Exploring bone mineral density changes in total knee arthroplasty revisions and the impact of conal implants

Introduction The link between low bone mineral density (BMD) leading to greater fracture risk is well established in the literature; what is not fully understood is the impact of total knee revisions (rTKR) and cone implantation on BMD. This is important due to the increasing fracture risk associated with reductions in BMD. This feasibility study investigated a new type of Stryker cone for rTKR patients, and its impact on BMD utilising different imaging technologies and providing recommendations to be implemented for a full follow up trial. Method A systematic review was conducted to investigate total knee replacement (TKR) and rTKR on BMD results to establish known reported BMD changes after surgery, and to highlight the knee regions investigated. A bovine study was then conducted in order to test the different setup imaging technologies and possible analysis of the cones. Additionally, a novel piece of 3D SHAPER hip software was utilised to investigate bone changes in the hip across three groups (TKR, rTKR, and controls) which could then be compared to the main BMD changes or used as an alternative to the other imaging options. The main study involved recruiting 37 participants all undergoing rTKR to either a cone or non cone group, with all participants undergoing a series of scans via: CT scans (only at six months), DXA and x ray at intervals of pre op, six weeks, three, six and 12 months. Additionally, all participants completed questionnaires on mental health, lower extremity functionality, and quality of life. In addition to BMD investigation, hip and knee alignment was also explored at pre and post op intervals, as well as pixel density changes, both utilising long leg x ray imaging. Results Systematic review results reported 2,431 papers, of which 27 studies were included, across all the studies BMD losses appeared greatest at 12 months. The bovine study helped develop the imaging and analysis required for the main study. The 3D SHAPER ability to be applied to hip DXA imaging showed promise; which was reflected in the control, rTKR and TKR data. The development of different imaging technologies have potential in moving forward into a full trial. Recommendations would include: utilising DXA imaging as the main modality, given its gold standard for BMD changes and its consistency when using a standardised positioning protocol and ROI placement. Long leg x- 3 ray imaging to be used to investigate alignment and pixel density changes, as this imaging is convenient as part of routine follow-up care, although the inclusion of a step wedge within all long leg images would be required to allow pixel density standardisation for investigating in-growth. Finally, the CT imaging could not determine ingrowth in this feasibility study, and therefore should not be utilised in the full study. For the main feasibility study results, 35 participants attended pre--op, 26 attended six weeks and three months, at six months 25 attended, and 22 at 12 months. Results show rTKR is associated with lower BMD in the tibial and femoral stems, and in the medial tibial condyle, and associated with increases beyond the tibial and femoral stems, in both groups. The main difference is in lateral tibial condyle where there are associated increases in BMD in the cone group, and losses reported in the non--cone group. The questionnaire results show a favourable impact for rTKR, with reductions in depression, anxiety, and increases in functionality post--surgery, with the cone group reporting greater changes, although not statistically significant between groups. Alignment analysis shows little difference between

Non-Relativistic Twistor Theory and Newton–Cartan Geometry

We develop a non-relativistic twistor theory, in which Newton--Cartan structures of Newtonian gravity correspond to complex three-manifolds with a four-parameter family of rational curves with normal bundle ${\mathcal O}\oplus{\mathcal O}(2)$. We show that the Newton--Cartan space-times are unstable under the general Kodaira deformation of the twistor complex structure. The Newton--Cartan connections can nevertheless be reconstructed from Merkulov's generalisation of the Kodaira map augmented by a choice of a holomorphic line bundle over the twistor space trivial on twistor lines. The Coriolis force may be incorporated by holomorphic vector bundles, which in general are non--trivial on twistor lines. The resulting geometries agree with non--relativistic limits of anti-self-dual gravitational instantons.We are grateful to Christian Duval, George Sparling and Paul Tod for helpful discussions. This work started when MD was visiting the Institute for Fundamental Sciences (IMP) in Tehran in April 2010. MD is grateful to IMP for the extended hospitality when volcanic eruption in Iceland halted air travel in Europe. The work of JG has been supported by an STFC studentship.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s00220-015-2557-

Computer-aided detection in musculoskeletal projection radiography: A systematic review

This is the author accepted manuscript. The final version is available from WB Saunders via the DOI in this record.Objectives To investigated the accuracy of computer-aided detection (CAD) software in musculoskeletal projection radiography via a systematic review. Key findings Following selection screening, eligible studies were assessed for bias, and had their study characteristics extracted resulting in 22 studies being included. Of these 22 three studies had tested their CAD software in a clinical setting; the first study investigated vertebral fractures, reporting a sensitivity score of 69.3% with CAD, compared to 59.8% sensitivity without CAD. The second study tested dental caries diagnosis producing a sensitivity score of 68.8% and specificity of 94.1% with CAD, compared to sensitivity of 39.3% and specificity of 96.7% without CAD. The third indicated osteoporotic cases based on CAD, resulting in 100% sensitivity and 81.3% specificity. Conclusion The current evidence reported shows a lack of development into the clinical testing phase; however the research does show future promise in the variation of different CAD systems

Global Localization and Orientation of the Cervical Spine in X-ray Imaging

Injuries in cervical spine X-ray images are often missed by emergency physicians. Many of these missing injuries cause further complications. Automated analysis of the images has the potential to reduce the chance of missing injuries. Towards this goal, this paper proposes an automatic localization of the spinal column in cervical spine X-ray images. The framework employs a random classification forest algorithm with a kernel density estimation-based voting accumulation method to localize the spinal column and to detect the orientation. The algorithm has been evaluated with 90 emergency room X-ray images and has achieved an average detection accuracy of 91% and an orientation error of 3.6◦. The framework can be used to narrow the search area for other advanced injury detection systems

Improving an Active Shape Model with Random Classification Forest for Segmentation of Cervical Vertebrae

X-ray is a common modality for diagnosing cervical vertebrae injuries. Many injuries are missed by emergency physicians which later causes life threatening complications. Computer aided analysis of X-ray images has the potential to detect missed injuries. Segmentation of the vertebrae is a crucial step towards automatic injury detection system. Active shape model (ASM) is one of the most successful and popular method for vertebrae segmentation. In this work, we propose a new ASM search method based on random classification forest and a kernel density estimation-based prediction technique. The proposed method have been tested on a dataset of 90 emergency room X-ray images containing 450 vertebrae and outperformed the classical Mahalanobis distancebased ASM search and also the regression forest-based method

Hough Forest-based Corner Detection for Cervical Spine Radiographs

The cervical spine (neck region) is highly sensitive to trauma related injuries, which must be analysed carefully by emergency physicians. In this work, we propose a Hough Forest-based corner detection method for cervical spine radiographs, as a first step towards a computer-aided diagnostic tool. We propose a novel patch-based model based on two-stage supervised learning (classification and regression) to estimate the corners of cervical vertebral bodies. Our method is evaluated using 106 cervical x-ray images consisting of 530 vertebrae and 2120 corners, which have been demarcated manually by an expert radiographer. The results show promising performance of the proposed algorithm, with a lowest median error of 1.98 m

Patch-based Corner Detection for Cervical Vertebrae in X-ray Images

Corners hold vital information about size, shape and morphology of a vertebra in an x-ray image, and recent literature [1, 2] has shown promising performance for detecting vertebral corners using a Hough forest-based architecture. To provide spatial context, this method generates a set of 12 patches around a vertebra and uses a machine learning approach to predict corners of a vertebral body through a voting process. In this paper, we extend this framework in terms of patch generation and prediction methods. During patch generation, the square region of interest has been replaced with data-driven rectangular and trapezoidal region of interest which better aligns the patches to the vertebral body geometry, resulting in more discriminative feature vectors. The corner estimation or the prediction stage has been improved by utilising more efficient voting process using a single kernel density estimation. In addition, advanced and more complex feature vectors are introduced. We also present a thorough evaluation of the framework with different patch generation methods, forest training mechanisms and prediction methods. In order to compare the performance of this framework with a more general method, a novel multi-scale Harris corner detector-based approach is introduced that incorporates a spatial prior through a naive Bayes method. All these methods have been tested on a dataset of 90 X-ray images and achieved an average corner localization error of 2.01 mm, representing a 33% improvement in localisation accuracy compared to the previous state-of-the-art method [2]

The feasibility of using citizens to segment anatomy from medical images: Accuracy and motivation

This is the final version. Available from Public Library of Science via the DOI in this record.Data cannot be shared publicly because participants did not consent for their data to be made publicly available, however, consent was granted to make the data available to researchers for use in related studies. Further information about the data and details of how to request access are available from the University of Exeter's institutional repository at: https://doi.org/10.24378/exe.1703.The development of automatic methods for segmenting anatomy from medical images is an important goal for many medical and healthcare research areas. Datasets that can be used to train and test computer algorithms, however, are often small due to the difficulties in obtaining experts to segment enough examples. Citizen science provides a potential solution to this problem but the feasibility of using the public to identify and segment anatomy in a medical image has not been investigated. Our study therefore aimed to explore the feasibility, in terms of performance and motivation, of using citizens for such purposes. Public involvement was woven into the study design and evaluation. Twenty-nine citizens were recruited and, after brief training, asked to segment the spine from a dataset of 150 magnetic resonance images. Participants segmented as many images as they could within three one-hour sessions. Their accuracy was evaluated by comparing them, as individuals and as a combined consensus, to the segmentations of three experts. Questionnaires and a focus group were used to determine the citizens’ motivation for taking part and their experience of the study. Citizen segmentation accuracy, in terms of agreement with the expert consensus segmentation, varied considerably between individual citizens. The citizen consensus, however, was close to the expert consensus, indicating that when pooled, citizens may be able to replace or supplement experts for generating large image datasets. Personal interest and a desire to help were the two most common reasons for taking part in the study.Wellcome Trus

A Review on Bone Mineral Density Loss in Total Knee Replacements Leading to Increased Fracture Risk

This is the author accepted manuscript. The final version is available from Humana Press via the DOI in this record.The link between low bone mineral density (BMD) scores leading to greater fracture risk is well established in the literature; what is not fully understood is the impact of total knee replacements/revisions or arthroplasties on BMD levels. This literature review attempts to answer this question. Several different databases using specific key terms were searched, with additional papers retrieved via bibliographic review. Based on the available evidence, total knee replacements/revisions and arthroplasties lower BMD and thus increase fracture risk. This review also addresses the possible implications of this research and possible options to reduce this risk.Author Michael Gundry’s current PhD is in part funded by the Stryker Institute with research investigating changes in BMD in bone surrounding cone implants on TKR revision patients. There is no grant number, but it is stated as an industry-funded, non-commercial study subject to a Masters Service Agreement between Stryker UK and the Royal Devon and Exeter Hospital. Additionally, authors Knapp and Hopkins have no conflict of interest to declare

Effect of substrate thermal resistance on space-domain microchannel

In recent years, Fluorescent Melting Curve Analysis (FMCA) has become an almost ubiquitous feature of commercial quantitative PCR (qPCR) thermal cyclers. Here a micro-fluidic device is presented capable of performing FMCA within a microchannel. The device consists of modular thermally conductive blocks which can sandwich a microfluidic substrate. Opposing ends of the blocks are held at differing temperatures and a linear thermal gradient is generated along the microfluidic channel. Fluorescent measurements taken from a sample as it passes along the micro-fluidic channel permits fluorescent melting curves to be generated. In this study we measure DNA melting temperature from two plasmid fragments. The effects of flow velocity and ramp-rate are investigated, and measured melting curves are compared to those acquired from a commercially available PCR thermocycler