Comparison of MR imaging against physical sectioning to estimate the volume of human cerebral compartments
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 hu...
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| Veröffentlicht in: | NeuroImage (Orlando, Fla.) Fla.), 2003-02, Vol.18 (2), p.505-516 |
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| creator | García-Fiñana, Marta Cruz-Orive, Luis M. Mackay, Clare E. Pakkenberg, Bente Roberts, Neil |
| description | 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
t 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 ρ = 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. |
| doi_str_mv | 10.1016/S1053-8119(02)00021-6 |
| format | Article |
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t 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 ρ = 1.04 g/cm
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t 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 ρ = 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. 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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
t 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 ρ = 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.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>12595203</pmid><doi>10.1016/S1053-8119(02)00021-6</doi><tpages>12</tpages></addata></record> |
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| subjects | Aged Biomedical research Brain Cavalieri volume estimator Cerebral Cortex - anatomy & histology Dominance, Cerebral - physiology Female Formalin-fixed specimens Gray matter Humans Image Processing, Computer-Assisted Imaging, Three-Dimensional Magnetic Resonance Imaging Male Methods Middle Aged MRI Numerical Analysis, Computer-Assisted Physical sectioning Point counting Reference Values Sensitivity and Specificity Software Stereology Studies Systematic sampling White matter |
| title | Comparison of MR imaging against physical sectioning to estimate the volume of human cerebral compartments |
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