posted on 2017-03-21, 03:14authored byPhillip George Dayan Ward
The cerebral
vasculature provides the oxygen and glucose the brain requires to function.
Severe disruption of the supply of blood to the brain, such as during ischaemic
and haemorrhagic stroke, can have catastrophic consequences. Subtle changes in
normal cerebral vasculature may be a potential biomarker of early stage
neurodegenerative changes, and larger changes with disease progression may
provide valuable prognostic information. Quantifying the risk associated with
subtle cerebrovascular changes requires the reliable measurement of vascular
anatomy and oxygenation.
The magnetic field of a MRI and the magnetic properties of
iron in the blood interact. This interaction makes imaging the cerebral veins
and measuring venous oxygenation possible. But, the many non-vein sources of
magnetism in the brain complicate this process. The aim of the thesis was to improve
automated characterisation of the cerebral veins by (i) the development of a
cerebral vein segmentation method, (ii) the application of this technique to
compute venous density and oxygen extraction fraction measures, (iii) the
construction of a vein frequency atlas to improve anatomical-heterogeneity in
vein segmentation, and (iv) development of a partial volume correction method
for analysing smaller veins.
The first experimental chapter introduces a technique for
mapping the location of veins using a number of post-processing techniques that
were unified into a single framework. The performance of the framework was
compared with alternatives from the literature and demonstrated to provide vein
maps with higher accuracy.
The second experimental chapter constructed an analysis
pipeline for mapping veins and measuring venous oxygenation. The pipeline was
used to compute venous oxygen extraction fraction measures in a large
brain-imaging database acquired from an elderly population of healthy
individuals (n>500). Reproducible patterns of venous oxygenation and
venous density were mapped throughout the brain, and anatomically-specific
correlations between anatomy and oxygenation were identified.
The third experimental chapter developed a technique for
maximising vein image contrast. The technique combined three image sources of
cerebral vein information with differing anatomical precision into a single
image. A vein atlas (and anatomical precision maps) were calculated using a
database of manually traced vein maps. Three vein segmentation techniques were
used together with a number of accuracy metrics to determine that the
combination of the three image sources yielded the optimal vein maps.
The final experimental chapter addressed an error in
measuring vein oxygenation with binary vein maps. Standard vein maps depict
veins as a collection of cubic voxels. The effect of incorporating cylindrical
geometry, rather than cubic geometry, when analysing venous maps was investigated.
A partial volume technique was developed to more accurately model the
cylindrical geometry of veins and improve the accuracy of venous oxygen
extraction fraction measurements.
In summary, the thesis includes contributions in vein
imaging, vein identification and mapping, and vein characterization and
measurement. Cerebrovascular anatomy and venous oxygenation were characterised
in a healthy elderly population. Application of the methods and technique
developments described in the thesis may be of benefit for future studies of
cerebrovascular disease and neurodegeneration.
History
Campus location
Australia
Principal supervisor
David L. Dowe
Additional supervisor 1
David G. Barnes
Additional supervisor 2
Parnesh Raniga
Additional supervisor 3
Gary F. Egan
Year of Award
2017
Department, School or Centre
Information Technology (Monash University Clayton)