Intra-Rater and Inter-Rater Reliability of Brain Surface Intensity Model (BSIM)-Based Cortical Thickness Analysis Using T MRI
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Purpose: Brain surface intensity model (BSIM)-based cortical thickness analysis doesnot require complicated 3D segmentation of brain gray/white matters. Instead, thistechnique uses the local intensity profile to compute cortical thickness. The aim ofthe present study was to evaluate intra-rater and inter-rater reliability of BSIMbasedcortical thickness analysis using images from elderly participants. Materials and Methods: Fifteen healthy elderly participants (ages, 55-84 years)were included in this study. High-resolution 3D T1-spoiled gradient recalled-echo(SPGR) images were obtained using 3T MRI. BSIM-based processing steps included aninhomogeneity correction, intensity normalization, skull stripping, atlas registration,extraction of intensity profiles, and calculation of cortical thickness. Processing stepswere automatic, with the exception of semiautomatic skull stripping. Individualcortical thicknesses were compared to a database indicating mean cortical thicknessof healthy adults, in order to produce Z-score thinning maps. Intra-class correlationcoefficients (ICCs) were calculated in order to evaluate inter-rater and intra-raterreliabilities. Results: ICCs for intra-rater reliability were excellent, ranging from 0.751-0.940 inbrain regions except the right occipital, left anterior cingulate, and left and rightcerebellum (ICCs = 0.65-0.741). Although ICCs for inter-rater reliability were fairto excellent in most regions, poor inter-rater correlations were observed for thecingulate and occipital regions. Processing time, including manual skull stripping, was17.07 ± 3.43 min. Z-score maps for all participants indicated that cortical thicknesseswere not significantly different from those in the comparison databases of healthyadults. Conclusion: BSIM-based cortical thickness measurements provide acceptable intraraterand inter-rater reliability. We therefore suggest BSIM-based cortical thicknessanalysis as an adjunct clinical tool to detect cortical atrophy.
Abstract
Purpose: Brain surface intensity model (BSIM)-based cortical thickness analysis doesnot require complicated 3D segmentation of brain gray/white matters. Instead, thistechnique uses the local intensity profile to compute cortical thickness. The aim ofthe present study was to evaluate intra-rater and inter-rater reliability of BSIMbasedcortical thickness analysis using images from elderly participants. Materials and Methods: Fifteen healthy elderly participants (ages, 55-84 years)were included in this study. High-resolution 3D T1-spoiled gradient recalled-echo(SPGR) images were obtained using 3T MRI. BSIM-based processing steps included aninhomogeneity correction, intensity normalization, skull stripping, atlas registration,extraction of intensity profiles, and calculation of cortical thickness. Processing stepswere automatic, with the exception of semiautomatic skull stripping. Individualcortical thicknesses were compared to a database indicating mean cortical thicknessof healthy adults, in order to produce Z-score thinning maps. Intra-class correlationcoefficients (ICCs) were calculated in order to evaluate inter-rater and intra-raterreliabilities. Results: ICCs for intra-rater reliability were excellent, ranging from 0.751-0.940 inbrain regions except the right occipital, left anterior cingulate, and left and rightcerebellum (ICCs = 0.65-0.741). Although ICCs for inter-rater reliability were fairto excellent in most regions, poor inter-rater correlations were observed for thecingulate and occipital regions. Processing time, including manual skull stripping, was17.07 ± 3.43 min. Z-score maps for all participants indicated that cortical thicknesseswere not significantly different from those in the comparison databases of healthyadults. Conclusion: BSIM-based cortical thickness measurements provide acceptable intraraterand inter-rater reliability. We therefore suggest BSIM-based cortical thicknessanalysis as an adjunct clinical tool to detect cortical atrophy.
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