Research Papers

Age-Dependent Regional Mechanical Properties of the Rat Hippocampus and Cortex

[+] Author and Article Information
Benjamin S. Elkin, Ashok Ilankovan, Barclay Morrison

Department of Biomedical Engineering, Columbia University, New York, NY 10027

J Biomech Eng 132(1), 011010 (Dec 18, 2009) (10 pages) doi:10.1115/1.4000164 History: Received March 14, 2009; Revised June 22, 2009; Published September 04, 2009; Online December 18, 2009

Age-dependent outcomes following traumatic brain injury motivate the study of brain injury biomechanics in experimental animal models at different stages of development. Finite element models of the rat brain are used to better understand the mechanical mechanisms behind these age-dependent outcomes; however, age- and region-specific rat brain tissue mechanical properties are required for biofidelity in modeling. Here, we have used the atomic force microscope (AFM) to measure region-dependent mechanical properties for subregions of the cortex and hippocampus in P10, P17, and adult rats. Apparent elastic modulus increased nonlinearly with indentation strain, and a nonlinear Ogden hyperelastic model was used to fit the force-deflection data. Subregional heterogeneous distributions of mechanical properties changed significantly with age. Apparent elastic modulus was also found to increase overall with age, increasing by >100% between P10 and adult rats. Unconfined compression tests (ε=0.3) were performed on whole slices of the hippocampus and cortex of P10, P17, and adult rats to verify the mechanical properties measured with the AFM. Mean apparent elastic modulus at an indentation strain of 30% from AFM measurements for each region and age correlated well with the long-term elastic modulus measured from 30% unconfined compression tests (slope not significantly different from 1, p>0.05). Protein, lipid, and sulfated glycosaminoglycan content of the brain increased with age and were positively correlated with tissue stiffness, whereas water content decreased with age and was negatively correlated with tissue stiffness. These correlations can be used to hypothesize mechanistic models for describing the mechanical behavior of brain tissue as well as to predict relative differences between brain tissue mechanical properties of other species, at different ages, and for different regions based on differences in tissue composition.

Copyright © 2010 by American Society of Mechanical Engineers
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Figure 8

Brain GAG content as a percent of wet weight: The region was not a significant factor affecting GAG while adult rats contained significantly more GAG than both P10 and P17 rats. Data presented as mean±standard deviation (n>4,  ∗=p<0.01).

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Figure 7

Brain tissue composition as a percent of wet weight: (a) water content, (b) protein content, and (c) lipid content as a function of age and region of interest. (d) The sum of all components for each region and age was approximately 100%. Data presented as mean±SEM (n>5,  ∗=p<0.05, all differences between ages are significant)

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Figure 6

Average of all subregions as measured by AFM at an engineering strain of 0.3, compared with long-term modulus from unconfined compression tests at an engineering strain of 0.3. Data presented as mean±SEM. Bivariate least-squares regression between the two methods resulted in a slope and intercept not significantly different than 1 and 0, respectively, (p>0.05).

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Figure 5

Light transmission image of a slice of the adult hippocampus prior to (a) and at the end of (b) a 30% unconfined compression test. Coverslip glass attached to the surface of each platen appears as transparent region above and below slice.

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Figure 4

Long-term elastic modulus of each anatomic region at each age as measured by unconfined compression tests performed to a strain of 30% (n>5). Data presented as mean±SEM,  ∗=p<0.05.

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Figure 3

Apparent elastic modulus at 30% strain as measured by AFM indentation for each region investigated in the (a) P10, (b) P17, and (c) adult rat brain (note the different scales on the y-axes). (d) The average of all apparent elastic moduli at 30% strain (including all regions) for each age investigated (all differences are significant). Error bars represent standard error of the mean (SEM),  ∗=p<0.05 and  ∗∗=p<0.01.

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Figure 2

(a) Subregions of the hippocampus and cortex probed with the AFM. Nonlinear apparent elastic modulus, Ê, measured by AFM indentation as a function of tissue strain (estimated using Eq. 2) for each subregion of the (b) P10, (c) P17, and (d) adult cortex and hippocampus. Data points represent mean apparent elastic modulus calculated from Eq. 1 at the specified strain and solid lines represent best fit of the Ogden hyperelastic model to the entire set of force-deflection data for each region within each age. Error bars are not included here for the sake of clarity. Maximum standard error is shown on each plot for each age group and was small compared with mean elastic modulus.

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Figure 1

Scanning electron micrograph of (a) 25 μm diameter probe tip used for AFM indentations, (b) CA1SR of the P10 rat hippocampus, and (c) CA1SR and CA1 pyramidal cell layer of the adult rat hippocampus. Scale bar=50 μm and applies to all images.



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