Faculty Collaboration Database

Morphology and morphometry of human chronic spinal cord injury using diffusion tensor imaging and fuzzy logic. Ann Biomed Eng 2008 Feb;36(2):224-36

Date

12/11/2007

Pubmed ID

18066663

DOI

10.1007/s10439-007-9415-6

Scopus ID

2-s2.0-38349125426 (requires institutional sign-in at Scopus site)   37 Citations

Abstract

Diffusion tensor imaging (DTI) was performed on regions rostral to the injury site in four human subjects with chronic spinal cord injury (SCI) and equivalent regions in four neurologically intact subjects. Apparent diffusion coefficients were measured and compared between subjects. A fuzzy logic tissue classification algorithm was used to segment gray and white matter regions for morphometric analysis, including comparisons of cross-sectional areas of gray and white matter along with frontal and sagittal diameters. Results indicated a general decrease in both longitudinal and transverse diffusivity in the upper cervical segments of subjects with chronic SCI. Further, a decrease in the cross-sectional area of the entire spinal cord was observed in subjects with SCI, consistent with severe atrophy of the spinal cord. These observations have implications in tracking the progression of SCI from the acute to the chronic stages. We conclude that DTI with fuzzy logic tissue classification has potential for monitoring morphological changes in the spinal cord in people with SCI.

Author List

Ellingson BM, Ulmer JL, Schmit BD

Author

Brian Schmit PhD Professor in the Biomedical Engineering department at Marquette University

MESH terms used to index this publication - Major topics in bold

Adult
Aged
Anatomy, Cross-Sectional
Diffusion Magnetic Resonance Imaging
Female
Fuzzy Logic
Humans
Image Interpretation, Computer-Assisted
Male
Middle Aged
Nerve Fibers, Myelinated
Neural Pathways
Neurons
Pattern Recognition, Automated
Spinal Cord
Spinal Cord Injuries