3D Human cartilage surface characterization by optical coherence tomography

Early diagnosis and treatment of cartilage degeneration is of high clinical interest. Loss of surface integrity is considered one of the earliest and most reliable signs of degeneration, but cannot currently be evaluated objectively. Optical Coherence Tomography (OCT) is an arthroscopically available light-based non-destructive real-time imaging technology that allows imaging at micrometre resolutions to millimetre depths. As OCT-based surface evaluation standards remain to be defined, the present study investigated the diagnostic potential of 3D surface profile parameters in the comprehensive evaluation of cartilage degeneration. To this end, 45 cartilage samples of different degenerative grades were obtained from total knee replacements (2 males, 10 females; mean age 63.8 years), cut to standard size and imaged using a spectral-domain OCT device (Thorlabs, Germany). 3D OCT datasets of 8  ×  8, 4  ×  4 and 1  ×  1 mm (width  ×  length) were obtained and pre-processed (image adjustments, morphological filtering). Subsequent automated surface identification algorithms were used to obtain the 3D primary profiles, which were then filtered and processed using established algorithms employing ISO standards. The 3D surface profile thus obtained was used to calculate a set of 21 3D surface profile parameters, i.e. height (e.g. Sa), functional (e.g. Sk), hybrid (e.g. Sdq) and segmentation-related parameters (e.g. Spd). Samples underwent reference histological assessment according to the Degenerative Joint Disease classification. Statistical analyses included calculation of Spearman's rho and assessment of inter-group differences using the Kruskal Wallis test. Overall, the majority of 3D surface profile parameters revealed significant degeneration-dependent differences and correlations with the exception of severe end-stage degeneration and were of distinct diagnostic value in the assessment of surface integrity. None of the 3D surface profile parameters investigated were capable of reliably differentiating healthy from early-degenerative cartilage, while scan area sizes considerably affected parameter values. In conclusion, cartilage surface integrity may be adequately assessed by 3D surface profile parameters, which should be used in combination for the comprehensive and thorough evaluation and overall improved diagnostic performance. OCT- and image-based surface assessment could become a valuable adjunct tool to standard arthroscopy.

[1]  Simo Saarakkala,et al.  Quantification of the optical surface reflection and surface roughness of articular cartilage using optical coherence tomography , 2009, Physics in medicine and biology.

[2]  Freddie H Fu,et al.  Arthroscopic Microscopy of Articular Cartilage Using Optical Coherence Tomography , 2004, The American journal of sports medicine.

[3]  R. Moskowitz The burden of osteoarthritis: clinical and quality-of-life issues. , 2009, The American journal of managed care.

[4]  Surface topography of viable articular cartilage measured with scanning white light interferometry. , 2009, Osteoarthritis and cartilage.

[5]  D. Shepherd,et al.  Investigation of techniques for the measurement of articular cartilage surface roughness. , 2013, Micron.

[6]  F. Noyes,et al.  A system for grading articular cartilage lesions at arthroscopy , 1989, The American journal of sports medicine.

[7]  Three dimensional surface characterization of human cartilages at a micron and nanometre scale , 2013 .

[8]  Hubert Welp,et al.  Contrast enhancement methods in Optical Coherence Tomography using spectral features , 2013, Biomedizinische Technik. Biomedical engineering.

[9]  J Fisher,et al.  The influence of continuous sliding and subsequent surface wear on the friction of articular cartilage , 1999, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[10]  C. Little,et al.  What constitutes an "animal model of osteoarthritis"--the need for consensus? , 2012, Osteoarthritis and cartilage.

[11]  Mirela Ionescu,et al.  The pathobiology of focal lesion development in aging human articular cartilage and molecular matrix changes characteristic of osteoarthritis. , 2003, Arthritis and rheumatism.

[12]  Gunther O. Hofmann,et al.  How valid is the arthroscopic diagnosis of cartilage lesions? Results of an opinion survey among highly experienced arthroscopic surgeons , 2009, Archives of Orthopaedic and Trauma Surgery.

[13]  Y. Zheng,et al.  Effects of optical beam angle on quantitative optical coherence tomography (OCT) in normal and surface degenerated bovine articular cartilage , 2011, Physics in medicine and biology.

[14]  Erik B. Dam,et al.  Diagnosis of Osteoarthritis by Cartilage Surface Smoothness Quantified Automatically from Knee MRI , 2011, Cartilage.

[15]  Stephen J. Matcher,et al.  Experimental validation of an extended Jones matrix calculus model to study the 3D structural orientation of the collagen fibers in articular cartilage using polarization-sensitive optical coherence tomography , 2012, Biomedical optics express.

[16]  S. Jimenez,et al.  Osteoarthritis cartilage histopathology: grading and staging. , 2006, Osteoarthritis and cartilage.

[17]  Lihong V. Wang,et al.  Jones-matrix imaging of biological tissues with quadruple-channel optical coherence tomography. , 2002, Journal of biomedical optics.

[18]  Robert Schmitt,et al.  Three‐dimensional imaging and analysis of human cartilage degeneration using Optical Coherence Tomography , 2015, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.

[19]  Y. P. Huang,et al.  Comparison of ultrasound and optical coherence tomography techniques for evaluation of integrity of spontaneously repaired horse cartilage , 2012, Journal of medical engineering & technology.

[20]  H. Dorfman,et al.  Biochemical and metabolic abnormalities in articular cartilage from osteo-arthritic human hips. II. Correlation of morphology with biochemical and metabolic data. , 1971, The Journal of bone and joint surgery. American volume.

[21]  Robert Schmitt,et al.  Morphometric grading of osteoarthritis by optical coherence tomography — An ex vivo study , 2014, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.

[22]  G N Duda,et al.  Altered cartilage mechanics and histology in knee osteoarthritis: relation to clinical assessment (ICRS Grade). , 2005, Osteoarthritis and cartilage.

[23]  N. Matsui,et al.  Analysis of the thickness and curvature of articular cartilage of the femoral condyle. , 2003, Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association.

[24]  Robert Schmitt,et al.  Evaluation of Single-Impact-Induced Cartilage Degeneration by Optical Coherence Tomography , 2015, BioMed research international.

[25]  Sion Glyn-Jones,et al.  Non-invasive imaging of cartilage in early osteoarthritis. , 2013, The bone & joint journal.

[26]  Costas Pitris,et al.  High-resolution optical coherence tomographic imaging of osteoarthritic cartilage during open knee surgery , 2005, Arthritis research & therapy.

[27]  Robert Schmitt,et al.  Optical coherence tomography-based parameterization and quantification of articular cartilage surface integrity. , 2015, Biomedical optics express.

[28]  Zenghai Lu,et al.  Comparative study of the angle-resolved backscattering properties of collagen fibers in bovine tendon and cartilage. , 2011, Journal of biomedical optics.

[29]  J. Jurvelin,et al.  Quantitative ultrasound imaging detects degenerative changes in articular cartilage surface and subchondral bone , 2006, Physics in medicine and biology.

[30]  Ulrich Marx,et al.  In vitro observation of cartilage-degeneration progression by Fourier-domain OCT , 2012, BiOS.

[31]  Kim Henriksen,et al.  Which elements are involved in reversible and irreversible cartilage degradation in osteoarthritis? , 2010, Rheumatology International.