Literature DB >> 32458188

Layer-specific analysis of femorotibial cartilage t2 relaxation time based on registration of segmented double echo steady state (dess) to multi-echo-spin-echo (mese) images.

David Fürst1,2,3, Wolfang Wirth4,5,6, Akshay Chaudhari7, Felix Eckstein4,5,6.   

Abstract

OBJECTIVE: To develop and validate a 3D registration approach by which double echo steady state (DESS) MR images with cartilage thickness segmentations are used to extract the cartilage transverse relaxation time (T2) from multi-echo-spin-echo (MESE) MR images, without direct segmentations for MESE.
MATERIALS AND METHODS: Manual DESS segmentations of 89 healthy reference knees (healthy) and 60 knees with early radiographic osteoarthritis (early ROA) from the Osteoarthritis Initiative were registered to corresponding MESE images that had independent direct T2 segmentations. For validation purposes, (a) regression analysis of deep and superficial cartilage T2 was performed and (b) between-group differences between healthy vs. early ROA knees were compared for registered vs. direct MESE analysis.
RESULTS: Moderate to high correlations were observed for the deep (r = 0.80) and the superficial T2 (r = 0.81), with statistically significant between-group differences (ROA vs. healthy) of + 1.4 ms (p = 0.002) vs. + 1.3 ms (p < 0.001) for registered vs. direct T2 segmentation in the deep, and + 1.3 ms (p = 0.002) vs. + 2.3 ms (p < 0.001) in the superficial layer. DISCUSSION: This registration approach enables extracting cartilage T2 from MESE scans using DESS (cartilage thickness) segmentations, avoiding the need for direct MESE T2 segmentations.

Entities:  

Keywords:  Cartilage; Magnetic resonance imaging; Registration; T2 relaxation

Year:  2020        PMID: 32458188     DOI: 10.1007/s10334-020-00852-6

Source DB:  PubMed          Journal:  MAGMA        ISSN: 0968-5243            Impact factor:   2.310


  7 in total

Review 1.  Rapid Knee MRI Acquisition and Analysis Techniques for Imaging Osteoarthritis.

Authors:  Akshay S Chaudhari; Feliks Kogan; Valentina Pedoia; Sharmila Majumdar; Garry E Gold; Brian A Hargreaves
Journal:  J Magn Reson Imaging       Date:  2019-11-21       Impact factor: 4.813

2.  Image registration.

Authors:  Joaien P W Pluim; J Michael Fitzpatrick
Journal:  IEEE Trans Med Imaging       Date:  2003-11       Impact factor: 10.048

3.  Automatic segmentation of the bone and extraction of the bone-cartilage interface from magnetic resonance images of the knee.

Authors:  Jurgen Fripp; Stuart Crozier; Simon K Warfield; Sébastien Ourselin
Journal:  Phys Med Biol       Date:  2007-02-27       Impact factor: 3.609

4.  Automatic atlas-based three-label cartilage segmentation from MR knee images.

Authors:  Liang Shan; Christopher Zach; Cecil Charles; Marc Niethammer
Journal:  Med Image Anal       Date:  2014-06-28       Impact factor: 8.545

5.  Computed tomography-guided catheter drainage with ozone in management of pyogenic liver abscess.

Authors:  Xiao-Xue Xu; Chuan Liu; Lang Wang; Yang Li; Han-Feng Yang; Yong Du; Chuan Zhang; Bing Li
Journal:  Pol J Radiol       Date:  2018-06-12

6.  Time-saving opportunities in knee osteoarthritis: T2 mapping and structural imaging of the knee using a single 5-min MRI scan.

Authors:  Susanne M Eijgenraam; Akshay S Chaudhari; Max Reijman; Sita M A Bierma-Zeinstra; Brian A Hargreaves; Jos Runhaar; Frank W J Heijboer; Garry E Gold; Edwin H G Oei
Journal:  Eur Radiol       Date:  2019-12-16       Impact factor: 5.315

  7 in total
  1 in total

1.  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

  1 in total

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