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Evan Calabrese, PhD candidate-Biomedical Engineering, and MSTP MD candidate (with A Badea, J Lee, BS Kwon, GA Johnson)

MR histology atlas of the developing rat brain

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SUMMARY: The increase in neurodevelopmental disorders like autism and attention deficit hyperactivity disorder (ADHD) has motivated scientists to investigate brain pathology using rat models and high-resolution MR microscopy (MRM) vs. conventional histology. A major barrier to effective use of MRM to study neurodevelopmental diseases is the lack of a high-quality MRM reference atlas of the developing rat brain—the goal of this work. See figures below for results of this study.

METHODS: (for detail, see Jiang /Johnson, 2011)

  • Ex-vivo imaging on a 7T small animal MRI system with 670 mT/m gradient coils
  • Specimens were actively stained using (formalin / ProHance)
  • Diffusion tensor imaging (DTI) data were acquired (spin-echo diffusion weighted pulse sequence)
  • Anatomic images were acquired with a 3D gradient recalled echo (GRE) sequence
  • Isotropic voxel size of 50 μm3 and 25 μm3 for GRE data
  • Acquisition time 20-50 hours, depending on specimen size
Coronal gradient recalled echo (GRE) images from each of the 9 atlas time-points. Each image is an average of 5 animals, with the image plane is through the anterior-most aspect of the hippocampus. 6 different images, all at the same coronal level demonstrate how the different acquisiton and post-processing strategies highlight different anatomical regions. (a) GRE image; (b) RF refocused spin echo (b=0 mm/ sec2); (c) Apparent Diffusion Coefficient (ADC) image; (d) Radial Diffusity (RD) image; (e) Fractional anisotropy (FA) image; (f) color FA image.

Volume rendering of a selection of 12 3D labels from a post-natal day 40 rat brain. (Not all available labels are listed.)

DTI data can be used to extract fiber connectivity between regions.

(a) Tractography volume of the whole brain showing 3% of fibers detected.

(b) Fiber tracts in specific structures (anterior commissure shown here) can be isolated.

(c) Magnified view of tractography data in the anterior commissure demonstrates the exquisite spatial resolution of these data.


RESULTS:

  • Atlas consists of image data from 5 animals, each at 9 time-points from birth to adulthood (post-natal days [PND] 0, 2, 4, 8, 12, 18, 24, 40, 80) for 45 total specimens
  • Each dataset consists of 7 different MRI contrasts plus 3D tractography
  • All image data have been segmented in to 20 ontologically-defined 3D structures that cover the entire rat brain
  • Labels have been used to extract structure volumes and local DTI metrics throughout neurodevelopment
REFERENCES: - see these references for background and more information about this work

- Calabrese E, Johnson GA, Watson C, An ontology-based segmentation scheme for tracking postnatal changes in the developing rodent brain with MRI, Neuroimage, 67:375-384, 2013. Guide to MRH-based segmentation of all 26 structures from the Neuroscience Lexicon wiki; Supplement NIHMS#426990.
- Calabrese E, Badea A, Watson C, Johnson GA, A quantitative magnetic resonance histology atlas of postnatal rat brain development with regional estimates of growth and variability, Neuroimage. 2013 Jan 23. http://dx.doi.org/10.1016/j.neuroimage.2013.01.017 [Epub ahead of print] Supplement
- Jiang Y, Johnson GA. Microscopic diffusion tensor atlas of the mouse brain. Neuroimage 56:1235-1243, 2011 Supplement
- Johnson GA, Cofer GP, Gewalt SL, Hedlund LW. Morphologic phenotyping with magnetic resonance microscopy: the visible mouse. Radiology 222:789-793 , 2002
- Mukherjee P, Berman JI, Chung SW, et al. AJNR Am J Neuroradiol 29:632-664, 2008
- Veraart J, Leergaard TB, Antonsen BT, et al. Population-averaged diffusion tensor imaging atlas of the Sprague Dawley rat brain. Neuroimage 58(4):975-983, 2011

 

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