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Improved Accuracy of Dynamic Susceptibility Contrast Magnetic Resonance Imaging Estimates of Relative Cerebral Blood Volume in Human Gliomas by Accounting for Bidirectional Contrast Agent Exchange

  • Author(s): Leu, Kevin
  • Advisor(s): Ellingson, Benjamin M
  • et al.
Abstract

Magnetic resonance imaging (MRI) plays an integral role in the diagnosis and monitoring of gliomas. One means by which MRI has been used to assess treatment efficacy has been measuring the volumes of contrast-enhancing lesions on post-contrast T1-weighted images. Clinically, an increase of the lesion volume by a certain percentage compared to a previous baseline scan warrants a change in treatment. However, this type of imaging has its limitations, as exemplified by false positive radiographic determination of tumor progression (“pseudoprogression”) and false positive radiographic determination of treatment response (“pseudoresponse”).

Given the vascular nature of gliomas, perfusion-weighted dynamic susceptibility contrast (DSC)-MRI has been studied in efforts to improve the detection, characterization, and monitoring of gliomas after treatment. However, applying DSC-MRI biomarkers is not necessarily straightforward. One of the biggest problems with the calculation of relative cerebral blood volume (rCBV) is that it is compromised by artifacts created by the extravasation of contrast agent from the vasculature. This can be a particular challenge in the neuro-oncology field since blood brain barrier disruption is a common feature of gliomas.

This work attempts to improve estimates of rCBV in gliomas by incorporating a two-compartment pharmacokinetic model into the indicator dilution theory, which we term the “bidirectional” leakage correction. In Chapter II, we use simulation methods to demonstrate improved accuracy gained by the bidirectional leakage correction, as compared to a current, popular leakage correction (“unidirectional” leakage correction). In Chapter III, we demonstrate that the bidirectional model-generated permeability curves have better correlation with DCE-MRI permeability curves than those generated by the unidirectional model. We also demonstrate that the rCBV is more similar for the bidirectional model between two separate pre-treatment scans from the same patient. In Chapter IV, we demonstrate that the change in bidirectional rCBV can stratify glioblastoma patients treated with bevacizumab according to long- or short-term survival. In all, the above works demonstrate that the new technique better combats leakage effects, thereby improving the clinical utility of rCBV for human gliomas.

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