臺灣博碩士論文加值系統

背景:多系統萎縮病變是一種包含小腦萎縮的神經退化性疾病，臨床上影響到的腦部區域，除了小腦以外，腦幹，脊髓，大腦皮質以及椎體外系統也都有受到影響。然而,傳統的影像學分析與判讀卻往往難以精確的判斷受影響的區域以及萎縮的程度。
目標與假設:在此研究中我們將使用碎形分析來找出腦部病發區域，碎形分析是一種評估型態變化與物體複雜度的可靠指標，可以用來將一具複雜形狀的圖形數據化。
資料與方法:在本實驗中，我們運用三維碎形分析的技術來量化患者以及正常人腦部的灰質與白質，進而比較兩者之間的差異。我們總共收集二十三位以小腦症狀為主的多系統萎縮患者，二十一位正常人，經腦部核磁共振掃描後重建三維的腦部影像，度量其三維的碎行維度值; 藉此觀察患者與正常人之間腦部不同區域之間的差異。
結果與結論:相較於傳統量測體積的方法，使用碎形分析所得到的結果不但對疾病的敏感性較高，而且也比較不受到性別或年紀的影響; 同時我們還發現有病態性退化的小腦區域與特定的大腦區域其碎形數值有明顯相關性存在，另外碎形數值的變化也與特定的小腦萎縮基因變異有關。

Background: Multiple System Atrophy of the Cerebellar Type (MSA-C) and spinocerebellar atrophy (SCA) area degenerative neurological diseases of the central nervous system. However, it is often difficult to evaluate the grade of atrophy in the brain and the cerebellum by the traditional image analysis.
Materials and methods: A three-dimensional fractal dimension (FD) analysis was used to quantify the structural complexity of both gray matter and white matter from the T-1 weighted magnetic resonance images. Twenty-three MSA-C patients and twenty-one normal subjects participated in this study.
Results: The FD method is superior to the conventionally volumetric method in terms of much smaller standard deviations, better sensitivity, and less gender effect. In addition, our results suggest that there is statistical significant correlation between the FD changes of cerebellar regions and the FD changes of cerebral cortices.
Conclusions: FD analysis is effectiveness in quantifying the structural changes of both cerebrum and cerebellar structures in MSA and SCA.

中文摘要 P4
英文摘要 P6
目錄 P7
圖表目錄 P8
1. 序言 P9
2. 材料與方法 P13
a. 資料收集 P13
b. 影像處理 P13
c. 使用盒計法進行碎形分析 P15
d. 統計分析 P17
3. 結果 P19
4. 討論 P22
5. 結論 P25
6. 未來研究計劃 P26
7. 初步成果 P28
8. 參考文獻 P29

圖表目錄
圖說 P38
表說 P42
圖一 影像處理流程圖 P44
圖二 由正常受試者所重建之小腦灰質與小腦白質 3D影像 P45
圖三 重建MSA-C 病患的小腦灰質與小腦白質 3D影像 P47
圖四 碎形維度估算對3D數位虛擬模型估算結果的電腦處理程序 P48
圖五 控制組內與病患組內的性別影響 P50
圖六 比較MSA-C病患與控制組的碎形維度值 P51
圖七 所有碎形維度值與體積值的散佈圖 P52
圖八 以小腦為例表現碎形維度數值變化與形態複雜度改變的相關性 P53
圖九 將大腦分為116 個區域後計算出不同腦區的碎形維度 P54
圖十 多系統萎縮症患者116 個腦部區域的碎形維度與腦部退化的相關性分析 P55
表一 各控制組受試者之小腦白質與小腦灰質之碎形維度值與體積 P56
表二 各MSA-C病患之小腦白質與小腦灰質之碎形維度值與體積 P58
表三 組間體積、組間碎形維度值與性別影響之雙因子變數分析 P60

Baloh, R.W., Ying, S.H., Jacobson K.M.,2003. A longitudinal study of gait and balance dysfunction in normal older people. Arch Neurol.60,835-9.
Berciano, J.,1982. Olivopontocerebellar Atrophy. A review of 117 cases, J. Neurol. Sci. 53,253-272.
Bishop, C.M., 1995. Neural Networks for Pattern Recognition. Oxford, U.K.: Oxford University.
Blanton, R.E., Levitt, J.G., Thompson, P.M., Narr, K.L., Capetillo-Cunliffe, L.,a, Nobel, A., Singerman, J.D., McCracken, J.T., Toga, A.W., 2001. Mapping cortical asymmetry and complexity patterns in normal children. Psychiatry Research: Neuroimaging , 107, 29-43
Bookstein F.L.,2001.”Voxel-Baesd morphometry“ should not be used with imperfectly registered images. NeuroImage, 14,1454-1462.
Brenneis, C., Egger, K., Scherfler, C., Seppi, K., Schocke, M., 2007. Progression of brain atrophy in multiple system atrophy. J. Neurol. 254,191–196.
Buchnicek, M, Nezadal, M, Zmeskal, O., 2000 Numeric calculation of fractal dimension. Proceedings of the third conference on prediction, synergetic and more.
Bürk, K., Globas, C., Wahl, T., Bühring, U., Diety, K., Yühlke, C., Luft, A., Schuly, J.B., Voigt, K., Dichgans, J., 2004. MRI-based volumetric differentiation of sporadic cerebellar ataxia. Brain,127,175-181.
Chebrolu, H., Slevin, J.T., Gash, D.A., Gerhardt, G.A., Young, B., Given, C.A., Smith, C.D., 2006. MRI volumetric and intensity analysis of the cerebellum in Parkinson's disease patients infused with glial-derived neurotrophic factor (GDNF). Experimental Neurology 198, 450-456.
Cook M.J., 1995. Fractal description of cerebral cortical patterns in frontal-lobe epilepsy. Eur Neurol, 35,6,327-35.
Cutting JE, Garvin JJ. Fractal curves and complexity. Percept Psychophys. 1987 Oct;42(4):365-70.
Davatzikos C., 2004. Why voxel-based morphometric analysis should be used with great caution when characterizing group differences, NeuroImage, 23 , 17-20
Esteban, F.J., Sepulcre, J., de Mendizabal, N.V., Goni, J., Navas, J., de Miras, J.R., Bejarano, B., Masdeu, J.C., Villoslada, P., 2007. Fractal dimension and white matter changes in multiple sclerosis. NeuroImage 36, 543-549.
Fernández E. and Jelinek H.F., 2001. Use of Fractal Theory in Neuroscience: Methods, Advantages, and Potential Problems. Methods 24, 309-321.
Free, S.L., Sisodiya, S.M., Cook, M.J., Fish, D.R., Shorvon, S.D., 1996. Three dimension fractal analysis of the white matter surface from magnetic resonance images of the human brain. Cereb. Cortex 6, 830-836.
Gilman, S., Low, P.A., Quinn, N., Albanese, A., Ben-Shlomo, Y., Fowler, C.J., Kaufmann, H., Klockgether, T., Lang, A.E., Lantos, P.L., Litvan, I., Mathias, C.J., Oliver, E., Robertson, D., Schatz, I., Wenning, G.K., 1999. Consensus statement on the diagnosis of multiple system atrophy. J. Neurol. Sci. 163, 94-98.
Good, C.D., Johnsrude, I.S., Ashburner, J., Henson, R.N.R. Friston, K.J., Frackowiak, R.S.J., 2001. A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains, NeuroImage, 14, 21–36
Graham, J.G., Oppenheimer, D.R., 1969. Orthostatic hypotension and nicotine sensitivity in a case of multiple system atrophy. J. Neurol. Neurosurg. Psychiatry 32, 28-34.
Ha, T.H., Yoon, U., Lee, K.J., Shin, Y.W., Lee, J.M., Kim, I.Y., Ha, K.S., Kim, S.I., Kwon, J.S., 2005. Fractal dimension of cerebral cortical surface in schizophrenia and obsessive–compulsive disorder. Neuroscience Letters 384, 172-176.
Horimoto, Y., Aiba, I., Yasuda, T., Ohkawa, Y., Katayama, T., Yokokawa, Y., Goto, A., Ito, Y., 2000. Cerebral atrophy in multiple system atrophy by MRI. J. Neurol. Sci. 173, 109-112.
Iftekharuddin, K.M., Jia, W., Marsh, R., 2000. A fractal analysis approach to identification of tumor in brain MR images. Eng. Med. Biol. Soc., Proc. of the 22nd Annu. Intl. Conference of the IEEE. 4,3064-3066.
Jarque, C.M., Bera, A.K., 1980. Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economic Letters 6, 255-259.
Jernigan, T.L, Archibald, S.L., Fennema-Notestine C., et al., 2001. Effects of age on tissues and regions of the cerebrum and cerebellum. Neurobiol. Aging 22,581-594.
Kiselev VG, Hahn, KR, Auer, DP, 2003. Is the brain cortex a fractal? , NeuroImage 20,1765-74.
Konagaya, M., Konagaya, Y., Sakai, M., Matsuoka, Y., Hashizume, Y., 2002. Progressive cerebral atrophy in multiple system atrophy. J. Neurol Sci. ,195, 123-127.
Kuriyama, N., Mizuno, T., Iida, A., Watanabe, Y., Nakagawa, M., 2005. Autonomic nervous evaluation in the early stages of olivopontocerebellar atrophy, Autonomic Neuroscience: Basic and Clinical 123, 87- 93.
Lee, E.A., Cho, H.I., Kim, S.S., Lee, W.Y., 2004a. Comparison of magnetic resonance imaging in subtypes of multiple system atrophy. Parkinsonism and Related Disorders, 10, 363-368.
Lee, J.M., Yoon, U., Kim, J.J., Kim, I.Y., Lee, D.S., Kwon, J.S., Kim, S.I., 2004b. Analysis of the Hemispheric Asymmetry Using Fractal Dimension of a Skeletonized Cerebral Surface. IEEE Trans. Biomedical Eng. 51, 1494-1498.
Levene, H., 1960, In Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling, I. Olkin et al. eds., Stanford University Press,pp. 278-292.
Liu, J.Z., Zhang, L.D., Yue, G.H., 2003. Fractal Dimension in Human Cerebellum Measured by Magnetic Resonance Imaging. Biophysical Journal 85, 4041-4046.
Lukas, C., Schöls, L., Bellenberg, B., Rüb, U., Przuntek, H., Schmid, G., Koster, O., Suchan, B., 2006. Dissociation of grey and white matter reduction in spinocerebellar ataxia type 3 and 6: A pixel-based morphometry study. Neurosci. Letters 408, 230-235.
Mandelbrot B.B., 1983, The Fractal Geometry of Nature. New York ,W.H. Freeman.
Nezadal, M., Zmeskal, O., Buchnicek, M., 2001.The box-counting: critical study. In: Proceedings of the fourth conference on prediction, synergetic and more. P.18 ISBN 80-7318-030-8
Papp, M.I., Kahn, J.E., Lantos, P.L., 1989, Glial cytoplasmic inclusions in the CNS of patients with multiple system atrophy (striatonigral degeneration, olivopontocerebellar atrophy and Shy–Drager syndrome). J. Neurol Sci;94:79-100.
Peitgen, H.O., Jurgens, H., Saupe, D., Chaos and Fractals New Frontiers of Science. New
York: Springer; 1992.
Pemde, H.K., Bakhshi, S., Kalra, V.,1995, Olivopontocerebellar atrophy: a case report, Brain & Development. 17:130-132
Peng, C.K., Mietus, J.E., Liu, Y., Lee, C., Jeffrey, M., Hausdorff, J.M., Stanley, H.E.,Goldberger, A.L., Lipsitz, L.A., 2002.Quantifying Fractal Dynamics of Human Respiration: Age and Gender Effects. Annals of Bio. Eng., 30, 683-692.
Pereira, D., Zambrano, C., Martin-Landrove, M., 2000. Evaluation of malignancy in tumors of the central nervous system using fractal dimension. Eng. Med. Biol. Soc. Proc. of the 22nd Annu. Intl. Conference of the IEEE. 3,1775-1778.
Sandu, A.L., Rasmussen Jr., I.A. b, Lundervold, A., Frank Kreuder, F., Neckelmann, G., Hugdahl, K., Specht, K., 2008.Fractal dimension analysis of MR images reveals grey matter structure irregularities in schizophrenia. Computerized Medical Imaging and Graphics 32 , 150–158.
Shan, Z.Y., Liu, J.Z., Glassa, J.O., Gajjarc, A., Lid, C.S., Reddicka, W.E., 2006. Quantitative morphologic evaluation of white matter in survivors of childhood medulloblastoma. Magnetic Resonance Imaging 24, 1015–1022.
Smith, C.D., Chebrolu, H., Wekstein, D.R., Schmitt, F.A., Markesbery, W.R., 2007. Age and gender effects on human brain anatomy: A pixel-based morphometric study in healthy elderly. Neurobiology of Aging 28, 1075–1087.
Smith, T.G. Jr., Marks, W.B.., Lange, G.D., Sheriff, W.H. Jr., Neale, E.A., 1989. A fractal analysis of cell images. J. Neurosci. Methods, 27, 173-180.
Soma, H., Yabe, I., Takei, A., Fujiki, N., Yanagihara, T., Sasaki, H., 2006. Heredity in multiple system atrophy. J. Neuro. Sci. 240, 107-110.
Specht, K., Minnerop, M., Müller-Hübenthal, J., Klockgetherb,T., 2005. Voxel-based analysis of multiple-system atrophy of cerebellar type: complementary results by combining voxel-based morphometry and voxel-based relaxometry. NeuroImage, 25, 287– 293.
Tisserand, D.J., Pruessner, J.C., Sanz Arigita, E.J., van Boxtel, M.P.J., Evans, A.C., Jolles, J., Uzlings, H.B.M., 2002. Regional frontal cortical volumes decrease differentially in aging: an MRI study to compare volumetric approaches and voxel-based morphometry. Neuroimage, 17,657–669.
Watanabe, H., Saito, Y., Terao, S., Ando, T., Kachi, T., Mukai, E., 2002. Progression and prognosis in multiple system atrophy: an analysis of 230 Japanese patients. Brain ;125:1070–1083.
Wenning, G.K, Ben-Shlomo, Y., Magalhaes, M., Daniel, S.E., Quinn, N.P., 1994. Clinical features and natural history of multiple system atrophy. An analysis of 100 cases. Brain, 117, 835-845.
Wenning, G.K., Colosimo, C., Geser, F., Werner Poewe, W., 2004. Multiple system atrophy.
The Lancent Neurology, 3, 93-103.
Wenning, G.K., Seppi, K., Tison, F., Jellinger,K., 2002. A novel grading scale for striatonigral degeneration (multiple system atrophy). J. Neural. Transm., 109, 307–320.
Woermann, F.G., Steiner, H., Barker, G.J., Bartlett, P.A., Elger, C.E., Duncan, J.S., Symms, M.R., 2001. A fast FLAIR dual-echo technique for hippocampal T2 relaxometry: first experiences in patients with temporal lobe epilepsy. J.Magn. Reson. Imaging 13, 547-552.
Zhang, L., Liu, J.Z., Dean, D., Sahgal, V., Yue, G.H., 2006. A three-dimensional fractal analysis method for quantifying white matter structure in human brain. J. Neurosci. Methods 150, 242-253.
Zhang, L., Dean, D., Liu, J.Z., Sahgal, V., Wang, X., Yue, G.H., 2007. Quantifying degeneration of white matter in normal aging using fractal dimension. Neurobiology of Aging 28, 1543-1555
Zook, J.M., Iftekharuddin, K.M., 2005. Statistical analysis of fractal-based brain tumor detection algorithms.Magnetic Resonance Imaging 23 , 671-678