Validation and Robustness Analysis of Dynamic Contrast Enhanced MRI

In Dynamic Contrast Enhanced MRI there are several steps from the initial signal to obtaining the pharmacokinetic parameters for tumor characterization. The aim of this work was to validate the steps in the flow of data focusing on T1-mapping, Contrast Agent (CA)-quantification and the pharmacokinet...

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Bibliographic Details
Main Author: Fransson, Samuel
Format: Others
Language:English
Published: Umeå universitet, Institutionen för fysik 2015
Subjects:
MRI
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-107987
Description
Summary:In Dynamic Contrast Enhanced MRI there are several steps from the initial signal to obtaining the pharmacokinetic parameters for tumor characterization. The aim of this work was to validate the steps in the flow of data focusing on T1-mapping, Contrast Agent (CA)-quantification and the pharmacokinetical (PK) model, using a digital phantom of a head. In the Digital Phantom tissues are assigned necessary values to obtain both a regular and contrast enhanced (using Parker AIF) representation and simulating an SPGR signal. The data analysis was performed in a software called MICE, as well as the Digital Phantom developed at the department of Radiation Sciences at Umeå University. The method of variable flip angles for the T1-mapping was analyzed with respect to SNR and number of flip angles, finding that the median value in each tissue is correct and stable. A "two point" inversion recovery sequence was tested with optimal combination of inversion times for white matter and CSF and obtaining correct T1-values when the inversion times were close to the tissue T1, otherwise with large deviations seen. Three different methods for CA-quantification were analyzed and a large underestimation was found assuming a linearity between signal and CA-concentration mainly for vessels at about 60%, but also for other tissue such as white matter at about 15%, improving when the assumption was removed. Still there was a noticeable underestimation of 30% and 10% and the quantification was improved further, achieving a near perfect agreement with the reference concentration, taking the T2*-effect into account. Applying Kety-model, discarding the vp-term, Ktrans was found to be stable with respect to noise in the tumor rim but ve noticeably underestimated with about 50%. The effect of different bolus arrival time, shifting the AIF required in the PK-model with respect to the CA-concentration, was tested with values up to 5 s, obtaining up to about 5% difference in Ktrans as well as the effect of a vascular transport function obtained by the means of an effective mean transit time up to 5 s and up to about 5% difference in Ktrans.