The assessment of joint space width (JSW) on hand X-ray images of patients suffering from rheumatoid arthritis (RA) is a time-consuming task. Manual assessment is semiquantitative and is observer dependent which hinders an accurate evaluation of joint damage, particularly in the early stages. Automated analysis of the JSW is an important step forward since it is observer independent and might improve the assessment sensitivity in the early RA stage. This study proposes a fully automatic method for both joint location and margin detection in RA hand radiographs. The location detection procedure is based on image features of the joint region and is aided by geometric relationship of finger joints. More than 99% of joint locations are detected with an error smaller than 3 mm with respect to the manually indicated gold standard. The joint margins are detected by combining intensity values and spatially constrained intensity derivatives, refined by an active contour model. More than 96% of the joints are successfully delineated. The JSW is calculated over the middle 60% of a landmark-defined joint span. The overall JSW error compared with the ground truth is 6.8%. In conclusion, the proposed method is able to automatically locate the finger joints in RA hand radiographs, and to quantify the JSW of these joints.

The measurement of joint space width (JSW) in hand x-ray images of patients suffering from Rheumatoid Arthritis (RA) is a time consuming task for radiologists. Manual assessment lacks accuracy and is observer-dependent, which hinders an accurate evaluation of joint degeneration in early diagnosis and follow-up studies. Automatic analysis of the JSW is crucial with regard to standardization, sensitivity, and reproducibility. In this paper, we focus on both joint location and joint margin detection. For the evaluation, five hand radiographs from RA patients, in which the joints have been manually delineated, are used. All finger joints are located correctly with margins differing 0.1 mm on average from the manual delineation.

Abstract. Computerized methods promise quick, objective, and sensitive tools to quantify progression of radiological damage in rheumatoid arthritis (RA). Measurement of joint space width (JSW) in finger and wrist joints with these systems performed comparable to the Sharp-van der Heijde score (SHS). A next step toward clinical use, validation of precision and accuracy in hand joints with minimal damage, is described with a close scrutiny of sources of error. A recently developed system to measure metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints was validated in consecutive hand images of RA patients. To assess the impact of image acquisition, measurements on radiographs from a multicenter trial and from a recent prospective cohort in a single hospital were compared. Precision of the system was tested by comparing the joint space in mm in pairs of subsequent images with a short interval without progression of SHS. In case of incorrect measurements, the source of error was analyzed with a review by human experts. Accuracy was assessed by comparison with reported measurements with other systems. In the two series of radiographs, the system could automatically locate and measure 1003/1088 (92.2%) and 1143/1200 (95.3%) individual joints, respectively. In joints with a normal SHS, the average (SD) size of MCP joints was 1.7 AE 0.2 and 1.6 AE 0.3 mm in the two series of radiographs, and of PIP joints 1.0 AE 0.2 and 0.9 AE 0.2 mm. The difference in JSW between two serial radiographs with an interval of 6 to 12 months and unchanged SHS was 0.0 AE 0.1 mm, indicating very good precision. Errors occurred more often in radiographs from the multicenter cohort than in a more recent series from a single hospital. Detailed analysis of the 55/1125 (4.9%) measurements that had a discrepant paired measurement revealed that variation in the process of image acquisition (exposure in 15% and repositioning in 57%) was a more frequent source of error than incorrect delineation by the software (25%). Various steps in the validation of an automated measurement system for JSW of MCP and PIP joints are described. The use of serial radiographs from different sources, with a short interval and limited damage, is helpful to detect sources of error. Image acquisition, in particular repositioning, is a dominant source of error. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.