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Commissioning, Benchmarking and Clinical Application of a Novel Fiber Optic CT Scanner for Precise Three-Dimensional Radiation Dosimetry
Radiotherapy is a prominent cancer treatment modality in medicine, aiming to deliver adequate doses to the target while minimizing harm to healthy tissue. Recent advancements in computer technology, machine engineering, and imaging have facilitated intricate treatment planning and accurate radiation administration. These advancements have allowed for more precise dose distributions to be delivered to cancer patients. However, even small discrepancies in setup or delivery can result in significant dose variations. While treatment planning systems provide 3D dose calculations, there is currently a lack of 3D measurement tools in the clinic to verify the accuracy of dose calculation and delivery. Presently, medical physicists rely on 2D dose plane comparisons with treatment planning calculations using gamma index analyses. However, these results do not directly correlate with clinical dose-volume constraints, and detecting delivery errors using 1D or 2D dosimetry is challenging. The implementation of 3D dosimetry not only ensures the safety of radiation treatment but also facilitates the development of new emerging radiation treatment techniques. This study aims to commission and validate a clinically viable optical scanner for 3D dosimetry and apply the developed system to address current clinical and pre-clinical challenges, thereby advancing our understanding of treatment uncertainties in modern radiotherapy.
The optical CT scanner that was developed comprises four key components: an LED illuminator, an aquarium with matching fluid, a fiber optic taper, and a CCD camera. The LED illuminator emits uniform and parallel red light at a peak wavelength of 625 nm and a full width at half maximum (FWHM) of 20 nm in continuous mode. The aquarium is constructed with transparent acrylic walls and is designed to accommodate the 3D dosimeter PRESAGE, which can be fixed on a rotation stage inside the tank. Clear acrylic has excellent optical clarity and light transmission, with a refractive index of 1.49 that is close to the average refractive index (1.54) of PRESAGE. To match the refractive index of the 3D dosimeters, a matching liquid composed of 90% Octyl Salicylate and 10% Octyl-P-Methoxy Cinnamate is filled in the tank. The fiber optic taper serves two functions: first, it demagnifies the projection images while preserving their shape, and second, it effectively reduces the acceptance angle of the light reaching the CCD camera. The CCD camera used in the system is an Allied Vision model with a resolution of 0.016 mm, capable of acquiring 2D projection images from various angles. The principle of the optical CT scanner follows that of CT imaging, where 2D projection images from different angles are used to reconstruct volumetric 3D dose images using the filtered back projection technique. To validate the dosimetric measurements and assess the uncertainties of the 3D dosimetry system, 21 benchmark experiments, including mechanical, imaging, and dosimetry tests were conducted. Furthermore, the developed system was employed for various applications, including patient-specific IMRT QA, small field dosimetry using kilovoltage and megavoltage beams, as well as end-to-end testing of stereotactic radiosurgery.
A comprehensive analysis assessed uncertainties in each scanner component. Mechanical tests showed maximum uncertainties below 1%. By employing background subtraction and calibration techniques, measurement uncertainty was reduced to <1% in the optimal dose range. Background subtraction resulted in a remarkable 77% reduction in uncertainty by mitigating artifacts, ambient light, and refractive light. Reproducibility was excellent, with mean and standard deviation of dose differences below 0.4% and 1.1%, respectively, in three repeat scans. Dose distribution measurements exhibited strong agreement (passing rates: 98%-100%) between 3D measurements, treatment planning calculations, and EBT3 film dosimetry. Results confirm the optical CT scanner's robustness and accuracy for clinical 3D radiation dosimetry. The study also demonstrates that the developed 3D dosimetry system surpasses the limitations of traditional 2D gamma tests by providing clinicians with more clinically relevant information. This includes measured dose-volume histograms (DVHs) and the evaluation of gamma failing points in 3D space, enabling a comprehensive assessment of individual treatment plans. Furthermore, the study showcased the feasibility of utilizing this system to characterize a radiosurgery platform. It successfully assessed mechanical and dosimetric errors in off-axis delivery and evaluated the accuracy of treatment planning dose calculations, including modeling small fields, out-of-field dose, and multi-leaf collimator (MLC) characteristics. In addition, compelling evidence was presented that the high-resolution 3D dosimeter used in this study is capable of accurate dosimetry for both megavoltage and kilovoltage small fields. Importantly, the dosimeter exhibits no energy or dose rate dependence, further supporting its reliability and suitability for precise dosimetry measurements.
The intricate and three-dimensional nature of dose distributions in modern radiotherapy necessitated the development of 3D dosimetry measurements, particularly for treatments with precise margins, such as SRS and SBRT. The newly developed 3D dosimetry system offers significant enhancements to current QA practices, delivering more clinically relevant comparison results and bolstering patient safety. Furthermore, it can be utilized for independent inspections across multiple institutions or remote dosimetry verification. Beyond its applications in clinical settings, the presented 3D dosimetry system holds the potential to expedite the development and utilization of novel radiation platforms
Cerebral Metamorphopsia: Perceived spatial distortion from lesions of the adult human central visual pathway
Metamorphopsia is the perceived visual illusion of spatial distortion. Cerebral causes of metamorphopsia are much less common than retinal or ocular causes. Cerebral metamorphopsia can be caused by lesions along the central visual pathway or as a manifestation of epileptogenic discharges. Geometric visual distortions may result from structural lesions of the central visual pathway after reorganisation of the retinotopic representation in the cortex. Very few experimental investigations have been performed regarding cerebral metamorphopsia as it is often viewed as a clinical curiousity and analysis of the perceived distortion is difficult due to its subjective nature. Investigations have been undertaken to understand cortical plasticity as an explanation for visual filling-in. There has been much interest in cortical reorganisation after injuries to the peripheral and central visual pathway. Behavioural experiments aimed at quantifying the possible visual spatial distortion surrounding homonymous paracentral scotomas may be able to demonstrate cortical reorganisation after brain-damage and provide clues regarding the neural processes of visual perception.
The aims of the thesis are:
1. To identify which cases of metamorphopsia, both published and unpublished, might be a consequence of cortical spatial reorganisation of retinotopic projections.
2. To investigate perceptual spatial distortion surrounding homonymous paracentral scotomas in adults with isolated unilateral injuries of the striate cortex.
A review of the literature describing cases of cerebral metamorphopsia was performed. Metamorphopsia caused by retinal or ocular pathology, psychiatric conditions, drugs or medications were excluded. A retrospective case series of eight patients with metamorphopsia from a cerebral cause was performed in two clinical neurology practices specialising in vision disorders. Two cases who suffered from paracentral homonymous scotomas due to isolated unilateral primary visual cortex (V1) lesions were identified from a Neuro-ophthalmology practice. Neuropsychophysical experiments to investigate visual spatial perception surrounding their scotomas were developed and tested using MATLAB and Psychtoolbox.
The use of the term 'metamorphopsia' was only in reference to cases in which contours or lines were experienced as distorted. In the published literature, few cases of cerebral metamorphopsia have been identified as being potentially due to cortical reorganisation. The main result is a statistically significant visual spatial distortion in the visual field surrounding a paracentral homonymous scotoma when compared to a normal control. There is also significant distortion of perception in the subjects' "unaffected" visual hemifield.
After lesions of V1, visual perceptual spatial distortions may occur in the visual field surrounding homonymous paracentral scotomas. The spatial distortion may also occur in the normal hemifield possibly due to long-range cortical connections crossing to the other hemisphere through the corpus callosum. A collaborative approach across disciplines within vision science is required to further investigate the mechanisms responsible for perceptual visual illusions. Behavioural testing in brain-damaged cases remains important in developing theories of normal visual processing. New neuroimaging and neuroscience techniques could then test these theories, furthering our understanding of visual perception. An understanding of normal visual perception could allow future modification of neuronal processes to harness cortical reorganisation and potentially restore functional vision in humans with lesions of the central visual pathway
Current issues of the management of socio-economic systems in terms of globalization challenges
The authors of the scientific monograph have come to the conclusion that the management of socio-economic systems in the terms of global challenges requires the use of mechanisms to ensure security, optimise the use of resource potential, increase competitiveness, and provide state support to economic entities. Basic research focuses on assessment of economic entities in the terms of global challenges, analysis of the financial system, migration flows, logistics and product exports, territorial development. The research results have been implemented in the different decision-making models in the context of global challenges, strategic planning, financial and food security, education management, information technology and innovation. The results of the study can be used in the developing of directions, programmes and strategies for sustainable development of economic entities and regions, increasing the competitiveness of products and services, decision-making at the level of ministries and agencies that regulate the processes of managing socio-economic systems. The results can also be used by students and young scientists in the educational process and conducting scientific research on the management of socio-economic systems in the terms of global challenges
Current Challenges in the Application of Algorithms in Multi-institutional Clinical Settings
The Coronavirus disease pandemic has highlighted the importance of artificial intelligence in multi-institutional clinical settings. Particularly in situations where the healthcare system is overloaded, and a lot of data is generated, artificial intelligence has great potential to provide automated solutions and to unlock the untapped potential of acquired data. This includes the areas of care, logistics, and diagnosis. For example, automated decision support applications could tremendously help physicians in their daily clinical routine. Especially in radiology and oncology, the exponential growth of imaging data, triggered by a rising number of patients, leads to a permanent overload of the healthcare system, making the use of artificial intelligence inevitable. However, the efficient and advantageous application of artificial intelligence in multi-institutional clinical settings faces several challenges, such as accountability and regulation hurdles, implementation challenges, and fairness considerations. This work focuses on the implementation challenges, which include the following questions: How to ensure well-curated and standardized data, how do algorithms from other domains perform on multi-institutional medical datasets, and how to train more robust and generalizable models? Also, questions of how to interpret results and whether there exist correlations between the performance of the models and the characteristics of the underlying data are part of the work. Therefore, besides presenting a technical solution for manual data annotation and tagging for medical images, a real-world federated learning implementation for image segmentation is introduced. Experiments on a multi-institutional prostate magnetic resonance imaging dataset showcase that models trained by federated learning can achieve similar performance to training on pooled data. Furthermore, Natural Language Processing algorithms with the tasks of semantic textual similarity, text classification, and text summarization are applied to multi-institutional, structured and free-text, oncology reports. The results show that performance gains are achieved by customizing state-of-the-art algorithms to the peculiarities of the medical datasets, such as the occurrence of medications, numbers, or dates. In addition, performance influences are observed depending on the characteristics of the data, such as lexical complexity. The generated results, human baselines, and retrospective human evaluations demonstrate that artificial intelligence algorithms have great potential for use in clinical settings. However, due to the difficulty of processing domain-specific data, there still exists a performance gap between the algorithms and the medical experts. In the future, it is therefore essential to improve the interoperability and standardization of data, as well as to continue working on algorithms to perform well on medical, possibly, domain-shifted data from multiple clinical centers
Microcircuit structures of inhibitory connectivity in the rat parahippocampal gyrus
Komplexe Berechnungen im Gehirn werden durch das Zusammenspiel von exzitatorischen und hemmenden Neuronen in lokalen Netzwerken ermöglicht. In kortikalen Netzwerken, wird davon ausgegangen, dass hemmende Neurone, besonders Parvalbumin positive Korbzellen, ein „blanket of inhibition” generieren. Dieser Sichtpunkt wurde vor kurzem durch Befunde strukturierter Inhibition infrage gestellt, jedoch ist die Organisation solcher Konnektivität noch unklar.
In dieser Dissertation, präsentiere ich die Ergebnisse unserer Studie Parvabumin positiver Korbzellen, in Schichten II / III des entorhinalen Kortexes und Präsubiculums der Ratte. Im entorhinalen Kortex haben wir dorsale und ventrale Korbzellen beschrieben und festgestellt, dass diese morphologisch und physiologisch ähnlich, jedoch in ihrer Konnektivität zu Prinzipalzellen dorsal stärker als ventral verbunden sind. Dieser Unterschied korreliert mit Veränderungen der Gitterzellenphysiologie. Ähnlich zeige ich im Präsubiculum, dass inhibitorische Konnektivität eine essenzielle Rolle im lokalen Netzwerk spielt. Hemmung im Präsubiculum ist deutlich spärlicher ist als im entorhinalen Kortex, was ein unterschiedliches Prinzip der Netzwerkorganisation suggeriert.
Um diesen Unterschied zu studieren, haben wir Morphologie und Netzwerkeigenschaften Präsubiculärer Korbzellen analysiert. Prinzipalzellen werden über ein vorherrschendes reziprokes Motif gehemmt die durch die polarisierte Struktur der Korbzellaxone ermöglicht wird. Unsere Netzwerksimulationen zeigen, dass eine polarisierte Inhibition Kopfrichtungs-Tuning verbessert.
Insgesamt zeigen diese Ergebnisse, dass inhibitorische Konnektivität, funktioneller Anforderungen der lokalen Netzwerke zur Folge, unterschiedlich strukturiert sein kann. Letztlich stelle ich die Hypothese auf, dass für lokale inhibitorische Konnektivität eine Abweichung von „blanket of inhibition― zur „maßgeschneiderten― Inhibition zur Lösung spezifischer computationeller Probleme vorteilhaft sein kann.Local microcircuits in the brain mediate complex computations through the interplay of excitatory and inhibitory neurons. It is generally assumed that fast-spiking parvalbumin basket cells, mediate a non-selective -blanket of inhibition-. This view has been recently challenged by reports structured inhibitory connectivity, but it’s precise organization and relevance remain unresolved.
In this thesis, I present the results of our studies examining the properties of fast-spiking parvalbumin basket cells in the superficial medial entorhinal cortex and presubiculum of the rat. Characterizing these interneurons in the dorsal and ventral medial entorhinal cortex, we found basket cells of the two subregions are more likely to be connected to principal cells in the dorsal compared to the ventral region. This difference is correlated with changes in grid physiology. Our findings further indicated that inhibitory connectivity is essential for local computation in the presubiculum. Interestingly though, we found that in this region, local inhibition is lower than in the medial entorhinal cortex, suggesting a different microcircuit organizational principle.
To study this difference, we analyzed the properties of fast-spiking basket cells in the presubiculum and found a characteristic spatially organized connectivity principle, facilitated by the polarized axons of the presubicular fast-spiking basket cells. Our network simulations showed that such polarized inhibition can improve head direction tuning of principal cells.
Overall, our results show that inhibitory connectivity is differently organized in the medial entorhinal cortex and the presubiculum, likely due to functional requirements of the local microcircuit. As a conclusion to the studies presented in this thesis, I hypothesize that a deviation from the blanket of inhibition, towards a region-specific, tailored inhibition can provide solutions to distinct computational problems
(b2023 to 2014) The UNBELIEVABLE similarities between the ideas of some people (2006-2016) and my ideas (2002-2008) in physics (quantum mechanics, cosmology), cognitive neuroscience, philosophy of mind, and philosophy (this manuscript would require a REVOLUTION in international academy environment!)
(b2023 to 2014) The UNBELIEVABLE similarities between the ideas of some people (2006-2016) and my ideas (2002-2008) in physics (quantum mechanics, cosmology), cognitive neuroscience, philosophy of mind, and philosophy (this manuscript would require a REVOLUTION in international academy environment!
Dynamics of spatial attention during motion tracking: Characterization and modeling as a function of motion predictability
Efficient information processing in ecological environments relies on spatial attention to selectively process relevant areas in the visual field. Attention has been shown to be biased ahead of simple, uniform target motion during smooth pursuit. However, real-world motion varies in predictability, and as such this study aimed to: a) determine how motion predictability affects attentional bias, b) characterize how visual attention adapts to changes in motion predictability, and c) implement a computational
model of visual attention during motion tracking.
Ten high-performance team sport athletes (5 male, 5 female) and ten healthy, young adults (5 male, 5 female) visually tracked a target moving at varying predictability levels. A probe was flashed ahead or behind target motion (2° or 6°), and manual response times (MRT) to probes were collected to indicate attention level. To investigate the temporal dynamics of attentional bias, a second tracking task was performed where the target changed predictability levels mid-trial. The effects of group, motion predictability, and probe distance, time & location on MRT bias were examined. Finally, a state-space model (input: target motion, output: attentional bias) was trained and tested on the motion tracking and MRT data using a 5-fold cross-validation.
MRT were significantly biased in athletes (distance=2°) and adults (distance=2°,6°) during predictable motion (p<0.01). There was no MRT bias for semi- and un-predictable motions. Furthermore, MRT bias took longer to accumulate, than it did to de-accumulate (p<0.01). Eye movements showed that catch-up saccades were larger (p<0.01) and more frequent (p<0.01) during unpredictable motion phases, and gradually reduced in size and frequency during sustained predictable motion. Cross-validation results demonstrated that the state-space model performance in predicting attentional bias had a mean absolute error of 18.6% (SD=0.04%).
In conclusion, the distribution of spatial attention during motion tracking is dependant on motion predictability, and the
accumulation of bias ahead of target motion takes longer than de-accumulation. These results indicate a conservative attentional allocation scheme that introduces bias based on predicted future errors in motion extrapolation. The state-space model developed based on these experimental results may extend existing dynamic saliency frameworks to factor in the effects of motion tracking on spatial attention
Gabriel Vacariu (c2023 to 2014) The UNBELIEVABLE similarities between the ideas of some people (2006-2016) and my ideas (2002-2008) in physics (quantum mechanics, cosmology), cognitive neuroscience, philosophy of mind, and philosophy
Unbelievable similar ideas to my ideas published long before..
Exploring Virtual Reality and Doppelganger Avatars for the Treatment of Chronic Back Pain
Cognitive-behavioral models of chronic pain assume that fear of pain and subsequent avoidance behavior contribute to pain chronicity and the maintenance of chronic pain. In chronic back pain (CBP), avoidance of movements often plays a major role in pain perseverance and interference with daily life activities. In treatment, avoidance is often addressed by teaching patients to reduce pain behaviors and increase healthy behaviors. The current project explored the use of personalized virtual characters (doppelganger avatars) in virtual reality (VR), to influence motor imitation and avoidance, fear of pain and experienced pain in CBP. We developed a method to create virtual doppelgangers, to animate them with movements captured from real-world models, and to present them to participants in an immersive cave virtual environment (CAVE) as autonomous movement models for imitation.
Study 1 investigated interactions between model and observer characteristics in imitation behavior of healthy participants. We tested the hypothesis that perceived affiliative characteristics of a virtual model, such as similarity to the observer and likeability, would facilitate observers’ engagement in voluntary motor imitation. In a within-subject design (N=33), participants were exposed to four virtual characters of different degrees of realism and observer similarity, ranging from an abstract stickperson to a personalized doppelganger avatar designed from 3d scans of the observer. The characters performed different trunk movements and participants were asked to imitate these. We defined functional ranges of motion (ROM) for spinal extension (bending backward, BB), lateral flexion (bending sideward, BS) and rotation in the horizontal plane (RH) based on shoulder marker trajectories as behavioral indicators of imitation. Participants’ ratings on perceived avatar appearance were recorded in an Autonomous Avatar Questionnaire (AAQ), based on an explorative factor analysis. Linear mixed effects models revealed that for lateral flexion (BS), a facilitating influence of avatar type on ROM was mediated by perceived identification with the avatar including avatar likeability, avatar-observer-similarity and other affiliative characteristics. These findings suggest that maximizing model-observer similarity may indeed be useful to stimulate observational modeling.
Study 2 employed the techniques developed in study 1 with participants who suffered from CBP and extended the setup with real-world elements, creating an immersive mixed reality. The research question was whether virtual doppelgangers could modify motor behaviors, pain expectancy and pain. In a randomized controlled between-subject design, participants observed and imitated an avatar (AVA, N=17) or a videotaped model (VID, N=16) over three sessions, during which the movements BS and RH as well as a new movement (moving a beverage crate) were shown. Again, self-reports and ROMs were used as measures. The AVA group reported reduced avoidance with no significant group differences in ROM. Pain expectancy increased in AVA but not VID over the sessions. Pain and limitations did not significantly differ. We observed a moderation effect of group, with prior pain expectancy predicting pain and avoidance in the VID but not in the AVA group. This can be interpreted as an effect of personalized movement models decoupling pain behavior from movement-related fear and pain expectancy by increasing pain tolerance and task persistence. Our findings suggest that personalized virtual movement models can stimulate observational modeling in general, and that they can increase pain tolerance and persistence in chronic pain conditions. Thus, they may provide a tool for exposure and exercise treatments in cognitive behavioral treatment approaches to CBP
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