Progress in the wear behavior investigation of artificial joint combination interfaces

PENG Yeping; KONG Deyu; ZHUANG Rongrun; WANG Song; CAO Guangzhong

doi:10.16511/j.cnki.qhdxxb.2023.26.065

Journal of Tsinghua University(Science and Technology) >

2024 , Vol. 64 >Issue 3: 409 - 420

DOI: https://doi.org/10.16511/j.cnki.qhdxxb.2023.26.065

FRONTIERS IN BIOTRIBOLOGY

Progress in the wear behavior investigation of artificial joint combination interfaces

PENG Yeping ,
KONG Deyu ,
ZHUANG Rongrun ,
WANG Song ,
CAO Guangzhong

Expand

1. Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robots, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China;
2. Biomechanics and Biotechnology Lab, Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China

Received date: 2023-09-08

Online published: 2024-03-06

Fold

Abstract

[Significance] Artificial joint replacement is an important technology for treating bone and joint disorders. However, the long-term wear loss of joint prosthesis and periprosthetic osteolysis induced by wear debris causes aseptic loosening, leading to early failure of the prosthesis. Investigating the wear behaviors of artificial joint combination interfaces, including sliding and immobile interfaces, forms the foundation for exploring the formation mechanism of wear debris, studying loosening and failure mechanisms, and improving the abrasion performance of artificial joints. Such an investigation represents a fundamental approach to elucidate the mechanisms behind wear debris formation, explore the factors contributing to loosening and failure, and enhance the abrasion resistance of artificial joints. The literatures on the wear behaviors of artificial joints has been meticulously reviewed and summarized using resources from the Web of Science and China’s national knowledge network databases. The primary aim of this study is to provide references for research on the wear behaviors of artificial joint combination interfaces. [Progress] Sliding and fretting wear of artificial joints were studied. Sliding wear was produced on the sliding interface between artificial joint prosthesis pairs, and a large amount of wear particles were generated, which were the main cause of prosthesis loosening and failure. Fretting wear occurred at the fixed interface between the prosthesis and bone, leading to the early loosening of artificial joints. Adhesive, abrasive, and fatigue wear were the three main wear mechanisms of artificial joints. The wear of artificial joints was caused by several factors, such as prosthesis structure, material, lubrication, wear debris, operation, and patient. Summarizing the factors influencing the wear behaviors of artificial joints revealed that the design of prosthesis structures and surface modification technologies will be crucial for optimizing and enhancing artificial joints. However, these influencing factors were interrelated; thus, the mechanisms affecting wear behaviors needed to be further discussed. To evaluate the friction and wear performance of artificial joints, researchers mainly used friction and wear experimental machines and joint simulators to obtain wear parameters through in vitro simulation tests. Some scholars had designed novel devices with special functions to implement complex and specific wear research. The sliding wear behaviors of artificial joints were commonly characterized by friction coefficient, abrasion loss, surface morphology, wear debris features, and material composition. By contrast, fretting wear was generally analyzed by the friction coefficient, dissipated energy, and fretting corrosion conditions. Based on the applications of computer vision and artificial intelligence technology, the automation and intelligence levels of wear monitoring had been considerably improved. [Conclusions and Prospects] Material modification technology is effective in improving the wear performance of artificial joints and is a hotspot in the research field. A novel design of wear devices can provide an in vitro simulation experimental platform for complex and specific wear behavior testing. Further, a comparative analysis of various wear parameters can also comprehensively describe wear behaviors. Moreover, the efficiency and accuracy of artificial joint simulation tests in vitro can be effectively improved using computer vision and artificial intelligence techniques. The friction coefficient, wear surface, wear debris, and material composition are important factors in the wear behaviors of artificial joints, and multiple information fusion is required to study these wear behaviors. The applications of computer vision and artificial intelligence technology provide more solutions for wear debris and mechanism analysis of artificial joints, which are the future directions of wear behavior investigation on artificial joint combination interfaces.

Key words： artificial joint; combination interfaces; sliding wear; fretting wear; wear monitoring

Cite this article

PENG Yeping , KONG Deyu , ZHUANG Rongrun , WANG Song , CAO Guangzhong . Progress in the wear behavior investigation of artificial joint combination interfaces[J]. Journal of Tsinghua University(Science and Technology), 2024 , 64(3) : 409 -420 . DOI: 10.16511/j.cnki.qhdxxb.2023.26.065

References

[1] 邵一伦, 崔文, 张小刚, 等. 金属对聚乙烯型人工髋关节摩擦学性能研究进展[J]. 润滑与密封, 2021, 46(5):126-136. SHAO Y L, CUI W, ZHANG X G, et al. Progress of tribological properties of metal on polyethylene artificial hip prosthesis[J]. Lubrication Engineering, 2021, 46(5):126-136. (in Chinese)
[2] WU X F, LIU S Y, CHEN K, et al. 3-D printed chitosan-gelatine hydrogel coating on titanium alloy surface as biological fixation interface of artificial joint prosthesis[J]. International Journal of Biological Macromolecules, 2021, 182:669-679.
[3] FENG C A, CAO Y, WU T, et al. Friction and wear mechanism of artificial joint composite material PEEK/ZnO under different decomposition motion modes of knee joint[J]. Tribology International, 2023, 189:108917.
[4] BIAN Y Y, ZHOU L, ZHOU G, et al. Study on biocompatibility, tribological property and wear debris characterization of ultra-low-wear polyethylene as artificial joint materials[J]. Journal of the Mechanical Behavior of Biomedical Materials, 2018, 82:87-94.
[5] XU H D, ZHANG D K, CHEN K, et al. Taper fretting behavior of PEEK artificial hip joint[J]. Tribology International, 2019, 137:30-38.
[6] WANG Z R, LI Q, CHEN X C, et al. High crystallinity makes excellent wear resistance in crosslinked UHMWPE[J]. Polymer, 2023, 280:126059.
[7] SU W P, HU Y H, FAN X L, et al. Clearance of senescent cells by navitoclax (ABT263) rejuvenates UHMWPE-induced osteolysis[J]. International Immunopharmacology, 2023, 115:109694.
[8] MARIAN M, SHAH R, GASHI B, et al. Exploring the lubrication mechanisms of synovial fluids for joint longevity:A perspective[J]. Colloids and Surfaces B:Biointerfaces, 2021, 206:111926.
[9] SHEN F, KE L L. A comparative study on fretting wear and frictional heating behavior of PEEK composites for artificial joint applications[J]. Polymer Testing, 2022, 109:107552.
[10] YANG W L, DIAO H, XIN H, et al. Wear assessment of a Ti-6Al-4V motion-preserving porous artificial-cervical-joint fabricated by SLM after surface carburization[J]. Ceramics International, 2022, 48(18):26137-26146.
[11] SAIKKO V. Effect of wear, acetabular cup inclination angle, load and serum degradation on the friction of a large diameter metal-on-metal hip prosthesis[J]. Clinical Biomechanics, 2019, 63:1-9.
[12] SEMETSE L, OBADELE B A, RAGANYA L, et al. Fretting corrosion behaviour of Ti6Al4V reinforced with zirconia in foetal bovine serum[J]. Journal of the Mechanical Behavior of Biomedical Materials, 2019, 100:103392.
[13] WANG S Q, ZHANG D K, SUN M, et al. Torsional fretting corrosion behaviors of the CoCrMo/Ti6Al4V couple[J]. International Journal of Electrochemical Science, 2018, 13(7):6414-6425.
[14] PRITCHETT J W. Hip resurfacing using highly cross-linked polyethylene:Prospective study results at 8.5 years[J]. The Journal of Arthroplasty, 2016, 31(10):2203-2208.
[15] CLARKE I C, GOOD V, ANISSIAN L, et al. Charnley wear model for validation of hip simulators' ball diameter versus polytetrafluoroethylene and polyethylene wear[J]. Proceedings of the Institution of Mechanical Engineers, Part H:Journal of Engineering in Medicine, 1997, 211(1):25-36.
[16] SAIKKO V. Wear and friction of thin, large-diameter acetabular liners made from highly cross-linked, vitamin-E-stabilized UHMWPE against CoCr femoral heads[J]. Wear, 2019, 432-433:202948.
[17] LITTLE N J, BUSCH C A, GALLAGHER J A, et al. Acetabular polyethylene wear and acetabular inclination and femoral offset[J]. Clinical Orthopaedics and Related Research, 2009, 467(11):2895-2900.
[18] [JP+2]DEL SCHUTTE H, LIPMAN A J, BANNAR S M, et al. Effects of acetabular abduction on cup wear rates in total hip arthroplasty[J]. Journal of Arthroplasty, 1998, 13(6):621-626.
[19] SHANKAR S, NITHYAPRAKASH N, SANTHOSH B R. Short term tribological behavior of ceramic and polyethylene biomaterials for hip prosthesis[J]. Materials Testing, 2021, 63(5):470-473.
[20] ZHANG X Y, HU Y, CHEN K, et al. Bio-tribological behavior of articular cartilage based on biological morphology[J]. Journal of Materials Science:Materials in Medicine, 2021, 32(11):132.
[21] SOBAJIMA A, OKIHARA T, MORIYAMA S, et al. Multiwall carbon nanotube composites as artificial joint materials[J]. ACS Biomaterials Science & Engineering, 2020, 6(12):7032-7040.
[22] UHLER M, BRAUN S, SCHROEDER S, et al. Wear investigation based on a novel, anatomic shoulder prosthesis with bearing materials inversion[J]. Journal of the Mechanical Behavior of Biomedical Materials, 2022, 127:105080.
[23] RAIMONDI M T, VENA P, PIETRABISSA R. Quantitative evaluation of the prosthetic head damage induced by microscopic third-body particles in total hip replacement[J]. Journal of Biomedical Materials Research, 2001, 58(4):436-448.
[24] International Organization for Standardization. Implants for surgery-wear of total hip-joint prostheses-part 1:Loading and displacement parameters for wear-testing machines and corresponding environmental conditions for test:ISO 4242-1:2014(E)[S]. Switzerland:ISO, 2014.
[25] JOHN K S. The effect of serum protein concentration on wear rates in a hip simulator[J]. Journal of Biomaterials Applications, 2010, 25(2):145-159.
[26] 谭琴, 张亚丽, 张小刚, 等. 滑液组分对人工关节摩擦学行为影响研究进展[J]. 摩擦学学报, 2023, 43(5):581-596. TAN Q, ZHANG Y L, ZHANG X G, et al. Progress of influence of synovial fluid compositions on tribological behavior of artificial joints[J]. Tribology, 2023, 43(5):581- 596. (in Chinese)
[27] GOOD V D, CLARKE I C, GUSTAFSON G A, et al. Wear of ultra-high molecular weight polyethylene and polytetrafluoroethylene in a hip simulator:A dose-response study of protein concentration[J]. Acta Orthopaedica Scandinavica, 2000, 71(4):365-369.
[28] MARSH M, NEWMAN S. Trends and developments in hip and knee arthroplasty technology[J]. Journal of Rehabilitation and Assistive Technologies Engineering, 2021, 8:2055668320952043.
[29] ZHANG X G, SHI G, SUN X J, et al. Factors influencing the outcomes of artificial hip replacements[J]. Cells Tissues Organs, 2019, 206(4-5):254-262.
[30] FENG C A, CEN J J, WU T, et al. Preparation and properties of the poly(ether ether ketone) (PEEK)/nano-zinc oxide (ZnO)-short carbon fiber (SCF) artificial joint composites[J]. ACS Applied Polymer Materials, 2022, 4(12):8869-8877.
[31] CAI Y, LI K M, LI L, et al. Anti-friction mechanism of textured artificial joint material under the walking conditions of human[J]. Journal of Materials Research and Technology, 2022, 20:2999-3007.
[32] LIU Y Y, ZHU Q, WANG C Y, et al. Tribological behavior of CoCrMo artificial knee joint with symmetrically biomimetic textured surfaces on PEEK[J]. Optics & Laser Technology, 2023, 157:108774.
[33] [JP+2]LIU D N, XIE H C, MA Z C, et al. Simultaneous enhancement of anti-friction and wear resistance performances via porous substrate and FeCoNiTiAl high entropy alloy coating of artificial joint materials[J]. Journal of Materials Research and Technology, 2022, 19:2907-2915.
[34] LIU D N, MA Z C, ZHANG W, et al. Superior antiwear biomimetic artificial joint based on high-entropy alloy coating on porous Ti6Al4V[J]. Tribology International, 2021, 158:106937.
[35] ZHAI W Z, BAI L C, ZHOU R H, et al. Recent progress on wear-resistant materials:Designs, properties, and applications[J]. Advanced Science, 2021, 8(11):2003739.
[36] NOSONOVSKY M, BHUSHAN B. Multiscale friction mechanisms and hierarchical surfaces in nano-and bio-tribology[J]. Materials Science & Engineering R:Reports, 2007, 58(3-5):162-193.
[37] 洪美娟, 刘金龙, 卢舟燕. 多功能人工关节模拟试验机设计[J]. 医疗装备, 2006, 19(10):15-17. HONG M J, LIU J L, LU Z Y. The design and modify of a multi-function tester for simulating artificial joints[J]. Medical Equipment, 2006, 19(10):15-17. (in Chinese)
[38] 华子恺. 人工关节润滑技术与摩擦学测试研究[D]. 上海:上海大学, 2011. HUA Z K. Research on artificial joint lubrication and tribological test technology[D]. Shanghai:Shanghai University, 2011. (in Chinese)
[39] TONG J, ZANT N P, WANG J Y, et al. Fatigue in cemented acetabular replacements[J]. International Journal of Fatigue, 2008, 30(8):1366-1375.
[40] 崔文, 张亚丽, 王志强, 等. 人工髋、膝关节磨损测试标准及模拟试验机研究进展[J]. 摩擦学学报, 2019, 39(2):248-258. CUI W, ZHANG Y L, WANG Z Q, et al. Review of the artificial hip and knee wear testing standards and simulation testing machines[J]. Tribology, 2019, 39(2):248-258. (in Chinese)
[41] JLAIEL K, YAHIAOUI M, PARIS J Y, et al. Tribolumen:A tribometer for a correlation between AE signals and observation of tribological process in real-time-application to a dry steel/glass reciprocating sliding contact[J]. Lubricants, 2020, 8(4):47.
[42] LYASHENKO I A, POPOV V L, POHRT R, et al. High-precision tribometer for studies of adhesive contacts[J]. Sensors, 2023, 23(1):456.
[43] LIU Y Y, ZHAO W W, LIU G X, et al. Self-powered artificial joint wear debris sensor based on triboelectric nanogenerator[J]. Nano Energy, 2021, 85:105967.
[44] ROTHAMMER B, MARIAN M, RUMMEL F, et al. Rheological behavior of an artificial synovial fluid-influence of temperature, shear rate and pressure[J]. Journal of the Mechanical Behavior of Biomedical Materials, 2021, 115:104278.
[45] SAIKKO V, MORAD O, VIITALA R. Effect of type and temperature of serum lubricant on VEXLPE wear and friction[J]. Wear, 2021, 470-471:203613.
[46] AFFATATO S, VALIGI M C, LOGOZZO S. Wear distribution detection of knee joint prostheses by means of 3D optical scanners[J]. Materials, 2017, 10(4):364.
[47] SAIKKO V, VUORINEN V, REVITZER H. Analysis of UHMWPE wear particles produced in the simulation of hip and knee wear mechanisms with the RandomPOD system[J]. Biotribology, 2015, 1-2:30-34.
[48] MATTEI L, TOMASI M, ARTONI A, et al. Combination of musculoskeletal and wear models to investigate the effect of daily living activities on wear of hip prostheses[J]. Proceedings of the Institution of Mechanical Engineers, Part J:Journal of Engineering Tribology, 2021, 235(12):2675-2687.
[49] TOH S M S, ASHKANFAR A, ENGLISH R, et al. Computational method for bearing surface wear prediction in total hip replacements[J]. Journal of the Mechanical Behavior of Biomedical Materials, 2021, 119:104507.
[50] ENGLISH R, ASHKANFAR A, ROTHWELL G. A computational approach to fretting wear prediction at the head-stem taper junction of total hip replacements[J]. Wear, 2015, 338-339:210-220.
[51] RUGGIERO A, SICILIA A. Lubrication modeling and wear calculation in artificial hip joint during the gait[J]. Tribology International, 2020, 142:105993.
[52] 冯一桐, 王智勇, 郭凤仪, 等. 弓网系统滑动电接触表面磨损特征研究[J]. 润滑与密封, 2023, 48(6):53-60. FENG Y T, WANG Z Y, GUO F Y, et al. Research on wear characteristics of sliding electrical contact surface in pantograph-catenary system[J]. Lubrication Engineering, 2023, 48(6):53-60. (in Chinese)
[53] PENG Y P, CAI J H, WU T H, et al. A hybrid convolutional neural network for intelligent wear particle classification[J]. Tribology International, 2019, 138:166-173.
[54] LI J H, WANG S, FU S Q, et al. Study on wear debris characteristics of different polyethylene under reciprocating sliding and compound motion modes[J]. Wear, 2023, 530-531:205062.
[55] 王涵, 左洪福, 刘珍珍, 等. 基于HOG和SVM算法的磨粒图像在线监测技术[J]. 南京航空航天大学学报, 2022, 54(6):1152-1158. WANG H, ZUO H F, LIU Z Z, et al. Online monitoring for oil wear particle images based on HOG feature extraction and SVM classification[J]. Journal of Nanjing University of Aeronautics and Astronautics, 2022, 54(6):1152-1158. (in Chinese)
[56] PENG Y P, CAI J H, WU T H, et al. WP-DRnet:A novel wear particle detection and recognition network for automatic ferrograph image analysis[J]. Tribology International, 2020, 151:106379.
[57] PENG Y P, YUE H T, WANG S, et al. Probability-weighted ensemble support vector machine for intelligent recognition of moving wear debris from joint implant[J]. Tribology International, 2023, 186:108583.
[58] PENG Y P, CAI J H, WU T H, et al. Online wear characterisation of rolling element bearing using wear particle morphological features[J]. Wear, 2019, 430-431:369-375.
[59] WANG J Q, BI J, WANG L J, et al. A non-reference evaluation method for edge detection of wear particles in ferrograph images[J]. Mechanical Systems and Signal Processing, 2018, 100:863-876.
[60] 伍锐斌, 彭业萍, 曹广忠, 等. 人工关节磨屑的显微单视图深度估计方法研究[J]. 润滑与密封, 2022, 47(7):40-48. WU R B, PENG Y P, CAO G Z, et al. Research on depth estimation from micro-single-view image of artificial joints wear particles[J]. Lubrication Engineering, 2022, 47(7):40-48. (in Chinese)
[61] 石新发, 贺石中, 谢小鹏, 等. 摩擦学系统润滑磨损故障诊断特征提取研究综述[J]. 摩擦学学报, 2023, 43(3):241-255. SHI X F, HE S Z, XIE X P, et al. Review on feature extraction of lubrication and wear fault diagnosis in tribology system[J]. Tribology, 2023, 43(3):241-255. (in Chinese)
[62] XU B, WEN G R, ZHANG Z F, et al. Wear particle classification using genetic programming evolved features[J]. Lubrication Science, 2018, 30(5):229-246.
[63] PENG Y P, WU T H, CAO G Z, et al. A hybrid search-tree discriminant technique for multivariate wear debris classification[J]. Wear, 2017, 392-393:152-158.
[64] HU X B, SONG J, LIAO Z H, et al. Morphological residual convolutional neural network (M-RCNN) for intelligent recognition of wear particles from artificial joints[J]. Friction, 2022, 10(4):560-572.
[65] WANG S, SHAO T, WU T H, et al. Knowledge-guided convolutional neural network model for similar three-dimensional wear debris identification with small number of samples[J]. Journal of Tribology, 2023, 145(9):091105.
[66] WANG S, WU T H, WANG K P, et al. 3-D particle surface reconstruction from multiview 2-D images with structure from motion and shape from shading (January 2020)[J]. IEEE Transactions on Industrial Electronics, 2021, 68(2):1626-1635.
[67] PENG Y P, WU Z B, CAO G Z, et al. Three-dimensional reconstruction of wear particles by multi-view contour fitting and dense point-cloud interpolation[J]. Measurement, 2021, 181:109638.
[68] ZHANG D K, ZHANG Y R, CHEN K, et al. Reducing taper fretting corrosion in artificial hip joints using a PEEK femoral head[J]. Journal of Materials Engineering and Performance, 2021, 30(6):4619-4628.

Options

Outlines

模态框（Modal）标题

Abstract

Cite this article

References

Visited