Literature DB >> 21515391

A novel fast knee cartilage segmentation technique for T2 measurements at MR imaging--data from the Osteoarthritis Initiative.

C Stehling1, T Baum, C Mueller-Hoecker, H Liebl, J Carballido-Gamio, G B Joseph, S Majumdar, T M Link.   

Abstract

Magnetic resonance imaging (MRI) T(2) relaxation time assesses non-invasively cartilage composition and can be used as early biomarker for knee osteoarthritis. Most knee cartilage segmentation techniques were primarily developed for volume measurements in DESS or SPGR sequences. For T(2) quantifications, these segmentations need to be superimposed on T(2) maps. However, given that these procedures are time consuming and require manual alignment, using them for analysis of T(2) maps in large clinical trials like the Osteoarthritis Initiative (OAI) is challenging. A novel direct segmentation technique (DST) for T(2) maps was therefore developed. Using the DST, T(2) measurements were performed and compared with those determined with an established segmentation superimposition technique (SST). MR images of five OAI participants were analysed with both techniques three times by one reader and five different images sets additionally with DST three times by two readers. Segmentations and T(2) measurements of one knee required on average 63±3min with DST (vs 302±13min for volume and T(2) measurements with SST). Bland-Altman plots indicated good agreement between the two segmentation techniques, respectively the two readers. Reproducibility errors of both techniques (DST vs SST) were similar (P>0.05) for whole knee cartilage mean T(2) (1.46% vs 2.18%), laminar (up to 2.53% vs 3.19%) and texture analysis (up to 8.34% vs 9.45%). Inter-reader reproducibility errors of DST were higher for texture analysis (up to 15.59%) than for mean T(2) (1.57%) and laminar analysis (up to 2.17%). Due to these results, the novel DST can be recommended for T(2) measurements in large clinical trials like the OAI.
Copyright © 2011 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21515391      PMCID: PMC6338671          DOI: 10.1016/j.joca.2011.04.002

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


  35 in total

1.  Association of magnetic resonance imaging-based knee cartilage T2 measurements and focal knee lesions with knee pain: data from the Osteoarthritis Initiative.

Authors:  Thomas Baum; Gabby B Joseph; Ahilan Arulanandan; Lorenzo Nardo; Warapat Virayavanich; Julio Carballido-Gamio; Michael C Nevitt; John Lynch; Charles E McCulloch; Thomas M Link
Journal:  Arthritis Care Res (Hoboken)       Date:  2012-02       Impact factor: 4.794

2.  Baseline mean and heterogeneity of MR cartilage T2 are associated with morphologic degeneration of cartilage, meniscus, and bone marrow over 3 years--data from the Osteoarthritis Initiative.

Authors:  G B Joseph; T Baum; H Alizai; J Carballido-Gamio; L Nardo; W Virayavanich; J A Lynch; M C Nevitt; C E McCulloch; S Majumdar; T M Link
Journal:  Osteoarthritis Cartilage       Date:  2012-04-11       Impact factor: 6.576

3.  Changes in knee cartilage T2 values over 24 months in subjects with and without risk factors for knee osteoarthritis and their association with focal knee lesions at baseline: data from the osteoarthritis initiative.

Authors:  Thomas Baum; Christoph Stehling; Gabby B Joseph; Julio Carballido-Gamio; Benedikt J Schwaiger; Christina Müller-Höcker; Michael C Nevitt; John Lynch; Charles E McCulloch; Thomas M Link
Journal:  J Magn Reson Imaging       Date:  2011-10-10       Impact factor: 4.813

4.  Spatial distribution and temporal progression of T2 relaxation time values in knee cartilage prior to the onset of cartilage lesions - data from the Osteoarthritis Initiative (OAI).

Authors:  M Kretzschmar; M C Nevitt; B J Schwaiger; G B Joseph; C E McCulloch; T M Link
Journal:  Osteoarthritis Cartilage       Date:  2019-02-23       Impact factor: 6.576

Review 5.  Quantitative MRI in the evaluation of articular cartilage health: reproducibility and variability with a focus on T2 mapping.

Authors:  Rachel K Surowiec; Erin P Lucas; Charles P Ho
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2013-10-30       Impact factor: 4.342

6.  Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging.

Authors:  Fang Liu; Zhaoye Zhou; Hyungseok Jang; Alexey Samsonov; Gengyan Zhao; Richard Kijowski
Journal:  Magn Reson Med       Date:  2017-07-21       Impact factor: 4.668

7.  Racial differences in biochemical knee cartilage composition between African-American and Caucasian-American women with 3 T MR-based T2 relaxation time measurements--data from the Osteoarthritis Initiative.

Authors:  A Yu; U Heilmeier; M Kretzschmar; G B Joseph; F Liu; H Liebl; C E McCulloch; M C Nevitt; N E Lane; T M Link
Journal:  Osteoarthritis Cartilage       Date:  2015-04-30       Impact factor: 6.576

8.  Association of trochlear dysplasia with degenerative abnormalities in the knee: data from the Osteoarthritis Initiative.

Authors:  Pia M Jungmann; Seng-Choe Tham; Hans Liebl; Michael C Nevitt; Charles E McCulloch; John Lynch; Thomas M Link
Journal:  Skeletal Radiol       Date:  2013-06-26       Impact factor: 2.199

9.  Conservatively treated knee injury is associated with knee cartilage matrix degeneration measured with MRI-based T2 relaxation times: data from the osteoarthritis initiative.

Authors:  Felix C Hofmann; Jan Neumann; Ursula Heilmeier; Gabby B Joseph; Michael C Nevitt; Charles E McCulloch; Thomas M Link
Journal:  Skeletal Radiol       Date:  2017-08-29       Impact factor: 2.199

10.  Longitudinal analysis of cartilage T2 relaxation times and joint degeneration in African American and Caucasian American women over an observation period of 6 years - data from the Osteoarthritis Initiative.

Authors:  M Kretzschmar; U Heilmeier; A Yu; G B Joseph; F Liu; M Solka; C E McCulloch; M C Nevitt; T M Link
Journal:  Osteoarthritis Cartilage       Date:  2016-03-10       Impact factor: 6.576

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