Time-Resolved Ultra–High Resolution Optical Coherence Tomography for Real-Time Monitoring of Selective Retina Therapy

Purpose: Selective retina therapy (SRT) is a novel treatment for retinal pathologies, solely targeting the retinal pigment epithelium (RPE). During SRT, the detection of an immediate tissue reaction is challenging as tissue effects remain limited to intracellular RPE photodisruption. Time-resolved ultra-high axial resolution optical coherence tomography (OCT) is thus evaluated for the monitoring of dynamic optical changes at and around the RPE during SRT. Methods: An experimental OCT system with an ultra-high axial resolution of 1.78 µm was combined with an SRT system and time-resolved OCT M-scans of the target area were recorded from four patients undergoing SRT. OCT scans were analyzed and OCT morphology was correlated with findings in fluorescein angiography, fundus photography and cross-sectional OCT. Results: In cases where the irradiation caused RPE damage proven by fluorescein angiography, the lesions were well discernible in time-resolved OCT images but remained invisible in fundus photography and cross-sectional OCT acquired after treatment. If RPE damage was introduced, all applied SRT pulses led to detectable signal changes in the time-resolved OCT images. The extent of optical signal variation seen in the OCT data appeared to scale with the applied SRT pulse energy. Conclusion: The first clinical results proved that successful SRT irradiation induces detectable changes in the OCT M-scan signal while it remains invisible in conventional ophthalmoscopic imaging. Thus, real-time high-resolution OCT is a promising modality to monitor and analyze tissue effects introduced by selective retina therapy and may be used to guide SRT in an automatic feedback mode.

SCAD: Sensor Context-aware Adaptive Duty-cycled Beaconless Opportunistic Routing for WSNs

Low quality of wireless links leads to perpetual transmission failures in lossy wireless environments. To mitigate this problem, opportunistic routing (OR) has been proposed to improve the throughput of wireless multihop ad-hoc networks by taking advantage of the broadcast nature of wireless channels. However, OR can not be directly applied to wireless sensor networks (WSNs) due to some intrinsic design features of WSNs. In this paper, we present a new OR solution for WSNs with suitable adaptations to their characteristics. Our protocol, called SCAD-Sensor Context-aware Adaptive Duty-cycled beaconless opportunistic routing protocol is a cross-layer routing approach and it selects packet forwarders based on multiple sensor context information. To reach a balance between performance and energy-efficiency, SCAD adapts the duty-cycles of sensors according to real-time traffic loads and energy drain rates. We compare SCAD against other protocols through extensive simulations. Evaluation results show that SCAD outperforms other protocols in highly dynamic scenarios.

Quantitative Analysis of Mouse Retinal Layers Using Automated Segmentation of Spectral Domain Optical Coherence Tomography Images.

PURPOSE Quantification of retinal layers using automated segmentation of optical coherence tomography (OCT) images allows for longitudinal studies of retinal and neurological disorders in mice. The purpose of this study was to compare the performance of automated retinal layer segmentation algorithms with data from manual segmentation in mice using the Spectralis OCT. METHODS Spectral domain OCT images from 55 mice from three different mouse strains were analyzed in total. The OCT scans from 22 C57Bl/6, 22 BALBc, and 11 C3A.Cg-Pde6b(+)Prph2(Rd2) /J mice were automatically segmented using three commercially available automated retinal segmentation algorithms and compared to manual segmentation. RESULTS Fully automated segmentation performed well in mice and showed coefficients of variation (CV) of below 5% for the total retinal volume. However, all three automated segmentation algorithms yielded much thicker total retinal thickness values compared to manual segmentation data (P < 0.0001) due to segmentation errors in the basement membrane. CONCLUSIONS Whereas the automated retinal segmentation algorithms performed well for the inner layers, the retinal pigmentation epithelium (RPE) was delineated within the sclera, leading to consistently thicker measurements of the photoreceptor layer and the total retina. TRANSLATIONAL RELEVANCE The introduction of spectral domain OCT allows for accurate imaging of the mouse retina. Exact quantification of retinal layer thicknesses in mice is important to study layers of interest under various pathological conditions.

A study of the time complexity of an Elitist Genetic Algorithm used for associating optical observations of MEO and GEO Space Debris

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both the correct associations among the observations, and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. Where S stands for the number of ’fences’ used in the problem, each fence consists of a set of observations that all originate from dierent targets. For a dimension of S ˃ the MTT problem becomes NP-hard. As of now no algorithm exists that can solve an NP-hard problem in an optimal manner within a reasonable (polynomial) computation time. However, there are algorithms that can approximate the solution with a realistic computational e ort. To this end an Elitist Genetic Algorithm is implemented to approximately solve the S ˃ MTT problem in an e cient manner. Its complexity is studied and it is found that an approximate solution can be obtained in a polynomial time. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to e ciently process large data sets with minimal manual intervention.

Streak detection algorithm for space debris detection on optical images.

Any image processing object detection algorithm somehow tries to integrate the object light (Recognition Step) and applies statistical criteria to distinguish objects of interest from other objects or from pure background (Decision Step). There are various possibilities how these two basic steps can be realized, as can be seen in the different proposed detection methods in the literature. An ideal detection algorithm should provide high recognition sensitiv ity with high decision accuracy and require a reasonable computation effort . In reality, a gain in sensitivity is usually only possible with a loss in decision accuracy and with a higher computational effort. So, automatic detection of faint streaks is still a challenge. This paper presents a detection algorithm using spatial filters simulating the geometrical form of possible streaks on a CCD image. This is realized by image convolution. The goal of this method is to generate a more or less perfect match between a streak and a filter by varying the length and orientation of the filters. The convolution answers are accepted or rejected according to an overall threshold given by the ackground statistics. This approach yields as a first result a huge amount of accepted answers due to filters partially covering streaks or remaining stars. To avoid this, a set of additional acceptance criteria has been included in the detection method. All criteria parameters are justified by background and streak statistics and they affect the detection sensitivity only marginally. Tests on images containing simulated streaks and on real images containing satellite streaks show a very promising sensitivity, reliability and running speed for this detection method. Since all method parameters are based on statistics, the true alarm, as well as the false alarm probability, are well controllable. Moreover, the proposed method does not pose any extraordinary demands on the computer hardware and on the image acquisition process.

Photometric monitoring of non-resolved space debris and databases of optical light curves.

The population of space debris increased drastically during the last years. Collisions involving massive objects may produce large number of fragments leading to significantly growth of the space debris population. An effective remediation measure in order to stabilize the population in LEO, is therefore the removal of large, massive space debris. To remove these objects, not only precise orbits, but also more detailed information about their attitude states will be required. One important property of an object targeted for removal is its spin period and spin axis orientation. If we observe a rotating object, the observer sees different surface areas of the object which leads to changes in the measured intensity. Rotating objects will produce periodic brightness vari ations with frequencies which are related to the spin periods. Photometric monitoring is the real tool for remote diagnostics of the satellite rotation around its center of mass. This information is also useful, for example, in case of contingency. Moreover, it is also important to take into account the orientation of non-spherical body (e.g. space debris) in the numerical integration of its motion when a close approach with the another spacecr aft is predicted. We introduce the two databases of light curves: the AIUB data base, which contains about a thousand light curves of LEO, MEO and high-altitude debris objects (including a few functional objects) obtained over more than seven years, and the data base of the Astronomical Observatory of Odessa University (Ukraine), which contains the results of more than 10 years of photometric monitoring of functioning satellites and large space debris objects in low Earth orbit. AIUB used its 1m ZIMLAT telescope for all light curves. For tracking low-orbit satellites, the Astronomical Observatory of Odessa used the KT-50 telescope, which has an alt-azimuth mount and allows tracking objects moving at a high angular velocity. The diameter of the KT-50 main mirror is 0.5 m, and the focal length is 3 m. The Odessa's Atlas of light curves includes almost 5,5 thousand light curves for ~500 correlated objects from a time period of 2005-2014. The processing of light curves and the determination of the rotation period in the inertial frame is challenging. Extracted frequencies and reconstructed phases for some interesting targets, e.g. GLONASS satellites, for which also SLR data were available for confirmation, will be presented. The rotation of the Envisat satellite after its sudden failure will be analyzed. The deceleration of its rotation rate within 3 years is studied together with the attempt to determine the orientation of the rotation axis.

Real-Time In Vivo Characterization of Primary Liver Tumors With Diffuse Optical Spectroscopy During Percutaneous Needle Interventions: Feasibility Study in Woodchucks

OBJECTIVE This study presents the first in vivo real-time optical tissue characterization during image-guided percutaneous intervention using near-infrared diffuse optical spectroscopy sensing at the tip of a needle. The goal of this study was to indicate transition boundaries from healthy tissue to tumors, namely, hepatic carcinoma, based on the real-time feedback derived from the optical measurements. MATERIALS AND METHODS Five woodchucks with hepatic carcinoma were used for this study. The woodchucks were imaged with contrast-enhanced cone beam computed tomography with a flat panel detector C-arm system to visualize the carcinoma in the liver. In each animal, 3 insertions were performed, starting from the skin surface toward the hepatic carcinoma under image guidance. In 2 woodchucks, each end point of the insertion was confirmed with pathologic examination of a biopsy sample. While advancing the needle in the animals under image guidance such as fluoroscopy overlaid with cone beam computed tomography slice and ultrasound, optical spectra were acquired at the distal end of the needles. Optical tissue characterization was determined by translating the acquired optical spectra into clinical parameters such as blood, water, lipid, and bile fractions; tissue oxygenation levels; and scattering amplitude related to tissue density. The Kruskal-Wallis test was used to study the difference in the derived clinical parameters from the measurements performed within the healthy tissue and the hepatic carcinoma. Kurtoses were calculated to assess the dispersion of these parameters within the healthy and carcinoma tissues. RESULTS Blood and lipid volume fractions as well as tissue oxygenation and reduced scattering amplitude showed to be significantly different between the healthy part of the liver and the hepatic carcinoma (P < 0.05) being higher in normal liver tissue. A decrease in blood and lipid volume fractions and tissue oxygenation as well as an increase in scattering amplitude were observed when the tip of the needle crossed the margin from the healthy liver tissue to the carcinoma. The kurtosis for each derived clinical parameter was high in the hepatic tumor as compared with that in the healthy liver indicating intracarcinoma variability. CONCLUSIONS Tissue blood content, oxygenation level, lipid content, and tissue density all showed significant differences when the needle tip was guided from the healthy tissue to the carcinoma and can therefore be used to identify tissue boundaries during percutaneous image-guided interventions.

Differentiation of Diabetic Macular Edema From Pseudophakic Cystoid Macular Edema by Spectral-Domain Optical Coherence Tomography.

PURPOSE: To differentiate diabetic macular edema (DME) from pseudophakic cystoid macular edema (PCME) based solely on spectral-domain optical coherence tomography (SD-OCT). METHODS: This cross-sectional study included 134 participants: 49 with PCME, 60 with DME, and 25 with diabetic retinopathy (DR) and ME after cataract surgery. First, two unmasked experts classified the 25 DR patients after cataract surgery as either DME, PCME, or mixed-pattern based on SD-OCT and color-fundus photography. Then all 134 patients were divided into two datasets and graded by two masked readers according to a standardized reading-protocol. Accuracy of the masked readers to differentiate the diseases based on SD-OCT parameters was tested. Parallel to the masked readers, a computer-based algorithm was established using support vector machine (SVM) classifiers to automatically differentiate disease entities. RESULTS: The masked readers assigned 92.5% SD-OCT images to the correct clinical diagnose. The classifier-accuracy trained and tested on dataset 1 was 95.8%. The classifier-accuracy trained on dataset 1 and tested on dataset 2 to differentiate PCME from DME was 90.2%. The classifier-accuracy trained and tested on dataset 2 to differentiate all three diseases was 85.5%. In particular, higher central-retinal thickness/retinal-volume ratio, absence of an epiretinal-membrane, and solely inner nuclear layer (INL)-cysts indicated PCME, whereas higher outer nuclear layer (ONL)/INL ratio, the absence of subretinal fluid, presence of hard exudates, microaneurysms, and ganglion cell layer and/or retinal nerve fiber layer cysts strongly favored DME in this model. CONCLUSIONS: Based on the evaluation of SD-OCT, PCME can be differentiated from DME by masked reader evaluation, and by automated analysis, even in DR patients with ME after cataract surgery. The automated classifier may help to independently differentiate these two disease entities and is made publicly available.

Dynamic Unicast: Information-Centric Multi-hop Routing for Mobile Ad-hoc Networks

Abstract Information-centric networking (ICN) offers new perspectives on mobile ad-hoc communication because routing is based on names but not on endpoint identifiers. Since every content object has a unique name and is signed, authentic content can be stored and cached by any node. If connectivity to a content source breaks, it is not necessarily required to build a new path to the same source but content can also be retrieved from a closer node that provides the same content copy. For example, in case of collisions, retransmissions do not need to be performed over the entire path but due to caching only over the link where the collision occurred. Furthermore, multiple requests can be aggregated to improve scalability of wireless multi-hop communication. In this work, we base our investigations on Content-Centric Networking (CCN), which is a popular {ICN} architecture. While related works in wireless {CCN} communication are based on broadcast communication exclusively, we show that this is not needed for efficient mobile ad-hoc communication. With Dynamic Unicast requesters can build unicast paths to content sources after they have been identified via broadcast. We have implemented Dynamic Unicast in CCNx, which provides a reference implementation of the {CCN} concepts, and performed extensive evaluations in diverse mobile scenarios using NS3-DCE, the direct code execution framework for the {NS3} network simulator. Our evaluations show that Dynamic Unicast can result in more efficient communication than broadcast communication, but still supports all {CCN} advantages such as caching, scalability and implicit content discovery.

Enhanced depth imaging optical coherence tomography of congenital cavitary optic disc anomaly (CODA).

AIM To report the finding of extension of the 4th hyper-reflective band and retinal tissue into the optic disc in patients with cavitary optic disc anomalies (CODAs). METHODS In this observational study, 10 patients (18 eyes) with sporadic or autosomal dominant CODA were evaluated with enhanced depth imaging optical coherence tomography (EDI-OCT) and colour fundus images for the presence of 4th hyper-reflective band extension into the optic disc. RESULTS Of 10 CODA patients (18 eyes), five patients (8 eyes) showed a definite 4th hyper-reflective band (presumed retinal pigment epithelium (RPE)) extension into the optic disc. In these five patients (seven eyes), the inner retinal layers also extended with the 4th hyper-reflective band into the optic disc. Best corrected visual acuity ranged from 20/20 to 20/200. In three patients (four eyes), retinal splitting/schisis was present and in two patients (two eyes), the macula was involved. In all cases, the 4th hyper-reflective band extended far beyond the termination of the choroid into the optic disc. The RPE extension was found either temporally or nasally in areas of optic nerve head excavation, most often adjacent to peripapillary pigment. Compared with eyes without RPE extension, eyes with RPE extension were more myopic (mean dioptres -0.9±2.6 vs -8.8±5, p=0.043). CONCLUSIONS The RPE usually stops near the optic nerve border separated by a border tissue. With CODA, extension of this hyper-reflective band and retinal tissue into the disc is possible and best evaluable using EDI-OCT or analogous image modalities. Whether this is a finding specific for CODA, linked to specific gene loci or is also seen in patients with other optic disc abnormalities needs further evaluation.

SPECTRAL DOMAIN-OPTICAL COHERENCE TOMOGRAPHY IMAGE CONTRAST AND BACKGROUND COLOR SETTINGS INFLUENCE IDENTIFICATION OF RETINAL STRUCTURES.

PURPOSE To evaluate image contrast and color setting on assessment of retinal structures and morphology in spectral-domain optical coherence tomography. METHODS Two hundred and forty-eight Spectralis spectral-domain optical coherence tomography B-scans of 62 patients were analyzed by 4 readers. B-scans were extracted in 4 settings: W + N = white background with black image at normal contrast 9; W + H = white background with black image at maximum contrast 16; B + N = black background with white image at normal contrast 12; B + H = black background with white image at maximum contrast 16. Readers analyzed the images to identify morphologic features. Interreader correlation was calculated. Differences between Fleiss-kappa correlation coefficients were examined using bootstrap method. Any setting with significantly higher correlation coefficient was deemed superior for evaluating specific features. RESULTS Correlation coefficients differed among settings. No single setting was superior for all respective spectral-domain optical coherence tomography parameters (P = 0.3773). Some variables showed no differences among settings. Hard exudates and subretinal fluid were best seen with B + H (κ = 0.46, P = 0.0237 and κ = 0.78, P = 0.002). Microaneurysms were best seen with W + N (κ = 0.56, P = 0.025). Vitreomacular interface, enhanced transmission signal, and epiretinal membrane were best identified using all color/contrast settings together (κ = 0.44, P = 0.042, κ = 0.57, P = 0.01, and κ = 0.62, P ≤ 0.0001). CONCLUSION Contrast and background affect the evaluation of retinal structures on spectral-domain optical coherence tomography images. No single setting was superior for all features, though certain changes were best seen with specific settings.