An efficient computational approach to characterize DSC-MRI signals arising from three-dimensional heterogeneous tissue structures

The systematic investigation of susceptibility-induced contrast in MRI is important to better interpret the influence of microvascular and microcellular morphology on DSC-MRI derived perfusion data. Recently, a novel computational approach called the Finite Perturber Method (FPM), which enables the...

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Bibliographic Details
Published in:PloS one 2014-01, Vol.9 (1), p.e84764
Main Authors: Semmineh, Natenael B, Xu, Junzhong, Boxerman, Jerrold L, Delaney, Gary W, Cleary, Paul W, Gore, John C, Quarles, C Chad
Format: Article
Language:English
Subjects:
Algorithms
Biology
Biomedical engineering
Blood
Blood Vessels - metabolism
Brain Neoplasms - diagnosis
Computed tomography
Computer applications
Computer simulation
Contrast agents
Contrast media
Contrast Media - pharmacokinetics
Diffusion
Diffusion rate
Engineering
Extravasation of Diagnostic and Therapeutic Materials - metabolism
Finite difference method
Fractals
Imaging, Three-Dimensional - methods
Information science
Kinetics
Magnetic fields
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Mathematical analysis
Medicine
Methods
Microvasculature
Models, Biological
Morphology
Partial differential equations
Perfusion
Physics
Radiology
Reagents
Reproducibility of Results
Science
Tissues
Tumors
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Summary:The systematic investigation of susceptibility-induced contrast in MRI is important to better interpret the influence of microvascular and microcellular morphology on DSC-MRI derived perfusion data. Recently, a novel computational approach called the Finite Perturber Method (FPM), which enables the study of susceptibility-induced contrast in MRI arising from arbitrary microvascular morphologies in 3D has been developed. However, the FPM has lower efficiency in simulating water diffusion especially for complex tissues. In this work, an improved computational approach that combines the FPM with a matrix-based finite difference method (FDM), which we call the Finite Perturber the Finite Difference Method (FPFDM), has been developed in order to efficiently investigate the influence of vascular and extravascular morphological features on susceptibility-induced transverse relaxation. The current work provides a framework for better interpreting how DSC-MRI data depend on various phenomena, including contrast agent leakage in cancerous tissues and water diffusion rates. In addition, we illustrate using simulated and micro-CT extracted tissue structures the improved FPFDM along with its potential applications and limitations.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0084764