Automatic quantification of vocal cord paralysis - an application of fibre-optic endoscopy video processing

Full movement of the vocal cords is necessary for life sustaining functions. To enable correct diagnosis of reduced vocal cord motion and thereby potentially enhance treatment outcomes, it is proposed to objectively determine the degree of vocal cord paralysis in contrast to the current clinical practice of subjective evaluation. Our study shows that quantitative assessment can be achieved using optical flow based motion estimation of the opening and closing movements of the vocal cords. The novelty of the proposed method lies in the automatic processing of fibre-optic endoscopy videos to derive an objective measure for the degree of paralysis, without the need for high-end data acquisition systems such as high speed cameras or stroboscopy. Initial studies with three video samples yield promising results and encourage further investigation of vocal cord paralysis using this technique

Evaluation of High-Speed Videoendoscopy for Bayesian Inference on Reduced Order Vocal Fold Models

The ability to use our voice occurs through a complex bio-mechanical process known as phonation. The study of this process is interesting, not only because of the complex physical phenomena involved, but also because of the presence of phonation disorders that can make the everyday task of using ones voice difficult. Clinical studies of phonation aim to help diagnose such disorders using various measurement techniques, such as microphone recordings, video of the vocal folds, and perceptual sound quality measures. In contrast, scientific investigations of phonation have focused on understanding the physical phenomena behind phonation using simplified physical and numerical models constructed using representative population based parameters. A particularly useful type of model, reduced-order numerical models, are simplified representations of the vocal folds with low computational complexity that allow broad parameter changes to be investigated. To bring the physical understanding of phonation from these models into clinical usage, it is necessary to have patient specific parameters. Due to the difficulty of measuring vocal fold parameters and other structures in phonation directly, inverse analysis techniques must be employed. These techniques estimate the parameters of a model, by finding model parameters that lead to outputs of the model which compare well with measured outputs. With the measured outputs being patient specific measurements, these techniques can produce patient specific model parameters. However, this is complicated by the fact that measurements are uncertain, which leads to uncertainty in inferred parameters. The uncertainty in the parameters provides a way to judge how confident clinicians should be in using them. Large measurements errors could result in high uncertainties (and vice versa), which should guide clinicians on whether or not to believe the estimated parameters. Bayesian inference is an inverse analysis technique, that can take into account the inherent uncertainty in measurements in a probabilistic framework. Applying Bayesian inference to reduced-order models and clinical measurements allows patient specific model parameters with associated uncertainties to be inferred. A promising clinical measurement for use in Bayesian inference is high-speed videoendoscopy, in which high-speed video is taken of the vocal folds in motion. This captures the time varying motion of the vocal folds, which allows many quantitative measurements to be derived from the resulting video, for example the glottal width (distance between the vocal folds) or glottal area (area between the vocal folds). High-speed videoendoscopy is subject to variable imaging parameters, in particular the frame rate, spatial resolution, and tilted views of the camera can all modify the resulting video of the vocal folds, changing the uncertainty in the derived measurements. To investigate the effect of these three imaging parameters on Bayesian inference applied to high-speed video endoscopy, a simulated high-speed videoendoscopy experiment was conducted. Using a reduced order model, with known parameters, a set of enlarged, artificial vocal folds were driven in slow motion. These were imaged by a consumer DSLR camera, where the slow motion increased the effective frame rate, and the enlarged vocal folds increased the effective spatial resolution, to a fidelity much greater than typical high-speed videos of the vocal folds. This allowed investigation of the three parameters; titled views of the camera were investigated by physically tilting the camera, while variable frame rates and spatial resolutions were investigated by numerical downsampling of the original recording. Bayesian inference was conducted on these simulated high-speed videos, by measuring the distance between the vocal folds (the glottal width), in order to determine the parameters of the same reduced-order model driving the artificial vocal folds. This provided a reference to compare the estimated parameters with. The changes in estimated parameters from Bayesian inference were then investigated as the angle of view, frame rate, and spatial resolution were modified. From the experiment, the effects of frame rate, spatial resolution, and angle of view in high-speed videoendoscopy were found relative to changes from a reference video. Specifically, uncertainty in estimates increased linearly with respect to downsampling factor of frame rate. A frame rate that is half that of the reference video will have an uncertainty on estimated parameters that is twice as large. Spatial resolution affects the level of uncertainty based on the edge detection techniques that are used to extract quantitative data (i.e., the glottal width in this study). As the spatial resolution was downsampled, the level of error from the edge detection algorithm increased linearly with respect to the downsampling factor, which subsequently led to the same linear increase in the level of uncertainty in the estimate. However, different edge detection algorithms will likely have different accuracies as the resolution of the image decreases. While in this study it is preferable to decrease spatial resolution instead of frame rate, more general conclusions would be dependent on the specific edge detection technique used. The angle of view was found to bias estimates as a result of projecting the vocal folds (glottis) onto an offset image plane (like viewing a coin from an angle, results in increasingly narrow ellipses until a single line is formed, rather than a circle). This decreased the glottal width measured, which biased the estimated parameters. To account for this bias, it is suggested that the angle of view can be treated as an uncertain parameter, which leads to increased uncertainty in the quantitative measures from high-speed video. Alternatively, the angle of view can be estimated as an additional parameter

A novel optogenetics-based therapy for obstructive sleep apnoea

Obstructive sleep apnoea (OSA) is characterised by repeat upper airway narrowing and/or collapse during sleep. Many patients are sub-optimally treated due to poor tolerance or incomplete response to established therapies. We propose a novel, optogenetics-based therapy, that enables light-stimulation induced upper airway dilator muscle contractions to maintain airway patency. The primary aims of this thesis were to determine feasibility in a rodent model of OSA, and identify effective optogenetic constructs for activating upper airway muscles. Chapters 2 and 3 outline the development of a novel construct for the expression of light-sensitive proteins (opsins) in upper airway muscles, comparing two promotors and two recombinant adeno-associated virus capsids (rAAV) for optogenetic gene transfer. Results show that a muscle-specific promotor (tMCK) was superior to a non-specific promotor (CAG). With tMCK, opsin expression in the tongue was 470% greater (p=0.013, RM-ANOVA), brainstem expression was abolished, and light stimulation facilitated a 66% increase in muscle activity from that recorded during unstimulated breaths in an acute model of OSA (p<0.001, linear mixed model) (Chapter 2). Moreover, a novel, highly myotropic rAAV serotype, AAVMYO, was superior to a wild-type serotype, AAV9. The AAVMYO serotype driven by tMCK facilitated a further increase in muscle activity with light stimulation to 194% of that recorded during unstimulated breaths (p<0.001, linear mixed model) (Chapter 3). Finally, ultrasound imaging confirmed that the optimised construct was able to generate effective light-induced muscle contractions and airway dilation (Chapter 4). A secondary aim was to advance preclinical trials for the proposed therapy. To this end, a surgical protocol for chronic implantation of light delivery hardware and recording electrodes in rodents was developed (Chapter 5). The final protocol will allow us to determine the effects of acute and chronic light stimulation on opsin-expressing upper airway muscles during natural sleep. In summary, Chapters 2 to 4 provide proof-of-concept for a non-invasive optogenetics-based OSA therapy. The combination of a muscle-specific promotor and a muscle-specific viral vector presents a novel and highly effective method of inducing light sensitivity into skeletal muscle and facilitating light-evoked airway dilation. Finally, Chapter 5 commences the development of a surgical protocol that will aid ongoing preclinical trials

Optical Methods in Sensing and Imaging for Medical and Biological Applications

The recent advances in optical sources and detectors have opened up new opportunities for sensing and imaging techniques which can be successfully used in biomedical and healthcare applications. This book, entitled ‘Optical Methods in Sensing and Imaging for Medical and Biological Applications’, focuses on various aspects of the research and development related to these areas. The book will be a valuable source of information presenting the recent advances in optical methods and novel techniques, as well as their applications in the fields of biomedicine and healthcare, to anyone interested in this subject

Smart Sensors for Healthcare and Medical Applications

This book focuses on new sensing technologies, measurement techniques, and their applications in medicine and healthcare. Specifically, the book briefly describes the potential of smart sensors in the aforementioned applications, collecting 24 articles selected and published in the Special Issue “Smart Sensors for Healthcare and Medical Applications”. We proposed this topic, being aware of the pivotal role that smart sensors can play in the improvement of healthcare services in both acute and chronic conditions as well as in prevention for a healthy life and active aging. The articles selected in this book cover a variety of topics related to the design, validation, and application of smart sensors to healthcare

Progenitor cells in auricular cartilage demonstrate promising cartilage regenerative potential in 3D hydrogel culture

The reconstruction of auricular deformities is a very challenging surgical procedure that could benefit from a tissue engineering approach. Nevertheless, a major obstacle is presented by the acquisition of sufficient amounts of autologous cells to create a cartilage construct the size of the human ear. Extensively expanded chondrocytes are unable to retain their phenotype, while bone marrow-derived mesenchymal stromal cells (MSC) show endochondral terminal differentiation by formation of a calcified matrix. The identification of tissue-specific progenitor cells in auricular cartilage, which can be expanded to high numbers without loss of cartilage phenotype, has great prospects for cartilage regeneration of larger constructs. This study investigates the largely unexplored potential of auricular progenitor cells for cartilage tissue engineering in 3D hydrogels

PRELIMINARY FINDINGS OF A POTENZIATED PIEZOSURGERGICAL DEVICE AT THE RABBIT SKULL

The number of available ultrasonic osteotomes has remarkably increased. In vitro and in vivo studies have revealed differences between conventional osteotomes, such as rotating or sawing devices, and ultrasound-supported osteotomes (Piezosurgery®) regarding the micromorphology and roughness values of osteotomized bone surfaces. Objective: the present study compares the micro-morphologies and roughness values of osteotomized bone surfaces after the application of rotating and sawing devices, Piezosurgery Medical® and Piezosurgery Medical New Generation Powerful Handpiece. Methods: Fresh, standard-sized bony samples were taken from a rabbit skull using the following osteotomes: rotating and sawing devices, Piezosurgery Medical® and a Piezosurgery Medical New Generation Powerful Handpiece. The required duration of time for each osteotomy was recorded. Micromorphologies and roughness values to characterize the bone surfaces following the different osteotomy methods were described. The prepared surfaces were examined via light microscopy, environmental surface electron microscopy (ESEM), transmission electron microscopy (TEM), confocal laser scanning microscopy (CLSM) and atomic force microscopy. The selective cutting of mineralized tissues while preserving adjacent soft tissue (dura mater and nervous tissue) was studied. Bone necrosis of the osteotomy sites and the vitality of the osteocytes near the sectional plane were investigated, as well as the proportion of apoptosis or cell degeneration. Results and Conclusions: The potential positive effects on bone healing and reossification associated with different devices were evaluated and the comparative analysis among the different devices used was performed, in order to determine the best osteotomes to be employed during cranio-facial surgery