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Optimizing parameter choice for FSL-Brain Extraction Tool (BET) on 3D T1 images in multiple sclerosis

Authors
Journal
NeuroImage
1053-8119
Publisher
Elsevier
Publication Date
Volume
61
Issue
4
Identifiers
DOI: 10.1016/j.neuroimage.2012.03.074
Keywords
  • Brain Extraction
  • Fsl
  • Bet
  • Segmentation
  • Mri
  • Multiple Sclerosis

Abstract

Abstract Background Brain atrophy studies often use FSL-BET (Brain Extraction Tool) as the first step of image processing. Default BET does not always give satisfactory results on 3DT1 MR images, which negatively impacts atrophy measurements. Finding the right alternative BET settings can be a difficult and time-consuming task, which can introduce unwanted variability. Aim To systematically analyze the performance of BET in images of MS patients by varying its parameters and options combinations, and quantitatively comparing its results to a manual gold standard. Methods Images from 159 MS patients were selected from different MAGNIMS consortium centers, and 16 different 3DT1 acquisition protocols at 1.5T or 3T. Before running BET, one of three pre-processing pipelines was applied: (1) no pre-processing, (2) removal of neck slices, or (3) additional N3 inhomogeneity correction. Then BET was applied, systematically varying the fractional intensity threshold (the “f” parameter) and with either one of the main BET options (“B” — bias field correction and neck cleanup, “R” — robust brain center estimation, or “S” — eye and optic nerve cleanup) or none. For comparison, intracranial cavity masks were manually created for all image volumes. FSL-FAST (FMRIB's Automated Segmentation Tool) tissue-type segmentation was run on all BET output images and on the image volumes masked with the manual intracranial cavity masks (thus creating the gold-standard tissue masks). The resulting brain tissue masks were quantitatively compared to the gold standard using Dice overlap coefficient (DOC). Normalized brain volumes (NBV) were calculated with SIENAX. NBV values obtained using for SIENAX other BET settings than default were compared to gold standard NBV with the paired t-test. Results The parameter/preprocessing/options combinations resulted in 20,988 BET runs. The median DOC for default BET (f=0.5, g=0) was 0.913 (range 0.321–0.977) across all 159 native scans. For all acquisition protocols, brain extraction was substantially improved for lower values of “f” than the default value. Using native images, optimum BET performance was observed for f=0.2 with option “B”, giving median DOC=0.979 (range 0.867–0.994). Using neck removal before BET, optimum BET performance was observed for f=0.1 with option “B”, giving median DOC 0.983 (range 0.844–0.996). Using the above BET-options for SIENAX instead of default, the NBV values obtained from images after neck removal with f=0.1 and option “B” did not differ statistically from NBV values obtained with gold-standard. Conclusion Although default BET performs reasonably well on most 3DT1 images of MS patients, the performance can be improved substantially. The removal of the neck slices, either externally or within BET, has a marked positive effect on the brain extraction quality. BET option “B” with f=0.1 after removal of the neck slices seems to work best for all acquisition protocols.

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