Anita Karsa1, Emma Biondetti1, Shonit Punwani2, and Karin Shmueli1
1Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 2Centre for Medical Imaging, University College London, London, United Kingdom
Susceptibility
Mapping has emerging clinical applications. To reduce scan time, clinical images
are often acquired with large slice spacing/thickness and reduced coverage.
The effect of these factors on susceptibility maps has not been investigated. Here,
we develop a simple framework to explore the effect of low-resolution and low-coverage
in the slice dimension on the accuracy of susceptibility maps. Our experiments
with digital phantoms and volunteer images have shown that the error in the
estimated susceptibility increases substantially with increasing slice spacing/thickness and decreasing coverage. These results
underscore the need for high-resolution, full-coverage acquisitions for
accurate susceptibility mapping.
