Literature DB >> 11358663

Measuring extraocular muscle volume using dynamic contours.

M J Firbank1, R M Harrison, E D Williams, A Coulthard.   

Abstract

The effect of medical treatment on extraocular muscle enlargement in thyroid associated ophthalmopathy (TAO) may be monitored by measuring the change in volume of the extraocular muscles on serial orbital MRI examinations. In theory, 3D image sets offer the opportunity to minimise errors due to poor repositioning and partial volume effects. This study describes an automated technique for estimating extraocular muscle volumes from 3D datasets. Operator input is minimal and the technique is robust. Verification of the technique on both simulated and real datasets is described. For simulated image sets, both automated segmentation and manual outlining produced estimates of volume which were on average 4% less than "true" volume. For real patient data, extraocular muscle volumes measured by the automated technique were 1.6% (SD 13%) less than volumes measured by manual outlining. Coefficient of variation for repeat outlining of the same image dataset for the automated technique was 1.0%, compared with 4% for manual outlining. The manual technique took an experienced operator approximately 20 min to perform, compared to 7 min for the automated technique. The automated method is therefore rapid, reproducible and at least as accurate as other available methods.

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Year:  2001        PMID: 11358663     DOI: 10.1016/s0730-725x(01)00234-x

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  5 in total

Review 1.  Differential involvement of orbital fat and extraocular muscles in graves' ophthalmopathy.

Authors:  Wilmar M Wiersinga; Noortje I Regensburg; Maarten P Mourits
Journal:  Eur Thyroid J       Date:  2013-02-26

2.  Graves' ophthalmopathy: the role of diffusion-weighted imaging in detecting involvement of extraocular muscles in early period of disease.

Authors:  R Kilicarslan; A Alkan; M M Ilhan; H Yetis; A Aralasmak; E Tasan
Journal:  Br J Radiol       Date:  2014-12-19       Impact factor: 3.039

3.  Semantic Segmentation of Extraocular Muscles on Computed Tomography Images Using Convolutional Neural Networks.

Authors:  Ramkumar Rajabathar Babu Jai Shanker; Michael H Zhang; Daniel T Ginat
Journal:  Diagnostics (Basel)       Date:  2022-06-26

4.  Correlation between Extraocular Muscle Size Measured by Computed Tomography and the Vertical Angle of Deviation in Thyroid Eye Disease.

Authors:  Ju-Yeun Lee; Kunho Bae; Kyung-Ah Park; In Jeong Lyu; Sei Yeul Oh
Journal:  PLoS One       Date:  2016-01-28       Impact factor: 3.240

5.  Extraocular muscle sampled volume in Graves' orbitopathy using 3-T fast spin-echo MRI with iterative decomposition of water and fat sequences.

Authors:  Ludovico M Garau; Daniele Guerrieri; Flaminia De Cristofaro; Alice Bruscolini; Giuseppe Panzironi
Journal:  Acta Radiol Open       Date:  2018-06-25
  5 in total

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