Neuroscience 2003 Abstract
| Presentation Number: | 863.17 |
|---|---|
| Abstract Title: | Effects of aging on automated segmentation of brain MRI. |
| Authors: |
Panzer, V.*1
; VanMeter, J.2
; Stevens, M.1,3
; Beckley, D.
; Wolfson, L.1
1Neurol., Univ. of Connecticut Hlth. Ctr., Farmington, CT 2DC, 263 Farmington Avenue, 06030-1840, 3USA, 263 Farmington Avenue, 06030-1840, |
| Primary Theme and Topics |
Techniques in Neuroscience - Data analysis, physiological methods, statistics |
| Session: |
863. Imaging Methods Poster |
| Presentation Time: | Wednesday, November 12, 2003 8:00 AM-9:00 AM |
| Location: | Morial Convention Center - Hall F-I, Board # VV60 |
| Keywords: |
It is well documented that gray matter (GM) and white matter (WM) volumes decrease with age, while CSF increases. Statistical Parametric Mapping (SPM) is a widely used method for automated segmentation of brain tissue on MRI images. SPM uses a material mixture model of the distribution of image intensities with initial estimates provided by apriori probablility maps. Tissue volumes are expressed relative to Intra-Cranial Cavity Volume (ICCV) to normalize across different sized brains.
Whole brain images of 24 elderly subjects (81.8 +/-6.3 years, 12 men) were acquired with a Siemens 1.5T Magnetom Vision scanner using a 3D MPRAGE sequence (TR/TE1= 11.4s/4.4) with 160-192 sagittal slices yielding 1mm3 voxels. SPM segmentation estimated normalized tissue volume (%ICCV). Individual subject tissue volume results (GM, WM and CSF) and ICCV were correlated with age.
Average tissue volumes were 39.3 GM, 30.0 WM and 30.6 CSF %ICCV, though individual results varied substantially. Visual inspection demonstrated that GM and CSF were often under or over-estimated in these brains, which exhibit typical atrophy. The confidence interval (mean +/- sd) of the mis-estimated class demonstrated overlap with other tissue classes in these scans. Only slight correlation with age was apparent for GM and CSF (r= -0.348 and 0.424), while WM and ICCV showed negligible relation to age (r= -0.197 and 0.213).
The lack of age-related changes in these data is likely the result of spatial normalization to a template based on 152 young subjects and probability maps from similarly young brains. While these elderly individuals do not exhibit evident neuropathology, their non-normal anatomy may limit the applicability of SPM. Accurate tissue classification in aging brains may require a subject-specific, rather than an atlas or probability map based approach.
Whole brain images of 24 elderly subjects (81.8 +/-6.3 years, 12 men) were acquired with a Siemens 1.5T Magnetom Vision scanner using a 3D MPRAGE sequence (TR/TE1= 11.4s/4.4) with 160-192 sagittal slices yielding 1mm3 voxels. SPM segmentation estimated normalized tissue volume (%ICCV). Individual subject tissue volume results (GM, WM and CSF) and ICCV were correlated with age.
Average tissue volumes were 39.3 GM, 30.0 WM and 30.6 CSF %ICCV, though individual results varied substantially. Visual inspection demonstrated that GM and CSF were often under or over-estimated in these brains, which exhibit typical atrophy. The confidence interval (mean +/- sd) of the mis-estimated class demonstrated overlap with other tissue classes in these scans. Only slight correlation with age was apparent for GM and CSF (r= -0.348 and 0.424), while WM and ICCV showed negligible relation to age (r= -0.197 and 0.213).
The lack of age-related changes in these data is likely the result of spatial normalization to a template based on 152 young subjects and probability maps from similarly young brains. While these elderly individuals do not exhibit evident neuropathology, their non-normal anatomy may limit the applicability of SPM. Accurate tissue classification in aging brains may require a subject-specific, rather than an atlas or probability map based approach.
Sample Citation:
[Authors]. [Abstract Title]. Program No. XXX.XX. 2003 Neuroscience Meeting Planner. New Orleans, LA: Society for Neuroscience, 2003. Online.
Copyright © 2003-2025 Society for Neuroscience; all rights reserved. Permission to republish any abstract or part of any abstract in any form must be obtained in writing by SfN office prior to publication.
