Identifying the Severity of Adolescent Idiopathic Scoliosis During Gait by Using Machine Learning

La scoliose idiopathique de l'adolescent (SIA) est une déformation de la colonne vertébrale dans les trois plans de l’espace objectivée par un angle de Cobb ≥ 10°. Celle-ci affecte les adolescents âgés entre 10 et 16 ans. L’étiologie de la scoliose demeure à ce jour inconnue malgré des recherches approfondies. Différentes hypothèses telles que l’implication de facteurs génétiques, hormonaux, biomécaniques, neuromusculaires ou encore des anomalies de croissance ont été avancées. Chez ces adolescents, l'ampleur de la déformation de la colonne vertébrale est objectivée par mesure manuelle de l’angle de Cobb sur radiographies antéropostérieures. Cependant, l’imprécision inter / intra observateur de cette mesure, ainsi que de l’exposition fréquente (biannuelle) aux rayons X que celle-ci nécessite pour un suivi adéquat, sont un domaine qui préoccupe la communauté scientifique et clinique. Les solutions proposées à cet effet concernent pour beaucoup l'utilisation de méthodes assistées par ordinateur, telles que des méthodes d'apprentissage machine utilisant des images radiographiques ou des images du dos du corps humain. Ces images sont utilisées pour classer la sévérité de la déformation vertébrale ou pour identifier l'angle de Cobb. Cependant, aucune de ces méthodes ne s’est avérée suffisamment précise pour se substituer l’utilisation des radiographies. Parallèlement, les recherches ont démontré que la scoliose modifie le schéma de marche des personnes qui en souffrent et par conséquent également les efforts intervertébraux. C’est pourquoi, l'objectif de cette thèse est de développer un modèle non invasif d’identification de la sévérité de la scoliose grâce aux mesures des efforts intervertébraux mesurés durant la marche. Pour atteindre cet objectif, nous avons d'abord comparé les efforts intervertébraux calculés par un modèle dynamique multicorps, en utilisant la dynamique inverse, chez 15 adolescents atteints de SIA avec différents types de courbes et de sévérités et chez 12 adolescents asymptomatiques (à titre comparatif). Par cette comparaison, nous avons pu objectiver que les efforts intervertébraux les plus discriminants pour prédire la déformation vertébrale étaient la force et le couple antéro-postérieur et la force médio-latérale. Par la suite, nous nous sommes concentrés sur la classification de la sévérité de la déformation vertébrale de 30 AIS ayant une courbure thoraco-lombaire / lombaire. Pour ce faire, nous avons testé différents modèles de classification. L'angle de Cobb a été identifié en exécutant différents modèles de régression. Les caractéristiques (features) servant à alimenter les algorithmes d'entraînement ont été choisies en fonction des efforts intervertébraux les plus pertinents à la déformation vertébrale au niveau de la charnière lombo-sacrée (vertèbres allantes de L5-S1). Les précisions les plus élevées pour la classification exécutant différents algorithmes ont été obtenues par un algorithme de classification d'ensemble comprenant les “K-nearest neighbors”, “Support vector machine”, “Random forest”, “multilayer perceptron”, et un modèle de “neural networks” avec une précision de 91.4% et 93.6%, respectivement. De même, le modèle de régression par “Decision tree” parmi les autres modèles a obtenu le meilleur résultat avec une erreur absolue moyenne égale à 4.6° de moyenne de validation croisée de 10 fois. En conclusion, nous pouvons dire que cette étude démontre une relation entre la déformation de la colonne vertébrale et les efforts intervertébraux mesurés lors de la marche. L'angle de Cobb a été identifié à l'aide d'une méthode sans rayonnement avec une précision prometteuse égale à 4.6°. Il s’agit d’une amélioration majeure par rapport aux méthodes précédemment proposées ainsi que par rapport à la mesure classique réalisée par des spécialistes présentant une erreur entre 5° et 10° (ceci en raison de la variation intra/inter observateur). L’algorithme que nous vous présentons peut être utilisé comme un outil d'évaluation pour suivre la progression de la scoliose. Il peut être considéré comme une alternative à la radiographie. Des travaux futurs devraient tester l'algorithme et l’adapter pour d’autres formes de SIA, telles que les scolioses lombaire ou thoracolombaire.----------ABSTRACT Adolescent idiopathic scoliosis (AIS) is a 3D deformation of the spine and rib cage greater than 10° that affects adolescents between the ages of 10 and 16 years old. The true etiology is unknown despite extensive research and investigation. However, different theories such as genetic and hormonal factors, growth abnormalities or biomechanical and neuromuscular reasons have been proposed as possible causes. The magnitude of spinal deformity in AIS is measured by the Cobb angle in degrees as the gold standard through the X-rays by specialists. The inter/intra observer error and the cumulative exposure to radiation, however, are sources of increasing concern among researchers with regards to the accuracy of manual measurement. Proposed solutions have therefore, focused on using computer-assisted methods such as Machine Learning using X-ray images, and/or trunk images to classify the severity of spinal deformity or to identify the Cobb angle. However, none of the proposed methods have shown the level of accuracy required for use as an alternative to X-rays. Meanwhile, scoliosis has been recognized as a pathology that modifies the gait pattern, subsequently impinging upon intervertebral efforts. The present thesis aims to develop a radiation-free model to identify the severity of idiopathic scoliosis in adolescents based on the intervertebral efforts during gait. To accomplish this objective, we compared the intervertebral efforts computed using a multibody dynamics model, by way of inverse dynamics, among 15 adolescents with AIS having different curve types and severities, as well as 12 typically developed adolescents. This resulted in the identification of the most relevant intervertebral efforts influenced by spinal deformity: mediolateral (ML) force; anteroposterior (AP) force; and torque. Additionally, we focused on the classification of the severity of spinal deformity among 30 AIS with thoracolumbar/lumbar curvature, testing different classification models. Lastly, the Cobb angle was identified running regression models. The features to feed training algorithms were chosen based on the most relevant intervertebral efforts to the spinal deformity on the lumbosacral (L5-S1) joint. The highest accuracies for the classification were obtained by the ensemble classifier algorithm, including “K-nearest neighbors”, “support vector machine”, “random forest”, and “multilayer perceptron”, as well as a neural network model with an accuracy of 91.4% and 93.6%, respectively. Likewise, the “decision tree regression” model achieved the best result with a mean absolute error equal to 4.6 degrees of an averaged 10-fold cross-validation. This study shows a relation between spinal deformity and the produced intervertebral efforts during gait. The Cobb angle was identified using a radiation-free method with a promising accuracy, providing a mean absolute error of 4.6°. Compared to measurement variations, ranging between 5° and 10° in the manual Cobb angle measurements by specialists, the proposed model provided reliable accuracy. This algorithm can be used as an assessment tool, alternative to the X-ray radiography, to follow up the progression of scoliosis. As future work, the algorithm should be tested and modified on AIS with other types of spine curvature than lumbar/thoracolumbar

A three dimensional analysis of soft tissue and bone changes following orthognathic surgery

Introduction: This report investigates the ability of surgeons to achieve predicted surgical movements in five different groups of patients, and analyses both the predictions and the changes in two dimensions using scale space analyses (Campos 1991). The report then progresses to the three dimensional analysis of the bone, the soft tissues and the ratio of soft tissue to bone following surgery, using a colour coded techniques (Fright and Linney, 1991) to illustrate the changes. The average soft tissue scans from each group of patients were averaged and compared to a control group at the preoperative, three months and 1 year postoperative stages (Fright, 1991) Data Acquisition: Bone measurements were recorded from lateral skull radiographs preoperatively and 48 hrs postoperatively, and CT scans preoperatively and 1 year postoperatively. Soft tissue measurements from an optical scanner, preoperatively, three months and 1 year postoperatively. Patients 1) Control group: 30 females and 30 males 2) Skeletal class 2 patients: 15 Females and 2 Males 3) Skeletal class 3 patients: 9 Females and 7 Males 4) Cleft Palate Patients a) Unilateral cleft lip and palate: I 6 Females: 2 left and 4 right sided clefts 7 Males: 3 left and 4 right sided clefts b) Bilateral cleft lip and palate: 5 Males and 1 Female c) Clefts of the Hard and Soft palate: 5 Females. Results: Prediction: There was a surprisingly poor match between the predicted and achieved movements in both the horizontal and vertical direction in all patient groups. The scale space analysis provided an efficient method of illustrating profile changes. Soft tissue movements There were definite patterns of change and relapse in the patient groups. The relapse being most marked in the cleft palate patients. Bone movements and soft tissue to bone ratios Definite patterns of movement for the maxilla and the mandible became apparent for both the bone and soft tissue to bone ratio of movement in each group. For maxillary impactions in the skeletal 2 group there was a 1:1 ratio of movement of the soft tissue to bone in the midline increasing to 1.25:1 in the canine region and 1.5:1 in the paranasal region. Conclusions: There is a need to develop a technique to aid the the surgeons in carrying out planned surgical movements. The colour coded method was shown to be a simple, efficient and easily understandable way of analysing surgical change. Diagnosis of surgical requirements was aided by the ability to objectively compare the individual to a control group. The prediction of surgical change should be greatly aided by adapting the current database to include the distinct patterns of movement in the bone and ratio of movements of the soft tissues to the bone

3-D surface modelling of the human body and 3-D surface anthropometry

This thesis investigates three-dimensional (3-D) surface modelling of the human body and 3-D surface anthropometry. These are two separate, but closely related, areas. 3-D surface modelling is an essential technology for representing and describing the surface shape of an object on a computer. 3-D surface modelling of the human body has wide applications in engineering design, work space simulation, the clothing industry, medicine, biomechanics and animation. These applications require increasingly realistic surface models of the human body. 3-D surface anthropometry is a new interdisciplinary subject. It is defined in this thesis as the art, science, and technology of acquiring, modelling and interrogating 3-D surface data of the human body. [Continues.

Shape classification: towards a mathematical description of the face

Recent advances in biostereometric techniques have led to the quick and easy acquisition of 3D data for facial and other biological surfaces. This has led facial surgeons to express dissatisfaction with landmark-based methods for analysing the shape of the face which use only a small part of the data available, and to seek a method for analysing the face which maximizes the use of this extensive data set. Scientists working in the field of computer vision have developed a variety of methods for the analysis and description of 2D and 3D shape. These methods are reviewed and an approach, based on differential geometry, is selected for the description of facial shape. For each data point, the Gaussian and mean curvatures of the surface are calculated. The performance of three algorithms for computing these curvatures are evaluated for mathematically generated standard 3D objects and for 3D data obtained from an optical surface scanner. Using the signs of these curvatures, the face is classified into eight 'fundamental surface types' - each of which has an intuitive perceptual meaning. The robustness of the resulting surface type description to errors in the data is determined together with its repeatability. Three methods for comparing two surface type descriptions are presented and illustrated for average male and average female faces. Thus a quantitative description of facial change, or differences between individual's faces, is achieved. The possible application of artificial intelligence techniques to automate this comparison is discussed. The sensitivity of the description to global and local changes to the data, made by mathematical functions, is investigated. Examples are given of the application of this method for describing facial changes made by facial reconstructive surgery and implications for defining a basis for facial aesthetics using shape are discussed. It is also applied to investigate the role played by the shape of the surface in facial recognition

Application of biomechanical techniques to improved design of products and environments for an ageing population

This work describes the development of a technique for the evaluation of the performance of a product's physical user interface. The technique is intended to combine the best features cat conventional user group testing with those of computer based biomechanical modelling. A requirement for the new technique exists as social pressure demands that consumer products he optimised for users with a wide range of physical capabilities, while shortening product lifecycles leave less time for extensive user evaluation programmes. A demonstration system was developed, based upon the use of an electromagnetic tracking system to gather upper limb motion data and a two segment, rigid link biomechanical model. Experimental work was carried out to test the effectiveness of the system at following limb movements and average error in reconstruction of hand position from segment angle data was 62mm (Standard deviation 41 mm) The modelling system was applied to the assessment of two types of product: cutlery and drinking vessels and the effectiveness of various statistical techniques in allowing the rapid identification of important design parameters was assessed. The use of Taguchi's smaller-the-better signal to noise ratio was found to be effective for the measurement of the effect of product design on shoulder and elbow forces. Cutlery with enlarged handles designed to reduce grip strength requirements tended to increase forces at the shoulder. The method was also applied to an interface optimisation problem involving the design of a lever mechanism. Partial factorial design was used to minimise experimental cost during the assessment of multiple factors, but strong interactions were detected between interface parameters, reducing the value of the analysis. The overall height of the lever handle relative to the user's shoulder was found to be the most significant design factor, with an optimum operating situation existing where the lever was low enough to require almost full extension of the elbow during use. The work concludes that biomechanical analysis holds further promise for the optimisation of interface parameters, provided the high experimental cost involved with present techniques can be reduced

Low Back Pain (LBP)

Low back pain (LBP) is a major public health problem, being the most commonly reported musculoskeletal disorder (MSD) and the leading cause of compromised quality of life and work absenteeism. Indeed, LBP is the leading worldwide cause of years lost to disability, and its burden is growing alongside the increasing and aging population. The etiology, pathogenesis, and occupational risk factors of LBP are still not fully understood. It is crucial to give a stronger focus to reducing the consequences of LBP, as well as preventing its onset. Primary prevention at the occupational level remains important for highly exposed groups. Therefore, it is essential to identify which treatment options and workplace-based intervention strategies are effective in increasing participation at work and encouraging early return-to-work to reduce the consequences of LBP. The present Special Issue offers a unique opportunity to update many of the recent advances and perspectives of this health problem. A number of topics will be covered in order to attract high-quality research papers, including the following major areas: prevalence and epidemiological data, etiology, prevention, assessment and treatment approaches, and health promotion strategies for LBP. We have received a wide range of submissions, including research on the physical, psychosocial, environmental, and occupational perspectives, also focused on workplace interventions

Imaging Sensors and Applications

In past decades, various sensor technologies have been used in all areas of our lives, thus improving our quality of life. In particular, imaging sensors have been widely applied in the development of various imaging approaches such as optical imaging, ultrasound imaging, X-ray imaging, and nuclear imaging, and contributed to achieve high sensitivity, miniaturization, and real-time imaging. These advanced image sensing technologies play an important role not only in the medical field but also in the industrial field. This Special Issue covers broad topics on imaging sensors and applications. The scope range of imaging sensors can be extended to novel imaging sensors and diverse imaging systems, including hardware and software advancements. Additionally, biomedical and nondestructive sensing applications are welcome