Visual Research Articles

Spatially Localized Visual Perception Estimation by Means of Prosthetic Vision Simulation

Retinal prosthetic devices aim to repair some vision in visually impaired patients by electrically stimulating neural cells in the visual system. Although there have been several notable advancements in the creation of electrically stimulated small dot-like perceptions, a deeper comprehension of the physical properties of phosphenes is still necessary. This study analyzes the influence of two independent electrode array topologies to achieve single-localized stimulation while the retina is electrically stimulated: a two-dimensional (2D) hexagon-shaped array reported in clinical studies and a patented three-dimensional (3D) linear electrode carrier. For both, cell stimulation is verified in COMSOL Multiphysics by developing a lifelike 3D computational model that includes the relevant retinal interface elements and dynamics of the voltage-gated ionic channels. The evoked percepts previously described in clinical studies using the 2D array are strongly associated with our simulation-based findings, allowing for the development of analytical models of the evoked percepts. Moreover, our findings identify differences between visual sensations induced by the arrays. The 2D array showed drawbacks during stimulation; similarly, the state-of-the-art 2D visual prostheses provide only dot-like visual sensations in close proximity to the electrode. The 3D design could offer a technique for improving cell selectivity because it requires low-intensity threshold activation which results in volumes of stimulation similar to the volume surrounded by a solitary RGC. Our research establishes a proof-of-concept technique for determining the utility of the 3D electrode array for selectively activating individual RGCs at the highest density via small-sized electrodes while maintaining electrochemical safety.

Prediction of Salicornia europaea L. biomass using a computer vision system to distinguish different salt-tolerant populations.

Salicornia europaea L. is emerging as a versatile crop halophyte, requiring a low-cost, non-destructive method for salt tolerance classification to aid selective breeding. We propose using a computer vision system (CVS) with multivariate analysis to classify S. europaea based on morphometric and colour traits to predict plant biomass and the salinity in their substrate. A trial and validation set of 96 and 24 plants from 2 populations confirmedthe efficacy. CVS and multivariate analysis evaluated the plants by morphometric traits and CIELab colour variability. Through Pearson analysis, the strongest correlations were between biomass fresh weight (FW) vs. projected area (PA) (0.91) and anatomical cross-section (ACS) vs. shoot diameter (Sd) (0.94). The PA and FW correlation retrieved different equation fits between lower and higher salt-tolerant populations (R2 = 0.93 for linear and 0.90 for 2nd-degree polynomial), respectively. The higher salt-tolerant reached a maximum biomass PA at 400 mM NaCl, while the lower salt-tolerant produced less under 200 and 400 mM. A second Pearson correlation and PCA described sample variability with 80% reliability using only morphometric-colour parameters. Multivariate discriminant analysis (MDA) demonstrated that the method correctly classifies plants (90%) depending on their salinity level and tolerance, which was validated with 100% effectiveness. Through multiple linear regression, a predictive model successfully estimated biomass production by PA, and a second model predicted the salinity substrate (Sal.s.) where the plants thrive. Plants' Sd and height influenced PA prediction, while Sd and colour difference (ΔE1) influenced Sal.s. Models validation of actual vs. predicted values showed a R2 of 0.97 and 0.90 for PA, and 0.95 and 0.97 for Sal.s. for lower and higher salt-tolerant, respectively. This outcome confirms the method as a cost-effective tool for managing S. europaea breeding. The CVS effectively extracted morphological and colour features from S. europaea cultivated at different salinity levels, enabling classification and plant sorting through image and multivariate analysis. Biomass and salinity substrate were accurately predicted by modelling non-destructive parameters. Enhanced by AI, machine learning and smartphone technology, this method shows great potential in ecology, bio-agriculture, and industry.

Image-processing-based model for surface roughness evaluation in titanium based alloys using dual tree complex wavelet transform and radial basis function neural networks.

In this study, we examine the assessment of surface roughness on turned surfaces of Ti 6Al 4V using a computer vision system. We utilize the Dual-Tree Complex Wavelet Transform (DTCWT) to break down the images of the turned surface into sub-images oriented in directions. Three different methods of feature generation have been compared, i.e., the use of Gray-Level Co-Occurrence Matrix (GLCM) and DTCWT-based extraction of second-order statistical features, DTCWT Image fusion, and the use of GLCM for feature extraction, and DTCWT image fusion using Particle Swarm Optimization (PSO) based GLCM features. Principal Component Analysis (PCA) was utilized to identify and select features. The model was developed using a Radial Basis Function Neural Network (RBFNN). Accordingly, six models were designed based on the three feature generation methods, considering all features and features selected using PCA. The RBFNN model, which incorporates DTCWT Image fusion and utilizes PSO with PCA features, achieved a training data prediction accuracy of 100% and a test data prediction accuracy of 99.13%.

Electrophysiology in ophthalmology

Electrophysiological examinations are used in ophthalmology to determine the functionality of the neurons of the visual pathway. As electrophysiological examinations are independent of the subjective perception and response of the patient, they are considered to be objective functional diagnostics of vision. Electroretinography (ERG) is used to examine the retina (especially the photoreceptors), electro-oculography (EOG) is used to examine the functionality of the retinal pigment epithelium and visually evoked potentials (VEP) are used to evaluate the integrity of the entire visual pathway. Abnormalities in electrophysiological responses should always be interpreted in the context of other functional and morphological findings.

Large Scale Ultrafast Manufacturing of Wireless Soft Bioelectronics Enabled by Autonomous Robot Arm Printing Assisted by a Computer Vision-Enabled Guidance System for Personalized Wound Healing.

A Customized wound patch for Advanced tissue Regeneration with Electric field (CARE), featuring an autonomous robot arm printing system guided by a computer vision-enabled guidance system for fast image recognition is introduced. CARE addresses the growing demand for flexible, stretchable, and wireless adhesive bioelectronics tailored for electrotherapy, which is suitable for rapid adaptation to individual patients and practical implementation in a comfortable design. The visual guidance system integrating a 6-axis robot arm enables scans from multiple angles to provide a 3D map of complex and curved wounds. The size of electrodes and the geometries of power-receiving coil are essential components of the CARE and are determined by a MATLAB simulation, ensuring efficient wireless power transfer. Three heterogeneous inks possessing different rheological behaviors can be extruded and printed sequentially on the flexible substrates, supporting fast manufacturing of large customized bioelectronic patches. CARE can stimulate wounds up to 10 mm in depth with an electric field strength of 88.8 mVmm-1. In vitro studies reveal the ability to accelerate cell migration by a factor of 1.6 and 1.9 for human dermal fibroblasts and human umbilical vein endothelial cells, respectively. This study highlights the potential of CARE as a clinical wound therapy method to accelerate healing.

Retina-Inspired X-Ray Optoelectronic Synapse Using Amorphous Ga2O3 Thin Film.

Machine vision techniques are widely applied for object identification in daily life and industrial production, where images are captured and processed by sensors, memories, and processing units sequentially. Neuromorphic optoelectronic synapses, as a preferable option to promote the efficiency of image recognition, are hotly pursued in non-ionizing radiation range, but rarely in ionizing radiation including X-rays. Here, the study proposes an X-ray optoelectronic synapse using amorphous Ga2O3 (a-Ga2O3) thin film. Boosted by the interfacial VO 2+ defects and its slow neutralization rate, the enhanced electron tunneling process at metal/a-Ga2O3 interface produces remarkable X-ray-induced post-synaptic current, contributing to a sensitivity of 20.5, 64.3, 164.1 µC mGy-1 cm-2 for the 1st, 5th, and 10th excitation periods, respectively. Further, a 64×64 imaging sensor is constructed on a commercial amorphous Si (a-Si) thin film transistor (TFT) array. The image contrast can be apparently improved under a series of X-ray pulses due to an outstanding long-term plasticity of the single pixel, which is beneficial to the subsequent image recognition and classification based on artificial neural network. The merits of large-scale production ability and good compatibility with modern microelectronic techniques belonging to amorphous oxide semiconductors may promote the development of neuro-inspired X-ray imagers and corresponding machine vision systems.

Newly discovered harvestmen relict eyes eyeing for their functions.

Most chelicerates operate the world with two kinds of visual organs, the median and lateral eyes of the arthropod ground plan. In harvestmen (Opiliones), however, members of the small and withdrawn suborder Cyphophthalmi lack eyes except for two genera with lateral eyes. In the other suborders (Eupnoi, Dyspnoi, and Laniatores), lateral eyes are absent but median eyes pronounced. To resolve the phylogenetic history of these contrasting trait states and the taxonomic position of a four-eyed harvestmen fossil, visual system development was recently studied in the daddy longleg Phalangium opilio (Eupnoi). This effort uncovered not only a highly regressed and internalized pair of lateral eyes but also a similarly cryptic pair of additional median eyes. After recounting the evo-devo discovery journey of uncompromising harvestmen taxonomists, this review explores comparative evidence that the enigmatic P. opilio relict eyes might serve the multichannel zeitgeber system of the biological clock.

Anesthetic effects on electrophysiological responses across the visual pathway.

Anesthetics are widely used in electrophysiological tests to assess retinal and visual system functions to avoid experimental errors caused by movement and stress in experimental animals. To determine the most suitable anesthetic for visual electrophysiological tests, excluding ketamine and chloral hydrate due to regulatory and side effect concerns, this study investigated the effects of ethyl carbamate (EC), avertin (AR), and pentobarbital sodium (PS) on visual signal conduction in the retina and primary visual cortex. Assessments included flash electroretinogram (FERG), pattern electroretinogram (PERG), pattern visual evoked potentials (PVEP), and flash visual evoked potentials (FVEP), FERG and FVEP were used to evaluate the responses of the retina and visual cortex to flash stimuli, respectively, while PERG and PVEP assessed responses to pattern stimuli. The research showed that AR demonstrates the least disruption to the visual signal pathway, as evidenced by consistently high characteristic peaks in the AR group across various tests. In contrast, mice given EC exhibited the lowest peak values in both FERG and FVEP, while subjects anesthetized with PS showed suppressed oscillatory potentials and PERG responses. Notably, substantial PVEP characteristic peaks were observed only in mice anesthetized with AR. Consequently, among the three anesthetics tested, AR is the most suitable for visual electrophysiological studies.

Research on Key Technologies of Image Steganography Based on Simultaneous Deception of Vision and Deep Learning Models

As machine learning continues to evolve, traditional image steganography techniques find themselves increasingly unable to meet the dual challenge of deceiving both the human visual system and machine learning models. In response, this paper introduces the Visually Robust Image Steganography (VRIS) model, specifically tailored for this dual deception task. The VRIS model elevates visual security through the use of specialized feature extraction and processing methodologies. It meticulously conducts feature-level fusion between secret images and cover images, ensuring a high level of visual similarity between them. To effectively mislead machine learning models, the VRIS model incorporates a sophisticated strategy utilizing random noise factors and discriminators. This involves adding controlled amounts of random Gaussian noise to the encrypted image, thereby enhancing the difficulty for machine learning frameworks to recognize it. Furthermore, the discriminator is trained to discern between the noise-infused encrypted image and the original cover image. Through adversarial training, the discriminator and VRIS model refine each other, successfully deceiving the machine learning systems. Additionally, the VRIS model presents an innovative method for extracting and reconstructing secret images. This approach safeguards secret information from unauthorized access while enabling legitimate users to non-destructively extract and reconstruct images by leveraging multi-scale features from the encrypted image, combined with advanced feature fusion and reconstruction techniques. Experimental results validate the effectiveness of the VRIS model, achieving high PSNR and SSIM scores on the LFW dataset and demonstrating significant deception capabilities against the ResNet50 model on the Mini-ImageNet dataset, with an impressive misclassification rate of 99.24%.

Synapses and dendritic spines are eliminated in the primary visual cortex of mice subjected to chronic intraocular pressure elevation

Synaptic plasticity is essential for maintaining neuronal function in the central nervous system and serves as a critical indicator of the effects of neurodegenerative disease. Glaucoma directly impairs retinal ganglion cells and their axons, leading to axonal transport dysfuntion, subsequently causing secondary damage to anterior or posterior ends of the visual system. Accordingly, recent evidence indicates that glaucoma is a degenerative disease of the central nervous system that causes damage throughout the visual pathway. However, the effects of glaucoma on synaptic plasticity in the primary visual cortex remain unclear. In this study, we established a mouse model of unilateral chronic ocular hypertension by injecting magnetic microbeads into the anterior chamber of one eye. We found that, after 4 weeks of chronic ocular hypertension, the neuronal somas were smaller in the superior colliculus and lateral geniculate body regions of the brain contralateral to the affected eye. This was accompanied by glial cell activation and increased expression of inflammatory factors. After 8 weeks of ocular hypertension, we observed a reduction in the number of excitatory and inhibitory synapses, dendritic spines, and activation of glial cells in the primary visual cortex contralateral to the affected eye. These findings suggest that glaucoma not only directly damages the retina but also induces alterations in synapses and dendritic spines in the primary visual cortex, providing new insights into the pathogenesis of glaucoma.

A subjective and objective fusion visual fatigue assessment system for different hardware and software parameters in SSVEP-based BCI applications.

With the development of brain-computer interface industry, large amounts of related applications have entered people's vision. BCI applications based on steady-state visual evoked potentials (SSVEP) are widely used because they do not require pre-training and have high information transmission rates. However, in the actual use of SSVEP stimulus paradigm, the subjects will produce visual fatigue with the use, and fatigue will affect the transmission efficiency. In this experiment, an experimental environment consisting of two paradigm stimulus frequencies (7.5Hz, 15Hz), three resolutions (800 × 600, 1280 × 720, 1920 × 1080) and three refresh rates (120Hz, 240Hz, 360Hz) is set up. The Likert scale is used to collect subjective fatigue and preference scores, and the EEG acquisition system and eye tracker are used to collect objective data. Using the proposed information entropy-CRITIC algorithm to combine subjective and objective indicators, a fatigue assessment system (display screen fitness-DSF) is innovated to score different experimental environments. The higher the DSF score, the better the visual experience. The results show that when using the 7.5Hz SSVEP paradigm, the combination of 360Hz and 1920 × 1080 can bring the best visual experience. When using the 15Hz SSVEP paradigm, the combination of 240Hz and 1280 × 720 is the best. DSF provides powerful help for hardware and software selection guidance and vision protection when using SSVEP-based BCI applications.

Hyperspectral imaging in neurosurgery: a review of systems, computational methods, and clinical applications.

Accurate identification between pathologic (e.g., tumors) and healthy brain tissue is a critical need in neurosurgery. However, conventional surgical adjuncts have significant limitations toward achieving this goal (e.g., image guidance based on pre-operative imaging becomes inaccurate up to 3cm as surgery proceeds). Hyperspectral imaging (HSI) has emerged as a potential powerful surgical adjunct to enable surgeons to accurately distinguish pathologic from normal tissues. We review HSI techniques in neurosurgery; categorize, explain, and summarize their technical and clinical details; and present some promising directions for future work. We performed a literature search on HSI methods in neurosurgery focusing on their hardware and implementation details; classification, estimation, and band selection methods; publicly available labeled and unlabeled data; image processing and augmented reality visualization systems; and clinical study conclusions. We present a detailed review of HSI results in neurosurgery with a discussion of over 25 imaging systems, 45 clinical studies, and 60 computational methods. We first provide a short overview of HSI and the main branches of neurosurgery. Then, we describe in detail the imaging systems, computational methods, and clinical results for HSI using reflectance or fluorescence. Clinical implementations of HSI yield promising results in estimating perfusion and mapping brain function, classifying tumors and healthy tissues (e.g., in fluorescence-guided tumor surgery, detecting infiltrating margins not visible with conventional systems), and detecting epileptogenic regions. Finally, we discuss the advantages and disadvantages of HSI approaches and interesting research directions as a means to encourage future development. We describe a number of HSI applications across every major branch of neurosurgery. We believe these results demonstrate the potential of HSI as a powerful neurosurgical adjunct as more work continues to enable rapid acquisition with smaller footprints, greater spectral and spatial resolutions, and improved detection.

Organic Optoelectronic Synaptic Transistor with Enhanced UV Light Response Based on Insulating Polymer-Assisted p-n Heterojunction.

Optoelectronic synaptic transistors possess the capability to simultaneously accomplish perception and process functions within a single device, thereby not only addressing the limitations of von Neumann architectures but also serving as a promising candidate for emulating neural vision systems. The extensive range of organic semiconductor materials offers a plethora of possibilities for device fabrication; however, the severe recombination of photogenerated carriers imposes limitations on the utilization of organic p-n bulk heterostructures in synaptic transistor construction. By incorporating an insulating polymer and implementing a p-n planar heterojunction architecture, the 30% PCBM@PAN-DPPDTT transistor was constructed using the PCBM/DPPDTT heterojunction and the PCBM@PAN photoresponsive charge trapping layer. Due to the effect of the photoresponsive charge trapping layer and interface traps, the device not only overcomes the shortcomings of p-n bulk heterojunction and exhibits typical synaptic properties but also demonstrates a significantly enhanced response to ultraviolet (UV) light, exhibiting nearly four times more excitatory postsynaptic current (ΔEPSC) compared to the device lacking PCBM. The transistor matrix was employed to simulate the image perception and memory functions of the human neural vision system. Furthermore, an artificial neural network with high recognition accuracy (∼95%) of handwritten numbers was constructed. This study proposes an additional approach for mitigating the issue of rapid recombination of photogenerated charge carriers in the construction of optoelectronic synaptic transistors by utilizing p-n heterojunction.

Less gets more attention: A novel human-centered MR remote collaboration assembly method with information recommendation and visual enhancement

Mixed reality remote collaboration assembly is a type of computer-supported collaborative assembly work that uses mixed reality technology to enable spatial information and collaboration status sharing among geographically distributed collaborators, including remote experts and local users. However, due to the abundance of mixed virtual and real-world information in the MR space and the limitations imposed by narrow field-of-view augmented reality (AR) glasses, users face challenges in effectively focusing on relevant and valuable visual information. Our research aims to enhance users' visual attention to critical guidance information in MR collaborative assembly tasks, thereby improving the clear expression of instructions and facilitating the transmission of collaborative intention. We developed the Information Recommendation and Visual Enhancement System (IRVES) through an assembly process information hierarchy division mechanism, a content-based information recommendation system, and a gesture interaction-based information visual enhancement method. IRVES can leverage the guidance expertise and preferences of remote experts to recommend information to filter out irrelevant information and present the key information that the remote expert conveys to the local user in an intuitive way through visual enhancement. We conducted a user study experiment of a collaborative assembly task of a small engine in a laboratory environment. The experimental results indicate that IRVES outperforms traditional MR remote collaborative assembly methods (VG3DV) in terms of time performance, operational errors, cognitive performance and user experience. Our research contributes a human-centered information visualization approach for remote experts and local users, providing a novel method and idea for designing visual information interfaces in MR remote collaboration assembly tasks.

Functional localization of the human auditory and visual thalamus using a thalamic localizer functional magnetic resonance imaging task

Abstract Functional magnetic resonance imaging (fMRI) of the auditory and visual sensory systems of the human brain is an active area of investigation in the study of human health and disease. The medial geniculate nucleus (MGN) and lateral geniculate nucleus (LGN) are key thalamic nuclei involved in the processing and relay of auditory and visual information, respectively, and are the subject of blood-oxygen-level-dependent (BOLD) fMRI studies of neural activation and functional connectivity in human participants. However, localization of BOLD fMRI signal originating from neural activity in MGN and LGN remains a technical challenge, due, in part, to the poor definition of boundaries of these thalamic nuclei in standard T1-weighted and T2-weighted magnetic resonance imaging sequences. Here, we report the development and evaluation of an auditory and visual sensory thalamic localizer (TL) fMRI task that produces participant-specific functionally-defined regions of interest (fROIs) of both MGN and LGN, using 3 Tesla multiband fMRI and a clustered-sparse temporal acquisition sequence, in less than 16 minutes of scan time. We demonstrate the use of MGN and LGN fROIs obtained from the TL fMRI task in standard resting-state functional connectivity (RSFC) fMRI analyses in the same participants. In RSFC analyses, we validated the specificity of MGN and LGN fROIs for signals obtained from primary auditory and visual cortex, respectively, and benchmarked their performance against alternative atlas- and segmentation-based localization methods. The TL fMRI task and analysis code (written in Presentation and MATLAB, respectively) have been made freely available to the wider research community.

Visible light visual indoor positioning system for based on residual convolutional networks and image restoration

Abstract Visible light positioning technology, with its advantages of low cost, strong anti-interference, and high precision, is widely researched and applied in various different scenarios. In this paper, for the complexity of indoor environments, considering the problem of occlusion by various obstacles that may exist in indoor spaces, which may lead to incomplete imaging of CMOS image sensors, a maximum gray value-based occlusion recovery and decoding scheme is proposed. This scheme effectively solves the problem of visible light transmission channel being blocked and accomplishes LED-ID decoding. In addition, the overflow effect due to uneven light irradiation gathered in each pixel row affects the accuracy of decoding LED-ID, which in turn leads to poor positioning accuracy. In this paper, we propose to use an adaptive gamma correction method to eliminate the influence of the overflow effect and to improve the accuracy of decoding. In order to improve the positioning accuracy, a visible light positioning algorithm based on residual convolutional network (VisiResNet) is proposed to achieve high accuracy positioning. The experimental results show that the average positioning error is 9.7 cm in a space of 9m× 3m× 3m, and a decoding accuracy of 90% within 1.4m is achieved in the face of different occlusion situations. The system can achieve centimeter-level positioning accuracy and meet the indoor positioning requirements.

STUDENTS’ AND TEACHERS’ PERCEPTION ON USING VIDEO STREAMING PLATFORM TO ENHANCE LISTENING SKILLS

This study investigates the influence of video streaming platforms on effective listening proficiency among English teachers and secondary school students in SMKA Tun Ahmadshah, Kota Kinabalu, Sabah. The research utilized a qualitative approach, interviewing 5 experienced English teachers and five students from Form 3 to Form 5. Among the reasons, the integration of modern technological tools was provided in the school. The theories of cognitivism and content-based learning (CBL) within the book are employed. The research focuses on these theories to explore cognitive and instructional merits of using video streaming platforms. Based on the findings, the content of video streaming platforms significantly sustains students’ engagement and motivation. At the same time, teachers comment on the content being interesting, relevant, and in multimedia format. It combines visual and auditory sense for their engagement. Among the challenges for the students was that they rely on subtitles on the video. The issue of buffering was not mentioned by the students, but it is likely to reduce their engagement. Teachers suggested that the platform content is authentic similar to that on social media, and students can receive other messages beside the expected ones. For effective teaching, the use of some features could be of help considering that buffering poses a major challenge, and some students rely on subtitles. Nevertheless, they could make the process simpler and with motivation by their utilization on the students’ part. The medium is significantly used in distance learning where it is effective since students rely on the authentic content and are engaged. Thus, the platform should be used for effective proficiency in listening with assistance from its video features. They require the employing of the platform features and adequate motivation from the participants. Keyword(s): Listening Skills, Content Based Learning (CBL), Video Streaming Platform, Cognitivism.

Functional characterization of optic photoreception in Lymnaea stagnalis.

Optic photoreception is a critical function for animal survival. Across the evolutionary spectrum, diverse animal models have been used to investigate visual system function and potential mechanisms under physiological or pathophysiological states. However less is known on photoreceptive behaviors and retinal processing in invertebrates, especially molluscs. This study focuses on the freshwater pond snail, Lymnaea stagnalis (L. stagnalis), to explore its visual function and underlying mechanisms. Using anatomical and histological approaches we characterized the L. stagnalis eye structure and demonstrated structural connections and retinal rhodopsin-positive sensory cells potentially critical for phototransduction. To assess the snail phototactic responses, we developed a new neurobehavioral protocol and employed DeepLabCut to track and quantify animal locomotion. We demonstrated that L. stagnalis exhibits a positive locomotory response to intense focal light and has diverse photo-locomotory responses. Further, we conducted phylogenetic and protein structure analyses and demonstrated that L. stagnalis has a unique repertoire of both vertebrate and invertebrate phototransduction genes. Further characterization of a rhodopsin-like gene identified unique characteristics compared to other mollusks and vertebrates, suggesting different mechanisms of phototransduction. Taken together, our work establishes L. stagnalis as a model organism for studying optic photoreception, offering new insights into the evolution and diversity of visual function across animal species.

Optic flow density modulates corner-cutting in a virtual steering task for younger and older adults.

There is a critical need to understand how aging visual systems contribute to age-related increases in vehicle accidents. We investigated the potential contribution of age-related detriments in steering based on optic flow, a source of information known to play a role in navigation control. Seventeen younger adults (mean age: 21.1 years) and thirteen older adults (mean age: 57.3 years) performed a virtual reality steering task. The virtual environment depicted movement at 19 m/s along a winding road. Participants were tasked with maintaining a central lane position while experiencing eight repetitions of each combination of optic flow density (low, medium, high), turn radius (35, 55, 75 m), and turn direction (left, right), presented in random order. All participants cut corners, but did so less on turns with rotational flow from distant landmarks and without proximal optic flow. We found no evidence of an interaction between age and optic flow density, although older adults cut corners more on all turns. An exploratory gaze analysis revealed no age-related differences in gaze behavior. The lack of age-related differences in steering or gaze behavior as a function of optic flow implies that processing of naturalistic optic flow stimuli when steering may be preserved with age.

RTID-05. STUDY PROTOCOL: A MULTICENTER, INTERNATIONAL RANDOMIZED CONFIRMATORY TRIAL: LOW-ENERGY X-RAY INTRAOPERATIVE RADIATION THERAPY (LEX-IORT) VS. ADJUVANT FRACTIONATED STEREOTACTIC RADIOTHERAPY (FSRT) IN THE MANAGEMENT OF BRAIN METASTASES (LEXIMATE)

Abstract BACKGROUND Fractionated stereotactic radiotherapy to the resection cavity boosts local control of resected brain metastases significantly. However, start of systemic tumor-directed treatment may be protracted and in-hospital times prolonged. Lately, lex-ioRT of BM has been described as a safe and effective one stop-shop treatment modality with a 1-year local control rate of up to 98% while potentially improving patient convenience. Study Design: The LEXIMATE-trial is a multicenter, international, randomized open-label confirmatory trial comparing lex-IORT with FSRT of resected BM. In the experimental arm, INTRABEAM (Carl Zeiss Meditec AG) is used to deliver IORT by application of 50-kV photons at a standard dose of 30 Gy prescribed to the applicator surface. Standard linear accelerator or Gamma Knife based FSRT (3-7 fractions) to the surgical bed is used in the control arm. The primary endpoint is the cumulative incidence of local recurrences (as per RANO-BM) considering death without prior local recurrence as competing event. Inclusion criteria include histologically confirmed BM with indication for resection according to EANO-ESMO/ASCO-SNO-ASTRO guidelines, ≤5 other brain lesions compatible with BM and amenable to radiosurgery and history of solid cancer or CT scan suggestive for localized or metastasized solid cancer (except germ cell tumors, lymphoma, small-cell lung cancer). The resection cavity must be <5cm in size, IORT doses to brainstem or optical tract may not exceed 8 Gy. Study design: Randomized, open-label, non-inferiority. Sample size: 70 patients per group to show a non-inferiority of the experimental therapy compared to the control therapy with a power of approximately 80%. DISCUSSION The best radio-oncologic procedure for resected BM remains under debate. The LEXIMATE-trial offers an opportunity to provide more solid prospective data on effectiveness, safety and patient comfort both for established and new RT techniques.