Estimation of Dynamic Contrast Enhanced Magnetic Resonance Imaging Parameters : Motion Artifact Correction

• Main Authors: Hao-Hsiang Hsu, 許皓翔
• Other Authors: Chung-Ming Chen
• Format: Others
• Language: en_US
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/32402256012928087447

碩士 === 國立臺灣大學 === 醫學工程學研究所 === 96 === Dynamic-contrast-enhanced MRI (DCE-MRI) is the usage of fast pulse sequence MRI for monitoring the perfusion of contrast materials in the blood stream. This application is useful in evaluating patients taking angiogenesis inhibitors. The behavior of the contrast material in the blood stream can then be modeled using a variety of different mathematical models. Currently, by measuring select data and employing the different mathematical models, it is possible to estimate the flow characteristics of the contrast materials in the blood stream as well as around the tumor. Subsequently, by using the different flow characteristics, it is possible to evaluate the tumor in a non-invasive way. The patients in this study were lung cancer patients, and had been given Avastin. By employing DCE-MRI, it may be possible to predict and evaluate the effect of the chemotherapy early in the treatment course. This study employs Mistar, which is the software that provides the multitude of mathematical models for the evaluation treatment response. Due to limitations of the software, however, inconsistencies resulting from image translation between tomography slices—due to spontaneous movements such as breathing—cannot be adjusted or corrected. Therefore, besides acquiring the DCE-MRI data for mathematical models, this study further employs image pre-processing for the correction of imaging errors due to subject movement. After dynamic comparison and correction, the image is vastly improved. Besides improvements in image quality, translational correction also drastically improves the data used in the mathematical models. The usage of translational correction, therefore, greatly affects the final image quality, as well as the statistical distribution of the data being measured. We hope these changes will have a landmark impact on the final evaluation of the effectiveness of the angiogenesis inhibitors as well.