Computational modelling of traumatic cerebral vasculature injury
File(s)
Author(s)
Duckworth, Harry
Type
Thesis
Abstract
The variety and severity of the physical and emotional effects caused by Traumatic Brain Injury
(TBI) has made it stand out among other prevalent diseases. Prognosis can vary substantially
between individuals despite similarity in injury cause or demographics, which makes each case
complex and unique. Microbleeds are a pathology seen from TBI and their occurrence and
amount are indicative of poorer outcomes. It is thought that their occurrence is linked to
biomechanical factors of the vessels; however, to-date there is no study which has investigated
this as of yet. This work aims to understand whether extension and/or rate of extension of the
veins in the brain is a key component of injury seen during a TBI. First, the computational
method smoothed particle hydrodynamics was used to test whether greater accuracy in
displacement was seen when modelling the fluid-like structure surrounding the brain, a medium
important in transferring impulses from the rigid-esque skull to the soft brain matter. Good
agreement to in-vivo brain displacements was found when using the method, which was to the
same level as the traditional method. A greater accuracy in strain was also seen; however, the
instabilities and resource requirements of the method were found to be impractical and was
therefore unable to be taken forward for the following modelling studies. Secondly, to
successfully model damage to the venous system a highly detailed model was created from three
and seven tesla brain images to create representations of over 50 structures in the brain. The venous system was segmented to diameters as low as 0.33 mm from the same patient using the
bioimaging software Materialise Mimics. Reconstructions of 46 TBI cadaver tests across five
subjects from literature were used to compare actual to predict displacement of the brain. Good
agreement of displacements was found in all tests showing the model is capable of accurately
predicting displacements of injury events typically seen during a TBI. The efficacy of the model
for predicting vasculature damage was shown through reconstruction of a case study where
microbleeds were seen. The strain and strain rate data from the simulation were found to peak in a similar location to those of the microbleeds found in the subject showing a correlation
between the vein biomechanics and pathology. Lastly, two more case studies with microbleeds
present were simulated, in addition to and enhanced version of the case study used previously.
The brain was divided into lobar or tract-based regions for statistical analysis. The regions
which experience larger 95th percentile axial strain and strain rates were seen to correlate with
the occurrence of venous damage. A large cohort (n = 74) of patient data was used to show that
the regions of the brain which frequently saw microbleeds also saw above average 95th
percentile axial strain and strain rates. This shows damage to the cerebral veins, which cause
microbleeds, is likely linked to axial extension they undergo during a TBI event. Limitations
exist with respect to the work presented, such as sample size, variety of case studies, and
exclusion of the cerebral arteries; however, these are found to not limit the impact of the work
and are natural topics for future study and investigation.
(TBI) has made it stand out among other prevalent diseases. Prognosis can vary substantially
between individuals despite similarity in injury cause or demographics, which makes each case
complex and unique. Microbleeds are a pathology seen from TBI and their occurrence and
amount are indicative of poorer outcomes. It is thought that their occurrence is linked to
biomechanical factors of the vessels; however, to-date there is no study which has investigated
this as of yet. This work aims to understand whether extension and/or rate of extension of the
veins in the brain is a key component of injury seen during a TBI. First, the computational
method smoothed particle hydrodynamics was used to test whether greater accuracy in
displacement was seen when modelling the fluid-like structure surrounding the brain, a medium
important in transferring impulses from the rigid-esque skull to the soft brain matter. Good
agreement to in-vivo brain displacements was found when using the method, which was to the
same level as the traditional method. A greater accuracy in strain was also seen; however, the
instabilities and resource requirements of the method were found to be impractical and was
therefore unable to be taken forward for the following modelling studies. Secondly, to
successfully model damage to the venous system a highly detailed model was created from three
and seven tesla brain images to create representations of over 50 structures in the brain. The venous system was segmented to diameters as low as 0.33 mm from the same patient using the
bioimaging software Materialise Mimics. Reconstructions of 46 TBI cadaver tests across five
subjects from literature were used to compare actual to predict displacement of the brain. Good
agreement of displacements was found in all tests showing the model is capable of accurately
predicting displacements of injury events typically seen during a TBI. The efficacy of the model
for predicting vasculature damage was shown through reconstruction of a case study where
microbleeds were seen. The strain and strain rate data from the simulation were found to peak in a similar location to those of the microbleeds found in the subject showing a correlation
between the vein biomechanics and pathology. Lastly, two more case studies with microbleeds
present were simulated, in addition to and enhanced version of the case study used previously.
The brain was divided into lobar or tract-based regions for statistical analysis. The regions
which experience larger 95th percentile axial strain and strain rates were seen to correlate with
the occurrence of venous damage. A large cohort (n = 74) of patient data was used to show that
the regions of the brain which frequently saw microbleeds also saw above average 95th
percentile axial strain and strain rates. This shows damage to the cerebral veins, which cause
microbleeds, is likely linked to axial extension they undergo during a TBI event. Limitations
exist with respect to the work presented, such as sample size, variety of case studies, and
exclusion of the cerebral arteries; however, these are found to not limit the impact of the work
and are natural topics for future study and investigation.
Version
Open Access
Date Issued
2022-02
Date Awarded
2023-03
Copyright Statement
Creative Commons Attribution NonCommercial Licence
License URL
Advisor
Ghajari, Mazdak
Sharp, David
Sponsor
Engineering and Physical Sciences Research Council
Grant Number
EP/N509486/1
Publisher Department
Dyson School of Design Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)