Adaptive Probabilistic Approach for Selecting Tumour Knee Prosthesis

Rupesh Ghyar1, Karupppasamy Subburaj2, B. Ravi1 and Manish Agarwal3

  1. OrthoCAD Network Research Centre, Indian Institute of Technology Bombay
    Powai, Mumbai, 400076, India
    {r.ghyar, b.ravi}@iitb.ac.in
  2. Department of Radiology and Biomedical Imaging, University of California San Francisco
    San Francisco, CA 94158, USA
    subburaj@radiology.ucsf.edu
  3. Department of Surgical Oncology, Hinduja Hospital and Medical Research Centre
    Mahim, Mumbai, 400016, India
    mgagarwal@gmail.com

Abstract

Tumour knee prostheses reconstruct bone gaps, left after resecting the tumour affected tissues, in limb salvage surgeries of bone cancer patients. They typically comprise of 6-12 different components chosen from a family of components that are manufactured in discrete variations (intended to cater to a wide range of patient conditions including gender, tumour position, leg (left/right), and resection length). These variations generate numerous combinations and selecting a correct set of components from a family of 100 or more total components has made the process difficult for a given patient. This article describes an adaptive probabilistic approach developed for selection of tumour knee prosthesis components, driven by geometric details. These details were extracted from the 3D virtual anatomical model, reconstructed from set of CT scan images of patients. The selection was performed in two steps. First, the grossly undersized and oversized components were eliminated. Then the geometric details of components were mapped, with the measured anatomical parameters of the patient, to form a fuzzy-logic based decision tree. This was based on pre-defined rules compiled from surgeons' experience. A set of measures (geometric difference, bone curvature, knee centre shift, and reconstruction length) were used to evaluate the selected prosthesis components. Evaluation was based on their suitability with respect to the patient's anatomy, and classified with a qualitative tag: "most suitable", "probably suitable", or "not suitable". A case study of distal femur replacement is presented to explain the proposed methodology. This approach eliminates the risk of over and under sizing of the prosthesis components and reduces the average inventory to be maintained for each patient.

Key words

tumour knee prosthesis, prosthesis selection, 3D anatomical models, preoperative planning

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS120405055G

Publication information

Volume 10, Issue 3 (June 2013)
Year of Publication: 2013
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

DownloadAvailable in PDF
Portable Document Format

How to cite

Ghyar, R., Subburaj, K., Ravi, B., Agarwal, M.: Adaptive Probabilistic Approach for Selecting Tumour Knee Prosthesis. Computer Science and Information Systems, Vol. 10, No. 3, 1407-1428. (2013)