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9th Panhellenic Conference on Biomedical Technology - Conference Proceedings & Book of Abstracts

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H παρούσα έκδοση αποτελεί τον τόμο Πρακτικών & Περιλήψεων (Proceedings) του 9ου Πανελληνίου Συνεδρίου Βιοϊατρικής Τεχνολογίας που διοργανώθηκε από την Ελληνική Εταιρία Βιοϊατρικής Τεχνολογίας (ΕΛΕΒΙΤ) στις 9-11 Σεπτεμβρίου με υβριδική μορφή (στην Αίθουσα Τελετών του Αριστοτελείου Πανεπιστημίου Θεσσαλονίκης και Διαδικτυακά) μαζί με το Aristotle Medical Forum. Τον τόμο επιμελήθηκαν οι Αλκίνοος Αθανασίου, Βασιλική Ζηλίδου & Παναγιώτης Μπαμίδης (editors) και εκδόθηκε με αριθμό ISBN 978-960-243-727-8 από το Εργαστήριο Ιατρικής Φυσικής του ΑΠΘ. Συνολικά 52 πρωτότυπες εργασίες έγιναν δεκτές για παρουσίαση στο συνέδριο και δημοσιεύονται στην παρούσα έκδοση με μορφή εκτεταμένης περίληψης (extended abstract). Tα ονόματα των συγγραφέων (authors) της κάθε εργασίας αναφέρονται στην αντίστοιχη σελίδα της περίληψης και στο πρόγραμμα των ανακοινώσεων.
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Conference Paper
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Introduction: Enhanced, immersive education content, in virtual, augmented or mixed reality (VR/AR/MR collectively XR), facilitates healthcare learning. Time and resource overheads are the core challenges. Co-creation mitigates these overheads by enabling educators to create decentralized content. Methods: This work presents the implemented methodology based on two bi-hourly workshops that involved 8 technologists, 2 medical educators and 2 supporting facilitators. These workshops elicited requirements through participatory design methods from stakeholders for the development of XR resources. Results: Garnering qualitative feedback from all actors after these episodes, a set of emerging guidelines from these activities were identified: a) Specificity of objectives enables engagement; the goal of the workshops should be specific, structured and founded on previous work. Well-defined aims lead to productive participation. b) Specificity of roles propels the discussion forward; technologists and healthcare educators collaborate optimally, when they enable each other by complementing the overarching design vision as it is formulated in the activity. c) Brainstorming tools enable only if they can be intuitively used; utilizing mind-mapping software, digital white-boards and other similar tools sometimes incurs digital skills overheads that can hinder the participatory process. d) Healthcare expert involvement at the earliest stages of co-creation allows for effective management in selecting/creating digital assets, degree of resolution, educational focus, while maintaining scientific validity. Early engagement saves group time and minimizes terminology incompatibilities. Conclusions: Identifying and following these simple guidelines can maintain the engagement of the participants in co-creative episodes, leading to successful outcomes and valid design of XR resources.
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Background Convenient and precise assessment of the severity in coronavirus disease 2019 (COVID-19) contributes to the timely patient treatment and prognosis improvement. We aimed to evaluate the ability of CT-based radiomics nomogram in discriminating the severity of patients with COVID-19 Pneumonia. Methods A total of 150 patients (training cohort n = 105; test cohort n = 45) with COVID-19 confirmed by reverse transcription polymerase chain reaction (RT-PCR) test were enrolled. Two feature selection methods, Max-Relevance and Min-Redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO), were used to extract features from CT images and construct model. A total of 30 radiomic features were finally retained. Rad-score was calculated by summing the selected features weighted by their coefficients. The radiomics nomogram incorporating clinical-radiological features was eventually constructed by multivariate regression analysis. Nomogram, calibration, and decision-curve analysis were all assessed. Results In both cohorts, 40 patients with COVID-19 pneumonia were severe and 110 patients were non-severe. By combining the 30 radiomic features extracted from CT images, the radiomics signature showed high discrimination between severe and non-severe patients in the training set [Area Under the Curve (AUC), 0.857; 95% confidence interval (CI), 0.775–0.918] and the test set (AUC, 0.867; 95% CI, 0.732–949). The final combined model that integrated age, comorbidity, CT scores, number of lesions, ground glass opacity (GGO) with consolidation, and radiomics signature, improved the AUC to 0.952 in the training cohort and 0.98 in the test cohort. The nomogram based on the combined model similarly exhibited excellent discrimination performance in both training and test cohorts. Conclusions The developed model based on a radiomics signature derived from CT images can be a reliable marker for discriminating the severity of COVID-19 pneumonia.
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In this study, an infusion roller pump comprising two separate innovative resilient tube designs is presented. The first incorporates the flexible tubing cross-section area in its relaxed state as a lenticular one for power reduction reasons. The second keeps the previous lenticular cross-section along its length, while it additionally incorporates an inflating portion, for creating a momentary flow positive pulse to balance the void generated by the roller disengagement. Fluid–Structure Interaction (FSI) simulations cannot provide quantitatively realistic results, due to the limitation of full compression of the tube, and are only used qualitatively to reveal by which way to set the inflated portion along the tube length in order to suppress backflow and achieve constant flow rate. Finally, indirect lumen volume measurements were performed numerically and an optimum design was found testing eight design approaches. These indirect fluid volume measurements assess the optimum inflated tube’s portion leading to backflow and pulsating elimination. The optimum design has an inflation portion of 75 degrees covering almost 42% of the curved part of the tube, while it has a constant zone with the maximum value of inflated lenticular cross-section, within the portion, of 55 degrees covering about 73% of the inflation portion.
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A mechanical heart valve (MHV) is an effective device to cure heart disease, which has the advantage of long life and high reliability. Due to the hemodynamic characteristics of blood, mechanical heart valves can lead to potential complications such as hemolysis, which have damage to the blood elements and thrombosis. In this paper, flowing features of the blood in the valve are analyzed and the cavitation mechanism in bileaflet mechanical heart valve (BMHV) is studied. Results show that the water hammer effect and the high-speed leakage flow effect are the primary causes of the cavitation in the valve. Compared with the high-speed leakage flow effect, the water hammer has a greater effect on the cavitation strength. The valve goes through four kinds of working condition within one heart beating period, including, fully opening stage, closing stage and fully closing stage. These four stages, respectively, make up 8.5%, 16.1%, 4.7% and 70.7% of the total period. The cavitation occurs on the fully closing stage. When the valve is in closing stage, the high pressure downstream of the valve lasts for about 20 ms and the high-speed leakage flow lasts for about 200 ms. This study systematically analyzes the causes of cavitation emerged in the process of periodic motion, which proposes the method for characterizing the intensity of the cavitation, and can be referred to for the cavitation suppression of the BHMV and similar valves.
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A neuroprosthesis is a type of precision medical device that is intended to manipulate the neuronal signals of the brain in a closed-loop fashion, while simultaneously receiving stimuli from the environment and controlling some part of a human brain or body. Incoming visual information can be processed by the brain in millisecond intervals. The retina computes visual scenes and sends its output to the cortex in the form of neuronal spikes for further computation. Thus, the neuronal signal of interest for a retinal neuroprosthesis is the neuronal spike. Closed-loop computation in a neuroprosthesis includes two stages: encoding a stimulus as a neuronal signal, and decoding it back into a stimulus. In this paper, we review some of the recent progress that has been achieved in visual computation models that use spikes to analyze natural scenes that include static images and dynamic videos. We hypothesize that in order to obtain a better understanding of the computational principles in the retina, a hypercircuit view of the retina is necessary, in which the different functional network motifs that have been revealed in the cortex neuronal network are taken into consideration when interacting with the retina. The different building blocks of the retina, which include a diversity of cell types and synaptic connections—both chemical synapses and electrical synapses (gap junctions)—make the retina an ideal neuronal network for adapting the computational techniques that have been developed in artificial intelligence to model the encoding and decoding of visual scenes. An overall systems approach to visual computation with neuronal spikes is necessary in order to advance the next generation of retinal neuroprosthesis as an artificial visual system.
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Episodic memory is sensitive to the influence of neuromodulators, such as dopamine and noradrenaline. These influences are considered important in the expression of several known memory biases, though their specific role in memory remains unclear. Using pharmacological agents with relatively high selectivity for either dopamine (400mg amisulpride) or noradrenaline (40mg propranolol) we examined their specific contribution to incidental memory. In a double-blind placebo-controlled human study (30 females, 30 males in total), we show that a memory selectivity bias was insensitive to propranolol but sensitive to amisulpride, consistent with a dominant influence from dopamine. By contrast, a putative arousal-induced memory boosting effect was insensitive to amisulpride but was sensitive to propranolol, consistent with a dominant noradrenaline effect. Thus, our findings highlight specific functional roles for dopamine and noradrenaline neurotransmission in the expression of incidental memory.
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Regular physical activity is considered one of the most important factors for lifestyle, for maintaining good health in older ages and increasing life expectancy. Dance is considered an activity that involves coordinating movements with music, as well as brain activation because it is constantly necessary to learn and remember new steps. Dance as a musical-kinetics skill, requires the coordination of body movements with rhythmic stimuli, developing the adaptability of the movement. One-hundred-thirty (130) elderly people aged 60 years and over (mean age 67 years old) with an average of 8 years of education, attended Greek traditional dance sessions for 32 weeks. The frequency was 2 times per week, for 75 min per session. Dances were selected from all over Greece with moderate intensity initially. During the program, they had the opportunity to try with greater intensity dances. At the beginning and after the end of intervention all the participants were evaluated by the Fullerton Senior Fitness Test for their physical fitness, the Single Leg Balance and the Handgrip Strength Test. The results showed a significant improvement in their physical fitness (Chair Stand: T = −5.459, p < 0.001; Arm Curl: T = −5.750, p < 0.001; Back Scratch: T = −4.648, p < 0.001; Sit and Reach: T = −4.759, p < 0.001; 2 min Step: T = −5.567, p < 0.001; Foot Up and Go: T = −8.599, p < 0.001) and at their static balance with eyes open (Balance 1 leg: T = −4.996, p < 0.001) and Handgrip Strength (Handgrip: T = −3.490, p < 0.001). Elderly seem to enjoy dancing as an activity while maintaining their functionality. Probably the elderly in traditional dance cause prosperity in their lives by promoting active aging.
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PsychoPy is an application for the creation of experiments in behavioral science (psychology, neuroscience, linguistics, etc.) with precise spatial control and timing of stimuli. It now provides a choice of interface; users can write scripts in Python if they choose, while those who prefer to construct experiments graphically can use the new Builder interface. Here we describe the features that have been added over the last 10 years of its development. The most notable addition has been that Builder interface, allowing users to create studies with minimal or no programming, while also allowing the insertion of Python code for maximal flexibility. We also present some of the other new features, including further stimulus options, asynchronous time-stamped hardware polling, and better support for open science and reproducibility. Tens of thousands of users now launch PsychoPy every month, and more than 90 people have contributed to the code. We discuss the current state of the project, as well as plans for the future.
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Neuroscience is developing rapidly by providing a variety of modern tools for analyzing the functional interactions of the brain and detection of pathological deviations due to neurodegeneration. The present study argues that the induction of neuroplasticity of the mature human brain leads to the prevention of dementia. Promising solution seems to be the dance programs because they combine cognitive and physical activity in a pleasant way. So, we investigated whether the traditional Greek dances can improve the cognitive, physical and functional status of the elderly always aiming at promoting active and healthy aging. Forty-four participants were randomly assigned equally to the training group and an active control group. The duration of the program was 6 months. Also, the participants were evaluated for their physical status and through an electroencephalographic (EEG) examination at rest (eyes-closed condition). The EEG testing was performed 1–14 days before (pre) and after (post) the training. Cortical network analysis was applied by modeling the cortex through a generic anatomical model of 20,000 fixed dipoles. These were grouped into 512 cortical regions of interest (ROIs). High quality, artifact-free data resulting from an elaborate pre-processing pipeline were segmented into multiple, 30 s of continuous epochs. Then, functional connectivity among those ROIs was performed for each epoch through the relative wavelet entropy (RWE). Synchronization matrices were computed and then thresholded in order to provide binary, directed cortical networks of various density ranges. The results showed that the dance training improved optimal network performance as estimated by the small-world property. Further analysis demonstrated that there were also local network changes resulting in better information flow and functional re-organization of the network nodes. These results indicate the application of the dance training as a possible non-pharmacological intervention for promoting mental and physical well-being of senior citizens. Our results were also compared with a combination of computerized cognitive and physical training, which has already been demonstrated to induce neuroplasticity (LLM Care).
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There has been a substantial rise in the utilization of large databases in radiation oncology research. The advantages of these datasets include a large sample size and inclusion of a diverse population of patients in a real-world setting. Such observational studies hold promise in enhancing our understanding of questions for which evidence is conflicting or absent in lung cancer radiotherapy. However, it is critical that investigators understand the strengths and limitations of large databases in order to avoid the common pitfalls that beset observational analyses. This review begins by outlining the data variables available in major registries that are used most often in observational analyses. This is followed by a discussion of the type of radiotherapy-related questions that can be addressed using such datasets, accompanied by examples from the lung cancer literature. Finally, we describe some limitations of observational research and techniques to mitigate bias and confounding. We hope that clinicians and researchers find this review helpful for designing new research studies and interpreting published analyses in the literature.