Literature DB >> 16644245

Reliability of an efficient MRI-based method for estimation of knee cartilage volume using surface registration.

J L Jaremko1, R W T Cheng, R G W Lambert, A F Habib, J L Ronsky.   

Abstract

OBJECTIVE: To aid in detection of osteoarthritis (OA) progression in serial magnetic resonance (MR) scans, we assessed feasibility and accuracy of rapid 3D image registration of the tibial plateau in normal and arthritic subjects, and inter-scan reliability of semi-automated cartilage volume measurement from these images.
DESIGN: Two T1 fat-suppressed knee MR scans were obtained 2 weeks apart in healthy adults (n = 9, age 23-48 years). Four scans of each of three patients with established OA were obtained over 2 years. At baseline, the tibial surface was digitized by semi-automated edge detection and medial tibial plateau cartilage volume was calculated from high-intensity voxels within a manually drawn region of interest (ROI). In subsequent scans, the digitized tibial surface was registered to the baseline location by photogrammetric 3D coordinate transformation, and cartilage volume was automatically recalculated by reuse of the ROI. We measured registration accuracy by root mean square (RMS) distance between registered tibial surfaces.
RESULTS: In normals, RMS distance between tibial surfaces in baseline and subsequent scans was 1/3 voxel length (0.121 mm), and medial tibial plateau cartilage volumes varied by 1.4+/-3.2%. Despite change in cartilage volumes by up to 20% over 2 years in arthritic patients, surface registration accuracy was unaffected (0.122 mm). User-supervised processing time was 15 min at baseline and 7 min in subsequent scans.
CONCLUSION: Tibial surfaces on magnetic resonance imaging (MRI) can be rapidly and accurately co-registered, even in arthritic knees, allowing direct visualization of changes over time. Compared to most current methods, cartilage volume measurement in registered images is faster and has equivalent inter-scan reliability in initially normal subjects.

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Year:  2006        PMID: 16644245     DOI: 10.1016/j.joca.2006.03.004

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


  8 in total

Review 1.  OARSI Clinical Trials Recommendations: Hip imaging in clinical trials in osteoarthritis.

Authors:  G E Gold; F Cicuttini; M D Crema; F Eckstein; A Guermazi; R Kijowski; T M Link; E Maheu; J Martel-Pelletier; C G Miller; J-P Pelletier; C G Peterfy; H G Potter; F W Roemer; D J Hunter
Journal:  Osteoarthritis Cartilage       Date:  2015-05       Impact factor: 6.576

Review 2.  Responsiveness and reliability of MRI in knee osteoarthritis: a meta-analysis of published evidence.

Authors:  D J Hunter; W Zhang; P G Conaghan; K Hirko; L Menashe; W M Reichmann; E Losina
Journal:  Osteoarthritis Cartilage       Date:  2011-03-23       Impact factor: 6.576

3.  Automatic segmentation and quantitative analysis of the articular cartilages from magnetic resonance images of the knee.

Authors:  Jurgen Fripp; Stuart Crozier; Simon K Warfield; Sébastien Ourselin
Journal:  IEEE Trans Med Imaging       Date:  2009-06-10       Impact factor: 10.048

4.  Development of a Rapid Cartilage Damage Quantification Method for the Lateral Tibiofemoral Compartment Using Magnetic Resonance Images: Data from the Osteoarthritis Initiative.

Authors:  Ming Zhang; Jeffrey B Driban; Lori Lyn Price; Grace H Lo; Eric Miller; Timothy E McAlindon
Journal:  Biomed Res Int       Date:  2015-12-02       Impact factor: 3.411

5.  A Coarse-to-Fine Framework for Automated Knee Bone and Cartilage Segmentation Data from the Osteoarthritis Initiative.

Authors:  Yang Deng; Lei You; Yanfei Wang; Xiaobo Zhou
Journal:  J Digit Imaging       Date:  2021-05-24       Impact factor: 4.903

6.  Development of a rapid knee cartilage damage quantification method using magnetic resonance images.

Authors:  Ming Zhang; Jeffrey B Driban; Lori Lyn Price; Daniel Harper; Grace H Lo; Eric Miller; Robert J Ward; Timothy E McAlindon
Journal:  BMC Musculoskelet Disord       Date:  2014-08-06       Impact factor: 2.362

7.  Accuracy of magnetic resonance imaging for measuring maturing cartilage: A phantom study.

Authors:  Jennifer R McKinney; Marshall S Sussman; Rahim Moineddin; Afsaneh Amirabadi; Tammy Rayner; Andrea S Doria
Journal:  Clinics (Sao Paulo)       Date:  2016-07       Impact factor: 2.365

8.  Fully Automatic Knee Bone Detection and Segmentation on Three-Dimensional MRI.

Authors:  Rania Almajalid; Ming Zhang; Juan Shan
Journal:  Diagnostics (Basel)       Date:  2022-01-06
  8 in total

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