title: Reproducibility and Bias in Healthy Brain Segmentation: Comparison of Two Popular Neuroimaging Platforms.
abstract: We evaluated and compared the performance of two popular neuroimaging processing platforms: Statistical Parametric Mapping (SPM) and FMRIB Software Library (FSL). We focused on comparing brain segmentations using Kirby21, a magnetic resonance imaging (MRI) replication study with 21 subjects and two scans per subject conducted only a few hours apart. We tested within- and between-platform segmentation reliability both at the whole brain and in 10 regions of interest (ROIs). For a range of fixed probability thresholds we found no differences between-scans within-platform, but large differences between-platforms. We have also found very large differences between- and within-platforms when probability thresholds were changed. A randomized blinded reader study indicated that: (1) SPM and FSL performed well in terms of gray matter segmentation; (2) SPM and FSL performed poorly in terms of white matter segmentation; and (3) FSL slightly outperformed SPM in terms of CSF segmentation. We also found that tissue class probability thresholds can have profound effects on segmentation results. We conclude that the reproducibility of neuroimaging studies depends on the neuroimaging software-processing platform and tissue probability thresholds. Our results suggest that probability thresholds may not be comparable across platforms and consistency of results may be improved by estimating a probability threshold correspondence function between SPM and FSL.
authors.affiliation: Department of Internal Medicine, University of PittsburghPittsburgh, PA, USA; Department of Biostatistics, University of PittsburghPittsburgh, PA, USA; Department of Psychiatry, University of PittsburghPittsburgh, PA, USA.
authors.forename: Dana L
authors.initials: DL
authors.lastname: Tudorascu
authors.affiliation: Department of Biomedical Engineering, University of Pittsburgh Pittsburgh, PA, USA.
authors.forename: Helmet T
authors.initials: HT
authors.lastname: Karim
authors.affiliation: Biostatistics Program, Louisiana State University Health Sciences Center New Orleans, LA, USA.
authors.forename: Jacob M
authors.initials: JM
authors.lastname: Maronge
authors.affiliation: Department of Neuroradiology, Barrow Neurological Institute Phoenix, AZ, USA.
authors.forename: Lea
authors.initials: L
authors.lastname: Alhilali
authors.affiliation: Department of Radiology, Banner Health and Hospital Systems Mesa, AZ, USA.
authors.forename: Saeed
authors.initials: S
authors.lastname: Fakhran
authors.affiliation: Department of Psychiatry, University of PittsburghPittsburgh, PA, USA; Department of Biomedical Engineering, University of PittsburghPittsburgh, PA, USA.
authors.forename: Howard J
authors.initials: HJ
authors.lastname: Aizenstein
authors.affiliation: Department of Biostatistics, Bloomberg School of Public Health, John Hopkins University Baltimore, MD, USA.
authors.forename: John
authors.initials: J
authors.lastname: Muschelli
authors.affiliation: Department of Biostatistics, Bloomberg School of Public Health, John Hopkins University Baltimore, MD, USA.
authors.forename: Ciprian M
authors.initials: CM
authors.lastname: Crainiceanu
keywords: MRI reproducibility; healthy brain segmentation; segmentation bias