Literature DB >> 12892325

Computer-aided method for quantification of cartilage thickness and volume changes using MRI: validation study using a synthetic model.

Claude Kauffmann1, Pierre Gravel, Benoît Godbout, Alain Gravel, Gilles Beaudoin, Jean-Pierre Raynauld, Johanne Martel-Pelletier, Jean-Pierre Pelletier, Jacques A de Guise.   

Abstract

The primary objective of this study was to develop a computer-aided method for the quantification of three-dimensional (3-D) cartilage changes over time in knees with osteoarthritis (OA). We introduced a local coordinate system (LCS) for the femoral and tibial cartilage boundaries that provides a standardized representation of cartilage geometry, thickness, and volume. The LCS can be registered in different data sets from the same patient so that results can be directly compared. Cartilage boundaries are segmented from 3-D magnetic resonance (MR) slices with a semi-automated method and transformed into offset-maps, defined by the LCS. Volumes and thickness are computed from these offset-maps. Further anatomical labeling allows focal volumes to be evaluated in predefined subregions. The accuracy of the automated behavior of the method was assessed, without any human intervention, using realistic, synthetic 3-D MR images of a human knee. The error in thickness evaluation is lower than 0.12 mm for the tibia and femur. Cartilage volumes in anatomical subregions show a coefficient of variation ranging from 0.11% to 0.32%. This method improves noninvasive 3-D analysis of cartilage thickness and volume and is well suited for in vivo follow-up clinical studies of OA knees.

Entities:  

Mesh:

Year:  2003        PMID: 12892325     DOI: 10.1109/TBME.2003.814539

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  28 in total

1.  Predicting early symptomatic osteoarthritis in the human knee using machine learning classification of magnetic resonance images from the osteoarthritis initiative.

Authors:  Beth G Ashinsky; Mustapha Bouhrara; Christopher E Coletta; Benoit Lehallier; Kenneth L Urish; Ping-Chang Lin; Ilya G Goldberg; Richard G Spencer
Journal:  J Orthop Res       Date:  2017-03-23       Impact factor: 3.494

2.  Intra- and inter-observer reproducibility of volume measurement of knee cartilage segmented from the OAI MR image set using a novel semi-automated segmentation method.

Authors:  K T Bae; H Shim; C Tao; S Chang; J H Wang; R Boudreau; C K Kwoh
Journal:  Osteoarthritis Cartilage       Date:  2009-06-23       Impact factor: 6.576

3.  A fully automated human knee 3D MRI bone segmentation using the ray casting technique.

Authors:  Pierre Dodin; Johanne Martel-Pelletier; Jean-Pierre Pelletier; François Abram
Journal:  Med Biol Eng Comput       Date:  2011-10-29       Impact factor: 2.602

4.  History of knee injury and MRI-assessed knee structures in middle- and older-aged adults: a cross-sectional study.

Authors:  Hussain Ijaz Khan; Dawn Aitken; Leigh Blizzard; Changhai Ding; Jean-Pierre Pelletier; Johanne Martel Pelletier; Flavia Cicuttini; Graeme Jones
Journal:  Clin Rheumatol       Date:  2014-08-14       Impact factor: 2.980

5.  Enabling early detection of osteoarthritis from presymptomatic cartilage texture maps via transport-based learning.

Authors:  Shinjini Kundu; Beth G Ashinsky; Mustapha Bouhrara; Erik B Dam; Shadpour Demehri; Mohammad Shifat-E-Rabbi; Richard G Spencer; Kenneth L Urish; Gustavo K Rohde
Journal:  Proc Natl Acad Sci U S A       Date:  2020-09-21       Impact factor: 11.205

6.  Fully automated system for the quantification of human osteoarthritic knee joint effusion volume using magnetic resonance imaging.

Authors:  Wei Li; François Abram; Jean-Pierre Pelletier; Jean-Pierre Raynauld; Marc Dorais; Marc-André d'Anjou; Johanne Martel-Pelletier
Journal:  Arthritis Res Ther       Date:  2010-09-16       Impact factor: 5.156

7.  Inter-subject comparison of MRI knee cartilage thickness.

Authors:  Julio Carballido-Gamio; Jan S Bauer; Robert Stahl; Keh-Yang Lee; Stefanie Krause; Thomas M Link; Sharmila Majumdar
Journal:  Med Image Anal       Date:  2007-08-31       Impact factor: 8.545

8.  Acetabular cartilage segmentation in CT arthrography based on a bone-normalized probabilistic atlas.

Authors:  Pooneh R Tabrizi; Reza A Zoroofi; Futoshi Yokota; Satoru Tamura; Takashi Nishii; Yoshinobu Sato
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-07-23       Impact factor: 2.924

9.  Multimodal evaluation of tissue-engineered cartilage.

Authors:  Joseph M Mansour; Jean F Welter
Journal:  J Med Biol Eng       Date:  2013-02-01       Impact factor: 1.553

10.  Meniscal tear and extrusion are strongly associated with progression of symptomatic knee osteoarthritis as assessed by quantitative magnetic resonance imaging.

Authors:  M-J Berthiaume; J-P Raynauld; J Martel-Pelletier; F Labonté; G Beaudoin; D A Bloch; D Choquette; B Haraoui; R D Altman; M Hochberg; J M Meyer; G A Cline; J-P Pelletier
Journal:  Ann Rheum Dis       Date:  2004-09-16       Impact factor: 19.103

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