title: Improved DTI registration allows voxel-based analysis that outperforms tract-based spatial statistics.
abstract: Tract-Based Spatial Statistics (TBSS) is a popular software pipeline to coregister sets of diffusion tensor Fractional Anisotropy (FA) images for performing voxel-wise comparisons. It is primarily defined by its skeleton projection step intended to reduce effects of local misregistration. A white matter "skeleton" is computed by morphological thinning of the inter-subject mean FA, and then all voxels are projected to the nearest location on this skeleton. Here we investigate several enhancements to the TBSS pipeline based on recent advances in registration for other modalities, principally based on groupwise registration with the ANTS-SyN algorithm. We validate these enhancements using simulation experiments with synthetically-modified images. When used with these enhancements, we discover that TBSS's skeleton projection step actually reduces algorithm accuracy, as the improved registration leaves fewer errors to warrant correction, and the effects of this projection's compromises become stronger than those of its benefits. In our experiments, our proposed pipeline without skeleton projection is more sensitive for detecting true changes and has greater specificity in resisting false positives from misregistration. We also present comparative results of the proposed and traditional methods, both with and without the skeleton projection step, on three real-life datasets: two comparing differing populations of Alzheimer's disease patients to matched controls, and one comparing progressive supranuclear palsy patients to matched controls. The proposed pipeline produces more plausible results according to each disease's pathophysiology.
authors.affiliation: Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA. Electronic address: schwarz.christopher@mayo.edu.
authors.forename: Christopher G
authors.initials: CG
authors.lastname: Schwarz
authors.affiliation: Department of Information Technology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Robert I
authors.initials: RI
authors.lastname: Reid
authors.affiliation: Department of Information Technology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Jeffrey L
authors.initials: JL
authors.lastname: Gunter
authors.affiliation: Department of Information Technology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Matthew L
authors.initials: ML
authors.lastname: Senjem
authors.affiliation: Department of Health Sciences Research, Division of Biostatistics, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Scott A
authors.initials: SA
authors.lastname: Przybelski
authors.affiliation: Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Samantha M
authors.initials: SM
authors.lastname: Zuk
authors.affiliation: Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Jennifer L
authors.initials: JL
authors.lastname: Whitwell
authors.affiliation: Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Prashanthi
authors.initials: P
authors.lastname: Vemuri
authors.affiliation: Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Keith A
authors.initials: KA
authors.lastname: Josephs
authors.affiliation: Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Kejal
authors.initials: K
authors.lastname: Kantarci
authors.affiliation: Imaging Genetics Center, Institute for Neuroimaging Informatics, USC Keck School of Medicine, Los Angeles, CA, USA; Departments of Neurology, Psychiatry, Radiology, Engineering, and Ophthalmology, USC Keck School of Medicine, Los Angeles, CA, USA.
authors.forename: Paul M
authors.initials: PM
authors.lastname: Thompson
authors.affiliation: Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Ronald C
authors.initials: RC
authors.lastname: Petersen
authors.affiliation: Department of Radiology, Mayo Clinic and Foundation, Rochester, MN, USA.
authors.forename: Clifford R
authors.initials: CR
authors.lastname: Jack
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000544:Alzheimer Disease / Q000473:pathology*; D001921:Brain / Q000473:pathology*; D003627:Data Interpretation, Statistical; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D009413:Nerve Fibers, Myelinated / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D013382:Subtraction Technique; D013494:Supranuclear Palsy, Progressive / Q000473:pathology*
keywords: DTI; Fractional Anisotropy; Registration; TBSS; VBM; Voxel-based analysis