研究生: |
葉星巧 Yeh, Shin-Chiao |
---|---|
論文名稱: |
利用Listmode Data與B-Spline活度曲線描述進行小動物PET動態成像:先導研究 Dynamic Animal PET Imaging Using Listmode Data and B-Spline Activity Curve Description : A Pilot Investigation |
指導教授: |
許靖涵
Hsu, Ching-Han |
口試委員: | |
學位類別: |
碩士 Master |
系所名稱: |
原子科學院 - 生醫工程與環境科學系 Department of Biomedical Engineering and Environmental Sciences |
論文出版年: | 2009 |
畢業學年度: | 97 |
語文別: | 中文 |
論文頁數: | 132 |
中文關鍵詞: | 動態 、正子斷層掃瞄 、時間活度 、曲線描述 、時間解析度 |
外文關鍵詞: | time activity curve, TAC, dynamic, B-spline, curve description, Listmode, temporal resolution |
相關次數: | 點閱:3 下載:0 |
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本研究在進行動態PET影像重建的過程中,採用List-Mode資料所提供的時間資訊對同符事件進行分期。結合傳統的疊代式影像重建方法與數值方法之Cubic B-spline,發展出適用於處理動態資料的演算方法,有效描述核種藥物在活體中的吸收代謝情形。
Cubic B-spline曲線描述可提供高時間解析度與核種隨時間增加活度變化的過程,輕易以非侵入方式取得藥物在生物體內之時間活度曲線。臨床實驗中,以圈選不同ROI的方式,對特定的組織器官進行時間活度曲線(TAC)之重現。根據大鼠心臟之三維結構,分別圈選整個心臟區以及高涵血區之影像進行實驗,觀察心臟對葡萄糖藥物的使用情形。可獲得整個心臟(包含心肌)的活度動態情形以及心臟內血液的動態變化過程,實驗結果顯示,藥物注射初期,無論大鼠心臟或腦部之活度皆隨時間漸漸累加,表示器官對葡萄糖的吸收代謝的速率大於核種衰減的速度。
本研究並提出以類週其變化之生理訊號的波形特徵對PET影像進行功能性分期,以降低正常生理活動(例如:心搏、呼吸)所造成的運動假影。未來可結合功能性分期與本研究採用之時依性分期,有效提高成像品質,並提供受測者生理狀態的動態變化情形。延伸至4D動態影像的應用,可觀察各種藥物在體內各組織器官真實的吸收、代謝與傳遞之長時間動態過程,在臨床研究中,提供可靠的藥物開發、診斷與治療等核種在活體內的生化反應過程。
Dynamic PET imaging based on listmode data acquisition can provide timing information of coincidence events, which permit a flexible way to sort the data into several consecutive time frames. In this work, by using the listmode data combined with B-spline representation of radio-tracer time activity curve (TAC), we proposed a maximum likelihood expectation and maximization (MLEM) to estimate the parameters of TAC curve and restore the continuous TAC curve. Such a continuous TAC curve can provide better temporal resolution for dynamic PET imaging.
In this pilot study, we evaluated the performance of the proposed method using clinical animal data acquired from an Inveon microPET scanner. We particularly focused on the FDG metabolic rate functions of heart and brain. Using these two organs as regions of interest (ROIs), the estimated TAC curves can depict the temporal variations of rate changes. In addition, the estimated TAC curves also matched with each other by using different sorting schemes (equal time and equal time).
Since the listmode data can incorporate external signal inputs (like gating or respiratory signals), arbitrary temporal segmentation can be achieved as well. In future, we can combine such a generic segmentation into the proposed method and generate high-quality TAC curves corresponding to various physiological changes. The proposed method can be extended to 4D dynamic PET imaging which can make the best use of all collected events. It is optimistically anticipated that the proposed method can provide reliable radiotracer responses and will be useful for applications like drug development, therapy or diagnosis.
[1] T. E. Nichols, J. Qi, E. Asma, R. M. Leahy, “Spatiotemporal Reconstruction of List-Mode PET”, Med. Imaging, IEEE Trans on, Vol.21, NO. 4, Apr. 2002
[2] Y. Yang, S. Rendig, S. Siege, D. F. Newport, and S. R. Cherry, “ Cardiac PET imaging in mice with simultaneous cardiac and respiratory gating” , Pub. 8 Jun. 2005
[3] R. A. Powsner and E. R. Powsner, “Essentials of Nuclear Medicine Physics”, Bala. Sci., 1998.
[4] F. H. Attix, “Introduction to radiological Physics and radiation dosimetry”, V1, pp.38-60, 2004
[5] Siemens, “micro PET QuickSliverTM Listmode Data Data Format”, 2006.
[6] T. E. Nichols1, J. Qi , and R. M. Leahy , “Continuous Time Dynamic PET Imaging Using List Mode Data”, IPMI’99, LNCS 1613, 1999.
[7] T. G. Turkingtone, “Introduction to PET Instrumentation”, J Nuc. Tech., Vol.29, No1, pp.1-8, 2001.
[8] L. A. Sheep and Y. Vardi, “A statistical Model for Positron Emission Tomography”, J. of Amer. statistical Ass., Vol. 180, No.389, pp.8-20, 1985.
[9] L. A. Sheep and Y. Vardi, “Maximum Likelihood Reconstruction for Emission Tomography”, Med. Imaging, IEEE Trans on, Vol. Mi-1, No. 2, Oct. 1982
[10] J. I. Lay, http://www.me.ncu.edu.tw/jylai/CAD/B-spline.doc, 2002.
[11] M. Unser, A. Aldroubi, and M. Eden, “Fast B-Spline Transforms for Continuous Image Representation and Interpolation”, Pat. Ana. & Mach. Intel. , IEEE Trans on, Vol. 13, NO. 3, MARCH 1999
[12] Parra, L. and H. Barrett “List-mode likelihood: EM algorithm and image quality estimation demonstrated on 2-D PET”, Med. Imaging, IEEE Trans on, 1998, 17, 228-235
[13] C. Byrne, “Likelihood maximization for list-mode emission tomographic image reconstruction”, Medical Imaging, IEEE Trans on, 2001, 20, 1084-1092
[14] H. H. Barrett, T. White and L. C. Parra, ”List-mode likelihood”, Journal of the Optical Society of America A: Optics, Image Science & Vision, OSA, 1997, 14, 2914-2923
[15] N. Grotus, A. J. Reader, S. Stute, J. C. Rosenwald, P. Giraud, and I. Buvat, “Fully 4D list-mode reconstruction applied to respiratory-gated PET scans”, Phy. in Med. and Bio., 2009, 54, 1705-1721