Semi-automated segmentation of magnetic resonance images for thigh skeletal muscle and fat using threshold technique after spinal cord injury

Magnetic resonance imaging is considered the “gold standard” technique for quantifying thigh muscle and fat cross-sectional area. We have developed a semi-automated technique to segment seven thigh compartments in persons with spinal cord injury. Thigh magnetic resonance images from 18 men (18–50 ye...

Full description

Bibliographic Details
Main Authors: Mina P Ghatas, Robert M Lester, M Rehan Khan, Ashraf S Gorgey
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2018-01-01
Series:Neural Regeneration Research
Subjects:
Online Access:http://www.nrronline.org/article.asp?issn=1673-5374;year=2018;volume=13;issue=10;spage=1787;epage=1795;aulast=Ghatas
id doaj-e9da80627ed84552a46788d1357a6835
record_format Article
spelling doaj-e9da80627ed84552a46788d1357a68352020-11-25T03:19:01ZengWolters Kluwer Medknow PublicationsNeural Regeneration Research1673-53742018-01-0113101787179510.4103/1673-5374.238623Semi-automated segmentation of magnetic resonance images for thigh skeletal muscle and fat using threshold technique after spinal cord injuryMina P GhatasRobert M LesterM Rehan KhanAshraf S GorgeyMagnetic resonance imaging is considered the “gold standard” technique for quantifying thigh muscle and fat cross-sectional area. We have developed a semi-automated technique to segment seven thigh compartments in persons with spinal cord injury. Thigh magnetic resonance images from 18 men (18–50 years old) with traumatic motor-complete spinal cord injury were analyzed in a blinded fashion using the threshold technique. The cross-sectional area values acquired by thresholding were compared to the manual tracing technique. The percentage errors for thigh circumference were (threshold: 170.71 ± 38.67; manual: 169.45 ± 38.27 cm2) 0.74%, subcutaneous adipose tissue (threshold: 65.99±30.79; manual: 62.68 ± 30.22) 5.2%, whole muscle (threshold: 98.18 ± 20.19; manual: 98.20 ± 20.08 cm2) 0.13%, femoral bone (threshold: 6.53 ± 1.09; manual: 6.53 ± 1.09 cm2) 0.64%, bone marrow fat (threshold: 3.12 ± 1.12; manual: 3.1 ± 1.11 cm2) 0.36%, knee extensor (threshold: 43.98 ± 7.66; manual: 44.61 ± 7.81 cm2) 1.78% and % intramuscular fat (threshold: 10.45 ± 4.29; manual: 10.92 ± 8.35%) 0.47%. Collectively, these results suggest that the threshold technique provided a robust accuracy in measuring the seven main thigh compartments, while greatly reducing the analysis time.http://www.nrronline.org/article.asp?issn=1673-5374;year=2018;volume=13;issue=10;spage=1787;epage=1795;aulast=Ghatasspinal cord injury; magnetic resonance imaging; semi-automated segmentation; subcutaneous adipose tissue; intramuscular fat
collection DOAJ
language English
format Article
sources DOAJ
author Mina P Ghatas
Robert M Lester
M Rehan Khan
Ashraf S Gorgey
spellingShingle Mina P Ghatas
Robert M Lester
M Rehan Khan
Ashraf S Gorgey
Semi-automated segmentation of magnetic resonance images for thigh skeletal muscle and fat using threshold technique after spinal cord injury
Neural Regeneration Research
spinal cord injury; magnetic resonance imaging; semi-automated segmentation; subcutaneous adipose tissue; intramuscular fat
author_facet Mina P Ghatas
Robert M Lester
M Rehan Khan
Ashraf S Gorgey
author_sort Mina P Ghatas
title Semi-automated segmentation of magnetic resonance images for thigh skeletal muscle and fat using threshold technique after spinal cord injury
title_short Semi-automated segmentation of magnetic resonance images for thigh skeletal muscle and fat using threshold technique after spinal cord injury
title_full Semi-automated segmentation of magnetic resonance images for thigh skeletal muscle and fat using threshold technique after spinal cord injury
title_fullStr Semi-automated segmentation of magnetic resonance images for thigh skeletal muscle and fat using threshold technique after spinal cord injury
title_full_unstemmed Semi-automated segmentation of magnetic resonance images for thigh skeletal muscle and fat using threshold technique after spinal cord injury
title_sort semi-automated segmentation of magnetic resonance images for thigh skeletal muscle and fat using threshold technique after spinal cord injury
publisher Wolters Kluwer Medknow Publications
series Neural Regeneration Research
issn 1673-5374
publishDate 2018-01-01
description Magnetic resonance imaging is considered the “gold standard” technique for quantifying thigh muscle and fat cross-sectional area. We have developed a semi-automated technique to segment seven thigh compartments in persons with spinal cord injury. Thigh magnetic resonance images from 18 men (18–50 years old) with traumatic motor-complete spinal cord injury were analyzed in a blinded fashion using the threshold technique. The cross-sectional area values acquired by thresholding were compared to the manual tracing technique. The percentage errors for thigh circumference were (threshold: 170.71 ± 38.67; manual: 169.45 ± 38.27 cm2) 0.74%, subcutaneous adipose tissue (threshold: 65.99±30.79; manual: 62.68 ± 30.22) 5.2%, whole muscle (threshold: 98.18 ± 20.19; manual: 98.20 ± 20.08 cm2) 0.13%, femoral bone (threshold: 6.53 ± 1.09; manual: 6.53 ± 1.09 cm2) 0.64%, bone marrow fat (threshold: 3.12 ± 1.12; manual: 3.1 ± 1.11 cm2) 0.36%, knee extensor (threshold: 43.98 ± 7.66; manual: 44.61 ± 7.81 cm2) 1.78% and % intramuscular fat (threshold: 10.45 ± 4.29; manual: 10.92 ± 8.35%) 0.47%. Collectively, these results suggest that the threshold technique provided a robust accuracy in measuring the seven main thigh compartments, while greatly reducing the analysis time.
topic spinal cord injury; magnetic resonance imaging; semi-automated segmentation; subcutaneous adipose tissue; intramuscular fat
url http://www.nrronline.org/article.asp?issn=1673-5374;year=2018;volume=13;issue=10;spage=1787;epage=1795;aulast=Ghatas
work_keys_str_mv AT minapghatas semiautomatedsegmentationofmagneticresonanceimagesforthighskeletalmuscleandfatusingthresholdtechniqueafterspinalcordinjury
AT robertmlester semiautomatedsegmentationofmagneticresonanceimagesforthighskeletalmuscleandfatusingthresholdtechniqueafterspinalcordinjury
AT mrehankhan semiautomatedsegmentationofmagneticresonanceimagesforthighskeletalmuscleandfatusingthresholdtechniqueafterspinalcordinjury
AT ashrafsgorgey semiautomatedsegmentationofmagneticresonanceimagesforthighskeletalmuscleandfatusingthresholdtechniqueafterspinalcordinjury
_version_ 1724624317888593920