title: Investigating the tradeoffs between spatial resolution and diffusion sampling for brain mapping with diffusion tractography: time well spent?
abstract: Interest in mapping white matter pathways in the brain has peaked with the recognition that altered brain connectivity may contribute to a variety of neurologic and psychiatric diseases. Diffusion tractography has emerged as a popular method for postmortem brain mapping initiatives, including the ex-vivo component of the human connectome project, yet it remains unclear to what extent computer-generated tracks fully reflect the actual underlying anatomy. Of particular concern is the fact that diffusion tractography results vary widely depending on the choice of acquisition protocol. The two major acquisition variables that consume scan time, spatial resolution, and diffusion sampling, can each have profound effects on the resulting tractography. In this analysis, we determined the effects of the temporal tradeoff between spatial resolution and diffusion sampling on tractography in the ex-vivo rhesus macaque brain, a close primate model for the human brain. We used the wealth of autoradiography-based connectivity data available for the rhesus macaque brain to assess the anatomic accuracy of six time-matched diffusion acquisition protocols with varying balance between spatial and diffusion sampling. We show that tractography results vary greatly, even when the subject and the total acquisition time are held constant. Further, we found that focusing on either spatial resolution or diffusion sampling at the expense of the other is counterproductive. A balanced consideration of both sampling domains produces the most anatomically accurate and consistent results.
authors.affiliation: Department of Radiology, Center for In Vivo Microscopy, Duke University Medical Center, Durham, North Carolina; Department of Biomedical Engineering, Duke University, Durham, North Carolina.
authors.forename: Evan
authors.initials: E
authors.lastname: Calabrese
authors.forename: Alexandra
authors.initials: A
authors.lastname: Badea
authors.forename: Christopher L
authors.initials: CL
authors.lastname: Coe
authors.forename: Gabriele R
authors.initials: GR
authors.lastname: Lubach
authors.forename: Martin A
authors.initials: MA
authors.lastname: Styner
authors.forename: G Allan
authors.initials: GA
authors.lastname: Johnson
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000033:anatomy & histology*; D001931:Brain Mapping; D003198:Computer Simulation; D056324:Diffusion Tensor Imaging; D007091:Image Processing, Computer-Assisted; D008253:Macaca mulatta; D008959:Models, Neurological; D009434:Neural Pathways / Q000033:anatomy & histology* / Q000502:physiology; D066127:White Matter / Q000033:anatomy & histology*
keywords: Macaca mulatta; connectome; diffusion magnetic resonance imaging; diffusion tensor imaging; neuroanatomy