An Investigation of Heredity in the Aetiology and Pathogenesis of Cleft Palate and of Cleft Lip and Palate

Cleft lip with or without cleft palate (CL(P)) and isolated cleft palate (CP) are caused by primary defects in the fusion of craniofacial processes that form the primary and secondary palate respectively. CL(P) and CP are considered to be separate diagnostic entities and for both multifactorial inheritance has been proposed, although the precise roles played by genes, environment and chance are unclear; and in particular the nature and number of genes involved is not known. The aim of this study was to try to identify parental characteristics (genotypic or phenotypic) which were associated with an increased risk of having a child with CL(P) or CP. The combination of phenotypic and genotypic data can improve the ability to predict parental predisposition towards CP or CL(P) beyond the predictive ability of either cephalometric or genetic data in isolation. The lack of correlation between these genotypes and the cephalometric parameters would suggest that other genetic loci are involved in the predisposition to CL(P) and CP and further analysis of other candidate genes using this approach would merit consideration. (Abstract shortened by ProQuest.)

Predicting and optimising the postoperative outcomes of sagittal craniosynostosis correction

The neonate skull consists of several flat bones, connected by fibrous joints called sutures. Sutures regulate the bone formation along their adjoining edges, while providing mailability to assist with the early phases of rapid brain growth and passing through the birth canal with minimal restriction. By adolescents, these sutures fuse into solid bone, protecting the brain from impacts. The premature fusion of one or more of these sutures is a medical condition known as craniosynostosis, with its most common form being sagittal craniosynostosis (fusion of the midline suture). The condition results in compensatory overgrowth perpendicular to the fused suture, leading to calvarial deformation and possible neurofunctional defects. Surgeons have developed several surgical techniques to restore the normative shape. This has led to debates as to which surgical option provides the most beneficial long term outcome. The overall aim of this thesis was to develop a computational approach using the finite element (FE) method capable of predicting and optimising the long term outcomes for treating sagittal craniosynostosis. A generic 3D pre-operative FE model was developed using patient specific CT data. The FE model was parameterised to predict the long term calvarial growth, the pattern of suture and bone formation, the pattern of bone healing across the replicated surgical techniques, and the changes in contact pressure levels across the modelled brain. All techniques underwent simulated growth up to the maximum age of 76 months. Morphological results were compared against the patient specific CT data at the same age. Where absent, technique specific follow up CT data were used instead. Results highlighted a good morphological agreement between the predicted models and their comparative CT data. The FE model was highly sensitive to the choice of input parameters. Based on the findings of this thesis, the *** approach proved the most optimal across the predicted outcomes. The novel methodology and platform developed here has huge potential to better inform surgeons of the impact various techniques could have on long term outcomes and continue to improve the quality of care for patients undergoing corrective surgery

Medical Robotics

The first generation of surgical robots are already being installed in a number of operating rooms around the world. Robotics is being introduced to medicine because it allows for unprecedented control and precision of surgical instruments in minimally invasive procedures. So far, robots have been used to position an endoscope, perform gallbladder surgery and correct gastroesophogeal reflux and heartburn. The ultimate goal of the robotic surgery field is to design a robot that can be used to perform closed-chest, beating-heart surgery. The use of robotics in surgery will expand over the next decades without any doubt. Minimally Invasive Surgery (MIS) is a revolutionary approach in surgery. In MIS, the operation is performed with instruments and viewing equipment inserted into the body through small incisions created by the surgeon, in contrast to open surgery with large incisions. This minimizes surgical trauma and damage to healthy tissue, resulting in shorter patient recovery time. The aim of this book is to provide an overview of the state-of-art, to present new ideas, original results and practical experiences in this expanding area. Nevertheless, many chapters in the book concern advanced research on this growing area. The book provides critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies. This book is certainly a small sample of the research activity on Medical Robotics going on around the globe as you read it, but it surely covers a good deal of what has been done in the field recently, and as such it works as a valuable source for researchers interested in the involved subjects, whether they are currently “medical roboticists” or not

Three-dimensional assessment of facial morphology in infants with cleft lip and palate

Differential growth was demonstrated between facial features and within some facial features. In particular, the columella, nostrils and philtrum did not grow significantly after surgery, although this would be considered normal in the age group studied. Facial growth in children with UCL and UCLP was independent of the head and body growth. The presence of a cleft of the secondary palate accentuated the amount of soft tissue disruption by the cleft in the lip and nose, but not the pattern of disruption. Primary lip / nose repair had no detrimental effect on the early growth and development of the facial features. Likewise, palate repair had no discernible effect on facial soft tissue growth at age 2 years. Primary lip /nose repair had a beneficial effect on facial morphology in terms of reducing asymmetry and was most successful in the improving philtrum and nasal base symmetry, less successful in improving the nasal rim asymmetry. A possible early beneficial effect of cleft repair remote from the surgery site was noted in the reduction of upper face asymmetry in the first year of life. Residual asymmetry in the facial features did not change by age 2 years, despite increases in size with growth. Facial morphology outcomes for UCL and UCLP children in this study was generally similar at 2 years of age, despite marked differences in pre-operative facial form. However, nasal base asymmetry, upper face asymmetry and residual nostril shape deformity were significantly greater in UCLP children at 2 years of age, than in UCL children. These shape differences were not detectable by measurement of facial dimensions alone

A Textbook of Advanced Oral and Maxillofacial Surgery

The scope of OMF surgery has expanded; encompassing treatment of diseases, disorders, defects and injuries of the head, face, jaws and oral cavity. This internationally-recognized specialty is evolving with advancements in technology and instrumentation. Specialists of this discipline treat patients with impacted teeth, facial pain, misaligned jaws, facial trauma, oral cancer, cysts and tumors; they also perform facial cosmetic surgery and place dental implants. The contents of this volume essentially complements the volume 1; with chapters that cover both basic and advanced concepts on complex topics in oral and maxillofacial surgery

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

CT Scanning

Since its introduction in 1972, X-ray computed tomography (CT) has evolved into an essential diagnostic imaging tool for a continually increasing variety of clinical applications. The goal of this book was not simply to summarize currently available CT imaging techniques but also to provide clinical perspectives, advances in hybrid technologies, new applications other than medicine and an outlook on future developments. Major experts in this growing field contributed to this book, which is geared to radiologists, orthopedic surgeons, engineers, and clinical and basic researchers. We believe that CT scanning is an effective and essential tools in treatment planning, basic understanding of physiology, and and tackling the ever-increasing challenge of diagnosis in our society

Recognition, Analysis, and Assessments of Human Skills using Wearable Sensors

One of the biggest social issues in mature societies such as Europe and Japan is the aging population and declining birth rate. These societies have a serious problem with the retirement of the expert workers, doctors, and engineers etc. Especially in the sectors that require long time to make experts in fields like medicine and industry; the retirement and injuries of the experts, is a serious problem. The technology to support the training and assessment of skilled workers (like doctors, manufacturing workers) is strongly required for the society. Although there are some solutions for this problem, most of them are video-based which violates the privacy of the subjects. Furthermore, they are not easy to deploy due to the need for large training data. This thesis provides a novel framework to recognize, analyze, and assess human skills with minimum customization cost. The presented framework tackles this problem in two different domains, industrial setup and medical operations of catheter-based cardiovascular interventions (CBCVI). In particular, the contributions of this thesis are four-fold. First, it proposes an easy-to-deploy framework for human activity recognition based on zero-shot learning approach, which is based on learning basic actions and objects. The model recognizes unseen activities by combinations of basic actions learned in a preliminary way and involved objects. Therefore, it is completely configurable by the user and can be used to detect completely new activities. Second, a novel gaze-estimation model for attention driven object detection task is presented. The key features of the model are: (i) usage of the deformable convolutional layers to better incorporate spatial dependencies of different shapes of objects and backgrounds, (ii) formulation of the gaze-estimation problem in two different way, as a classification as well as a regression problem. We combine both formulations using a joint loss that incorporates both the cross-entropy as well as the mean-squared error in order to train our model. This enhanced the accuracy of the model from 6.8 by using only the cross-entropy loss to 6.4 for the joint loss. The third contribution of this thesis targets the area of quantification of quality of i actions using wearable sensor. To address the variety of scenarios, we have targeted two possibilities: a) both expert and novice data is available , b) only expert data is available, a quite common case in safety critical scenarios. Both of the developed methods from these scenarios are deep learning based. In the first one, we use autoencoders with OneClass SVM, and in the second one we use the Siamese Networks. These methods allow us to encode the expert’s expertise and to learn the differences between novice and expert workers. This enables quantification of the performance of the novice in comparison to the expert worker. The fourth contribution, explicitly targets medical practitioners and provides a methodology for novel gaze-based temporal spatial analysis of CBCVI data. The developed methodology allows continuous registration and analysis of gaze data for analysis of the visual X-ray image processing (XRIP) strategies of expert operators in live-cases scenarios and may assist in transferring experts’ reading skills to novices

Manifold Learning for Natural Image Sets, Doctoral Dissertation August 2006

The field of manifold learning provides powerful tools for parameterizing high-dimensional data points with a small number of parameters when this data lies on or near some manifold. Images can be thought of as points in some high-dimensional image space where each coordinate represents the intensity value of a single pixel. These manifold learning techniques have been successfully applied to simple image sets, such as handwriting data and a statue in a tightly controlled environment. However, they fail in the case of natural image sets, even those that only vary due to a single degree of freedom, such as a person walking or a heart beating. Parameterizing data sets such as these will allow for additional constraints on traditional computer vision problems such as segmentation and tracking. This dissertation explores the reasons why classical manifold learning algorithms fail on natural image sets and proposes new algorithms for parameterizing this type of data