Intra- and interscanner variability of automated voxel-based volumetry based on a 3D probabilistic atlas of human cerebral structures.
Neuroimage 2009;
49:2216-24. [PMID:
19878722 DOI:
10.1016/j.neuroimage.2009.10.066]
[Citation(s) in RCA: 108] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2009] [Revised: 10/01/2009] [Accepted: 10/22/2009] [Indexed: 11/22/2022] Open
Abstract
The intra- and inter-scanner variability of an automated method for MRI-based volumetry was investigated. Using SPM5 algorithms and predefined masks derived from a probabilistic whole-brain atlas, this method allows to determine the volumes of various brain structures (e.g., hemispheres, lobes, cerebellum, basal ganglia, grey and white matter etc.) in single subjects in an observer-independent fashion. A healthy volunteer was scanned three times at six different MRI scanners (including different vendors and field strengths) to calculate intra- and inter-scanner volumetric coefficients of variation (CV). The mean intra-scanner CV values per brain structure ranged from 0.50% to 4.4% (median, 0.89%), while the inter-scanner CV results varied between 0.66% and 14.7% (median, 4.74%). The overall (=combined intra- and inter-scanner) variability of measurements was only marginally higher, with CV results of 0.87-15.1% (median, 4.80%). Furthermore, the minimum percentage volume difference for detecting a significant volume change between two volume measurements in the same subject was calculated for each substructure. For example, for the total brain volume, mean intra-scanner, inter-scanner, and overall CV results were 0.50%, 3.78%, and 3.80%, respectively, and the cut-offs for significant volume changes between two measurements in the same subject amounted to 1.4% for measurements on the same scanner and 10.5% on different scanners. These findings may be useful for planning and assessing volumetric studies in neurological diseases, for the differentiation of certain patterns of atrophy, or for longitudinal studies monitoring the course of a disease and potential therapeutic effects.
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