Effects of different sampling schemes of diffusion imaging on tract-based analysis

• Main Authors: Yao-Chang Yang, 楊曜彰
• Other Authors: Wen-Yi Tseng
• Format: Others
• Language: en_US
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/upumsk

碩士 === 國立臺灣大學 === 醫療器材與醫學影像研究所 === 107 === Introduction: Magnetic Resonance Imaging (MRI) has been used for brain scanning for many years. The machines and methods of magnetic resonance imaging continue to evolve with the advancement of technology. However, this also creates a problem. The results obtained by different machines and different imaging methods cannot be compared together, which makes the reproducibility and comparativeness of the research results be questioned. In recent years, multi-shell diffusion imaging (MSI) has received great attention because of its modularity and the adjustment of sampling points, b-value, which make it easily to obtain the desired research results. This means as long as the selection of MSI with similar b-values and sampling points can reduce the comparative doubts. However, MSI has a big disadvantage, the scan time required for it is too long due to the large number of sampling points, which is a big burden for the subject. Therefore, we want to reduce the b-value and the number of sampling points to make it be used in clinical research, and also explore the effects of b-value and sampling points on the research results. Material and method: 35 healthy subjects’ MSI data were provided by the database of the Massachusetts General Hospital (MGH). The MSI is scanned on a 3T CONNECTOM scanner and consists of four shell b-values of 1000, 3000, 5000, 10000 and corresponding sampling points of 64, 64, 128, 256 points. The average one-person scan time is 89 minutes. After we did quality assessment (QA), we screened out four of the subjects with excessive quality differences from others, and the remaining 31 subjects. Then we used the MSI data with total 512 sampling points, through the algorithm reducing the sampling points, divided into various sets. We used the Tract-based automatic analysis (TBAA) to measure the Mean Apparent Propagator MRI index (MAP-MRI index) and diffusion tensor index of the 76 major tracts in the whole brain. Through these index, the feasibility of clinical use and the effects of changes in b-values and sampling points are evaluated. Due to the need for comparison, we selected three MSI sets as reference standards. A set with total 512 sampling points and maximum b-value 10000 was the first standard to be used as the MAP-MRI index standard; A set with total 256 sampling points and maximum b-value 5000 was the second standard for clinical trials; A set with total 64 sampling points and maximum b-value 1000 was the third standard to be used as the diffusion tensor index standard. Results and Discussions: We found that when we reduced the MSI sampling points to 128 points compared with the first standard, the MAP-MRI index did not have much difference, which was less than 10 percentage points. This represented even if we greatly reduced the number of sampling points of the MSI we can still obtain an acceptable MAP-MRI index. In terms of the diffusion tensor index, we found that when we compared the third standard with other sets, the percentage difference is greater than 20 or more. We know that if we take the entire MSI to sample the diffusion tensor coefficient, the obtained results are very different from the standard. It is better to extract the portion of the MSI with b-value 1000 as a comparison to obtain a more accurate diffusion tensor index. For the standard of clinical trials, we compared the set with b-value 5000 and 64 sampling points with the second standard and found that the MAP-MRI index difference was less than 10 percentage points, and the scan time required only 11 Minutes, which was close to the scan time in general clinical use. Our research mainly found the adjustability of MSI and its feasibility in clinical use. We successfully reduced the number of sampling points and b-value, but also got a good performance. In future research, we will confirm these sets can be stable in their appropriate area.