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Healthc Inform Res > Volume 15(4); 2009 > Article
Journal of Korean Society of Medical Informatics 2009;15(4):483-492.
DOI: https://doi.org/10.4258/jksmi.2009.15.4.483    Published online December 31, 2009.
A Study of Joint Space Narrowing and Erosion in Rheumatoid Arthritis
Ho Chul Kang1, Kwang Gi Kim1, Jang Pyo Bae1, Chang Bu Jeong1, Sungjun Kim2
1Biomedical Engineering Branch, Division of Cancer, National Cancer Center, Korea.
2Department of Radiology, Yonsei University College of Medicine, Gangnam Severance Hospital, Korea.
Correspondence:  Kwang Gi Kim,
Received: 5 August 2009
Abstract

Objective: This study was conducted to measure radiographic joint space width and to estimate erosion in the hands of patients with rheumatoid arthritis. It showed that joint space width, homogeneity, and invariant moments are parameters to discriminate between the normal and the rheumatoid joint.

Methods: In order to measure the joint space width and to estimate erosion in the finger joint, 32 radiographic images were used - 16 images for training and 16 images for testing. The joint space width was measured in order to quantify the joint space narrowing. Also, homogeneity and invariant moments was computed in order to quantify erosion. Finally, artificial neural networks were constructed and tested as a classifier distinguishing between the normal and the rheumatoid joint.

Results: The joint space width of normal was 1.04±0.15 mm and the width of patients with rheumatoid arthritis was 0.94±0.15 mm. The Homogeneity of normal was 16568.83±2669.83 and invariant moments were 6843.45±2937.55. They were statistically difference (p<.05). Using these characteristics, artificial neural networks showed that they discriminate between normal and rheumatoid arthritis (AUC=0.91).

Conclusion: Measuring joint space width, estimating homogeneity, and invariant moments provide the capability to distinguish between a normal joint and a rheumatoid joint.

Key Words: Rheumatoid Arthritis, Joint Space Narrowing, Erosion, Computer-aided Diagnosis, Image Processing
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