簡易檢索 / 詳目顯示

研究生: 施軍存
Chun-tsun Shih
論文名稱: 結合磁振頻譜影像與平行影像技術測量肝臟脂肪含量
Using Proton Echo Planar Spectroscopic Imaging (PEPSI) with Parallel Imaging on Liver Fat Measurement
指導教授: 林益如
Yi-ru Lin
口試委員: 黃騰毅
Teng-yi Huang
蔡尚岳
Shang-yueh Tsai
學位類別: 碩士
Master
系所名稱: 電資學院 - 電子工程系
Department of Electronic and Computer Engineering
論文出版年: 2013
畢業學年度: 101
語文別: 英文
論文頁數: 36
中文關鍵詞: 非酒精性脂肪肝肝臟核磁共振頻譜影像質子迴訊磁共振頻譜影像平行影像
外文關鍵詞: NAFLD, parallel imaging, GRAPPA
相關次數: 點閱:387下載:1
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 非酒精性脂肪肝(NAFLD)在已開發國家中是一個很常見的肝臟疾病,為了預防加重成肝纖維化或肝硬化,早期偵測是否有非酒精脂肪肝變得很重要。之前我們使用快速磁振頻譜影像技術(PEPSI)來取得肝臟脂肪含量,對於16x32 的空間解析度只需要18 秒,而且時間夠短可以要求受試者閉氣,並且證實具有足夠的準確性。現在我們想要進一步提高空間解析度到24x32,並且掃描時間能維持跟以前一樣。所以我們搭配上平行影像的技術來縮短掃描的時間,搭配上平行影像技術後,我們需要調查在取得脂肪含量的表現是否跟以往只使用快速磁振頻譜影像時一樣準確,我們將只使用快速頻譜影像的資料作為標準,比較於搭配上平行影像技術的資料,我們所用的平行影像技術為GRAPPA。結果顯示,水訊號的重建比起脂肪訊號是較穩定的,在脂肪含量的計算上,模擬加速比起實際加速是比較接近只使用快速磁振頻譜影技術。結論上,我們能確實利用平行影像技術來達到2 倍加速,只是在取得脂肪含量的表現上還需要更進一步的改進。


    Non-alcoholic fatty liver disease (NAFLD) is a common liver disease in developed country, for preventing it develop to further complications such as fibrosis and cirrhosis, early detection of NAFLD becomes very important. In the past, we use proton echo planar spectroscopic imaging (PEPSI) to acquire the hepatic fat content (HFC) and PEPSI is proved that it is able to acquire the HFC accurately. For matrix size 16x32 the scan time is 18 seconds, and the scan time is short enough to ask the subject to hold his breath. Now, we want to further the matrix size to 24x32 and the scan time can be as short as before. So, we combine PEPSI and parallel imaging technology to shorten scan time. We want to investigate the performance of PEPSI with parallel imaging to see if it has the same accuracy as PEPSI. We set full-sampled PEPSI as the standard, compared with PEPSI with parallel imaging. One of the parallel imaging technology, generalized autocalibrating partially parallel acquisitions (GRAPPA) is enrolled. The results showed that the reconstruction of water signal is more stable than lipid signal. Simulated GRAPPA is more close to full-sampled PEPSI than real GRAPPA on quantifying HFC. In conclusion, 2-fold accelerated PEPSI is implemented successfully but the performance need further improvement.

    Chapter 1. Introduction ........................................................................................... 1 Chapter 2. Material and Method ............................................................................. 4 2.1 Experiments ............................................................................................... 4 2.1.1 Subjects .......................................................................................... 4 2.1.2 Experimental Parameters ............................................................... 4 2.2 GRAPPA Reconstruction ............................................................................. 5 2.3 Spectral Process ......................................................................................... 7 2.4 Quantification ............................................................................................ 7 2.5 Statistical Analysis ...................................................................................... 8 Chapter 3. Results .................................................................................................... 9 3.1 Spectral Images .......................................................................................... 9 3.2 Spectra...................................................................................................... 10 3.3 RMS errors ............................................................................................... 12 3.4 Hepatic Fat Content ................................................................................. 15 3.5 Investigation of the number of coils ........................................................ 18 Chapter 4. Discussion............................................................................................. 24 Chapter 5. Conclusion ............................................................................................ 27 Chapter 6. References ............................................................................................ 28

    [1] R. Lomonaco, J. Chen, and K. Cusi, "An Endocrine Perspective of
    Nonalcoholic Fatty Liver Disease (NAFLD)," Ther Adv Endocrinol Metab,
    vol. 2, pp. 211-25, Oct 2011.
    [2] J. F. Cobbold, D. Patel, and S. D. Taylor-Robinson, "Assessment of
    inflammation and fibrosis in non-alcoholic fatty liver disease by
    imaging-based techniques," J Gastroenterol Hepatol, vol. 27, pp. 1281-92,
    Aug 2012.
    [3] E. Bugianesi, E. Vanni, and G. Marchesini, "NASH and the risk of cirrhosis
    and hepatocellular carcinoma in type 2 diabetes," Curr Diab Rep, vol. 7, pp.
    175-80, Jun 2007.
    [4] N. A. Johnson, D. W. Walton, T. Sachinwalla, C. H. Thompson, K. Smith, P. A.
    Ruell, et al., "Noninvasive assessment of hepatic lipid composition:
    Advancing understanding and management of fatty liver disorders,"
    Hepatology, vol. 47, pp. 1513-23, May 2008.
    [5] N. F. Schwenzer, F. Springer, C. Schraml, N. Stefan, J. Machann, and F.
    Schick, "Non-invasive assessment and quantification of liver steatosis by
    ultrasound, computed tomography and magnetic resonance," J Hepatol, vol.51, pp. 433-45, Sep 2009.
    [6] A. E. Bohte, J. R. van Werven, S. Bipat, and J. Stoker, "The diagnostic
    accuracy of US, CT, MRI and 1H-MRS for the evaluation of hepatic steatosis
    compared with liver biopsy: a meta-analysis," Eur Radiol, vol. 21, pp. 87-97,
    Jan 2011.
    [7] G. Hamilton, M. S. Middleton, M. Bydder, T. Yokoo, J. B. Schwimmer, Y.
    Kono, et al., "Effect of PRESS and STEAM sequences on magnetic resonance
    spectroscopic liver fat quantification," J Magn Reson Imaging, vol. 30, pp.
    145-52, Jul 2009.
    [8] A. Chu, J. R. Alger, G. J. Moore, and S. Posse, "Proton echo-planar
    spectroscopic imaging with highly effective outer volume suppression using
    combined presaturation and spatially selective echo dephasing," Magn Reson
    Med, vol. 49, pp. 817-21, May 2003.
    [9] F. H. Lin, S. Y. Tsai, R. Otazo, A. Caprihan, L. L. Wald, J. W. Belliveau, et al.,
    "Sensitivity-encoded (SENSE) proton echo-planar spectroscopic imaging
    (PEPSI) in the human brain," Magn Reson Med, vol. 57, pp. 249-57, Feb
    2007.
    [10] S. Posse, S. R. Dager, T. L. Richards, C. Yuan, R. Ogg, A. A. Artru, et al., "In vivo measurement of regional brain metabolic response to hyperventilation
    using magnetic resonance: proton echo planar spectroscopic imaging
    (PEPSI)," Magn Reson Med, vol. 37, pp. 858-65, Jun 1997.
    [11] S. R. Chen, "Quantitative Analysis of Liver Lipid Using Proton Echo Planar
    Spectroscopic Imaging (PEPSI)," National Taiwan University of Science and
    Technology, 2011.
    [12] J. J. Chiu, "Assessment of Liver Fat With T2 Correction Using Magnetic
    Resonance Spectroscopic Image," National Taiwan University of Science and
    Technology, 2012.
    [13] M. A. Griswold, P. M. Jakob, R. M. Heidemann, M. Nittka, V. Jellus, J. Wang,
    et al., "Generalized autocalibrating partially parallel acquisitions (GRAPPA),"
    Magn Reson Med, vol. 47, pp. 1202-10, Jun 2002.
    [14] S. Y. Tsai, R. Otazo, S. Posse, Y. R. Lin, H. W. Chung, L. L. Wald, et al.,
    "Accelerated proton echo planar spectroscopic imaging (PEPSI) using
    GRAPPA with a 32-channel phased-array coil," Magn Reson Med, vol. 59, pp.
    989-98, May 2008.
    [15] M. Blaimer, F. Breuer, M. Mueller, R. M. Heidemann, M. A. Griswold, and P.
    M. Jakob, "SMASH, SENSE, PILS, GRAPPA: how to choose the optimal method," Top Magn Reson Imaging, vol. 15, pp. 223-36, Aug 2004.
    [16] A. Deshmane, V. Gulani, M. A. Griswold, and N. Seiberlich, "Parallel MR
    imaging," J Magn Reson Imaging, vol. 36, pp. 55-72, Jul 2012.
    [17] F. A. Breuer, S. A. Kannengiesser, M. Blaimer, N. Seiberlich, P. M. Jakob, and M. A. Griswold, "General formulation for quantitative G-factor calculation in
    GRAPPA reconstructions," Magn Reson Med, vol. 62, pp. 739-46, Sep 2009.

    QR CODE