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Proceedings Paper

Assessment of brain perfusion using parametric and factor images extracted from dynamic contrast-enhanced MRI images
Author(s): Anne L. Martel; Alan R. Moody
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Paper Abstract

Contrast-enhanced magnetic resonance (MR) imaging offers a minimally invasive method of investigating brain blood flow. This paper describes two different methods of extracting quantitative and qualitative information from this data. The first approach is to generate parametric images showing blood flow, blood volume and time-to-peak activity on a pixel by pixel basis. The second approach uses factor analysis. Principal components are extracted from the data and these orthogonal factors are then rotated to give a set of oblique factors, which satisfy certain simple constraints. In most cases three factors can be identified: a background or non- enhancing factor, an early vascular factor which is strongly correlated to arterial flow, and a late vascular factor which is strongly correlated to venous flow. The parametric and factor images are complimentary in nature: the former provides quantitative information that is readily understood by the clinician, while the latter makes no a priori assumptions about the underlying physiology and also allows more subtle changes in cerebral blood flow to be assessed. The factor images may also be of great value in defining regions of interest over which to carry out a more detailed quantitative analysis. This dual approach can be readily adapted to assess perfusion in other organs such as the heart or kidneys.

Paper Details

Date Published: 3 July 1998
PDF: 11 pages
Proc. SPIE 3337, Medical Imaging 1998: Physiology and Function from Multidimensional Images, (3 July 1998); doi: 10.1117/12.312572
Show Author Affiliations
Anne L. Martel, Univ. of Nottingham Faculty of Medicine and Hospital (United Kingdom)
Alan R. Moody, Univ. of Nottingham Faculty of Medicine (United Kingdom)


Published in SPIE Proceedings Vol. 3337:
Medical Imaging 1998: Physiology and Function from Multidimensional Images
Eric A. Hoffman, Editor(s)

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