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Author Notes:

Longchuan Li, PhD, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, Email: longchuan.li@emory.edu

Xiaodong Zhang, PhD, Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University Atlanta, GA, Email: xzchang8@emory.edu

X Zhang, C Li, Y Yan, L Li, G Nair: Investigation, data processing and analysis, experimental design; T Preuss, J Herndon, J Rilling, X Hu: conceptualization, methodology, editing, funding acquisition; X Zhang, L Li: writing.

The authors thank the vet team of Yerkes Imaging Center and the Animal Resources of Yerkes National Primate Research Center for animal care during MRI data collection.

The authors declare that they have no conflict of interest.

Subjects:

Research Funding:

This project was supported in part by P01 AG026423-02 (Herndon) and National Center for Research Resources (NCRR) and currently by the Office of Research Infrastructure Programs of the National Institutes of Health (NIH) (P51RR000165 and OD P51OD011132). L. Li is supported by R01EB027147, R01MH119251, P50MH100029, R01MH118285 and R01MH118534.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Radiology, Nuclear Medicine & Medical Imaging
  • DTI
  • Fiber tracking
  • Distortion correction
  • Optic nerve
  • Non-human primate
  • Large animals
  • Aging
  • WHITE-MATTER INTEGRITY
  • CEREBRAL-BLOOD-FLOW
  • AGE-RELATED DECLINE
  • ECHO-PLANAR IMAGES
  • NONHUMAN-PRIMATES
  • RHESUS-MONKEY
  • RADIAL DIFFUSIVITY
  • COGNITIVE DECLINE
  • IMAGING DETECTS
  • TENSOR

In-vivo diffusion MRI protocol optimization for the chimpanzee brain and examination of aging effects on the primate optic nerve at 3T

Tools:

Journal Title:

MAGNETIC RESONANCE IMAGING

Volume:

Volume 77

Publisher:

, Pages 194-203

Type of Work:

Article | Post-print: After Peer Review

Abstract:

Background: Diffusion MRI (dMRI) data acquisition protocols are well-established on modern high-field clinical scanners for human studies. However, these protocols are not suitable for the chimpanzee (or other large-brained mammals) because of its substantial difference in head geometry and brain volume compared with humans. Therefore, an optimal dMRI data acquisition protocol dedicated to chimpanzee neuroimaging is needed. Methods: A multi-shot (4 segments) double spin-echo echo-planar imaging (MS-EPI) sequence and a single-shot double spin-echo EPI (SS-EPI) sequence were optimized separately for in vivo dMRI data acquisition of chimpanzees using a clinical 3T scanner. Correction for severe susceptibility-induced image distortion and signal drop-off of the chimpanzee brain was performed and evaluated using FSL software. DTI indices in different brain regions and probabilistic tractography were compared. A separate DTI data set from n=34 chimpanzees (13 to 56 years old) was collected using the optimal protocol. Age-related changes in diffusivity indices of optic nerve fibers were evaluated. Results: The SS-EPI sequence acquired dMRI data of the chimpanzee brain with approximately doubled the SNR as the MS-EPI sequence given the same scan time. The quality of white matter fiber tracking from the SS-EPI data was much higher than that from MS-EPI data. However, quantitative analysis of DTI indices showed no difference in most ROIs between the SS-EPI and MS-EPI sequences. The progressive evolution of diffusivity indices of optic nerves indicated mild changes in fiber bundles of chimpanzees aged 40 years and above. Conclusion: The single-shot EPI-based acquisition protocol provided better image quality of dMRI for chimpanzee brains and is recommended for in vivo dMRI study or clinical diagnosis of chimpanzees (or other large animals) using a clinical scanner. Also, the tendency of FA decrease or diffusivity increase in the optic nerve of aged chimpanzees was seen but did not show significant age-related changes, suggesting aging may have less impact on optic nerve fiber integrity of chimpanzees, in contrast to previous results for both macaque monkeys and humans.

Copyright information:

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/rdf).
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