基於功能區與神經模型的腦手術路徑規劃

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：7

、訪客IP：18.191.253.62

姓名

羅健峻(Chien-Chun Lo) 查詢紙本館藏

畢業系所

機械工程學系

論文名稱

基於功能區與神經模型的腦手術路徑規劃

相關論文

★ 雙光子光致聚合微製造系統之研發	★ 雙光子光致聚合五軸微製造系統之雷射加工路徑生成研究
★ 椎弓根螺釘定位演算法及導引夾治具自動化設計流程開發	★ 雙光子聚合微製造技術以能量均勻橢圓體為基之曝光時間最佳化研究
★ 雙光子光致聚合微製造以弦高誤差為基之切層演算法	★ 雙光子光致聚合微製造技術以螺旋線雷射掃描路徑增強微結構強度研究
★ 雙光子聚合微製造技術之三維結構製造品質改進研究	★ 利用二維多重圖像建構三維三角網格模型的生成與品質改進
★ 組織工程用冷凍成型製造系統之自動化製作流程開發	★ 自動相機校正與二維影像輪廓萃取研究
★ 基於雙光子光致聚合技術之四軸微製造系統製作高深寬比結構之研究	★ 冷凍成型積層製造之機台設計與組織工程支架製作參數調校研究
★ 基於二維影像輪廓重建三維模型技術之多視角相機群組空間座標系統整合	★ 應用於大型物體三維模型重建之多重二維校正板相機校正流程開發
★ 組織工程用冷凍成型積層製造之固態水支撐結構生成研究	★ 聚醚醚酮之積層製造系統開發

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

[檢視]

[下載]

本電子論文使用權限為同意立即開放。
已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。

摘要(中)

在進行腦部手術之前，醫師依靠患者所拍攝的醫學解剖影像，如電腦斷層(CT)或磁振造影(MRI)，以及自身的知識與手術經驗進行手術路徑規劃，但2D影像能提供的資訊量有限，可能導致手術時對患者的腦部組織產生傷害。若是能在手術路徑規劃的時候提供腦部功能區與白質神經纖維的3D模型，將可以幫助醫師規劃出更安全的手術路徑，降低對患者可能產生的傷害。
本研究結合皮質層功能區模型與白質神經纖維模型，發展出一套可幫助醫師於術前了解皮質層功能區分布及腫瘤周圍神經纖維分布的系統。研究內容包含了皮質層功能區以及白質神經纖維的3D模型重建、影像對位以及腫瘤所在區域的神經模型感興趣區域(ROI)設定。使用FreeSurfer對MRI影像進行功能區的辨識而後重建出皮質層功能區模型。白質神經纖維則使用DTI影像針對不同的神經纖維追蹤演算法進行正確性比對；影像對位是將皮質層功能區與白質神經束纖維的座標空間轉換為MRI影像座標，之後醫師可依據對位好的融合影像及設定在腫瘤周遭的感興趣區,規畫出可避開重要組織的安全路徑。
所建構的皮質層功能區模型根據解剖特徵進行比對，比對結果顯示重要的功能區如初級體感皮層、初級運動皮層、初級視覺皮層以及初級聽覺皮層均有完整重建又與Desikan-Killiany Atlas進行比對，顯示出功能區都有成功識別出來，因此模型是具有可靠性的。白質神經纖維模型針對上、下縱束、鉤束、弓狀束、下枕額束、扣帶束、放射冠以及胼胝體的完整性進行確認，結果顯示以Tensorline神經纖維追蹤演算法較為完整可靠。皮質層功能區影像與MRI影像對位準確度，使用棋盤分類法可以觀察到大腦輪廓、白質、灰質以及腫瘤皆接合在一起，以此推論對位精準度是可靠的。

摘要(英)

Before undergoing brain surgery, surgeons can only rely on the patient’s medical anatomical images, such as computerized tomography (CT) or magnetic resonance imaging (MRI), and their knowledge to plan surgical paths. However, 2D images can provide limited information. If 3D models of brain functional areas and white matter nerve fibers can be provided, it can help surgeons plan safer surgical paths.
This research includes 3D model reconstruction of cortical functional areas and white matter nerve fibers, image alignment, and region of interest (ROI) setting of neural model around the tumor. MRI images are used to identify functional areas and then reconstruct cortical functional area models. Different nerve fiber tracking algorithms are applied to generate white matter nerve fibers using DTI images and their correctness of reconstructed nerve fibers is compared. The coordinate frames of cortical functional areas and white matter nerve fibers are converted and aligned with MRI images coordinate frame. Then the surgeon can plan a safe surgical path based on the fused images.
By comparing with anatomical features, the constructed cortex functional area model shows that important functional areas have been completely reconstructed and identified. The white matter nerve fiber model is confirmed for the integrity of the superior, inferior longitudinal fasciculus, the uncinate fasciculus, the arcuate fasciculus, the inferior occipitofrontal fasciculus, the cingulate fasciculus, the corona radiata, and the corpus callosum. The results show that the Tensorline algorithm is much better. The alignment accuracy of cortical functional area images and MRI images is evaluated by using the checkerboard classification method. The results show that the brain outline, white matter, gray matter, and tumors are all connected smoothly, so it can be inferred that the alignment accuracy is reliable.

關鍵字(中)

★ 手術路徑規劃系統
★ DTI
★ 大腦皮質層
★ 腦部手術

關鍵字(英)

★ Surgical Planning Path System
★ DTI
★ Cerebral Cortex
★ Brain Surgery

論文目次

摘要 I
Abstract II
目錄 III
圖目錄 V
表目錄 IX
第一章緒論 1
1-1研究動機 1
1-2文獻回顧 2
1-3研究內容簡介 4
第二章研究方法 6
2-1系統介紹 6
2-2座標系定義 7
2-3皮質層功能區重建方法 9
2-3-1皮質層功能區介紹 10
2-3-2皮質層功能區重建演算法 11
2-4腦白質神經纖維束重建方法 13
2-4-1 擴散張量影像與FA指標介紹 13
2-4-2 神經纖維束重建演算法比較 15
2-4-3神經纖維束雜訊去除與ROI設定 20
2-5皮質層功能區腫瘤區域ROI設定 26
2-5-1判斷腫瘤座標演算法 28
2-5-2影像ROI重建 33
2-6 皮質層功能區影像與MRI影像對位 34
2-6-1 皮質層功能區與MRI影像座標系及影像格式介紹 35
2-6-2皮質層功能區影像座標轉換流程 36
2-7 手術路徑設計與調整 37
2-8 基於手術路徑的視角調整 39
2-9 基於腦功能區與神經纖維的手術路徑規劃系統介面設計 40
第三章實驗與結果討論 44
3-1 影像重建三維模型可靠度評估 44
3-1-1 皮質層功能區模型可靠度評估 44
3-1-2 兩種演算重建之白質神經束模型特徵比對 47
3-2影像對位方法準確性評估 53
第四章結論與未來展望 59
參考文獻 61

參考文獻

[1] 衛生福利部 110年國人死因統計結果 https://www.mohw.gov.tw/cp-5269-70314-1.html
[2] U. Mezger, C. Jendrewski, and M. Bartels, "Navigation in surgery," Langenbecks Arch Surg, vol. 398, no. 4, pp. 501-514, 2013
[3] R. B. Kochanski, J. M. Lombardi, J. L. Laratta, R. A. Lehman, and J. E. O’Toole, "Image-Guided Navigation and Robotics in Spine Surgery," Neurosurgery, vol. 84, no. 6, pp. 1179-1189, 2019
[4] X. Shao, Q. Yuan, D. Qian, Z. Ye, G. Chen, K. L. Zhuang, X. Jiang, Y. Jin, and D. Qiang, "Virtual reality technology for teaching neurosurgery of skull base tumor," BMC Med Educ, vol. 20, no. 1, p. 3, Jan. 2020
[5] D. A. Orringer, A. Golby, and F. Jolesz, "Neuronavigation in the surgical management of brain tumors: current and future trends," Expert Rev Med Devices, vol. 9, no. 5, pp. 491-500, 2012
[6] Z. D. Travis, P. Sherchan, W. K. Hayes, and J. H. Zhang, "Surgically-induced brain injury: where are we now?," Chinese Neurosurgical Journal, vol. 5, no. 1, p. 29, Dec. 2019
[7] Medtronic, "Stealth station surgical navigation system," https://www.medtronic.com/us-en/index.html
[8] BrainLab, "Vector vision system," https://www.brainlab.com/
[9] Y. Y. Hsu, N. Schuff, A. T. Du, K. Mark, X. Zhu, D. Hardin, and M. W. Weiner, “Comparison of automated and manual MRI volumetry of hippocampus in normal aging and dementia,” J Magn Reson Imaging, vol. 16, no. 1, pp.305 – 310, 2002
[10] M. I. Miller, M. Hosakere, A. R. Barker, C. E. Priebe, N. Lee, J. T. Ratnanather, L. Wang, M. Gado, J. C. Morris, and J. G. Csernansky, “Labeled cortical mantle distance maps of the cingulate quantify differences between dementia of the Alzheimer type and healthy aging,” Natl. Acad. Sci. U. S. A., vol. 100, no. 25, pp.15172 – 15177, 2003
[11] B. Fischl, D. H. Salat, E.a Busa, M. Albert, M. Dieterich, C. Haselgrove, A. v. d. Kouwe, R. Killiany, D. Kennedy, S. Klaveness, A. Montillo, N. Makris, B. Rosen, and A. M. Dale, “Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain,” Neuron, vol. 33, no. 3, pp.341 – 355, Jan. 2002
[12] P. M. Thompson, C. Schwartz, and A. W. Toga, “High-resolution random mesh algorithms for creating a probabilistic 3D surface atlas of the human brain,” NeuroImage, vol. 3, no. 1, pp.19–34, 1996
[13] B. Fischl, A.V. D. Kouwe, C. Destrieux, E. Halgren, F. Ségonne, D. H. Salat, E. Busa, L. J. Seidman, J. Goldstein, D. Kennedy, V. Caviness, N. Makris, B. Rosen, and A. M. Dale, “Automatically parcellating the human cerebral cortex,” Cereb Cortex, vol. 14, no. 1, pp.11-22, Jan. 2004
[14] P. J. Basser, J. Mattiello, and D. LeBihan, “MR diffusion tensor spectroscopy and imaging,” Biophys J, vol. 66, no. 1, pp. 259-267, Jan. 1994
[15] C. Nimsky, “Fiber tracking—a reliable tool for neurosurgery?,” World Neurosurg, vol. 74, no. 1, pp.105-106, Jul. 2010
[16] C. Nimsky, O. Ganslandt, and R. Fahlbusch, “Implementation of fiber tract navigation,” Neurosurgery, vol. 61, no. 1, pp. 306-317, Jul. 2007
[17] C. Nimsky, O. Ganslandt, P. Hastreiter, R. Wang, T. Benner, A. G. Sorensen, and R. Fahlbusch, “Preoperative and intraoperative diffusion tensor imaging-based fiber tracking in glioma surgery,” Neurosurgery, vol. 61, no. 1, pp. 178-185, Jul. 2007
[18] P. J. Basser, S. Pajevic, C. Pierpaoli, J. Duda, and A. Aldroubi, “In vivo fiber tractography using DT-MRI data,” Magn Reson Med, vol. 44, no. 4, pp. 625-632, Oct. 2000
[19] T. E. J. Behrens, H. Johansen-Berg, M. W. Woolrich, S. M. Smith, C. A. M. Wheeler-Kingshott, P. A. Boulby, G. J. Barker, E. L. Sillery, K. Sheehan, O. Ciccarelli, A. J. Thompson, J. M. Brady, and P. M. Matthews, “Noninvasive mapping of connections between human thalamus and cortex using diffusion imaging,” Nat Neurosci, vol. 6, no. 7, pp.750-757, Jul. 2003
[20] T. E. Conturo, N. F. Lori, T. S. Cull, E. Akbudak, A. Z. Snyder, J. S. Shimony, R. C. McKinstry, H. Burton, and M. E. Raichle, “Tracking neuronal fiber pathways in the living human brain,” Proc Natl Acad Sci U S A, vol. 96, no. 18, pp. 10422-10427, 1999
[21] M. A. Koch, D. G. Norris, amd M. Hund-Georgiadis, “An investigation of functional and anatomical connectivity using magnetic resonance imaging,” NeuroImage, vol. 16, no. 1, pp. 241-250, 2002
[22] B. Fischl, A. Dale, M. Sereno, and D. Greve, “FreeSurfer,” https://surfer.nmr.mgh.harvard.edu/
[23] P. A. Rinck, "Magnetic resonance, a critical peer-reviewed introduction; functional MRI," European Magnetic Resonance Forum, Nov. 2014
[24] S. A. Huettel, A. W. Song, G. McCarthy, and M. J. Singleton, “functional magnetic resonance imaging,” Yale J Biol Med, vol.82, no. 4, pp. 233, Dec. 2009
[25] K. Brodmann, L. J. Garey, “Brodmann’s localisation in the cerebral cortex,” Journal of Anatomy, vol. 196, no. 3, pp. 493-496, 2000
[26] “The caret Package,” http://topepo.github.io/caret/index.html
[27] 黃信誠,“空間統計簡介,”自然科學簡訊, vol.13, no. 3, pp. 101-104, Aug. 2000
[28] D. L. Collins, P. Neelin, T. M. Peters, and A. C. Evans, “Automatic 3-D intersubject reg- istration of MR volumetric data in standardized Talairach space,” J. Comput Assist Tomogr, vol. 18, no. 2, pp. 192-205, Mar. 1994
[29] R. S. Desikan, F. Ségonne, B. Fischl, B. T. Quinn, B. C. Dickerson, D. Blacker, R. L. Buckner, A. M. Dale, R. P. Maguire, B. T. Hyman, M. S. Albert, R. J. Killiany, “An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest,” NeuroImage, vol. 31, no. 3. pp. 968-980, Jan. 2006
[30] M. Ono, S. Kubik, and C. D. Abernathey, “Atlas of the cerebral sulci,” Journal of the Neurological Sciences, 1990
[31] R. Wang and V. J. Wedeen, "TRACKVIS," http://TRACKVIS.org/
[32] P. Mukherjee, J. I. Berman, S. W. Chung, C. P. Hess, and R. G. Henry, "Diffusion tensor MR imaging and fiber tractography: theoretic underpinnings," American Journal of Neuroradiology, vol. 29, no. 4, pp.632-641, 2008
[33] A. Crippa, A.C. Jalba, and J.B.T.M. Roerdink, “Enhanced DTI tracking with Adaptive Tensor Interpolation,” Visualization in Medicine and Life Sciences II, pp. 173-190, Jan. 2012
[34] B. Chen and A. W. Song, “DTI fiber tracking with local tissue property sensitivity: phantom and In vivo validation,” Magn Reson Imaging, vol. 26, no. 1, pp. 103-108, Jan. 2008
[35] A. Rößler, "Second order Runge–Kutta methods for itô stochastic differential equations," SIAM Journal on Numerical Analysis, vol. 47, no. 3, pp. 1713–1738, 2009
[36] D. Weinstein, G. Kindlmann, and E. Lundberg, “Tensorlines: advection-diffusion based propagation through diffusion tensor fields,” Proceedings Visualization, vol. 99, pp.249-530, 1999
[37] G. C. Feigl, W. Hiergeist, C. Fellner, K. M. Schebesch, C. Doenitz, T. Finkenzeller, A. Brawanski, and J. Schlaier, “Magnetic resonance imaging diffusion tensor tractography: evaluation of anatomic accuracy of different fiber tracking software packages,” World Neurosurg, vol. 81, no. 1, pp. 144-150, Jan. 2014
[38] Q. Wen and D. B. Chklovskii, “Segregation of the Brain into Gray and White Matter: A Design Minimizing Conduction Delays,” PLoS Comput Biol, vol. 1, no. 7. e.78, Dec. 2005
[39] FreeSurfer “The MGH/MGZ Volume Format” https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/MghFormat
[40] WIKI “Coordinate systems” https://www.slicer.org/wiki/Coordinate_systems
[41] WIKI “Visual cortex” https://en.wikipedia.org/wiki/Visual_cortex
[42] WIKI “Postcentral gyrus” https://en.wikipedia.org/wiki/Postcentral_gyrus
[43] WIKI “Primary motor cortex” https://en.wikipedia.org/wiki/Primary_motor_cortex
[44] WIKI “Brodmann Area 4” https://en.wikipedia.org/wiki/Brodmann_area_4
[45] WIKI “Auditory cortex” https://en.wikipedia.org/wiki/Auditory_cortex
[46] WIKI “Inferior longitudinal Fasciculus” https://en.wikipedia.org/wiki/Inferior_longitudinal_FAsciculus
[47] WIKI “Uncinate Fasciculus” https://en.wikipedia.org/wiki/Uncinate_FAsciculus
[48] B. J. Jellison, A. S. Field, J. Medow, M. Lazar, M. S. Salamat, and A. L. Alexander, “Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns,” AJNR Am J Neuroradiol, vol. 25, no. 3, pp. 256-269, Mar. 2004
[49] WIKI “Cingulum (brain)” https://en.wikipedia.org/wiki/Cingulum_(brain)
[50] J. E. Bruni and D. G. Montemurro, “Human neuroanatomy: a text, brain atlas, and laboratory dissection guide,” Oxford University Press, 2009
[51] WIKI “Corona Radiata” https://en.wikipedia.org/wiki/Corona_radiata
[52] J. D. Schmahmann and D. N. Pandya. “Fiber pathways of the brain,” Oxford Academic, 2006
[53] WIKI “Corpus callosum” https://en.wikipedia.org/wiki/Corpus_callosum
[54] M. Malinsky, R. Peter, E. Hodneland, A. J. Lundervold, A. Lundervold, and J. Jan, "Registration of FA and T1-weighted MRI data of healthy human brain based on template matching and normalized cross-correlation," Journal of digital imaging, vol. 26, no. 4, pp. 774-785, 2013

指導教授

廖昭仰(Chao-Yaug Liao)

審核日期

2023-6-28

推文