Literature DB >> 24664976

Local area cartilage segmentation: a semiautomated novel method of measuring cartilage loss in knee osteoarthritis.

Jeffrey Duryea, Tannaz Iranpour-Boroujeni, Jamie E Collins, Case Vanwynngaarden, Ali Guermazi, Jeffrey N Katz, Elena Losina, Ruby Russell, Charles Ratzlaff.   

Abstract

OBJECTIVE: To assess the responsiveness and reader time of a novel semiautomated tool to detect knee cartilage loss over 2 years in subjects with knee osteoarthritis.
METHODS: A total of 122 subjects from the Osteoarthritis Initiative progression cohort were selected. A reader used the software method to segment cartilage on double-echo steady-state sequence scans in the medial compartment of the femur from the baseline and 24-month visits. Change in cartilage volume (ΔV) was measured at a fixed weight-bearing (WB) location with respect to the 3-dimensional coordinate system based on cylindrical coordinates. Change was measured for 5 regions of varying WB surface area centered on the fixed point. The average change (ΔV), the SD of ΔV, and the standardized response mean (SRM) are reported.
RESULTS: The SRM was −0.52 for the largest region and decreased in magnitude as smaller regions of cartilage were probed. The average evaluation time was <20 minutes per knee compartment, split approximately evenly between a technician and a trained reader.
CONCLUSION: The results establish that measurement of cartilage loss in a local region can be done efficiently and that the resultant measures are responsive to loss of cartilage over time. The coordinate system can potentially be used to objectively examine and establish a consistent location for all knees that is most responsive to change in cartilage volume. This technique can provide rapidly an objective quantitative measure of cartilage loss and could substantially reduce study costs for large trials and data sets.

Entities:  

Mesh:

Year:  2014        PMID: 24664976      PMCID: PMC4175290          DOI: 10.1002/acr.22332

Source DB:  PubMed          Journal:  Arthritis Care Res (Hoboken)        ISSN: 2151-464X            Impact factor:   4.794


  15 in total

1.  Accuracy and precision of quantitative assessment of cartilage morphology by magnetic resonance imaging at 3.0T.

Authors:  Felix Eckstein; H Cecil Charles; Robert J Buck; Virginia B Kraus; Ann E Remmers; Martin Hudelmaier; Wolfgang Wirth; Jeffrey L Evelhoch
Journal:  Arthritis Rheum       Date:  2005-10

2.  Proposal for a nomenclature for magnetic resonance imaging based measures of articular cartilage in osteoarthritis.

Authors:  F Eckstein; G Ateshian; R Burgkart; D Burstein; F Cicuttini; B Dardzinski; M Gray; T M Link; S Majumdar; T Mosher; C Peterfy; S Totterman; J Waterton; C S Winalski; D Felson
Journal:  Osteoarthritis Cartilage       Date:  2006-05-26       Impact factor: 6.576

3.  Automatic segmentation of the articular cartilage in knee MRI using a hierarchical multi-class classification scheme.

Authors:  Jenny Folkesson; Erik Dam; Ole Fogh Olsen; Paola Pettersen; Claus Christiansen
Journal:  Med Image Comput Comput Assist Interv       Date:  2005

4.  Articular cartilage volume in the knee: semiautomated determination from three-dimensional reformations of MR images.

Authors:  M A Piplani; D G Disler; T R McCauley; T J Holmes; J P Cousins
Journal:  Radiology       Date:  1996-03       Impact factor: 11.105

5.  Novel fast semi-automated software to segment cartilage for knee MR acquisitions.

Authors:  J Duryea; G Neumann; M H Brem; W Koh; F Noorbakhsh; R D Jackson; J Yu; C B Eaton; P Lang
Journal:  Osteoarthritis Cartilage       Date:  2006-12-22       Impact factor: 6.576

Review 6.  Use of novel interactive input devices for segmentation of articular cartilage from magnetic resonance images.

Authors:  E J McWalter; W Wirth; M Siebert; R M O von Eisenhart-Rothe; M Hudelmaier; D R Wilson; F Eckstein
Journal:  Osteoarthritis Cartilage       Date:  2005-01       Impact factor: 6.576

Review 7.  The reliability of a new scoring system for knee osteoarthritis MRI and the validity of bone marrow lesion assessment: BLOKS (Boston Leeds Osteoarthritis Knee Score).

Authors:  D J Hunter; G H Lo; D Gale; A J Grainger; A Guermazi; P G Conaghan
Journal:  Ann Rheum Dis       Date:  2007-05-01       Impact factor: 19.103

8.  Determination of 3D cartilage thickness data from MR imaging: computational method and reproducibility in the living.

Authors:  T Stammberger; F Eckstein; K H Englmeier; M Reiser
Journal:  Magn Reson Med       Date:  1999-03       Impact factor: 4.668

9.  Change in cartilage morphometry: a sample of the progression cohort of the Osteoarthritis Initiative.

Authors:  D J Hunter; J Niu; Y Zhang; S Totterman; J Tamez; C Dabrowski; R Davies; M-P Hellio Le Graverand; M Luchi; Y Tymofyeyev; C R Beals
Journal:  Ann Rheum Dis       Date:  2008-04-13       Impact factor: 19.103

10.  Risk factors associated with the loss of cartilage volume on weight-bearing areas in knee osteoarthritis patients assessed by quantitative magnetic resonance imaging: a longitudinal study.

Authors:  Jean-Pierre Pelletier; Jean-Pierre Raynauld; Marie-Josée Berthiaume; François Abram; Denis Choquette; Boulos Haraoui; John F Beary; Gary A Cline; Joan M Meyer; Johanne Martel-Pelletier
Journal:  Arthritis Res Ther       Date:  2007       Impact factor: 5.156

View more
  8 in total

1.  Quantitative measurement of medial femoral knee cartilage volume - analysis of the OA Biomarkers Consortium FNIH Study cohort.

Authors:  L F Schaefer; M Sury; M Yin; S Jamieson; I Donnell; S E Smith; J A Lynch; M C Nevitt; J Duryea
Journal:  Osteoarthritis Cartilage       Date:  2017-01-30       Impact factor: 6.576

2.  Dual-pathway multi-echo sequence for simultaneous frequency and T2 mapping.

Authors:  Cheng-Chieh Cheng; Chang-Sheng Mei; Jeffrey Duryea; Hsiao-Wen Chung; Tzu-Cheng Chao; Lawrence P Panych; Bruno Madore
Journal:  J Magn Reson       Date:  2016-02-04       Impact factor: 2.229

3.  Quantitative measurement of cartilage volume is possible using two-dimensional magnetic resonance imaging data sets.

Authors:  L F Schaefer; V Nikac; J A Lynch; J Duryea
Journal:  Osteoarthritis Cartilage       Date:  2018-04-25       Impact factor: 6.576

4.  Automatic measurement and visualization of focal femoral cartilage thickness in stress-based regions of interest using three-dimensional knee models.

Authors:  Marios Pitikakis; Andra Chincisan; Nadia Magnenat-Thalmann; Lorenzo Cesario; Patrizia Parascandolo; Loris Vosilla; Gianni Viano
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-07-21       Impact factor: 2.924

5.  Cluster analysis of quantitative MRI T2 and T relaxation times of cartilage identifies differences between healthy and ACL-injured individuals at 3T.

Authors:  U D Monu; C D Jordan; B L Samuelson; B A Hargreaves; G E Gold; E J McWalter
Journal:  Osteoarthritis Cartilage       Date:  2016-10-05       Impact factor: 6.576

6.  Open Source Software for Automatic Subregional Assessment of Knee Cartilage Degradation Using Quantitative T2 Relaxometry and Deep Learning.

Authors:  Kevin A Thomas; Dominik Krzemiński; Łukasz Kidziński; Rohan Paul; Elka B Rubin; Eni Halilaj; Marianne S Black; Akshay Chaudhari; Garry E Gold; Scott L Delp
Journal:  Cartilage       Date:  2021-09-08       Impact factor: 3.117

7.  Integration of accelerated MRI and post-processing software: a promising method for studies of knee osteoarthritis.

Authors:  J Duryea; C Cheng; L F Schaefer; S Smith; B Madore
Journal:  Osteoarthritis Cartilage       Date:  2016-06-11       Impact factor: 6.576

8.  Cartilage Topography Assessment With Local-Area Cartilage Segmentation for Knee Magnetic Resonance Imaging.

Authors:  Alexander Mathiessen; Erin L Ashbeck; Emily Huang; Edward John Bedrick; C Kent Kwoh; Jeffrey Duryea
Journal:  Arthritis Care Res (Hoboken)       Date:  2021-07-05       Impact factor: 5.178

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.