4 Brain Tissue Mechanical Properties
89
on subsequent measured data. Gefen and Margulies discuss this in some detail
[91]. A recent study in spinal cord tissue suggests that the amplitude of the
preconditioning has a strong effect on the subsequently measured properties [95],
and more recent data from our laboratory also suggests preconditioning strain rate
can alter subsequently measured properties.
It must be remembered here that the properties of prime interest are the in vivo
properties of human brain tissue. It is only very recently that it has been possible to
measure human brain properties in vivo, using MR elastography, and then only at
very small deformations, corresponding to the linear viscoelastic regime. Response
of brain tissue in vivo at larger deformations must be inferred from a combination
of ex vivo tests and animal in vivo tests. This brings with it much uncertainty about
how to extrapolate the available ex vivo data and animal in vivo results to the in vivo
human brain.
4.7 Future Directions
It is clear from the discussion above that while we have made great strides in
characterising the mechanical properties of brain tissue, there is still much to be
done. Consistent data sets for different loading regimes, such as shear, compression,
and tension, are still not readily available. Data for complex loading histories, such
as multiple step loading and step reversals, which have been found to be useful in
developing and testing accurate constitutive models for other complex nonlinearly
viscoelastic materials are highly desirable. It is essential that such data be collected
with full consideration of the methodological issues noted above.
The use of more rigorous rheological testing protocols in compression and testing
may allow for more definitive determination of the true linear viscoelastic limit for
brain tissue. The collection of data through the full loading and unloading cycle in
oscillatory testing may also assist in all test modes.
The other key gap in the body of knowledge regarding brain tissue is integration
of data from different loading types – particularly reconciling shear, compression,
and tensile loading data. To date, this is not possible because data that has been
collected in different testing modes comes from different species and has been
subject to different loading regimes (strains, strain rates), been subject to different
preparation methods, and been tested at different post-mortem times. There is a clear
need for multimodal data (shear, compression, tension, and combination loading) to
be collected using robust rheological techniques so that reliable constitutive models
can be developed and validated across all loading types. One recent ex vivo human
brain rheological study has begun this endeavour by testing tension, compression,
and shear loading in a single study [82].
Definitive conclusions about the effect of tissue perfusion pressure on the
properties of brain tissue would be valuable in determining what corrections (if any)
are required to adapt ex vivo data to predict in vivo brain response. Further in vivo
measurements, of both linear viscoelastic (e.g. using MR elastography or similar
89
on subsequent measured data. Gefen and Margulies discuss this in some detail
[91]. A recent study in spinal cord tissue suggests that the amplitude of the
preconditioning has a strong effect on the subsequently measured properties [95],
and more recent data from our laboratory also suggests preconditioning strain rate
can alter subsequently measured properties.
It must be remembered here that the properties of prime interest are the in vivo
properties of human brain tissue. It is only very recently that it has been possible to
measure human brain properties in vivo, using MR elastography, and then only at
very small deformations, corresponding to the linear viscoelastic regime. Response
of brain tissue in vivo at larger deformations must be inferred from a combination
of ex vivo tests and animal in vivo tests. This brings with it much uncertainty about
how to extrapolate the available ex vivo data and animal in vivo results to the in vivo
human brain.
4.7 Future Directions
It is clear from the discussion above that while we have made great strides in
characterising the mechanical properties of brain tissue, there is still much to be
done. Consistent data sets for different loading regimes, such as shear, compression,
and tension, are still not readily available. Data for complex loading histories, such
as multiple step loading and step reversals, which have been found to be useful in
developing and testing accurate constitutive models for other complex nonlinearly
viscoelastic materials are highly desirable. It is essential that such data be collected
with full consideration of the methodological issues noted above.
The use of more rigorous rheological testing protocols in compression and testing
may allow for more definitive determination of the true linear viscoelastic limit for
brain tissue. The collection of data through the full loading and unloading cycle in
oscillatory testing may also assist in all test modes.
The other key gap in the body of knowledge regarding brain tissue is integration
of data from different loading types – particularly reconciling shear, compression,
and tensile loading data. To date, this is not possible because data that has been
collected in different testing modes comes from different species and has been
subject to different loading regimes (strains, strain rates), been subject to different
preparation methods, and been tested at different post-mortem times. There is a clear
need for multimodal data (shear, compression, tension, and combination loading) to
be collected using robust rheological techniques so that reliable constitutive models
can be developed and validated across all loading types. One recent ex vivo human
brain rheological study has begun this endeavour by testing tension, compression,
and shear loading in a single study [82].
Definitive conclusions about the effect of tissue perfusion pressure on the
properties of brain tissue would be valuable in determining what corrections (if any)
are required to adapt ex vivo data to predict in vivo brain response. Further in vivo
measurements, of both linear viscoelastic (e.g. using MR elastography or similar