Noninvasive Clinical Assessment of Trunk Deformities Associated With Scoliosis

Besides the spinal deformity, scoliosis modifies notably the general appearance of the trunk resulting in trunk rotation, imbalance, and asymmetries that constitutes patients' major concern. Existing classifications of scoliosis, based on the type of spinal curve as depicted on radiographs, are currently used to guide treatment strategies. Unfortunately, even though a perfect correction of the spinal curve is achieved, some trunk deformities remain, making patients dissatisfied with the treatment received. The purpose of this study is to identify possible shape patterns of trunk surface deformity associated with scoliosis. First, trunk surface is represented by a multivariate functional trunk shape descriptor based on 3-D clinical measurements computed on cross sections of the trunk. Then, the classical formulation of hierarchical clustering is adapted to the case of multivariate functional data and applied to a set of 236 trunk surface 3-D reconstructions. The highest internal validity is obtained when considering 11 clusters that explain up to 65% of the variance in our dataset. Our clustering result shows a concordance with the radiographic classification of spinal curves in 68% of the cases. As opposed to radiographic evaluation, the trunk descriptor is 3-D and its functional nature offers a compact and elegant description of not only the type, but also the severity and extent of the trunk surface deformity along the trunk length. In future work, new management strategies based on the resulting trunk shape patterns could be thought of in order to improve the esthetic outcome after treatment, and thus patients satisfaction.CIHR / IRS

Non invasive classification system of scoliosis curve types using least-squares support vector machines

Objective To determine scoliosis curve types using non invasive surface acquisition, without prior knowledge from X-ray data. Methods Classification of scoliosis deformities according to curve type is used in the clinical management of scoliotic patients. In this work, we propose a robust system that can determine the scoliosis curve type from non invasive acquisition of the 3D back surface of the patients. The 3D image of the surface of the trunk is divided into patches and local geometric descriptors characterizing the back surface are computed from each patch and constitute the features. We reduce the dimensionality by using principal component analysis and retain 53 components using an overlap criterion combined with the total variance in the observed variables. In this work, a multi-class classifier is built with least-squares support vector machines (LS-SVM). The original LS-SVM formulation was modified by weighting the positive and negative samples differently and a new kernel was designed in order to achieve a robust classifier. The proposed system is validated using data from 165 patients with different scoliosis curve types. The results of our non invasive classification were compared with those obtained by an expert using X-ray images. Results The average rate of successful classification was computed using a leave-one-out cross-validation procedure. The overall accuracy of the system was 95%. As for the correct classification rates per class, we obtained 96%, 84% and 97% for the thoracic, double major and lumbar/thoracolumbar curve types, respectively. Conclusion This study shows that it is possible to find a relationship between the internal deformity and the back surface deformity in scoliosis with machine learning methods. The proposed system uses non invasive surface acquisition, which is safe for the patient as it involves no radiation. Also, the design of a specific kernel improved classification performance.IRSC / CIH

Statistical model based 3D shape prediction of postoperative trunks for non-invasive scoliosis surgery planning

One of the major concerns of scoliosis patients undergoing surgical treatment is the aesthetic aspect of the surgery outcome. It would be useful to predict the postoperative appearance of the patient trunk in the course of a surgery planning process in order to take into account the expectations of the patient. In this paper, we propose to use least squares support vector regression for the prediction of the postoperative trunk 3D shape after spine surgery for adolescent idiopathic scoliosis. Five dimensionality reduction techniques used in conjunction with the support vector machine are compared. The methods are evaluated in terms of their accuracy, based on the leave-one-out cross-validation performed on a database of 141 cases. The results indicate that the 3D shape predictions using a dimensionality reduction obtained by simultaneous decomposition of the predictors and response variables have the best accuracy.CIHR / IRS

A physically based trunk soft tissue modeling for scoliosis surgery planning systems

One of the major concerns of scoliotic patients undergoing spinal correction surgery is the trunk's external appearance after the surgery. This paper presents a novel incremental approach for simulating postoperative trunk shape in scoliosis surgery. Preoperative and postoperative trunk shapes data were obtained using three-dimensional medical imaging techniques for seven patients with adolescent idiopathic scoliosis. Results of qualitative and quantitative evaluations, based on the comparison of the simulated and actual postoperative trunk surfaces, showed an adequate accuracy of the method. Our approach provides a candidate simulation tool to be used in a clinical environment for the surgery planning process.IRSC / CIH

Modified Large Margin Nearest Neighbor Metric Learning for Regression

The main objective of this letter is to formulate a new approach of learning a Mahalanobis distance metric for nearest neighbor regression from a training sample set. We propose a modified version of the large margin nearest neighbor metric learning method to deal with regression problems. As an application, the prediction of post-operative trunk 3-D shapes in scoliosis surgery using nearest neighbor regression is described. Accuracy of the proposed method is quantitatively evaluated through experiments on real medical data.IRSC / CIH

Analyse de la relation entre les déformations scoliotiques du tronc et celles des structures osseuses sous-jacentes

RÉSUMÉ La scoliose idiopathique adolescente est une déformation tridimensionnelle complexe de la colonne vertébrale et de la cage thoracique qui entraine des déformations visibles à la surface du tronc. On remarque généralement une asymétrie des épaules, des omoplates, de la taille et du bassin ainsi qu’une bosse dans le dos. Ces déformations esthétiques constituent, d’une part, les premiers signes d’une scoliose, et d’autre part, la principale préoccupation des jeunes patients qui voient leur corps se développer différemment des jeunes de leur âge. Les outils cliniques utilisés pour quantifier les déformations du tronc, comme le scoliomètre ou le fil à plomb, sont peu fiables. C’est pourquoi, aujourd’hui, l’évaluation de la scoliose repose principalement sur des radiographies de face et de profil du tronc complet. Celles-ci permettent d’apprécier le type de courbure rachidienne et de quantifier son degré de sévérité, en fonction de quoi une stratégie de traitement sera décidée. Cependant, une exposition répétée des patients aux rayons X peut entrainer des effets indésirables sur leur santé. De plus, ces paramètres radiographiques ne permettent pas de documenter les déformations esthétiques. Cette différence notable entre ce que le patient perçoit, et ce que le clinicien est capable d’évaluer, peut mener à l’insatisfaction des patients suite au traitement. Comparativement aux radiographies, la surface du tronc reconstruite par les systèmes de numériseurs optiques 3D représente mieux les déformations que les patients observent et dont ils se soucient principalement, comme la gibbosité. De plus, l’absence de rayonnement ionisant est un avantage majeur de ces systèmes optiques, qui favorise une évaluation aussi fréquente que souhaité. Toutefois, l’absence de consensus sur un ensemble de mesures des déformations de la surface du tronc fait en sorte qu’elles restent encore considérées comme secondaires dans l’évaluation clinique; pourtant elles sont au coeur des préoccupations des patients. De cette double problématique, découle la question de recherche globale de cette thèse : comment compléter, voire remplacer, les évaluations clinique et radiographique actuelles de la scoliose par de l’information quantitative obtenue de manière non irradiante et qui permet de prendre davantage en considération les préoccupations des patients par rapport à leurs déformations esthétiques du tronc ? Parmi les premiers signes de scoliose, la gibbosité est une déformation esthétique qui ne peut être évaluée sur des radiographies, ni sur une reconstruction 3D de la colonne vertébrale.----------ABSTRACT Adolescent idiopathic scoliosis is a complex three-dimensional deformation of the spine and rib cage which leads to visible deformations at the trunk surface. The first signs of scoliosis include a hump on the back, a lateral shift of the trunk and asymmetries of the shoulders, the scapula, the waist and the hips. These esthetic deformities constitute major concern of patients and the reason for which they seek treatment. Currently, the tools available in clinical practice to quantify trunk deformations have limited reliability. For this reason, current scoliosis assessment is mainly based on frontal and lateral radiographs of the entire spine. These images allow clinicians to determine the type of the spinal curvature and its severity, according to which the treatment strategy is decided. However, the repeated exposure of patients to X-ray radiation can be harmful. Moreover, these radiographic measures do not give an indication as to the esthetic deformities of the trunk. This significant difference between what patients perceive and what clinicians are able to evaluate can lead to patient dissatisfaction following treatment. Compared to X-rays, the trunk surface acquired and reconstructed in 3D using optical digitizers better represents the deformations that patients observe and are primarily concerned with, such as the rib hump. In addition, the major advantage of these optical systems is their lack of ionizing radiation, thus allowing for a more frequent scoliosis assessment when compared to X-rays. However, there is currently no consensus on a set of indices that optimally quantifies trunk surface deformations. For this reason, trunk surface indices are still considered as secondary in the clinical evaluation, even though they are at the heart of the patients’ preoccupations. These problems lead to the main research question of this thesis: How can we complete, or even replace, the current clinical and radiographic evaluations of scoliosis with quantitative information obtained without ionizing radiation that takes more into account the patients’ concerns about their cosmetic trunk deformities? Among the first signs of scoliosis, the rib hump is a cosmetic deformity that cannot be assessed on radiographs, nor on a 3D reconstruction of the spine. It is mainly associated with rib cage deformity. It is therefore intuitive to suppose that the axial rotations of the ribs and of the back surface are highly correlated. Nevertheless, previous works have failed to demonstrate a strong relationship between these measurements. This might be explained by the limited accuracy of the technique used for the 3D reconstruction of the ribs. Consequently, in this work, a novel metho

Modélisation physique des tissus mous du tronc scoliotique pour la simulation de l'apparence post-chirurgicale

RÉSUMÉ La scoliose idiopathique de l'adolescence (SIA) est une déformation tridimensionnelle complexe de la colonne vertébrale et de la cage thoracique. Dans le cas de déformation sévère, le recours à la chirurgie correctrice de la colonne vertébrale est requis comme moyen de traitement. Environ un patient sur mille atteint de SIA aura à subir une chirurgie correctrice de la colonne vertébrale. Cependant, dans la plupart des cas, une correction optimale de la colonne vertébrale n'entraine pas nécessairement une correction optimale de l'apparence externe. Une asymétrie du tronc peut persister à l'issue de la chirurgie et cela est difficile à prédire par les chirurgiens. Cela est problématique, car l'apparence externe est un facteur important de satisfaction pour les patients. Il serait intéressant de disposer d'outils d'assistance à la planification de chirurgie pour la scoliose prenant en compte les attentes du patient concernant l'esthétique de l'apparence du tronc. La simulation médicale sur ordinateur est devenue un outil important d'assistance à la prise de décision clinique. Elle est utilisée pour permettre de prédire et analyser les effets de traitements médicaux, ainsi que la prédiction de changements anatomiques dus à l'évolution d'une pathologie. Dans le contexte de la chirurgie pour la scoliose, des simulateurs de chirurgie correctrice de la colonne vertébrale existent. Des modèles biomécaniques pour la simulation de l'instrumentation de la colonne vertébrale en chirurgie de la scoliose ont été développés par différents chercheurs. Toutefois, ceux-ci ne prédisent pas la forme externe du tronc après chirurgie. De cet état des choses, découle la problématique et les objectifs de cette thèse: modéliser le tronc scoliotique en vue de la simulation de la forme postopératoire du tronc, et améliorer la précision des prédictions afin de proposer une stratégie opératoire optimale. La question de recherche abordée dans cette thèse concerne le développement de méthodes pour la simulation et la prédiction de la forme post-opératoire du tronc en chirurgie pour la scoliose. Quatre objectifs spécifiques de recherche ont été définis. La première partie du travail (traitant du premier objectif) a consisté à développer un modèle physique de déformation pour le tronc scoliotique. Contrairement au modèle existant, un nouveau modèle physique de déformation incrémentale est proposé pour tenir compte des grandes déformations du tronc. L'inspection qualitative des surfaces de tronc simulées et réelles montre une bonne approximation de la correction de la gibbosité. L'évaluation quantitative de la simulation est basée sur l'indice de rotation de la surface du dos (indice BSR). Il se définit comme l'angle formé par la double tangente du côté postérieur de chaque section horizontale de la surface du tronc et l'axe passant par les épines iliaques antéro-supérieures (ASIS) projeté sur le plan frontal. Les valeurs d'indices BSR, mesurées à différents niveaux vertébraux, montrent une erreur moyenne de 1.20º (± 0.73) à 3.20º (± 0.83) dans la région thoracique, indiquant un accord entre les troncs prédits et les données réelles. La deuxième partie (regroupant les trois autres objectifs spécifiques) a consisté à améliorer la précision des prédictions. Nous proposons deux méthodes de détermination de formes à priori de tronc postopératoire (soit basé sur une prédiction statistique, soit basé sur une prédiction de type proche voisin). Ces outils exploitent l'intuition de choisir la restriction du champ de déplacement à la frontière du domaine du tronc (la surface externe) comme une première approximation de la déformation du tronc. La réalisation des objectifs de cette recherche est à l'origine de contributions originales à l'état de l'art aussi bien en simulation physique de tissus mous qu'en apprentissage machine pour l'analyse de formes. Ce projet propose une nouvelle méthode de modélisation des déformations de tissus mous du tronc scoliotique pour la simulation de l'apparence postopératoire. Cette méthode présente, ainsi, l'avantage de constituer un outil pour les systèmes de planification par ordinateur de traitement chirurgical de la scoliose. En perspective, des études complémentaires sont suggérées pour surmonter certaines limitations des méthodes proposées. En particulier, l'incorporation d'un modèle du tronc obtenu par une fusion multimodale d'images (IRM/RX/TOPO) de patients scoliotiques, pour une meilleure personnalisation géométrique, devrait conduire à une amélioration de la précision de la simulation.----------ABSTRACT Adolescent Idiopathic scoliosis (AIS) is a complex three-dimensional deformation of the spine and rib cage. In case of severe spine deformity, a spine surgery is required as a treatment. Approximately one in a thousand patients suffering from AIS will have a spine surgery. However, in most cases, an optimal correction of the spine does not necessarily results in an optimal correction of the external appearance. A trunk asymmetry may persist after surgery and it is difficult to predict by surgeons. This is problematic because the external appearance is one of the most important factor for the patient satisfaction. It would be interesting to have available computer based scoliosis surgery planning assistance tools that takes into account the expectation of the patient regarding the aesthetics of the trunk appearance. Computer based medical simulation is becoming an important tool to support clinical decision making. It is used to predict and analyze the effects of treatments, as well as the predictions of changes due to pathology evolution. In the context of scoliosis surgery, spine correction surgery simulators exist. Biomechanical models for the simulation of the spine instrumentation in scoliosis surgery have been developed by different researchers. However, they do not simulate the postoperative appearance of the trunk. From this observation arise the problem and objectives of this thesis: modeling the scoliotic trunk in order to simulate the postoperative trunk shape, and improve predictions accuracy in order to propose an optimal surgery strategy. The research question of this thesis concerns the development of methods for the simulation and the prediction of the trunk postoperative shape in scoliosis surgery. Four research objectives have been defined. The first part of this work (dealing with the first objective) consisted in developing a physically based deformation model of the scoliotic trunk. Unlike the existing model, a novel incremental approach is proposed to take into account large deformations of the trunk. The qualitative visual inspection of the simulated and actual trunk surfaces show a good approximation of the correction of the rib hump. The quantitative evaluation of the simulation is based on the back surface rotation index (BSR index). It is defined as the angle formed by the dual tangent to the posterior side of each section of the trunk surface and the axis passing through the patient's anterior superior iliac spines (ASIS), projected onto the axial plane. The BSR indices, measured at different vertebral levels, shows an average error in the range of 1.20º (± 0.73) to 3.20º (± 0.83$) in the thoracic region, indicating a good agreement between the predicted and actual trunk surfaces. The second part (dealing with the remaining three objectives) addressed the prediction accuracy improvement. In this regard, two tools have been developed: one for predicting 3D trunk shapes based on a statistical approach, and the other being a prediction tool based on nearest neighbor methods. These tools make use of the intuition of choosing the restriction of the displacement field on the trunk domain boundary (the external surface) as a first approximation of the trunk deformation. The achievement of the research objectives has resulted in original contributions to the state of the art in physical simulation of soft tissues as well as in machine learning for shape analysis. This project proposes a novel method for modeling scoliotic trunk soft tissue deformation for the simulation of the postoperative appearance. This method has, thus, the advantage of being a potential tool for computer based scoliosis surgery planning systems. As perspectives, further research studies may be suggested in order to overcome the limitations of the proposed methods. In particular, the incorporation of a trunk model obtained from a multimodal image fusion (MRI / RX / TOPO) for a better personalization of the physical constants may lead to the improvement of the simulation accuracy

DEVELOPMENT OF AN INTEGRATED SYSTEM FOR HUMAN SPINE DEFORMITY MEASUREMENT

Ph.DDOCTOR OF PHILOSOPH