About Us

We are a group of researchers within the Tribology Laboratory, Department of Mechanical Engineering at Curtin University who are working on the development of mathematical methods and numerical tools for the detection and prediction of osteoarthritis (OA) in human joints.

The development is complex process encompassing three following research areas, i.e.:

1. Directional fractal signature and dissimilarity measures

We have developed new methods for the characterization of bone texture regions selected on knee or hand x-ray images, as marked on the picture below.

Unlike other techniques in use our methods produce fractal texture parameters that are able to quantify bone roughness at different scales and directions.

  • M. Wolski, P. Podsiadlo and G.W. Stachowiak, Directional fractal signature analysis of trabecular bone: evaluation of different methods to detect early osteoarthritis in knee radiographs. Proceedings of the Institution of Mechanical Engineers, Part H, Journal of Engineering in Medicine, 223 (2009) 211-236. (go to the article)
  • M. Wolski, P. Podsiadlo and G. W. Stachowiak, Directional fractal signature methods for trabecular bone texture in hand radiographs: Data from the Osteoarthritis Initiative, Medical Physics 41, 081914 (2014). (go to the article)

We also develop methods that produce dissimilarity measures (DMs; distances between images) that are used to quantify bone texture at each pixel location over all scales and directions.

  • T. Woloszynski, P. Podsiadlo, G.W. Stachowiak, M. Kurzynski, A signature dissimilarity measure for trabecular bone texture in knee radiographs, Medical Physics, 37 (2010) 2030-2042. (go to the article)

2. Detection of osteoarthritic changes in bone

We have shown that tibial trabecular bone texture on x-ray images is different between knees with and without OA. With our methods we can detect subtle (invisible to human eye) changes occurring in knee and hand bones at the early stages of OA. We have demonstrated that our methods are so sensitive that they could detect minute changes occurring in bone on a pathway to OA. In knees without pre-existing OA we detected differences in tibial trabecular bone texture between knees with and without cartilage defects (the OA risk factor).

  • P. Podsiadlo, L. Dahl, M. Englund, L.S. Lohmander and G.W. Stachowiak, Differences in trabecular bone texture between knees with and without radiographic osteoarthritis detected by fractal methods, Osteoarthritis and Cartilage, 16 (2008) 323-329. (go to the article)
  • M. Wolski, P. Podsiadlo and G.W. Stachowiak, Differences in trabecular bone texture between knees with and without radiographic osteoarthritis detected by directional fractal signature method, Osteoarthritis and Cartilage, 18 (2010) 684-690. (go to the article)
  • M. Wolski, G.W. Stachowiak, A.R. Dempsey, P.M. Mills, F.M. Cicuttini, Y. Wang, K.K. Stoffel, D.G. Lloyd, P. Podsiadlo, Trabecular bone texture detected by plain radiography and variance orientation transform method is different between knees with and without cartilage defects. Journal of Orthopaedic Research, 29 (2011) 1161-1167. (go to the article)

3. Prediction of osteoarthritis and knee replacement

Based on the analysis of data provided by these methods we should be able to predict the onset of OA and its progression. Our preliminary studies using dissimilarity measures together with regression models/classifiers showed that tibial trabecular bone texture is predictive of joint space loss, i.e. it is also predictable of OA. In addition, the fractal parameters that we have used showed the mean trabecular roughness is associated with the risk of knee replacement.

  • T. Woloszynski, P. Podsiadlo, G.W. Stachowiak, M. Kurzynski, L.S. Lohmander and M. Englund, Prediction of progression of radiographic knee osteoarthritis using tibial trabecular bone texture, Arthritis & Rheumatism, 64 (2012) 688-95. (go to the article)
  • T. Woloszynski, P. Podsiadlo, G.W. Stachowiak, M. Kurzynski, A dissimilarity-based multiple classifier system for trabecular bone texture in detection and prediction of progression of knee osteoarthritis, Proceedings of the Institution of Mechanical Engineers Part H: Journal of Engineering in Medicine 226 (2012) 887-94. (go to the article)
  • P. Podsiadlo, F.M. Cicuttini, M. Wolski, G.W. Stachowiak, A.E. Wluka, Trabecular bone texture detected by plain radiography is associated with an increased risk of knee replacement in patients with osteoarthritis: a 6 year prospective follow up study, Osteoarthritis and Cartilage 22 (2014) 71-75. (go to the article)

Staff and current research activities related to this project

Senior Members

  • Professor G.W. Stachowiak
    He is the founder and head of the Tribology Laboratory. His research activities are in the areas of development of new methods for the multi-scale characterization/analysis of 3D surfaces, image analysis, lubrication and wear of synovial joints and factors contributing to osteoarthritis.
  • Associate Professor Pawel Podsiadlo
    His research includes development of methods for the analyses of trabecular bone micro-architecture in human joints and its relationships to osteoarthritis.

Members

  • Dr Marcin Wolski (Research Fellow)
    His research focuses on the development of methods for bone region selection and fractal signature analyses.
  • Dr Tomasz Woloszynski (Research Fellow)
    His research activities include development of dissimilarity measures, multiple classifiers and regression models.

Our collaborators

Prediction of osteoarthritis is a complex problem requiring efforts of many research groups. Thus, for the last 15 years we have been collaborating with the world leading institutions in osteoarthritis in Australia, Europe and USA on OA related problems.

Australia

Griffith University

Monash University & Alfred Hospital

  • Prof Flavia Cicuttini, Head of Rheumatology Unit at Alfred Hospital, Head of Musculoskeletal Unit in School of Public Health and Preventive Medicine at Monash University
  • Assoc Prof Anita Wluka, Department of Epidemiology and Preventive Medicine

Monash University

Murdoch University

Murdoch Orthopaedic Clinic

Europe

Lund University, Sweden

  • Prof Stefan Lohmander, Editor in Chief, Osteoarthritis and Cartilage, Department of Orthopaedics, Lund University, Sweden, and also Department Orthopaedics and Traumatology, University of Southern, Denmark
  • Assoc Prof Martin Englund, Department of Orthopaedics, Lund University, Sweden, and also Clinical Epidemiology Research and Training Unit, Boston University School of Medicine, Boston MA

Wroclaw University of Technology, Poland

  • Prof Marek Kurzynski, Chair of Computer Systems and Networks, Faculty of Electronics

USA

University of California, San Francisco

Boston University, Massachusetts

  • Prof David Felson, Clinical Epidemiology Research and Training Unit, Boston University School of Medicine

University of Alabama, Birmingham

  • Prof C.E. Lewis, Director of the Division’s Preventive Medicine Clinic, Department of Medicine

The University of Iowa