BACKGROUND AND PURPOSE: MR-based volumetric measures of cerebral structures are increasingly used for diagnostic purposes and to measure progression of atrophy. Variations in individual head size may be corrected by normalization with use of a total intracranial volume (TIV) measurement. The TIV also may be used to correct for voxel size fluctuations in serial studies. The TIV should be measured from the same images used for structural volumetry, usually T1-weighted imaging. The objectives were to show that normalization with TIV reduces interindividual variation, to develop and validate a simple protocol for measuring TIV from T1-weighted MR images, and to apply TIV normalization to serial brain measures in controls and subjects with Alzheimer disease (AD). METHODS: We measured TIV with a semiautomated segmentation technique on T1- and T2-weighted MR images in 55 controls, 10 AD patients, and two persons at risk of familial AD. Whole-brain volumes also were measured and normalized with TIVs. RESULTS: The TIV normalization of cross-sectional brain volumes significantly reduced interindividual variation; the coefficient of variation (CV) was reduced from 10.0% to 6.0% in controls (P < .001). The TIVs measured on T1-weighted images had low variability (CV, 0.16%) and did not differ significantly from those measured on T2-weighted images (P = .16). The TIV normalization of serial brain-volume measurements reduced interimage differences caused by voxel-scaling variations (CV reduced from 1.3% to 0.5%, P = .002) in 10 controls and five AD patients. CONCLUSION: Structural volumes should be normalized with a TIV, measured cross-sectionally, to reduce interindividual variation, and longitudinally with a concurrent measurement, to reduce subtle interimage differences. This may have important implications in progression studies.
|Original language||English (US)|
|Number of pages||7|
|Journal||American Journal of Neuroradiology|
|State||Published - Sep 27 2001|
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Clinical Neurology