Summary
Objectives: The cerebroarterial system is a complex network of arteries that supply the brain
cells with vitally important nutrients and oxygen. The inter-individual differences
of the cerebral arteries, especially at a finer level, are still not understood sufficiently.
The aim of this work is to present a statistical cerebroarterial atlas that can be
used to overcome this problem.
Methods: Overall, 700 Time-of-Flight (TOF) magnetic resonance angiography (MRA) data sets
of healthy subjects were used for atlas generation. Therefore, the cerebral arteries
were automatically segmented in each dataset and used for a quantification of the
vessel diameters. After this, each TOF MRA dataset as well as the corresponding vessel
segmentation and vessel diameter dataset were registered to the MNI brain atlas. Fi
-nally, the registered datasets were used to calculate a statistical cerebroarterial
atlas that incorporates information about the average TOF intensity, probability for
a vessel occurrence and mean vessel diameter for each voxel.
Results: Visual analysis revealed that arteries with a diameter as small as 0.5 mm are well
represented in the atlas with quantitative values that are within range of anatomical
reference values. Moreover, a highly significant strong positive correlation between
the vessel diameter and occurrence probability was found. Furthermore, it was shown
that an intensity-based automatic segmentation of cerebral vessels can be considerable
improved by incorporating the atlas information leading to results within the range
of the inter-observer agreement.
Conclusion: The presented cerebroarterial atlas seems useful for improving the understanding
about normal variations of cerebral arteries, initialization of cerebrovascular segmentation
methods and may even lay the foundation for a reliable quantification of subtle morphological
vascular changes.
Keywords
Magnetic resonance imaging - angiography - arteries - statistical atlas - computer-assisted
image processing
