Literature DB >> 24216061

Trabecular bone texture detected by plain radiography is associated with an increased risk of knee replacement in patients with osteoarthritis: a 6 year prospective follow up study.

P Podsiadlo1, F M Cicuttini2, M Wolski3, G W Stachowiak3, A E Wluka2.   

Abstract

OBJECTIVE: To examine the association between trabecular bone texture and knee joint replacement (KJR) measured using a variance orientation transform (VOT) method.
METHODS: The association of trabecular bone texture and KJR was examined prospectively over 6 years in 123 subjects with symptomatic knee osteoarthritis (OA): data regarding KJR was available for 114 (93%). At baseline, weight-bearing anteroposterior tibio-femoral radiographs were acquired. Trabecular bone texture regions were selected from the medial and lateral subchondral tibia. The VOT method was applied to each region and five fractal bone texture parameters, i.e., mean fractal dimension (FDMEAN), fractal dimensions in the horizontal (FDH) and vertical (FDV) directions, and along the roughest part of trabecular bone (FD(Sta)), and texture aspect ratio (Str) were calculated. The association between groups with increasing baseline fractal parameters (defined using tertiles) with risk of JR was examined using logistic regression.
RESULTS: 28 (25%) participants' study knees underwent KJR over 6 years. Participants with KJR had lower medial FD(MEAN) and FD(H) parameters (P = 0.02 for difference). With increasing FD(MEAN), adjusted for age, gender, body mass index (BMI), osteophyte grade, joint space narrowing (JSN) grade and WOMAC pain score, the odds of KJR was reduced (P = 0.04 for trend).
CONCLUSION: This study suggests that the texture of medial tibial trabecular bone measured from plain radiographs is related to the risk of KJR: with increasing FD(MEAN) (the overall measure of bone texture roughness) the risk of KJR was reduced, independent of other clinical predictors of joint replacement. Tibial trabecular bone texture may be a useful marker of disease progression and a target of therapy in OA.
Copyright © 2013 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Fractals; Knee replacement; Radiography; Trabecular bone

Mesh:

Year:  2013        PMID: 24216061     DOI: 10.1016/j.joca.2013.10.017

Source DB:  PubMed          Journal:  Osteoarthritis Cartilage        ISSN: 1063-4584            Impact factor:   6.576


  8 in total

1.  Video-assisted thoracic surgery resection of rib osteophytes.

Authors:  Zhiyong Su; Yuqin Bai; Yilei Zhang; Baihan Su; Tianshuo Jiang; Xin Zhao; Hongliang Bian; Bo Zhao
Journal:  J Thorac Dis       Date:  2015-03       Impact factor: 2.895

2.  Subchondral tibial bone texture of conventional X-rays predicts total knee arthroplasty.

Authors:  Ahmad Almhdie-Imjabbar; Hechmi Toumi; Khaled Harrar; Antonio Pinti; Eric Lespessailles
Journal:  Sci Rep       Date:  2022-05-18       Impact factor: 4.996

3.  Study of the Efficacy of Artificial Intelligence Algorithm-Based Analysis of the Functional and Anatomical Improvement in Polynucleotide Treatment in Knee Osteoarthritis Patients: A Prospective Case Series.

Authors:  Ji Yoon Jang; Ji Hyun Kim; Min Woo Kim; Sung Hoon Kim; Sang Yeol Yong
Journal:  J Clin Med       Date:  2022-05-18       Impact factor: 4.964

4.  Predictive Validity of Radiographic Trabecular Bone Texture in Knee Osteoarthritis: The Osteoarthritis Research Society International/Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium.

Authors:  Virginia Byers Kraus; Jamie E Collins; H Cecil Charles; Carl F Pieper; Lawrence Whitley; Elena Losina; Michael Nevitt; Steve Hoffmann; Frank Roemer; Ali Guermazi; David J Hunter
Journal:  Arthritis Rheumatol       Date:  2017-12-15       Impact factor: 10.995

5.  Bone Structure Analysis of the Radius Using Ultrahigh Field (7T) MRI: Relevance of Technical Parameters and Comparison with 3T MRI and Radiography.

Authors:  Mohamed Jarraya; Rafael Heiss; Jeffrey Duryea; Armin M Nagel; John A Lynch; Ali Guermazi; Marc-André Weber; Andreas Arkudas; Raymund E Horch; Michael Uder; Frank W Roemer
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6.  Deep learning for early detection of pathological changes in X-ray bone microstructures: case of osteoarthritis.

Authors:  Livija Jakaite; Jiří Hladůvka; Sergey Minaev; Aziz Ambia; Wojtek Krzanowski; Vitaly Schetinin
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Review 7.  Prognostic factors for progression of clinical osteoarthritis of the knee: a systematic review of observational studies.

Authors:  Alex N Bastick; Jos Runhaar; Janneke N Belo; Sita M A Bierma-Zeinstra
Journal:  Arthritis Res Ther       Date:  2015-06-08       Impact factor: 5.156

8.  Risk factors for pain and functional impairment in people with knee and hip osteoarthritis: a systematic review and meta-analysis.

Authors:  Sandeep Sandhar; Toby O Smith; Kavanbir Toor; Franklyn Howe; Nidhi Sofat
Journal:  BMJ Open       Date:  2020-08-07       Impact factor: 2.692

  8 in total

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