Fast and accurate semi-automated segmentation method of spinal cord MR images at 3T applied to the construction of a cervical spinal cord template.

OBJECTIVE: To design a fast and accurate semi-automated segmentation method for spinal cord 3T MR images and to construct a template of the cervical spinal cord. MATERIALS AND METHODS: A semi-automated double threshold-based method (DTbM) was proposed enabling both cross-sectional and volumetric measures from 3D T2-weighted turbo spin echo MR scans of the spinal cord at 3T. Eighty-two healthy subjects, 10 patients with amyotrophic lateral sclerosis, 10 with spinal muscular atrophy and 10 with spinal cord injuries were studied. DTbM was compared with active surface method (ASM), threshold-based method (TbM) and manual outlining (ground truth). Accuracy of segmentations was scored visually by a radiologist in cervical and thoracic cord regions. Accuracy was also quantified at the cervical and thoracic levels as well as at C2 vertebral level. To construct a cervical template from healthy subjects' images (n=59), a standardization pipeline was designed leading to well-centered straight spinal cord images and accurate probability tissue map. RESULTS: Visual scoring showed better performance for DTbM than for ASM. Mean Dice similarity coefficient (DSC) was 95.71% for DTbM and 90.78% for ASM at the cervical level and 94.27% for DTbM and 89.93% for ASM at the thoracic level. Finally, at C2 vertebral level, mean DSC was 97.98% for DTbM compared with 98.02% for TbM and 96.76% for ASM. DTbM showed similar accuracy compared with TbM, but with the advantage of limited manual interaction. CONCLUSION: A semi-automated segmentation method with limited manual intervention was introduced and validated on 3T images, enabling the construction of a cervical spinal cord template.

Validation of a semiautomated spinal cord segmentation method.

PURPOSE: To validate semiautomated spinal cord segmentation in healthy subjects and patients with neurodegenerative diseases and trauma. MATERIALS AND METHODS: Forty-nine healthy subjects, as well as 29 patients with amyotrophic lateral sclerosis, 19 with spinal muscular atrophy, and 14 with spinal cord injuries were studied. Cord area was measured from T2 -weighted 3D turbo spin echo images (cord levels from C2 to T9) using the semiautomated segmentation method of Losseff et al (Brain [1996] 119(Pt 3):701-708), compared with manual segmentation. Reproducibility was evaluated using the inter- and intraobserver coefficient of variation (CoV). Accuracy was assessed using the Dice similarity coefficient (DSC). Robustness to initialization was assessed by simulating modifications to the contours drawn manually prior to segmentation. RESULTS: Mean interobserver CoV was 4.00% for manual segmentation (1.90% for Losseff's method) in the cervical region and 5.62% (respectively 2.19%) in the thoracic region. Mean intraobserver CoV was 2.34% for manual segmentation (1.08% for Losseff's method) in the cervical region and 2.35% (respectively 1.34%) in the thoracic region. DSC was high (0.96) in both cervical and thoracic regions. DSC remained higher than 0.8 even when modifying initial contours by 50%. CONCLUSION: The semiautomated segmentation method showed high reproducibility and accuracy in measuring spinal cord area.