Measurement of migration of a humeral head resurfacing prosthesis using radiostereometry without implant marking: An experimental study

Today, the shoulder joint is the third most commonly replaced joint after the hip and knee joints and the incidence is increasing. In Sweden, 1863 primary Shoulder Arthroplasties and 195 revisions were performed in 2017. The most common diagnoses are Osteoarthritis and irreparable tears of the rotator cuff, with or without arthropathy, often referred to as cuff tear arthropathy. Different Shoulder Arthroplasty (SA) concepts include anatomical total shoulder arthroplasty (TSA), hemiarthroplasty (HSA) and reversed shoulder arthroplasty, but also humeral head resurfacing (HHR) and stemless arthroplasties. All concepts offer pain relief, improvement of function and in quality of life for the different diagnoses. Unfortunately, there are sometimes complications after SA. They involve periprosthetic joint infection, humeral and glenoid fractures, stress shielding, loosening of the glenoid and humeral component but also glenoid erosion and cuff rupture. Some of these complications are most common within 1 year after operation, some after several years, both may lead to a revision. This, together with the fact that new designs of implants and methods of fixation of SA continues to develop, stresses the importance of continuous monitoring of implant survival and follow-up. The overall aim of this thesis was to describe clinical examples of different methods to assess the outcome after Shoulder Arthroplasty. The most common methods are clinical examination, radiographic assessment, Patient Reported Outcome Measure (PROM), National Joint registries, where revisions are an important outcome, but also Clinical Trials. All of these methods are used in one or more of the 4 papers in this thesis and shows the complexity of the topic and the practical work. In paper I we used Radio Stereometric Analysis (RSA) in an experimental set-up and concluded that marker-free RSA can be used for a humeral head resurfacing arthroplasty. In paper II we used data from the Swedish Shoulder Arthroplasty Registry (SSAR) with PROM and revisions to conclude that age is the only factor that affects revision when comparing HSA and HHR. Paper III is a long-time follow-up of a Randomized controlled study where we used radiological assessment, PROM and revisions. The conclusion was that both TSA and HSA develop severe radiological changes 10 year after primary operation. Paper IV is a prospective RSA cohort study where we also evaluated PROM and revisions. The conclusion is that HHR seems to obtain a secure fixation in the humerus, after an initial migration. But also that the prostheses shows continuous glenoid wear. The main conclusion of this thesis is that patient’s operated with SA needs continuous monitoring and several methods may be used to evaluate the outcome

Pareto optimality solution of the multi-objective photogrammetric resection-intersection problem

Reconstruction of architectural structures from photographs has recently experienced intensive efforts in computer vision research. This is achieved through the solution of nonlinear least squares (NLS) problems to obtain accurate structure and motion estimates. In Photogrammetry, NLS contribute to the determination of the 3-dimensional (3D) terrain models from the images taken from photographs. The traditional NLS approach for solving the resection-intersection problem based on implicit formulation on the one hand suffers from the lack of provision by which the involved variables can be weighted. On the other hand, incorporation of explicit formulation expresses the objectives to be minimized in different forms, thus resulting in different parametric values for the estimated parameters at non-zero residuals. Sometimes, these objectives may conflict in a Pareto sense, namely, a small change in the parameters results in the increase of one objective and a decrease of the other, as is often the case in multi-objective problems. Such is often the case with error-in-all-variable (EIV) models, e.g., in the resection-intersection problem where such change in the parameters could be caused by errors in both image and reference coordinates.This study proposes the Pareto optimal approach as a possible improvement to the solution of the resection-intersection problem, where it provides simultaneous estimation of the coordinates and orientation parameters of the cameras in a two or multistation camera system on the basis of a properly weighted multi-objective function. This objective represents the weighted sum of the square of the direct explicit differences of the measured and computed ground as well as the image coordinates. The effectiveness of the proposed method is demonstrated by two camera calibration problems, where the internal and external orientation parameters are estimated on the basis of the collinearity equations, employing the data of a Manhattan-type test field as well as the data of an outdoor, real case experiment. In addition, an architectural structural reconstruction of the Merton college court in Oxford (UK) via estimation of camera matrices is also presented. Although these two problems are different, where the first case considers the error reduction of the image and spatial coordinates, while the second case considers the precision of the space coordinates, the Pareto optimality can handle both problems in a general and flexible way

Simulating C cycles in forest soils: Including the active role of micro-organisms in the ANAFORE forest model

A soil module was developed to improve on the ecosystem-scale simulations of forest models. The module includes simulations of bacteria, mycorrhizal and non-mycorrhizal fungi. The inclusion of these soil organisms allows for the simulation of several soil biological processes in a more mechanistic way. In this paper the soil module is used in combination with the forest model ANAFORE (ANAlysing Forest Ecosystems) a stand-scale forest model that simulates wood tissue development, carbon (C) and water (H2O) fluxes dynamically from physiological principles. Although the main purpose of this paper is the model description, a showcase run of the new soil model was performed using a Bayesian parameterization procedure for 16 forest sites (pedunculate oak, beech, Scots pine and poplar) on different soils in Belgium. Emphasis was on the soil organic horizons formation. The results show that one single parameter set could be used for the different forests in the study, and yielded reasonably close fits for most sites concerning pH and formation of the humus layer. Although running the Bayesian procedure to obtain good input parameter distributions was time-consuming (several months), runs using the developed parameter set are reasonably fast (days). These results are promising. However, the high uncertainty of both the input and the output of the model indicates that it is mainly useful as an experimental tool, rather than a predictive instrument

MODULAR BUNDLE ADJUSTMENT FOR PHOTOGRAMMETRIC COMPUTATIONS

In this paper we investigate how the residuals in bundle adjustment can be split into a composition of simple functions. According to the chain rule, the Jacobian (linearisation) of the residual can be formed as a product of the Jacobians of the individual steps. When implemented, this enables a modularisation of the computation of the bundle adjustment residuals and Jacobians where each component has limited responsibility. This enables simple replacement of components to e.g. implement different projection or rotation models by exchanging a module. The technique has previously been used to implement bundle adjustment in the open-source package DBAT (Börlin and Grussenmeyer, 2013) based on the Photogrammetric and Computer Vision interpretations of Brown (1971) lens distortion model. In this paper, we applied the technique to investigate how affine distortions can be used to model the projection of a tilt-shift lens. Two extended distortion models were implemented to test the hypothesis that the ordering of the affine and lens distortion steps can be changed to reduce the size of the residuals of a tilt-shift lens calibration. Results on synthetic data confirm that the ordering of the affine and lens distortion steps matter and is detectable by DBAT. However, when applied to a real camera calibration data set of a tilt-shift lens, no difference between the extended models was seen. This suggests that the tested hypothesis is false and that other effects need to be modelled to better explain the projection. The relatively low implementation effort that was needed to generate the models suggest that the technique can be used to investigate other novel projection models in photogrammetry, including modelling changes in the 3D geometry to better understand the tilt-shift lens

Guidelines for standardization of radiostereometry (RSA) of implants.

There is a need for standardization of radiostereometric (RSA) investigations to facilitate comparison of outcome reported from different research groups. In this document, 6 research centers have agreed upon standards for terminology, description and use of RSA arrangement including radiographic set-up and techniques. Consensus regarding minimum requirements for marker stability and scatter, choice of coordinate systems, and preferred way of describing prosthetic micromotion is of special interest. Some notes on data interpretation are also presented. Validation of RSA should be standardized by preparation of protocols for assessment of accuracy and precision. Practical issues related to loading of the joint by weight bearing or other conditions, follow-up intervals, length of follow-up, radiation dose, and the exclusion of patients due to technical errors are considered. Finally, we present a checklist of standardized output that should be included in any clinical RSA paper.This document will form the basis of a detailed standardization protocol under supervision of ISO and the European Standards Working Group on Joint Replacement Implants (CEN/TC 285/WG4). This protocol will facilitate inclusion of RSA in a standard protocol for implant testing before it is released for general use. Such a protocol-also including other recognized clinical outcome parameters-will reduce the risk of implanting potentially inferior prostheses on a large scale

Improving Underwater Accuracy by Empirical Weighting of Image Observations

An underwater imaging system with camera and lens behind a flat port does not behave as a standard pinhole camera with additional parameters. Indeed, whenever the entrance pupil of the lens is not in contact with the flat port, the standard photogrammetric model is not suited anymore and an extended mathematical model that considers the different media would be required. Therefore, when dealing with flat ports, the use of the classic photogrammetric formulation represents a simplification of the image formation phenomenon, clearly causing a degradation in accuracy. Furthermore, flat ports significantly change the characteristics of the enclosed imaging device and negatively affect the image quality, introducing heavy curvilinear distortions and optical aberrations. With the aim of mitigating the effect of systematic errors introduced by a combination of (i) image quality degradation, induced by the flat ports, and (ii) a non-rigorous modelling of refraction, this paper presents a stochastic model for image observations that penalises those that are more affected by aberrations and departure from the pinhole model. Experiments were carried out at sea and in pools showing that the use of the proposed stochastic model is beneficial for the final accuracy with improvements up to 50 %