Download Quantitative Analysis of Multi-dimensional and Multivariate Magnetic

Quantitative Analysis of Multi-dimensional and Multivariate Magnetic Resonance Imaging
Data: Impact upon the Management of Patients with Brain Tumors
Sarah J. Nelson, PhD
Professor of Radiology, UCSF and Professor of Bioengineering UCB
The management of patients with brain tumors is driven to a great extent by visual interpretation
of serial imaging data obtained using non-invasive modalities such as Magnetic Resonance
(MR). The past ten years have seen an explosion in the spatial resolution of MR data, the speed
of acquisition and in the number of different types of image contrast that can be obtained.
Clinical examinations of 30 to 60 minutes are now acquiring thousands of images of the brain
and contain information concerning not only the anatomy but also physiological parameters
describing the tissue architecture, microvasculature and biochemical properties of normal and
abnormal regions. These imaging examinations are important for diagnosis, surgical planning,
targeting focal therapy, selecting the most appropriate treatment and evaluating patterns of
response. At UCSF we are developing more effective MR data acquisition protocols, improved
reconstruction algorithms and quantitative metrics that provide an objective assessment of tumor
burden. These methodologies will be discussed in the context of the computational and
mathematical tools required to implement them in a time efficient manner and will address the
impact that the resulting data are likely to have upon patient care.