The evolution of polymer wear debris from total disc arthroplasty

Abstract

a b s t r a c tTotal disc arthroplasty is an alternative to spinal fusion, aimed at preserving flexibility; these devices typically involve a cobalt chrome molybdenum alloy socket articulating against an ultra-high molecular weight polyethylene (UHMWPE) ball. As with all artificial joints, wear debris is of particular concern due to its effect on both implant life and the in vivo biological reactions that can occur. In this paper, a profile of the UHMWPE wear debris generated from disc arthroplasty, tested on a spine simulator, is built with a combination of SEM image analysis tools. SEM images were analysed by computer vision, which allowed size and shape information to be extracted and images to be categorised by the shared topological features on individual wear particles. The computer visions techniques were based on a Scale Invariant Feature Transform (SIFT) to extract key point data from individual images and a Support Vector Decision Machine (SVM) to filter images based on a series of trained parameters. As certain wear particle morphology is predominantly produced by a particular wear regime, grouping wear particles by morphology and size made it possible to infer the relative rates of various wear regimes responsible for wear debris generation. By sampling synovial lubricant at intervals throughout the tribological test, the predominant wear regimes and particle sizes were tracked over the course of the implant life. Wear debris samples were taken at 12 intervals over a 5 million cycle test. The majority of debris was found to be 0.88 μm in equivalent circle diameter, with an aspect ratio (defined as the major over the minor diameter of the smallest possible encompassing ellipse of the debris) of 1.55. There was a decreasing trend in average particle size as the number of cycles increased. During the early stages of the test, adhesion and abrasion were dominant in forming particle morphologies, however after 2 million cycles; particles generated as a result of fatigue became the major particle morphology.

Dynamic Viscoelasticity and Surface Properties of Porcine Left Anterior Descending Coronary Arteries

“…Surface roughness can be quantified using Ra (the arithmetic average of absolute values of sampling length). Although its applications are mainly in tribology and wear, 21 , 60 it has recently been used to study biological tissues such as articular cartilage in order to assess its surface roughness. 35 , 88 It has also been trialled for cardiovascular applications, not involving tribology.…”

Morphological residual convolutional neural network (M-RCNN) for intelligent recognition of wear particles from artificial joints

“…It is suggested that the subsphaeroidal wear debris from the artificial hip joints took up the majority of the debris but shared a smaller percentage of the total volume, indicating the type distribution was imbalanced [12]. Eckold et al [23] suggested that the majority of the morphological occurrences of wear particles from artificial discs was fibril. Regarding the artificial knee and hip joints, it was concluded that the particle morphology can be strongly influenced by the lack of experimental precision with different quantitative approaches and the in vivo wear particle distribution was not homogeneous owing to the clumping and clearing of particles through drainage [10].…”

The Effect of Mechanical Overloading on Surface Roughness of the Coronary Arteries

“…The physical properties of the surfaces of the materials are usually quantified through their mean surface roughness, Ra, the arithmetic average of absolute values of sampling length [17]. Applications are typically associated with tribology and wear [18, 19], which has led to the biomedical studies of articulating tissues such as the articular cartilage [20, 21]. Recently, though, the feasibility of quantitatively measuring the surface roughness has been established for the coronary arteries [1, 22], which provides a step change from qualitative surface analysis [23].…”