Analysis of diffusion tensor measurements of the human cervical
spinal cord based on semiautomatic segmentation of the white
and gray matter

J 2018

Analysis of diffusion tensor measurements of the human cervical spinal cord based on semiautomatic segmentation of the white and gray matter

DOSTÁL, Marek, Miloš KEŘKOVSKÝ, Eva KORIŤÁKOVÁ, Eva NĚMCOVÁ, Jakub STULÍK et. al.

Basic information

Original name

Analysis of diffusion tensor measurements of the human cervical spinal cord based on semiautomatic segmentation of the white and gray matter

Authors

DOSTÁL, Marek (203 Czech Republic, belonging to the institution), Miloš KEŘKOVSKÝ (203 Czech Republic, guarantor, belonging to the institution), Eva KORIŤÁKOVÁ (203 Czech Republic, belonging to the institution), Eva NĚMCOVÁ (203 Czech Republic), Jakub STULÍK (203 Czech Republic, belonging to the institution), Monika STAŇKOVÁ (203 Czech Republic, belonging to the institution) and Vladan BERNARD (203 Czech Republic, belonging to the institution)

Edition

Journal of Magnetic Resonance Imaging, Hoboken, Wiley, 2018, 1053-1807

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

30224 Radiology, nuclear medicine and medical imaging

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 3.732

RIV identification code

RIV/00216224:14110/18:00106924

Organization unit

Faculty of Medicine

DOI

http://dx.doi.org/10.1002/jmri.26166

UT WoS

000448081300006

Keywords in English

ITK-SNAP; Spinal Cord Toolbox; diffusion tensor imaging; gray and white matter segmentation; spinal cord segmentation

Abstract

V originále

BackgroundPurposeSegmentation of the gray and white matter (GM, WM) of the human spinal cord in MRI images as well as the analysis of spinal cord diffusivity are challenging. When appropriately segmented, diffusion tensor imaging (DTI) of the spinal cord might be beneficial in the diagnosis and prognosis of several diseases. To evaluate the applicability of a semiautomatic algorithm provided by ITK-SNAP in classification mode (CLASS) for segmenting cervical spinal cord GM, WM in MRI images and analyzing DTI parameters. Study TypeSubjectsProspective. Twenty healthy volunteers. SequencesAssessment1.5T, turbo spin echo, fast field echo, single-shot echo planar imaging. Three raters segmented the tissues by manual, CLASS, and atlas-based methods (Spinal Cord Toolbox, SCT) on T-2-weighted and DTI images. Masks were quantified by similarity and distance metrics, then analyzed for repeatability and mutual comparability. Masks created over T-2 images were registered into diffusion space and fractional anisotropy (FA) values were statistically evaluated for dependency on method, rater, or tissue. Statistical TestsResultst-test, analysis of variance (ANOVA), coefficient of variation, Dice coefficient, Hausdorff distance. CLASS segmentation reached better agreement with manual segmentation than did SCT (P<0.001). Intra- and interobserver repeatability of SCT was better for GM and WM (both P<0.001) but comparable with CLASS in entire spinal cord segmentation (P=0.17 and P=0.07, respectively). While FA values of whole spinal cord were not influenced by choice of segmentation method, both semiautomatic methods yielded lower FA values (P<0.005) for GM than did the manual technique (mean differences 0.02 and 0.04 for SCT and CLASS, respectively). Repeatability of FA values for all methods was sufficient, with mostly less than 2% variance.

Links

MUNI/A/1464/2014, interní kód MU

Name: Pokročilé techniky analýzy dat MR zobrazení tenzorů difuze míchy u pacientů s roztroušenou sklerózou

Investor: Masaryk University, Category A

NV15-32133A, research and development project

Name: Predikce konverze klinicky izolovaného syndromu do roztroušené sklerózy pomocí pokročilých technik zobrazení magnetickou rezonancí

Citovat

DOSTÁL, Marek, Miloš KEŘKOVSKÝ, Eva KORIŤÁKOVÁ, Eva NĚMCOVÁ, Jakub STULÍK, Monika STAŇKOVÁ and Vladan BERNARD. Analysis of diffusion tensor measurements of the human cervical spinal cord based on semiautomatic segmentation of the white and gray matter. Journal of Magnetic Resonance Imaging. Hoboken: Wiley, 2018, vol. 48, No 5, p. 1217-1227. ISSN 1053-1807. Available from: https://dx.doi.org/10.1002/jmri.26166.

@article{1419019,
   author = {Dostál, Marek and Keřkovský, Miloš and Koriťáková, Eva and Němcová, Eva and Stulík, Jakub and Staňková, Monika and Bernard, Vladan},
   article_location = {Hoboken},
   article_number = {5},
   doi = {http://dx.doi.org/10.1002/jmri.26166},
   keywords = {ITK-SNAP; Spinal Cord Toolbox; diffusion tensor imaging; gray and white matter segmentation; spinal cord segmentation},
   language = {eng},
   issn = {1053-1807},
   journal = {Journal of Magnetic Resonance Imaging},
   title = {Analysis of diffusion tensor measurements of the human cervical spinal cord based on semiautomatic segmentation of the white and gray matter},
   url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jmri.26166},
   volume = {48},
   year = {2018}
}

TY  - JOUR
ID  - 1419019
AU  - Dostál, Marek - Keřkovský, Miloš - Koriťáková, Eva - Němcová, Eva - Stulík, Jakub - Staňková, Monika - Bernard, Vladan
PY  - 2018
TI  - Analysis of diffusion tensor measurements of the human cervical spinal cord based on semiautomatic segmentation of the white and gray matter
JF  - Journal of Magnetic Resonance Imaging
VL  - 48
IS  - 5
SP  - 1217-1227
EP  - 1217-1227
PB  - Wiley
SN  - 10531807
KW  - ITK-SNAP
KW  - Spinal Cord Toolbox
KW  - diffusion tensor imaging
KW  - gray and white matter segmentation
KW  - spinal cord segmentation
UR  - https://onlinelibrary.wiley.com/doi/abs/10.1002/jmri.26166
N2  - BackgroundPurposeSegmentation of the gray and white matter (GM, WM) of the human spinal cord in MRI images as well as the analysis of spinal cord diffusivity are challenging. When appropriately segmented, diffusion tensor imaging (DTI) of the spinal cord might be beneficial in the diagnosis and prognosis of several diseases. To evaluate the applicability of a semiautomatic algorithm provided by ITK-SNAP in classification mode (CLASS) for segmenting cervical spinal cord GM, WM in MRI images and analyzing DTI parameters. Study TypeSubjectsProspective. Twenty healthy volunteers. SequencesAssessment1.5T, turbo spin echo, fast field echo, single-shot echo planar imaging. Three raters segmented the tissues by manual, CLASS, and atlas-based methods (Spinal Cord Toolbox, SCT) on T-2-weighted and DTI images. Masks were quantified by similarity and distance metrics, then analyzed for repeatability and mutual comparability. Masks created over T-2 images were registered into diffusion space and fractional anisotropy (FA) values were statistically evaluated for dependency on method, rater, or tissue. Statistical TestsResultst-test, analysis of variance (ANOVA), coefficient of variation, Dice coefficient, Hausdorff distance. CLASS segmentation reached better agreement with manual segmentation than did SCT (P<0.001). Intra- and interobserver repeatability of SCT was better for GM and WM (both P<0.001) but comparable with CLASS in entire spinal cord segmentation (P=0.17 and P=0.07, respectively). While FA values of whole spinal cord were not influenced by choice of segmentation method, both semiautomatic methods yielded lower FA values (P<0.005) for GM than did the manual technique (mean differences 0.02 and 0.04 for SCT and CLASS, respectively). Repeatability of FA values for all methods was sufficient, with mostly less than 2% variance.
ER  -

DOSTÁL, Marek, Miloš KEŘKOVSKÝ, Eva KORIŤÁKOVÁ, Eva NĚMCOVÁ, Jakub STULÍK, Monika STAŇKOVÁ and Vladan BERNARD. Analysis of diffusion tensor measurements of the human cervical spinal cord based on semiautomatic segmentation of the white and gray matter. \textit{Journal of Magnetic Resonance Imaging}. Hoboken: Wiley, 2018, vol.~48, No~5, p.~1217-1227. ISSN~1053-1807. Available from: https://dx.doi.org/10.1002/jmri.26166.

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