利用磁振造影腦部影像模擬X光電腦斷層影像衰減係數校正圖譜應用於正子電腦斷層暨磁振造影雙功能掃描系統

The purpose of this study was to investigate the toolbox based on the attenuation correction algorithm proposed by Thomas Beyer at el. in 2008 which seems to be useful for PET image reconstruction using MRI data in the brain. We retrospectively included six patients who had MRI examination and the FDG PET/CT scan. Histogram-matching algorithm was applied to transform the MR images to the so-called “pseudo-CT” images which are simulated as attenuation correction map for PET image reconstruction. The two model corrected PET images were visually analyzed and SUV were compared. The results showed better image quality and good correlation of SUV analysis on both supra-tentorial brain images than on infra-tentorial brain images. It is therefore the intensity transformation method seems to provide a simple way to transform the MR images to pseudo-CT for the attenuation correction of PET images in PET/MR, but needs more technical implementation to solve some pitfalls in the future.

並列關鍵字

PET/MRI ； Attenuation Correction ； PET/CT ； The Hybrid Image System

參考文獻

1. Chowdhury, F. and A. Scarsbrook (2008). "The role of hybrid SPECT-CT in oncology: current and emerging clinical applications." Clinical Radiology 63(3): 241-251.

2. Beyer, T., M. Weigert, et al. (2008). "MR-based attenuation correction for torso-PET/MR imaging: pitfalls in mapping MR to CT data." European Journal of Nuclear Medicine and Molecular Imaging 35(6): 1142-1146

3. Alavi, A. and L. Hirsch (1991). Studies of central nervous system disorders with single photon emission computed tomography and positron emission tomography: evolution over the past 2 decades.

4. Rohren, E., T. Turkington, et al. (2004). Clinical Applications of PET in Oncology 1, RSNA. 231: 305-332.

5. Hofmann, M., F. Steinke, et al. (2008). "MRI-based attenuation correction for PET/MRI: a novel approach combining pattern recognition and atlas registration." Journal of Nuclear Medicine 49(11): 1875.

延伸閱讀

Kuo, C. J., Chen, L. K., Peng, H. L., & Wu, C. C. (2004). Marchiafava-Bignami Disease：電腦斷層、磁振造影、單光子射出電腦斷層的影像表現. 中華放射線醫學雜誌, 29(2), 87-91. https://www.airitilibrary.com/Article/Detail?DocID=10188940-200404-29-2-87-91-a
游耀芳（2019）。回溯研究-探討腦部無施打顯影劑電腦斷層和軸切擴散加權成像磁振造影與中風的相關性〔碩士論文，高雄醫學大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0011-1108201922453800
Chang, Y. W. (2020). 結合微機電掃描技術與光學同調斷層掃描術以及血管攝影術於鼠腦成像技術開發 [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU202003743
傳家啓、蔡志文、陳啓昌、王安祥、盧宗斌、徐賢鈞（2005）。Brain Segmentation by Pulse Coupled Neural Networks in Magnetic Resonance Imaging。中華放射線醫學雜誌，30(2)，83-94。https://www.airitilibrary.com/Article/Detail?DocID=10188940-200505-30-2-83-94-a
Mendrik, A. M., Vincken, K. L., Kuijf, H. J., Breeuwer, M., Bouvy, W. H., Bresser, J. D., Alansary, A., Bruijne, M. D., Carass, A., Baz, A. E., Jog, A., Katyal, R., Khan, A. R., Lijn, F. V. D., Mahmood, Q., Mukherjee, R., Opbroek, A. V., Paneri, S., Pereira, S., Persson, M., Rajchl, M., Sarikaya, D., Smedby, Ö., Silva, C. A., Vrooman, H. A., Vyas, S., Wang, C., Zhao, L., Biessels, G. J., & Viergever, M. A. (2015). MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans. Computational Intelligence and Neuroscience, 2015(), 1235-1250. https://doi.org/10.1155/2015/813696

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利用磁振造影腦部影像模擬X光電腦斷層影像衰減係數校正圖譜應用於正子電腦斷層暨磁振造影雙功能掃描系統

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