaD leads to a scattering tail under these drusen that gives the illusion of a quantifiable optical coherence tomography angiography signal, but this signal does not contain the angiographic information required to assess CCFDs. For this reason, CCFDs cannot be reliably measured under CaD, and CaD must be identified and excluded from macular CCFD measurements.

K-Space Approach in Optical Coherence Tomography: Rigorous Digital Transformation of Arbitrary-Shape Beams, Aberration Elimination and Super-Refocusing beyond Conventional Phase Correction Procedures.

For the most popular method of scan formation in Optical Coherence Tomography (OCT) based on plane-parallel scanning of the illuminating beam, we present a compact but rigorous K-space description in which the spectral representation is used to describe both the axial and lateral structure of the illuminating/received OCT signals. Along with the majority of descriptions of OCT-image formation, the discussed approach relies on the basic principle of OCT operation, in which ballistic backscattering of the illuminating light is assumed. This single-scattering assumption is the main limitation, whereas in other aspects, the presented approach is rather general. In particular, it is applicable to arbitrary beam shapes without the need for paraxial approximation or the assumption of Gaussian beams. The main result of this study is the use of the proposed K-space description to analytically derive a filtering function that allows one to digitally transform the initial 3D set of complex-valued OCT data into a desired (target) dataset of a rather general form. An essential feature of the proposed filtering procedures is the utilization of both phase and amplitude transformations, unlike conventionally discussed phase-only transformations. To illustrate the efficiency and generality of the proposed filtering function, the latter is applied to the mutual transformation of non-Gaussian beams and to the digital elimination of arbitrary aberrations at the illuminating/receiving aperture. As another example, in addition to the conventionally discussed digital refocusing enabling depth-independent lateral resolution the same as in the physical focus, we use the derived filtering function to perform digital "super-refocusing." The latter does not yet overcome the diffraction limit but readily enables lateral resolution several times better than in the initial physical focus.

Automatic and real-time tissue sensing for autonomous intestinal anastomosis using hybrid MLP-DC-CNN classifier-based optical coherence tomography.

Anastomosis is a common and critical part of reconstructive procedures within gastrointestinal, urologic, and gynecologic surgery. The use of autonomous surgical robots such as the smart tissue autonomous robot (STAR) system demonstrates an improved efficiency and consistency of the laparoscopic small bowel anastomosis over the current da Vinci surgical system. However, the STAR workflow requires auxiliary manual monitoring during the suturing procedure to avoid missed or wrong stitches. To eliminate this monitoring task from the operators, we integrated an optical coherence tomography (OCT) fiber sensor with the suture tool and developed an automatic tissue classification algorithm for detecting missed or wrong stitches in real time. The classification results were updated and sent to the control loop of STAR robot in real time. The suture tool was guided to approach the object by a dual-camera system. If the tissue inside the tool jaw was inconsistent with the desired suture pattern, a warning message would be generated. The proposed hybrid multilayer perceptron dual-channel convolutional neural network (MLP-DC-CNN) classification platform can automatically classify eight different abdominal tissue types that require different suture strategies for anastomosis. In MLP, numerous handcrafted features (∼1955) were utilized including optical properties and morphological features of one-dimensional (1D) OCT A-line signals. In DC-CNN, intensity-based features and depth-resolved tissues' attenuation coefficients were fully exploited. A decision fusion technique was applied to leverage the information collected from both classifiers to further increase the accuracy. The algorithm was evaluated on 69,773 testing A-line data. The results showed that our model can classify the 1D OCT signals of small bowels in real time with an accuracy of 90.06%, a precision of 88.34%, and a sensitivity of 87.29%, respectively. The refresh rate of the displayed A-line signals was set as 300 Hz, the maximum sensing depth of the fiber was 3.6 mm, and the running time of the image processing algorithm was ∼1.56 s for 1,024 A-lines. The proposed fully automated tissue sensing model outperformed the single classifier of CNN, MLP, or SVM with optimized architectures, showing the complementarity of different feature sets and network architectures in classifying intestinal OCT A-line signals. It can potentially reduce the manual involvement of robotic laparoscopic surgery, which is a crucial step towards a fully autonomous STAR system.

Deep learning-based label-free imaging of lymphatics and aqueous veins in the eye using optical coherence tomography

We demonstrate an adaptation of deep learning for label-free imaging of the micro-scale lymphatic vessels and aqueous veins in the eye using optical coherence tomography (OCT). The proposed deep learning-based OCT lymphangiography (DL-OCTL) method was trained, validated and tested, using OCT scans (23 volumetric scans comprising 19,736 B-scans) from 11 fresh ex vivo porcine eyes with the corresponding vessel labels generated by a conventional OCT lymphangiography (OCTL) method based on thresholding with attenuation compensation. Compared to conventional OCTL, the DL-OCTL method demonstrates comparable results for imaging lymphatics and aqueous veins in the eye, with an Intersection over Union value of 0.79 ± 0.071 (mean ± standard deviation). In addition, DL-OCTL mitigates the imaging artifacts in conventional OCTL where the OCT signal modelling was corrupted by the tissue heterogeneity, provides ~ 10 times faster processing based on a rough comparison and does not require OCT-related knowledge for correct implementation as in conventional OCTL. With these favorable features, DL-OCTL promises to improve the practicality of OCTL for label-free imaging of lymphatics and aqueous veins for preclinical and clinical imaging applications.

Co-registered optical coherence tomography and X-ray angiography for the prediction of fractional flow reserve.

Cardiovascular disease (CVD) stands as the leading global cause of mortality, and coronary artery disease (CAD) has the highest prevalence, contributing to 42% of these fatalities. Recognizing the constraints inherent in the anatomical assessment of CAD, Fractional Flow Reserve (FFR) has emerged as a pivotal functional diagnostic metric. Herein, we assess the potential of employing an ensemble approach with deep neural networks (DNN) to predict invasively measured Fractional Flow Reserve (FFR) using raw anatomical data extracted from both optical coherence tomography (OCT) and X-ray coronary angiography (XA). In this study, we used a challenging dataset, with 46% of the lesions falling within the FFR range of 0.75 to 0.85. Despite this complexity, our model achieved an accuracy of 84.3%, demonstrating a sensitivity of 87.5% and a specificity of 81.4%. Our results demonstrate that incorporating both OCT and XA signals, co-registered, as inputs for the DNN model leads to an important increase in overall accuracy.

Linear multifractional stable motion for modeling of fluid-filled regions in retinal optical coherence tomography images

Fluid appears in several retinal disorders can be visualized by optical coherence tomography (OCT) images. Since manual survey of OCT images is challenging, automatic fluid detection is desirable. This paper develops a generalized multifractal framework to model the local scale-invariant property of retinal OCT signals and accordingly proposes a simple methodology for automatic localization of fluid-filled regions. The proposed framework comprises both local self-similarity and heavy tailed distribution of OCT signals by generalization of fractional Levy stable motion (fLsm) to the Riemann-Liouville multifractional Levy stable motion (RL-mLsm). In order to measure the multifractality appears in RL-mLsm, the scaling properties of Levy flights and stochastic differential equations (SDEs) are used to develop a fractional momentbased algorithm namely, multi-fractional Levy fluctuation analysis (MLFA) algorithm. Here, we apply MLFA to model OCT images. Modeling results indicate the significant difference between the multifractal bandwidth in non-fluid and fluid regions. In addition, by utilizing various surrogate series of the signals, we discover the source of multifractality of OCT signals. As an application of the proposed multifractal modeling, we propose a new method, based on simple clustering of estimated local scaling exponent of modeled OCT signals, to localize fluid regions in OCT images. The localization method is validated, and the experimental results reveal the superiority of proposed method. Overall, the proposed multifractal framework has full advantages on excellent improvement of fluid localization, which promises the proposed model is suitable for effective description of self-similar nature of normal and abnormal OCT images independent of capturing device.

MCOCT: an experimentally and numerically validated, open-source Monte Carlo simulator for optical coherence tomography.

Here, we present MCOCT, a Monte Carlo simulator for optical coherence tomography (OCT), incorporating a Gaussian illumination scheme and bias to increase backscattered event collection. MCOCT optical fluence was numerically compared and validated to an established simulator (MCX) and showed concordance at the focus while diverging slightly with distance to it. MCOCT OCT signals were experimentally compared and validated to OCT signals acquired in tissue-mimicking phantoms with known optical properties and showed a similar attenuation pattern with increasing depth while diverging beyond 1.5 mm and proximal to layer interfaces. MCOCT may help in the design of OCT systems for a wide range of applications.

Optics and quantitative assessment of corneal transparency

While some optical properties of cornea like its stromal birefringence had been known since the early nineteenth century, theories explaining its transparency remained inconclusive until the publication of David Maurice' emblematic paper in 1957 Maurice made a model calculation of light scattering by a single collagen fibril as a “dielectric needle”. The volume density of the fibrils being known, Maurice could demonstrate that in the absence of any order among the fibrils the cornea would be opaque. Maurice postulated the hexagonal structure which since has been confirmed by electron microscopy. In modern terms, the order among the collagen fibrils within a stromal collagen lamella is described by a “structure factor” in the radiative transfer equation. This term corresponds to a description of the structure in reciprocal space and is thus equivalent to the representation of crystalline lattices in the first Brillouin zone used for structural modelling in crystallography.In a recent study we further analysed the collagen structure of healthy and oedematous corneas on a nanometric level observed by transmission electron microscopy (TEM). By automated image analysis we could retrieve the so‐called “pair correlation function” and calculate light attenuation within the corresponding cornea. Our findings show that the 1/e light penetration depth within healthy cornea could be calculated as 7300 ± 800 μm, which explains well the transparency of healthy cornea. However, the photon mean free path of oedematous cornea turned out to be from two to three times that value. In oedematous cornea, the “dilution” effect of the scatters is in fact stronger than the degradation of transparency by the perturbation of the structure. The actual loss of transparency in oedematous cornea may therefore be attributed to scattering processes at the micrometric level induced by the augmented optical contrast at the sites of the keratocytes between the collagen lamellae.Perturbations in corneal transparency do not only hamper vision, they also impact optical imaging methods on cornea. This, in turn, permits to study the transparency properties of the corneal tissue. One of the main research interests of our group is to analyse corneal images recorded by optical coherence tomography (OCT) and to extract quantitative parameters like photon mean path length and the fraction of coherently transmitted light.Our partners could show that in the light scattering regime, a term in the radiation transfer equation may be neglected and the attenuation of the full field OCT signal in the volume of the tissue reduces to a Lambert–Beer law. We developed a data analysis algorithm based on Bayesian inference to extract the attenuation coefficient and used it for the analysis of ex vivo corneal high‐resolution FF‐OCT images.In a second step, we developed an image processing algorithm for clinical OCT images removing typical artefacts and compensating for inhomogeneous illumination and corneal curvature. We presently are able to extract corneal transparency parameters from routine clinical OCT images and to provide post‐op follow‐up after keratoplasty or other surgical interventions.

Understanding the coaxial optical coherence tomography signal during the laser welding of hidden T-joints

In the case of “hidden” T-joints, the nonvisible web sheet is welded through the face sheet. Positioning tolerances and movement due to the distortion of the web sheet represent the main challenges to maintain on track during laser beam welding. This study investigated the assumption that keyhole monitoring based on optical coherence tomography (OCT) could be utilized for seam tracking by detecting critical misalignments between the laser beam and the web sheet position. It hereby analyzed whether an emerging misalignment between the laser beam and the web sheet could be discerned in the OCT data before the laser beam misses the web sheet and penetrated only the face sheet. This prediction represents a key requirement for the industrial use of this approach. To this end, this study investigated the welding of hidden T-joints with angular and parallel offsets of the laser path relative to the web sheet centerline while recording with OCT. The interface zone between the web and face sheets was recorded by a high-speed camera to detect the transmission of laser radiation through a lower keyhole opening. It was shown that a lower keyhole opening, in combination with transmitted radiation, was advantageous for the reliable detection of an emerging misalignment. This lower keyhole opening can occur lateral to the web sheet prior to a misalignment, therefore enabling a prediction of spot misalignments via OCT. The welding parameter dependent maximum distance of the laser spot edge to the web sheet edge at detection was 0.1 mm in this study.

Poster Session II: Investigating photoreceptor function in disease-affected retinas using optoretinography.

Assessing the functional response of photoreceptors is vital in understanding retinal disease progression. Traditional subjective methods like visual acuity and visual fields, and objective ones like electroretinography, have limitations. An ideal complement to these techniques is optoretinography (ORG), which images the retina and tests its function at once. ORG utilizes the phase of the optical coherence tomography (OCT) signal to quantify nanometer-scale changes, measuring subtle photoreceptor responses to stimuli. Efforts to observe stimulus-evoked responses in human cone photoreceptors began with adaptive optics (AO) and common path interferometry, enabling the resolution and tracking of individual cells. Advances in OCT systems with cellular resolution through AO or digital aberration correction successfully measured ORG responses from single cones and rods. This method tracks phase differences between outer segment tips (COST or ROST) and the inner-outer segment junction (IS/OS) to assess individual cell responses. A novel velocity-based method recently demonstrated the feasibility of measuring ORG signals with clinical-grade OCT systems. In the present work, we implemented this technique on disease-affected human retinas, revealing lower magnitudes of response compared to healthy retinas, and highlighting its potential clinical applications.

Axial super-resolution optical coherence tomography via complex-valued network

Optical coherence tomography (OCT) is a fast and non-invasive optical interferometric imaging technique that can provide high-resolution cross-sectional images of biological tissues. OCT’s key strength is its depth resolving capability which remains invariant along the imaging depth and is determined by the axial resolution. The axial resolution is inversely proportional to the bandwidth of the OCT light source. Thus, the use of broadband light sources can effectively improve the axial resolution and however leads to an increased cost. In recent years, real-valued deep learning technique has been introduced to obtain super-resolution optical imaging. In this study, we proposed a complex-valued super-resolution network (CVSR-Net) to achieve an axial super-resolution for OCT by fully utilizing the amplitude and phase of OCT signal. The method was evaluated on three OCT datasets. The results show that the CVSR-Net outperforms its real-valued counterpart with a better depth resolving capability. Furthermore, comparisons were made between our network, six prevailing real-valued networks and their complex-valued counterparts. The results demonstrate that the complex-valued network exhibited a better super-resolution performance than its real-valued counterpart and our proposed CVSR-Net achieved the best performance. In addition, the CVSR-Net was tested on out-of-distribution domain datasets and its super-resolution performance was well maintained as compared to that on source domain datasets, indicating a good generalization capability.

Bond-selective full-field optical coherence tomography.

Optical coherence tomography (OCT) is a label-free, non-invasive 3D imaging tool widely used in both biological research and clinical diagnosis. Conventional OCT modalities can only visualize specimen tomography without chemical information. Here, we report a bond-selective full-field OCT (BS-FF-OCT), in which a pulsed mid-infrared laser is used to modulate the OCT signal through the photothermal effect, achieving label-free bond-selective 3D sectioned imaging of highly scattering samples. We first demonstrate BS-FF-OCT imaging of 1 µm PMMA beads embedded in agarose gel. Next, we show 3D hyperspectral imaging of up to 75 µm of polypropylene fiber mattress from a standard surgical mask. We then demonstrate BS-FF-OCT imaging on biological samples, including cancer cell spheroids and C. elegans. Using an alternative pulse timing configuration, we finally demonstrate the capability of BS-FF-OCT on imaging a highly scattering myelinated axons region in a mouse brain tissue slice.

An Evaluation of Lymphedema Using Optical Coherence Tomography: A Rat Limb Model Approach.

Lymphedema is a pathology caused by poor lymphatic flow which may lead to complete disability. Currently, precise, non-invasive techniques for quantifying lymphedema are lacking. In this paper, the results of an in vivo assessment of lymphedema via a developed small-animal model using the hindlimbs of rats and an optical coherence tomography (OCT) technique are presented. This model of lymphedema was based on a surgical lymph node resection and subsequent two-step X-ray exposure. The development of lymphedema was verified via the histological examination of tissue biopsies. The properties of the lymphedematous skin were analyzed in vivo and compared with healthy skin via OCT. The main differences observed were (1) a thickening of the stratum corneum layer, (2) a thinning of the viable epidermis layer, and (3) higher signal attenuation in the dermis layer of the lymphedematous skin. Based on the distribution of the OCT signal's intensity in the skin, a machine learning algorithm was developed which allowed for a classification of normal and lymphedematous tissue sites with an accuracy of 90%. The obtained results pave the way for in vivo control over the development of lymphedema.

Depth-dependent attenuation and backscattering characterization of optical coherence tomography by stationary iterative method.

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.

Ex-vivo analysis of demineralisation on irradiated teeth using optical coherence tomography

Head and neck cancer patients are prone to dental caries after radiotherapy. An ex-vivo study was conducted to assess the feasibility of optical coherence tomography (OCT) to detect tooth demineralization due to caries in irradiated teeth. Thirty-nine human molar teeth were subjected to caries lesion induction through irradiation (Group 1), pH cycling (Group 2–1), and both (Group 2–2). The OCT signal attenuation coefficient, µR was assessed and validated against microhardness test and scanning electron microscope (SEM). The µR for Group 1 increased from 10 Gy to 40 Gy, and subsequently decreased after irradiated to 50 Gy and 60 Gy due to damaged enamel microstructure. In Group 2–1, the µR decreased with duration of pH cycling from day 1 to day 14 due to the increase of porosity in enamel layer. However, the µR showed decreasing trend from day 14 to day 28 of pH cycling, resulted from mineral deposition in the enamel layer. Although no significant difference was found in the µR between Group 2–1 and 2–2, SEM of Group 2–2 demonstrated visually higher porosity and larger gaps between microstructures. Irradiation may accelerate caries damage to tooth microstructure by increasing its porosity and brittleness, but larger sample size may be needed to further prove the effect. OCT could potentially be used for early detection of tooth demineralization in vivo based on the measurable µR changes for all groups which are shown negatively correlated with microhardness value (p < 0.05).

Association of Retinal Pigment Epithelium Reflectivity on Optical Coherence Tomography with Recurrence of Vogt-Koyanagi-Harada Disease: A Retrospective Observational Study.

Despite the necessity of optical coherence tomography (OCT) for diagnosis and longitudinal monitoring in patients with Vogt-Koyanagi-Harada (VKH) disease, no studies have identified useful OCT markers for predicting recurrence in these patients. Although the precise reason for this remains unclear, one possibility is that infiltration of inflammatory cells into the choroid attenuates the OCT signal, making it difficult to precisely assess the structure of the choroid. Therefore, this study aimed to investigate changes in retinal pigment epithelium (RPE) reflectivity immediately above the choroid in eyes with acute VKH disease, as well as the association between RPE reflectivity and VKH disease recurrence. This single-centered retrospective observational study included 20 treatment-naïve patients with acute VKH disease presenting with serous retinal detachment (SRD) in the posterior pole at the initial visit between October 2015 and January 2020, as well as 15 healthy control eyes. All patients were followed up for at least 6 months and received treatment with intravenous methylprednisolone followed by oral administration of prednisolone. Swept-source OCT images through the fovea were used to measure central retinal thickness, central choroidal thickness, and RPE reflectivity. During an observation period of 37.2 ± 30.8 months, recurrence of inflammation was observed in 11 patients (55.0%). Initial visual acuity was worse in patients who developed recurrence than in those who did not (P=0.024). On initial OCT images, RPE reflectivity differed significantly between patients with and without recurrence (1.75 ± 0.42 vs 1.35 ± 0.20; P=0.018), while there were no significant differences in other chorioretinal parameters, such as central retinal thickness and choroidal thickness. RPE reflectivity on OCT images may be useful for predicting the recurrence of inflammation in patients with VKH disease.