Share Email Print
cover

Proceedings Paper

Investigation of temporal radiographic texture analysis for the detection of periprosthetic osteolysis
Author(s): Joel R. Wilkie; Maryellen L. Giger; Charles A. Engh; John M. Martell
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Periprosthetic osteolysis is a disease caused by the body's response to submicron polyethylene debris particles from the hip implant in total hip replacement (THR) patients. It leads to resorption of bone surrounding the implant and deterioration of the bone's trabecular texture, but this is difficult to detect until the later stages of disease progression. Radiographic texture analysis methods have shown promise in detecting this disease at an earlier stage; however, changes in texture over time may be more important than absolute texture measures. In this research, we investigated temporal radiographic texture analysis (tRTA) methods as possible aids in the detection of osteolysis. A database of 48 THR cases with images available from four different follow-up time intervals was used. ROIs were selected within the osteolytic region of the most recent follow-up image (or comparable region for normal cases) and visually matched on all previous images. Texture features were calculated from the ROIs and then trend analysis was performed using a simple linear regression method, an LDA method and a BANN method. The performance of these three methods was evaluated by ROC analysis. Maximum AUC values of 0.68, 0.78, and 0.88 for the task of distinguishing between osteolysis and normal cases were achieved for the respective tRTA features. These performances were superior to those of our prior stationary, non-temporal texture analysis. The results suggest that tRTA may have the potential to help detect osteolysis at an earlier, more treatable stage.

Paper Details

Date Published: 20 March 2006
PDF: 8 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61446Z (20 March 2006); doi: 10.1117/12.653594
Show Author Affiliations
Joel R. Wilkie, Univ. of Chicago (United States)
Maryellen L. Giger, Univ. of Chicago (United States)
Charles A. Engh, Anderson Orthopaedic Research Institute (United States)
John M. Martell, Univ. of Chicago (United States)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

© SPIE. Terms of Use
Back to Top