Standardization proposal of soft tissue artefact description for data sharing in human motion measurements

Soft tissue artefact (STA) represents one of the main obstacles for obtaining accurate and reliable skeletal kinematics from motion capture. Many studies have addressed this issue, yet there is no consensus on the best available bone pose estimator and the expected errors associated with relevant results. Furthermore, results obtained by different authors are difficult to compare due to the high variability and specificity of the phenomenon and the different metrics used to represent these data. Therefore, the aim of this study was twofold: firstly, to propose standards for description of STA; and secondly, to provide illustrative STA data samples for body segments in the upper and lower extremities and for a range of motor tasks specifically, level walking, stair ascent, sit-to-stand, hip- and knee-joint functional movements, cutting motion, running, hopping, arm elevation and functional upper-limb movements. The STA dataset includes motion of the skin markers measured in vivo and ex vivo using stereophotogrammetry as well as motion of the underlying bones measured using invasive or bio-imaging techniques (i.e., X-ray fluoroscopy or MRI). The data are accompanied by a detailed description of the methods used for their acquisition, with information given about their quality as well as characterization of the STA using the proposed standards. The availability of open-access and standard-format STA data will be useful for the evaluation and development of bone pose estimators thus contributing to the advancement of three-dimensional human movement analysis and its translation into the clinical practice and other applications

Multi-modal Image Registration

In different areas, particularly medical image analysis, there is a vital need to access and analyse dynamic three dimensional (3D) images of the anatomical structures of the human body. This can enable specialists to track events as well as clinically conduct and evaluate surgical and radio therapeutical procedures. For example, measuring the 3D kinematics of knee joints in a dynamic manner is essential for understanding their normal functions and diagnosing any pathology, such as ligament injury and osteoarthritis. For evaluations of subsequent treatments, such as surgery and rehabilitation, and designs of joint replacements, having knowledge of the movements of knee joints is necessary. Image registration is increasingly being applied to medical image analysis. Whereas in mono-modal registration, the images to be registered are acquired by the same sensor, in multi-modal image registration, they can be taken from different devices or imaging protocols which makes this registration process much more challenging. The invasive or non-invasive nature of the registration method used, the computational time it requires as well as its accuracy and robustness against a large range of initial displacements are the most important features used for its evaluation. As currently available approaches have limited capabilities to register images with large initial displacements and are either not sufficiently accurate or very computationally expensive, the objective of this research is to propose new registration methods, that provide dynamic 3D images, to address these issues. In the first part of this study, I conducted research on registering an individuals’ natural knee bones that can provide 3D information of knee joint kinematics which can be very helpful for improving the accuracy of diagnosis and enabling targeted treatments. A fast, accurate and robust hybrid rigid body registration method based on two different multi-modal similarity measures, the edge position difference (EPD) and sum-of-conditional variance (SCV), is proposed. It uses a gradient descent optimisation technique to register multi-modal images and determine the best transformation parameters. It helps to achieve a trade-off among different challenges, including time complexity, accuracy and robustness against a large range of initial displacements. To evaluate it, several experiments were performed on two different databases: one collected from the knee bones of four patients and the other from three knee cadavers installed on a mechanical positioning system, with the results showing that this method is accurate, fast and robust against large initial displacement. Then, I conducted research on registering implanted human knee joints and proposed a non-invasive, robust 3D-to-2D registration method which can be used for 3D evaluations of the status of knee implants after joint replacement surgeries. In this method, 3D models of the implants for an individual with the relevant post-operative fluoroscopy frames are able to be used in the registration process. As a result, it is possible to perform 3D analysis at any time after a surgery by simply taking single-plane radiographs. This approach uses the EPD multi-modal similarity measure together with a steepest descent optimisation method. It applies coarse-to-fine registration steps to determine the transformation parameters that lead to the best alignment between the model used and X-ray images to be registered. The experimental results showed that not only does the proposed registration method have a high success rate but that it is also much faster than the most relevant competitive approach. Although the experiments were designed for a 3D analysis of total knee arthroplasty (TKA) components, this proposed method can be applied to other joints such as the ankle or hip. In the final part of my research, I developed a multi-frame 2D fluoroscopy to 3D model registration method for measuring the kinematics of post-operative knee joints. It uses a coarse-to-fine approach and applies the normalised EPD (NEPD) and SCV similarity measures together with a gradient descent optimisation method and an interpolation estimation one. In order to measure the kinematics of post- operative knee joints, after a TKA surgery, a 3D knee implant model can be registered with a number of single-plane fluoroscopy frames of the patient’s knee. Generally, when this number is quite high, the computational cost for registering the frames and a 3D model is expensive. Therefore, in order to speed up the registration process, a cubic spline interpolation prediction method is applied to initialise and estimate the 3D positions of the 3D model in each fluoroscopy frame instead of applying a registration algorithm on all the frames, one after the other. The estimated 3D positions are then tuned using a registration improvement step. The experimental results demonstrated that the proposed registration method is much faster than the best existing one and achieves almost the same accuracy. It also provides smooth registration results which can lead to more natural 3D modelling of joint movements

Validation of the multi-segment foot model with bi-planar fluoroscopy

A multi-segment foot model (MSFM) is a useful tool for measuring foot joint kinematics although soft-tissue artefact is often present. Quantifying this error is needed to evaluate the accuracy of this model. This study validated the MSFM against bi-planar radiostereometric analysis (RSA) fluoroscopy. Heel-strike, mid-stance, and toe-off events during the stance phase were compared between motion capture and fluoroscopy. Rise/drop of the medial longitudinal arch showed a significant difference (p \u3c 0.05) during toe-off, but no significant difference during heel-strike or mid-stance. Hindfoot supination/pronation and internal/external rotation, and forefoot supination/pronation motions showed no significant difference between the two techniques. The lack of significant difference will allow the MSFM to be used as a sufficiently accurate technique for measuring foot joint motions

In vivo evaluation of the translations of the gleno-humeral joint using Magnetic resonance imaging

Gleno-humeral joint (GHJ) is the most mobile joint of the human body. This is related to theincongr uence between the large humeral head articulating with the much smaller glenoid (ratio 3:1). The GHJ laxity is the ability of the humeral head to be passively translated on the glenoid fossa and, when physiological, it guarantees the normal range of motion of the joint. Three-dimensional GHJ linear displacements have been measured, both in vivo and in vitro by means of different instrumental techniques. In vivo gleno-humeral displacements have been assessed by means of stereophotogrammetry, electromagnetic tracking sensors, and bio-imaging techniques. Both stereophotogrammetric systems and electromagnetic tracking devices, due to the deformation of the soft tissues surrounding the bones, are not capable to accurately assess small displacements, such as gleno-humeral joint translations. The bio-imaging techniques can ensure for an accurate joint kinematic (linear and angular displacement) description, but, due to the radiation exposure, most of these techniques, such as computer tomography or fluoroscopy, are invasive for patients. Among the bioimaging techniques, an alternative which could provide an acceptable level of accuracy and that is innocuous for patients is represented by magnetic resonance imaging (MRI). Unfortunately, only few studies have been conducted for three-dimensional analysis and very limited data is available in situations where preset loads are being applied. The general aim of this doctoral thesis is to develop a non-invasive methodology based on open-MRI for in-vivo evaluation of the gleno-humeral translation components in healthy subjects under the application of external loads.L’articolazione gleno-omerale rappresenta l’articolazione più mobile del corpo umano. Le ragioni di ciò sono da ricondursi alla parziale congruenza tra la testa omerale che si articola con la più piccola cavità glenoidea (rapporto 3:1). La lassità dell’articolazione gleno-omerale rappresenta l’attitudine della testa omerale a essere traslata passivamente rispetto alla cavità glenoidea; essa garantisce, quando fisiologica, il normale range di movimento dell’articolazione. Gli spostamenti lineari tridimensionali (lassità) sono stati misurati, sia in vivo sia in vitro per mezzo di diverse tecniche strumentali. In vivo gli spostamenti dell’articolazione gleno-omerale sono stati valutati con sistemi stereofotogrammetrici, sensori di tracciamento elettromagnetici, e tecniche di bio-imaging. Sia i sistemi stereofotogrammetrici sia i dispositivi di tracciamento elettromagnetici, a causa della deformazione dei tessuti molli che circondano le ossa, non sono adatti a stimare accuratamente piccoli spostamenti, come possono essere le traslazioni dell’articolazione gleno-omerale. Le tecniche di bioimaging possono garantire un’accurata descrizione della cinematica articolare (spostamenti lineari e angolari), ma a causa dell’esposizione alle radiazioni molte di queste tecniche, come la tomografia assiale computerizzata e la fluoroscopia, sono invasive per i pazienti. Tra le tecniche di bio-imaging, un’alternativa che può garantire un accettabile livello di accuratezza e che risulta innocua per i pazienti è rappresentata dall’imaging di risonanza magnetica (RM). Sfortunatamente, solo pochi studi sono stati condotti sull’analisi tridimensionale e pochi dati sono disponibili in situazioni in cui l’articolazione è soggetta all’azione di carichi esterni noti. L’obiettivo generale di questa tesi di dottorato è di sviluppare una metodologia non invasiva basata sulla RM aperta per la valutazione in vivo delle componenti traslazionali dell’articolazione glenoomerale in soggetti sani e con l’applicazione di carichi esterni

An innovative approach to tibiofemoral joint modelling

Musculoskeletal models allow non-invasive predictions of non-directly measurable forces exchanged within the human body in motion. Despite this information has plenty of potential applications, actual adoption of current models is impeded by limitations related to the insufficient number of validation studies or the drastic modelling assumptions often made. This thesis aims to address these limitations developing an innovative approach to the mechanical modelling of the tibiofemoral joint. To achieve this, three main sections are presented: Effects of the soft tissue artefact on current musculoskeletal models – this study used a statistical approach to develop a realistic distribution of soft tissue artefact, which was used to assess the sensitivity of the estimates of three publicly-available musculoskeletal models. Results showed joint-dependent variations, decreasing from hip to ankle, providing awareness for the research community on the investigated models and indications to better interpret simulation outcomes. Modelling the mechanical behaviour of the tibiofemoral joint using compliance matrices – this part of the thesis proposed a method to characterise the tibiofemoral joint mechanical behaviour using a discrete set of compliance matrices. Model calibration and validation was performed using data from ex vivo testing. Accurate results were found in close proximity to where the model was calibrated, opening the way to a more biofidelic joint representations. The developed model was included in the calculation pipeline to estimate joint kinematics using penalty-based method. For this inclusion, validation using in vivo data for these estimates was promising, providing remarkable alternatives to traditional methods. A force-based approach to personalised tibiofemoral models – this section attested on an ex vivo dataset that the model based on compliance matrices can be personalised using data from clinical tests. Since the latter are usually performed in vivo, this opens the way to future exciting applications

Model-based wear measurements in total knee arthroplasty : development and validation of novel radiographic techniques

The primary aim of this work was to develop novel model-based mJSW measurement methods using a 3D reconstruction and compare the accuracy and precision of these methods to conventional mJSW measurement. This thesis contributed to the development, validation and clinical application of model-based mJSW measurements for the natural knee and for total knee prostheses. The majority of this work focusses on measuring linear wear of the total knee protheses by estimating the remaining insert thickness with the mJSW. Both in vivo and in vitro research shows that the application of model-based techniques can give a large improvement in measurement accuracy and precision. This applies for measurements based on both Röntgen Stereogrammetric Analysis (RSA) and standard radiographs. Secondary, this work investigated volumetric wear measurement and the effect of patient positioning on the measurement outcome. In conclusion, this work presents convincing evidence that the mJSW measurement accuracy and precision is improved using model-based measurement techniques in RSA images as well as in standard AP radiographs. The next steps towards clinical application are to improve the measurement software and to conduct further research on the influence of knee flexion and implant design on the reliability of mJSW as surrogate for the insert thickness.  LUMC / Geneeskund

Estimation par optimisation multi-corps de la cinématique 3D de genoux sains et arthrosiques au cours d'accroupissements : performance de modèles articulaires personnalisés

Il existe un manque de consensus au sujet des mouvements du genou. Aucune des méthodes utilisées pour analyser la cinématique 3D du genou n’est acceptée de façon unanime par la communauté scientifique. Ces dernières présentent en effet des limites, soit en termes d’applicabilité en routine clinique, soit en termes de compensation des artéfacts des tissus mous (ATM). L’objectif principal de ce projet de doctorat consiste donc à améliorer l’évaluation fonctionnelle du genou en proposant une méthode de mesure de la cinématique 3D qui soit à la fois précise, non invasive et peu irradiante. Cette méthode fait intervenir le système de captation du mouvement KneeKG™, la méthode d’optimisation multi-corps (MBO), et le système de radiographie biplan EOS®. Premièrement, les ATM affectant les mesures du KneeKG™ au cours d’accroupissements sous charge effectués par des sujets sains et arthrosiques ont été quantifiés à l’aide d’EOS®. L’impact de ces ATM sur la cinématique 3D du genou des sujets a ensuite été évalué. Cette étude montre que les ATM du KneeKG™ oscillent entre 3-9° et 5-13 mm, et qu’ils engendrent des erreurs de l’ordre de 9-10° et 7-10 mm au niveau de la cinématique 3D du genou. Deuxièmement, les accroupissements dynamiques et quasi-statiques effectués par les sujets ont été comparés en termes de cinématique 3D, de cinétique 3D et d’électromyographie des membres inférieurs. Cette étude montre que les deux conditions d’accroupissement sont similaires. Les différences cinématiques observées au genou sont inférieures à 1,5° et 1,9 mm. Troisièmement, les performances de huit combinaisons de modèles articulaires utilisées lors de la MBO pour compenser les ATM du KneeKG™ ont été évaluées. Cette étude montre qu’aucune des combinaisons actuelles n’est idéale pour corriger l’ensemble de ces ATM. Les erreurs de mesures résiduelles atteignent 13° et 7 mm après correction. Quatrièmement, des modèles personnalisés du genou ont été développés à partir de modèles 3D des os issus d’EOS®. Utilisés lors de la MBO, ces modèles personnalisés s’avèrent les plus efficaces pour corriger les ATM du KneeKG™. Les erreurs résiduelles oscillent entre 2-6° et 2-4 mm pour les rotations et déplacements des genoux sains et OA. Cinquièmement, la méthode de mesure développée a été mise à profit pour proposer une méthode de fusion de la géométrie 3D et de la cinématique 3D du genou, et ainsi calculer les surfaces de contact articulaires du genou. Les résultats obtenus par cette étude sont prometteurs. En conclusion, la combinaison du KneeKG™, de la MBO et du système EOS® a permis d’obtenir une méthode quantifiant de manière relativement précise, non invasive et peu irradiante la cinématique 3D de genou sains et OA au cours d’accroupissements dynamiques