A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume
Introduction
Morphometric analysis of brain structure confronts the challenge that head size markedly differs among individuals—a challenge also present in functional data analysis. Measurement of regional volumes, rates of atrophy, and estimated premorbid whole-brain volume require some form of procedure to measure and account for head size variation. Quantities that have been used for this purpose in morphometric analysis include height Bartzokis et al., 2001, Raz et al., 1997, head circumference Graves et al., 1996, Schofield et al., 1997, and MRI-based measurement of the total intracranial volume (TIV; also sometimes called TICV and ICV) Blatter et al., 1995, Edland et al., 2002, Jenkins et al., 2000, Mathalon et al., 1993. The usual assumption, supported by postmortem findings Davis and Wright, 1977, Epstein and Epstein, 1978, is that these measures serve as proxy variables for the premorbid (unatrophied) brain volume. Normalization by head size increases the robustness of expected mophometric effects, for example, gray-matter volume differences in aging (Mathalon et al., 1993). Moreover, as clinical practice moves to routine use of morphometric variables, automated head size measurement and correction will be required to compare individual patients against normative values.
Here we present a fast, automated procedure for head size correction that is validated against manual TIV measurement. The method uses the volume-scaling factor derived by registration of each individual to an atlas template to automatically generate a good estimate of TIV. Atlas normalization, of this form, is also commonly used in functional data analysis. By using atlas-based head size normalization, the same validated procedures derive robust morphometric quantities for structural comparisons as well as normalized images for between-subject and between-group functional data analysis.
Section snippets
Overview
We evaluated automated atlas-based registration as a means of measuring and correcting for variation in head size. Each subject was registered to an atlas-representative template. The template consisted of a merged, averaged image representing the atlas of Talairach and Tournoux (1988). This template was generated from data acquired in 12 young and 12 healthy old adults. The Atlas Scaling Factor (ASF) was computed as the determinant of the affine transform connecting each individual to the
Atlas normalization reduces head size variance and equates head size across the age span
The first set of results concerns the effect of atlas normalization on head size as measured by manual total intracranial volume. Fig. 4 plots the relation between age and total intracranial volume measured in atlas space (TIVatl) and also in native space (TIVnat). The sample consists of the 147 individuals described in Table 2. Several features of atlas normalization are apparent.
First, TIVnat shows a slight age-related volume decrease manifesting as a small, but significant, negative
Discussion
Automated measures of head size using atlas-based transformation are proportional to manual total intracranial volume normalization (r = 0.93) and reliable from 1 day to the next (r = 1.00). Potential bias due to atrophy minimally influenced head size measurement indicating that atlas-based normalization is appropriate for comparisons between populations in studies that seek to quantify global and regional volume differences. The normative values generated by our atlas-based procedure are
Acknowledgements
We thank the Washington University ADRC and the Conte Center for clinical assistance and participant recruitment, Elizabeth Grant, PhD, for database assistance, and Susan Larson, Amy Sanders, Laura Girton, and Glenn Foster for assistance with MRI data collection. This study was supported by NIH grants P50 AG05681, AG03991, the Alzheimer's Association, the James S. McDonnell Foundation, and the Howard Hughes Medical Institute.
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