Elizabeth B Hutchinson1,2, Laura D Reyes1,2, Okan Irfanoglu1, Sharon L Juliano3, and Carlo Pierpaoli1
1NIBIB, NIH, Bethesda, MD, United States, 2Henry M. Jackson Foundation, Inc, Bethesda, MD, United States, 3APG, USUHS, Bethesda, MD, United States
Synopsis
An efficient pipeline for the processing and
analysis of diffusion MRI microscopy data has been applied to study neurodevelopmental
abnormaities in a ferret model of Zika infection. Individual and group differences in DTI
values were found using Z-score and Cohen’s D maps to compare Zika treated and
untreated P0 ferret brain specimens. Morphometric
abnormalities were also identified using DTI-driven tensor based morphometry
(DTBM) to show reduced local volume in the developing cortex. These results highlight the utility of this
pipeline and advance the basic understanding of neurodevelopmental
abnormalities that can result from exposure to the Zika virus during gestation.
Introduction
The orchestration of prenatal brain development
is remarkable in organization and complexity and also vulnerable to genetic
mutations and adverse factors of the in-utero
environment. Characterization of anatomic and cellular outcomes in
neurodevelopmental disorders is generally performed in animal models and often
relies on histologic evidence and coarse measurements of length and
weight. Non-invasive imaging can provide
more sophisticated tools for the evaluation of morphometric and microstructural
abnormalities across the whole brain that may improve the understanding of
these disorders. In particular, diffusion tensor MRI (DTI) microscopy can
resolve small anatomic regions such as the cortical proliferation and migration
zones and also is sensitive to features of the microscale tissue environment
that may be altered by abnormal development(1). Furthermore,
the advancement of voxelwise and DTI-driven tensor based morphometry (DTBM)(2)
has enabled streamlined and sophisticated analysis of microstructure and
morphometry across brain specimens. Recently, maternal infection by the Zika
virus has been associated with offspring cerebral microcephaly in humans(3, 4). Although
the mechanisms for this relationship are not yet well understood, studies in
animal models have begun to provide important clues along several lines of
research(5, 6). To extend these findings especially for the
evaluation of cerebral anatomic outcomes, the ferret has been put forward as an
advantageous species as it is well suited for developmental studies by its
folded cortex and the timing of birth relative to gestation(7, 8). In the present study we have optimized and
applied DTI microscopy analysis tools for voxelwise comparison and DTBM to evaluate
the developmental effects of gestational Zika infection on neuroanatomic and
microstructural outcomes in ferret brains.Methods
Ex-vivo brain specimens (n=6) were obtained from
ferret kits at post-natal day 0 from litters for which the ferret jil was
either infected by the Zika virus or not.
The brains were imaged using a Bruker 7T microimaging system to acquire
multi-shell diffusion weighted images (DWIs) with b=100-10,000 and 100 micron
isotropic resolution using a 3DEPI pulse sequence. After DWI corrections and diffusion
tensor(DT) fitting(9, 10), a study-specific template was generated using DTs
from the untreated brains. Then each DT
volume in the study was registered to the template using DT based affine and
non-linear registration(11). A single
brain mask was generated in template space and warped to the native space of
each brain to determine the brain volume.
Voxelwise Z-score and Cohen’s D effect size maps were generated to
compare the treated individual and group values for fractional anisotropy (FA)
and Trace (TR) with the untreated group.
For morphometric analysis, maps of the Log of the Jacobian of the
determinant of the deformation fields (LogJ) were calculated and also used to
generate effect size maps. Results
Whole brain volumes were
significantly reduced in the Zika treated group (Figure 1, p=0.028 by
Mann-Whitney U-test). Increased Trace
values were found in the outermost cortical plate zone of the cortex by for
Cohen’s D maps for group effect size and also for individual Z-score maps
(Figure 2). No consistent effects were
found for FA in these maps (Figure 3).
The most prominent abnormality of this study was decreased local volume
found in the Cohen’s D and individual Z-score maps in the ventricular and
migratory zones of the cortex (Figure 4).
This finding was consistent with histology from the same litters showing
reduced thickness of the subventricular zone (Figure 5).Discussion
The high quality and high spatial resolution of
the acquired DWI data enabled the evaluation of small anatomic regions
including cortical proliferation and migration zones. The advanced registration algorithms used in
this study were able to provide minimally smoothed template maps with clear
tissue boundaries and anatomically faithful registration of brain structures
across specimens in the study. This
combination of high quality DWIs and high quality registration enabled the
bias-free comparison of DTI values in treated and untreated brains ultimately
resulting in novel observations about the regions affted by Zika treatment and
the nature of microstructural and moprphometric outcomes namely increased
diffusivity in the cortical plate and decreased local volume in other cortical
zones. The similarity of Z-score and
Cohen’s D maps in this study imply that the observed abnormalities are
consistent across treated specimens.Conclusion
The results of this study point to specific
neuroanatomic and microstructural abnormalities resulting from Zika virus
treatment during gestation. The methods
of this study comprise an efficient pipeline for acquisition, processing,
registration and voxelwise analysis that uniquely provide combined DTI microscopy
and DTBM analysis in way that is powerful for phenotyping and screening of
neurodevelopmental abnormalities and other brain disorders.Acknowledgements
The authors thank
Mitali Chatterjee, Francis Djankpa, William
G. Valiant, Bernard Dardzinsky and Joseph J. Mattapalli for their contributions to related aspects of this work associated with the study of Zika virus in ferrets. We also thank the section for quanitative imaging and tissue science in the NICHD/NIH for enabling MRI scanning of the specimens.References
1. Huang H, Yamamoto A, Hossain M, Younes
L, & Mori S (2008) Quantitative cortical mapping of fractional anisotropy
in developing rat brains. The Journal of
Neuroscience 28(6):1427-1433.
2. Sadeghi
N, et al. (2018) Tensor-based morphometry
using scalar and directional information of diffusion tensor MRI data (DTBM):
Application to hereditary spastic paraplegia. Hum Brain Mapp.
3. Brasil
P, et al. (2016) Zika virus infection
in pregnant women in Rio de Janeiro. New
England Journal of Medicine 375(24):2321-2334.
4. Moore
CA, et al. (2017) Characterizing the
Pattern of Anomalies in Congenital Zika Syndrome for Pediatric Clinicians. JAMA pediatrics 171(3):288-295.
5. Garcez
PP, et al. (2018) Zika virus impairs
the development of blood vessels in a mouse model of congenital infection. Scientific reports 8(1):12774.
6. Li H,
Saucedo-Cuevas L, Shresta S, & Gleeson JG (2016) The Neurobiology of Zika
Virus. Neuron 92(5):949-958.
7. Empie
K, Rangarajan V, & Juul SE (2015) Is the ferret a suitable species for
studying perinatal brain injury? International
journal of developmental neuroscience : the official journal of the
International Society for Developmental Neuroscience 45:2-10.
8. Poluch
S, Jablonska B, & Juliano SL (2008) Alteration of interneuron migration in
a ferret model of cortical dysplasia. Cerebral
cortex (New York, N.Y. : 1991) 18(1):78-92.
9. Irfanoglu
MO, Nayak A, Jenkins J, & Pierpaoli C (2017) TORTOISE v3: Improvements and
New Features of the NIH Di. 25th Annual
Meeting of the International Society fro Magnetic Resonance in Medicine.
10. Pierpaoli
CW, L.; Irfanoglu, M.; Barnett, A.; Chang, L.-C.; Koay, C.;
Pajevic, S.; Rohde, G.; Sarlls, J.;
Wu, M. (2010) TORTOISE: an integrated software package for processing of
diffusion MRI data. in ISMRM 18th annual
meeting (Stockholm, Sweeden).
11. Irfanoglu
MO, et al. (2016) DR-TAMAS:
Diffeomorphic Registration for Tensor Accurate Alignment of Anatomical
Structures. NeuroImage 132:439-454.