4.7 Article

Comparison of MR imaging against physical sectioning to estimate the volume of human cerebral compartments

Journal

NEUROIMAGE
Volume 18, Issue 2, Pages 505-516

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/S1053-8119(02)00021-6

Keywords

Cavalieri volume estimator; formalin-fixed specimens; gray matter; MRI; physical sectioning; point counting; stereology; systematic sampling; white matter

Ask authors/readers for more resources

The purpose of this study was to compare magnetic resonance imaging (MRI) against physical sectioning techniques to estimate the volume of human cerebral hemisphere compartments (cortex, subcortex, and their union, called total). The volume of these compartments was estimated postmortem for six human subjects from MRI virtual sections and from physical sections using the Cavalieri design with point counting. Cursory paired I tests revealed no significant differences between the two methods for any of the three compartments considered, although P = 0.06 for the subcortex. A sharper analysis incorporating recent error prediction formulae revealed a significant discrepancy between the two methods in the estimation of subcortex and total volume for three of the specimens. Yet, none of these analyses is adequate to detect possible biases. The incorporation of an explanatory variable, namely hemisphere weight, and the adoption of a specific gravity p = 1.04 g/cm(3) for the material, enabled us to carry out an allometric analysis for the total compartment which revealed a significant bias of the MRI data. The new error prediction formulae are illustrated by way of example, and their accuracy is checked by a resampling experiment on a data set of 274 MRI sections. (C) 2003 Elsevier Science (USA). All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available