title: Mapping registration sensitivity in MR mouse brain images.
abstract: Nonlinear registration algorithms provide a way to estimate structural (brain) differences based on magnetic resonance images. Their ability to align images of different individuals and across modalities has been well-researched, but the bounds of their sensitivity with respect to the recovery of salient morphological differences between groups are unclear. Here we develop a novel approach to simulate deformations on MR brain images to evaluate the ability of two registration algorithms to extract structural differences corresponding to biologically plausible atrophy and expansion. We show that at a neuroanatomical level registration accuracy is influenced by the size and compactness of structures, but do so differently depending on how much change is simulated. The size of structures has a small influence on the recovered accuracy. There is a trend for larger structures to be recovered more accurately, which becomes only significant as the amount of simulated change is large. More compact structures can be recovered more accurately regardless of the amount of simulated change. Both tested algorithms underestimate the full extent of the simulated atrophy and expansion. Finally we show that when multiple comparisons are corrected for at a voxelwise level, a very low rate of false positives is obtained. More interesting is that true positive rates average around 40%, indicating that the simulated changes are not fully recovered. Simulation experiments were run using two fundamentally different registration algorithms and we identified the same results, suggesting that our findings are generalizable across different classes of nonlinear registration algorithms.
authors.affiliation: Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Ontario, Canada. matthijsvaneede@gmail.com
authors.forename: Matthijs C
authors.initials: MC
authors.lastname: van Eede
authors.forename: Jan
authors.initials: J
authors.lastname: Scholz
authors.forename: M Mallar
authors.initials: MM
authors.lastname: Chakravarty
authors.forename: R Mark
authors.initials: RM
authors.lastname: Henkelman
authors.forename: Jason P
authors.initials: JP
authors.lastname: Lerch
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000033:anatomy & histology*; D001931:Brain Mapping / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL
keywords: Atrophy simulation; Deformation based morphometry; Evaluation; MRI; Mouse brain; Neuroanatomy