Investigating the tradeoffs between spatial resolution and diffusion sampling for brain mapping with diffusion tractography: time well spent?

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • Calabrese, E; Badea, A; Coe, CL; Lubach, GR; Styner, MA; Johnson, GA

Published Date

  • November 2014

Published In

Volume / Issue

  • 35 / 11

Start / End Page

  • 5667 - 5685

PubMed ID

  • 25044786

Pubmed Central ID

  • PMC4206697

Electronic International Standard Serial Number (EISSN)

  • 1097-0193

Digital Object Identifier (DOI)

  • 10.1002/hbm.22578


  • eng

Conference Location

  • United States