Overview: Diffusion MRI (dMRI) fiber tracking is the only imaging method with clinical potential to map fiber pathways in the human brain. Unfortunately, clinical application of dMRI fiber tracking is impeded by a lack of knowledge about the influence of histological features on accurate fiber tracking. Here, we propose to determine the influence of histological features on the dMRI signal through a comparison of dMRI fiber tracking and a new gold-standard 3D histology called CLARITY. Relevance: Improved deep brain stimulation targeting via dMRI fiber tracking has the potential to transform deep brain stimulation procedures by obviating the need for awake surgeries, reducing the number of brain penetrations (and thus reduce patient risk), eliminating imprecise, indirect-targeting methods and helping to expand the scope of neurological conditions that can be treated. Approach: To learn the basic relationships between histological features and dMRI tracking accuracy we propose to compare postmortem dMRI fiber tracking against direct optical observation of individual neurons using a gold-standard CLARITY in the same intact, fixed human brain tissue and then relate these results back to in vivo data. Summary: This proposal aims to define the basic relationships between the dMRI signal and histological features such that dMRI fiber tracking can be accurately applied and interpreted for neurosurgical targeting. Our research team includes world-class experts and inventors of high-resolution postmortem dMRI and CLARITY 3D histology. We have established a strong collaboration across the disparate fields of MRI physics, neuroradiology, neuropathology, neurosurgery, neurology and bioengineering (tissue clearing/optical imaging).

Public Health Relevance

In this grant, we aim to improve the application and interpretation of diffusion MRI fiber tracking for neurosurgical guidance. We will achieve this by determining the influence of specific histological features (fiber pathway diameter, myelination and distance between neighbouring pathways) on the diffusion MRI signal. This proposal specifically focuses on deep brain stimulation targets but will benefit a range of neuro-interventions including targeting for neurosurgical ablations (using lasers or ultra-sound) and planning neurosurgical resections to spare critical fiber pathways.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
1R01NS095985-01A1
Application #
9194248
Study Section
Biomedical Imaging Technology B Study Section (BMIT-B)
Program Officer
Babcock, Debra J
Project Start
2016-07-01
Project End
2019-06-30
Budget Start
2016-07-01
Budget End
2017-06-30
Support Year
1
Fiscal Year
2016
Total Cost
$480,133
Indirect Cost
$171,406
Name
Stanford University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Yang, Grant; Tian, Qiyuan; Leuze, Christoph et al. (2017) Double diffusion encoding MRI for the clinic. Magn Reson Med :
Leuze, Christoph; Aswendt, Markus; Ferenczi, Emily et al. (2017) The separate effects of lipids and proteins on brain MRI contrast revealed through tissue clearing. Neuroimage 156:412-422