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Fully automated segmentation of the cervical cord from T1-weighted MRI using PropSeg: Application to multiple sclerosis

Marios C. Yiannakas, Ahmed M. Mustafa, Benjamin De Leener, Hugh Kearney, Carmen Tur, Daniel R. Altmann, Floriana De Angelis, Domenico Plantone, Olga Ciccarelli, David H. Miller, Julien Cohen-Adad and Claudia Angela M. Gandini Wheeler-Kingshott

Article (2015)

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Spinal cord (SC) atrophy, i.e. a reduction in the SC cross-sectional area (CSA) over time, can be measured by means of image segmentation using magnetic resonance imaging (MRI). However, segmentation methods have been limited by factors relating to reproducibility or sensitivity to change. The purpose of this study was to evaluate a fully automated SC segmentation method (PropSeg), and compare this to a semi-automated active surface (AS) method, in healthy controls (HC) and people with multiple sclerosis (MS). MRI data from 120 people were retrospectively analysed; 26 HC, 21 with clinically isolated syndrome, 26 relapsing remitting MS, 26 primary and 21 secondary progressive MS. MRI data from 40 people returning after one year were also analysed. CSA measurements were obtained within the cervical SC. Reproducibility of the measurements was assessed using the intraclass correlation coefficient (ICC). A comparison between mean CSA changes obtained with the two methods over time was performed using multivariate structural equation regression models. Associations between CSA measures and clinical scores were investigated using linear regression models. Compared to the AS method, the reproducibility of CSA measurements obtained with PropSeg was high, both in patients and in HC, with ICC &gt; 0.98 in all cases. There was no significant difference between PropSeg and AS in terms of detecting change over time. Furthermore, PropSeg provided measures that correlated with physical disability, similar to the AS method. PropSeg is a time-efficient and reliable segmentation method, which requires no manual intervention, and may facilitate large multi-centre neuroprotective trials in progressive MS.

Uncontrolled Keywords

Cord cross-sectional area; Grey matter; Image segmentation; Magnetic resonance imaging; White matter; Adult; Atrophy; Automatic Data Processing; Cervical Cord; Female; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Middle Aged; Multiple Sclerosis; Reproducibility of Results; Retrospective Studies

Subjects: 2500 Electrical and electronic engineering > 2500 Electrical and electronic engineering
Department: Department of Electrical Engineering
Research Center: Other
PolyPublie URL: https://publications.polymtl.ca/3481/
Journal Title: NeuroImage - Clinical (vol. 10)
Publisher: Elsevier
DOI: 10.1016/j.nicl.2015.11.001
Official URL: https://doi.org/10.1016/j.nicl.2015.11.001
Date Deposited: 08 Nov 2018 15:52
Last Modified: 29 Sep 2023 15:32
Cite in APA 7: Yiannakas, M. C., Mustafa, A. M., De Leener, B., Kearney, H., Tur, C., Altmann, D. R., De Angelis, F., Plantone, D., Ciccarelli, O., Miller, D. H., Cohen-Adad, J., & Wheeler-Kingshott, C. A. M. G. (2015). Fully automated segmentation of the cervical cord from T1-weighted MRI using PropSeg: Application to multiple sclerosis. NeuroImage - Clinical, 10, 71-77. https://doi.org/10.1016/j.nicl.2015.11.001


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