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A novel technique for modeling susceptibility-based contrast mechanisms for arbitrary microvascular geometries: the finite perturber method. Neuroimage 2008 Apr 15;40(3):1130-43 PMID: 18308587 PMCID: PMC2408763

Abstract

Recently, we demonstrated that vessel geometry is a significant determinant of susceptibility-induced contrast in MRI. This is especially relevant for susceptibility-contrast enhanced MRI of tumors with their characteristically abnormal vessel morphology. In order to better understand the biophysics of this contrast mechanism, it is of interest to model how various factors, including microvessel morphology contribute to the measured MR signal, and was the primary motivation for developing a novel computer modeling approach called the Finite Perturber Method (FPM). The FPM circumvents the limitations of traditional fixed-geometry approaches, and enables us to study susceptibility-induced contrast arising from arbitrary microvascular morphologies in 3D, such as those typically observed with brain tumor angiogenesis. Here we describe this new modeling methodology and some of its applications. The excellent agreement of the FPM with theory and the extant susceptibility modeling data, coupled with its computational efficiency demonstrates its potential to transform our understanding of the factors that engender susceptibility contrast in MRI.

Author List

Pathak AP, Ward BD, Schmainda KM

Author

Kathleen M. Schmainda PhD Professor in the Radiology department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Algorithms
Animals
Artifacts
Capillaries
Cerebral Cortex
Cerebrovascular Circulation
Diffusion Magnetic Resonance Imaging
Electromagnetic Fields
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Models, Neurological
Protons
Rats



View this publication's entry at the Pubmed website PMID: 18308587
jenkins-FCD Prod-130 96200611f8481f0aa4f84230b11dd74d063847a3