Literature DB >> 23245655

The usefulness of computer-aided joint space analysis in the assessment of rheumatoid arthritis.

Alexander Pfeil1, Diane M Renz, Andreas Hansch, Franz Kainberger, Gabriele Lehmann, Ansgar Malich, Gunter Wolf, Joachim Böttcher.   

Abstract

OBJECTIVE: Computer-aided joint space analysis (CAJSA) is a newly developed technique for the measurement of radiogeometrically detectable joint space widths of the metacarpal-phalangeal (JSD-MCP) and proximal-interphalangeal articulations (JSD-PIP). The aim of this study was to verify the sensitivity and specificity of these CAJSA measurements in the assessment of established RA.
METHODS: Four hundred and fifty-eight participants (248 healthy subjects, 210 RA patients) underwent computerized semi-automated measurements of the JSD-MCP and JSD-PIP articulations (CAJSA, Radiogrammetry Kit, Version 1.3.6) based on digitally performed radiographs. The Sharp joint space narrowing score was also performed to determine RA-related joint space narrowing.
RESULTS: The significant severity-dependent reduction for JSD-MCP was -44.0% and for JSD-PIP, -25.94% between Sharp scores 0 and 3. The sensitivity and specificity of JSD-MCP (total) was 88.1% versus 77.8%, respectively (AUC = 0.920; P < 0.001). Furthermore, JSD-PIP (total) revealed a lower sensitivity and specificity with 61.4% and 88.7% (AUC = 0.878; P < 0.001).
CONCLUSION: The CAJSA method presented a reliable assessment of disease-related joint space narrowing in patients suffering from RA with excellent sensitivity and specificity. By providing quantitative data, other scoring methods could be significantly improved, and thereby the accuracy of the diagnosis and a better therapeutic evaluation could be achieved.
Copyright © 2012 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.

Entities:  

Keywords:  AUC; Area under the curve; CAD; CAJSA; CV; Coefficient of variation; Computer-aided diagnosis; Computer-aided joint space analysis; Finger; JSD; JSD-MCP; JSD-PIP; Joint space distance; Joint space distance of the metacarpal-phalangeal joint; Joint space distance of the proximal-interphalangeal joint; Joint space width; MCP; Metacarpal-phalangeal joint; PIP; Proximal-interphalangeal joint; RA; Rheumatoid arthritis; SD; Sharp score; Standard deviation

Mesh:

Year:  2012        PMID: 23245655     DOI: 10.1016/j.jbspin.2012.10.022

Source DB:  PubMed          Journal:  Joint Bone Spine        ISSN: 1297-319X            Impact factor:   4.929


  11 in total

1.  Validation of automatic joint space width measurements in hand radiographs in rheumatoid arthritis.

Authors:  Olga Schenk; Yinghe Huo; Koen L Vincken; Mart A van de Laar; Ina H H Kuper; Kees C H Slump; Floris P J G Lafeber; Hein J Bernelot Moens
Journal:  J Med Imaging (Bellingham)       Date:  2016-11-23

2.  Radiographic quantifications of joint space narrowing progression by computer-based approach using temporal subtraction in rheumatoid wrist.

Authors:  Shota Ichikawa; Tamotsu Kamishima; Kenneth Sutherland; Takanobu Okubo; Kou Katayama
Journal:  Br J Radiol       Date:  2015-10-20       Impact factor: 3.039

3.  Performance of computer-based analysis using temporal subtraction to assess joint space narrowing progression in rheumatoid patients.

Authors:  Shota Ichikawa; Tamotsu Kamishima; Kenneth Sutherland; Takanobu Okubo; Kou Katayama
Journal:  Rheumatol Int       Date:  2015-08-23       Impact factor: 2.631

Review 4.  Computer-aided diagnosis in rheumatic diseases using ultrasound: an overview.

Authors:  Josefina Gutiérrez-Martínez; Carlos Pineda; Hugo Sandoval; Araceli Bernal-González
Journal:  Clin Rheumatol       Date:  2019-11-06       Impact factor: 2.980

5.  A reliability study using computer-based analysis of finger joint space narrowing in rheumatoid arthritis patients.

Authors:  Katsuya Hatano; Tamotsu Kamishima; Kenneth Sutherland; Masaru Kato; Ikuma Nakagawa; Shota Ichikawa; Keisuke Kawauchi; Shota Saitou; Masaya Mukai
Journal:  Rheumatol Int       Date:  2016-10-28       Impact factor: 2.631

Review 6.  Machine Learning in Rheumatic Diseases.

Authors:  Mengdi Jiang; Yueting Li; Chendan Jiang; Lidan Zhao; Xuan Zhang; Peter E Lipsky
Journal:  Clin Rev Allergy Immunol       Date:  2021-02       Impact factor: 8.667

7.  Computer-Based Radiographic Quantification of Joint Space Narrowing Progression Using Sequential Hand Radiographs: Validation Study in Rheumatoid Arthritis Patients from Multiple Institutions.

Authors:  Shota Ichikawa; Tamotsu Kamishima; Kenneth Sutherland; Jun Fukae; Kou Katayama; Yuko Aoki; Takanobu Okubo; Taichi Okino; Takahiko Kaneda; Satoshi Takagi; Kazuhide Tanimura
Journal:  J Digit Imaging       Date:  2017-10       Impact factor: 4.056

8.  Fully automated joint space width measurement and digital X-ray radiogrammetry in early RA.

Authors:  Michael Platten; Yogan Kisten; Johan Kälvesten; Laurent Arnaud; Kristina Forslind; Ronald van Vollenhoven
Journal:  RMD Open       Date:  2017-06-29

9.  Computer-assisted Joint Space Area Measurement: A New Technique in Patients With Knee Osteoarthritis.

Authors:  İlker Ilhanli; Necip Güder; Alptekin Tosun; Esin Avci; Canan Çelik
Journal:  Arch Rheumatol       Date:  2017-04-17       Impact factor: 1.472

10.  An Efficient CNN for Hand X-Ray Classification of Rheumatoid Arthritis.

Authors:  Gitanjali S Mate; Abdul K Kureshi; Bhupesh Kumar Singh
Journal:  J Healthc Eng       Date:  2021-06-14       Impact factor: 2.682

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