title: Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements.
abstract: Many studies of the human brain have explored the relationship between cortical thickness and cognition, phenotype, or disease. Due to the subjectivity and time requirements in manual measurement of cortical thickness, scientists have relied on robust software tools for automation which facilitate the testing and refinement of neuroscientific hypotheses. The most widely used tool for cortical thickness studies is the publicly available, surface-based FreeSurfer package. Critical to the adoption of such tools is a demonstration of their reproducibility, validity, and the documentation of specific implementations that are robust across large, diverse imaging datasets. To this end, we have developed the automated, volume-based Advanced Normalization Tools (ANTs) cortical thickness pipeline comprising well-vetted components such as SyGN (multivariate template construction), SyN (image registration), N4 (bias correction), Atropos (n-tissue segmentation), and DiReCT (cortical thickness estimation). In this work, we have conducted the largest evaluation of automated cortical thickness measures in publicly available data, comparing FreeSurfer and ANTs measures computed on 1205 images from four open data sets (IXI, MMRR, NKI, and OASIS), with parcellation based on the recently proposed Desikan-Killiany-Tourville (DKT) cortical labeling protocol. We found good scan-rescan repeatability with both FreeSurfer and ANTs measures. Given that such assessments of precision do not necessarily reflect accuracy or an ability to make statistical inferences, we further tested the neurobiological validity of these approaches by evaluating thickness-based prediction of age and gender. ANTs is shown to have a higher predictive performance than FreeSurfer for both of these measures. In promotion of open science, we make all of our scripts, data, and results publicly available which complements the use of open image data sets and the open source availability of the proposed ANTs cortical thickness pipeline.
authors.affiliation: Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA. Electronic address: ntustison@virginia.edu.
authors.forename: Nicholas J
authors.initials: NJ
authors.lastname: Tustison
authors.affiliation: Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Philip A
authors.initials: PA
authors.lastname: Cook
authors.affiliation: Sage Bionetworks, Seattle, WA, USA.
authors.forename: Arno
authors.initials: A
authors.lastname: Klein
authors.affiliation: Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Gang
authors.initials: G
authors.lastname: Song
authors.affiliation: Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Sandhitsu R
authors.initials: SR
authors.lastname: Das
authors.affiliation: Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Jeffrey T
authors.initials: JT
authors.lastname: Duda
authors.affiliation: Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Benjamin M
authors.initials: BM
authors.lastname: Kandel
authors.affiliation: Sage Bionetworks, Seattle, WA, USA; Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway.
authors.forename: Niels
authors.initials: N
authors.lastname: van Strien
authors.affiliation: Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA.
authors.forename: James R
authors.initials: JR
authors.lastname: Stone
authors.affiliation: Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: James C
authors.initials: JC
authors.lastname: Gee
authors.affiliation: Penn Image Computing and Science Laboratory, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Brian B
authors.initials: BB
authors.lastname: Avants
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology; D000465:Algorithms; D002540:Cerebral Cortex / Q000033:anatomy & histology* / Q000254:growth & development; D002648:Child; D002675:Child, Preschool; D016208:Databases, Factual; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012727:Sex Characteristics; D012984:Software; D055815:Young Adult
keywords: Advanced Normalization Tools; Age prediction; Gender prediction; MRI; Open science; Scientific reproducibility