Computer-aided grading and quantification of hip osteoarthritis severity employing shape descriptors of radiographic hip joint space

Ioannis Boniatis; Dionisis Cavouras; Lena Costaridou; Ioannis Kalatzis; Elias Panagiotopoulos; George Panayiotakis

doi:10.1016/j.compbiomed.2007.05.005

Computer-aided grading and quantification of hip osteoarthritis severity employing shape descriptors of radiographic hip joint space

Comput Biol Med. 2007 Dec;37(12):1786-95. doi: 10.1016/j.compbiomed.2007.05.005. Epub 2007 Jul 10.

Authors

Ioannis Boniatis¹, Dionisis Cavouras, Lena Costaridou, Ioannis Kalatzis, Elias Panagiotopoulos, George Panayiotakis

Affiliation

¹ University of Patras, School of Medicine, Department of Medical Physics, 265 00 Patras, Greece.

PMID: 17624323
DOI: 10.1016/j.compbiomed.2007.05.005

Abstract

A computer-based system was designed for the grading and quantification of hip osteoarthritis (OA) severity. Employing an active-contours segmentation model, 64 hip joint space (HJS) images (18 normal, 46 osteoarthritic) were obtained from the digitized radiographs of 32 unilateral and bilateral OA-patients. Shape features, generated from the HJS-images, and a hierarchical decision tree structure was used for the grading of OA. A shape features based regression model quantified the OA-severity. The system accomplished high accuracies in characterizing hips as "Normal" (100%), of "mild/moderate"-OA (93.8%) or "severe"-OA (96.7%). OA-severity values, as expressed by HJS-narrowing, correlated highly (r=0.9,p<0.001) with the values predicted by the regression model. The system may contribute to OA-patient management.

Publication types

Clinical Trial
Research Support, Non-U.S. Gov't

MeSH terms

Aged
Aged, 80 and over
Diagnosis, Computer-Assisted*
Hip Joint / diagnostic imaging*
Hip Joint / pathology
Humans
Middle Aged
Osteoarthritis, Hip / classification
Osteoarthritis, Hip / diagnostic imaging*
Osteoarthritis, Hip / pathology
Radiographic Image Interpretation, Computer-Assisted
Severity of Illness Index