跳到主要內容

臺灣博碩士論文加值系統

(216.73.216.136) 您好!臺灣時間:2025/09/21 05:53
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:陳柏翰
研究生(外文):Po-Han Chen
論文名稱:非小細胞肺癌之放射線治療電腦斷層影像量化研究:多時間點對位演算法之發展以及肺實質損傷變化與計畫劑量分佈關聯分析
論文名稱(外文):Quantification of Radiotherapy CT image for Non-Small Cell Lung Cancer: Development of Longitudinal Registration Algorithm and Correlation Analysis of Lung Parenchyma Change and Planning Radiation Dose Distribution
指導教授:陳中明陳中明引用關係
指導教授(外文):Chung-Ming Chen
口試委員:張允中郭頌鑫王靖維
口試委員(外文):Yeun-Chung ChangSung-Hsin KuoChing-Wei Wang
口試日期:2015-01-20
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:醫學工程學研究所
學門:工程學門
學類:綜合工程學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:中文
論文頁數:41
中文關鍵詞:放射治療引發之肺實質變化骨骼分割肺部下緣分割特徵點群採樣多時間點影像對位
外文關鍵詞:parenchyma change induced by radiotherapybone segmentationlower lung surface segmentationfeature point samplinglongitudinal registration
相關次數:
  • 被引用被引用:0
  • 點閱點閱:247
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
肺癌是世界上最主要的癌症死亡原因之一,在台灣也同樣不分性別地高居所有癌症死亡原因第一位,其中在男性死亡率更高達48.9%。早期肺癌最佳的治療方式為外科手術切除,然而適合手術治療之早期肺癌病患僅佔總體約15%,大多數之肺癌被發現時已進入中晚期,不再適合僅以外科手術方式治療,因此,化學治療、放射線治療及化學治療合併放射線治療在針對中晚期肺癌治療扮演相當重要的角色。在病患接受放射線治療過程中,高能放射線除了對腫瘤進行治療,同時也會傷害鄰近的肺部正常組織導致併發症,包含急性期產生放射性肺炎及晚期發生肺纖維化等症狀,造成病人肺功能下降且影響病人治療後之生活品質。
本研究提出一用於評估放射治療後肺實質變化之多時間點對位演算法,並且針對肺實質變化與劑量強度以及時間之關聯性進行探討。在所提出之對位演算法中,透過肺區以外鄰近肺臟的解剖結構,克服過往大範圍之肺實質改變導致對位困難之問題。於所提之演算法中以脊椎作為剛性對位的參考對象;以鄰近肺區的所有骨骼組織表面,包含胸骨柄、肋骨、脊椎等,以及氣管壁與肺部下緣表面,共三個肺區周圍主要的肺區周圍解剖特徵作為非剛性對位中描述不同時間點時呼吸飽滿度所造成的肺部擴張差異之依據,並對此三個解剖特徵進行特徵點群參考點採樣後進行連貫性群點對位。
使用本研究發展之多時間點對位演算法對治療前與治療後之肺臟進行對位後,探討肺實質變化與劑量強度以及時間之關聯性,得到了在22 Gy 以上的劑量區間在3~7個月時便有顯著的肺實質變化的結論。


Lung cancer is one of the leading cause of cancer deaths worldwide, including Taiwan, across gender. In Taiwan, the male mortality rate of lung cancer is as high as 48.9%. Surgery is the best and effective method in the early stage of the lung cancer. However, only 15% of the diagnosed patients are suitable for early-stage surgery. Surgery only is no longer considered for those being diagnosed at the middle to the late stage. Treatment for patients with middle-stage and late-stage may involve chemotherapy, radiotherapy, or a concurrent chemoradiation therapy. Radiation therapy, which is one of the primary therapeutic approaches for non-small cell lung cancer, is a treatment that uses high-energy rays or particles that destroy lung cancer cells. Radiation-induced lung damage (RILD) is a severe complication of radiotherapy in lung cancer patients that presents as a progressive pulmonary injury affecting prognosis and quality of life in patients.
In this study a longitudinal registration algorithm is proposed for evaluating the lung parenchyma change after radiotherapy and the correlation to the given radiation strength and distribution of dosage. The proposed registration algorithm overcomes the large parenchyma change which makes the registration much harder by using anatomical structures around the lung, including using spine for the reference set of rigid registration step; using three anatomical structures: bone structures surface, including sternal, rib and spine, airway wall and surface of lower lung to describe the longitudinal difference of breath holding degree. Reference points are sampled from these three anatomical feature structures for the further step of coherent point set registration.
Registered by the proposed longitudinal registration algorithm developed by this study, the correlation of regional dose distribution with longitudinal parenchyma change has been evaluated and obvious parenchyma change in the region of radiation dosage above 22 Gy and in 3~7 month is observed.


誌謝 i
中文摘要 ii
ABSTRACT iii
目錄 iv
圖目錄 vi
表目錄 ix
第一章 緒論 1
1.1. 研究背景 1
1.1.1 肺癌介紹及治療方式 1
1.1.2 放射線治療造成之正常肺部組織損傷 2
1.2. 研究動機與目的 4
第二章 文獻探討 7
2.1.1 肺功能損傷與臨床肺功能之關聯性 7
2.1.2 肺實質損傷量化分析 7
2.1.3 量化分析中使用的多時間點對位技術探討 9
第三章 研究材料與方法 10
3.1. 研究材料 10
3.2. 演算法流程 11
3.3. 影像來源前處理 13
3.4. 肺區周圍解剖特徵擷取 13
3.4.1 骨骼組織分割 13
3.4.2 脊椎擷取 15
3.4.3 支氣管壁分割 15
3.4.4 肺部下緣分割 16
3.5. 剛性對位演算法 17
3.6. 解剖特徵點集合參考點擷取 20
3.7. 非剛性對位演算法 22
3.8. 肺實質變化與治療劑量探討 27
第四章 結果與討論 28
4.1. 參考點選取對於對位結果之影響比較 28
4.1.1 僅使用骨骼組織作為參考點之結果 29
4.1.2 使用骨骼與氣管壁作為參考點之結果 29
4.1.3 肺部下緣參考點對於對位之影響 31
4.2. 多時間點對位演算法評估 32
4.3. 肺實質影像變化劑量區間分析 35
第五章 結論與未來展望 37
參考文獻 39


1. Bernard WS, Christopher PW (2014) World Cancer Report 2014. International Agency for Research on Cancer. World Heal. Organ. Lyon, Fr.
2. 行政院衛生署統計公布欄 http://www.mohw.gov.tw.
3. 台灣癌症登記中心. http://tcr.cph.ntu.edu.tw/main.php.
4. 國家衛生研究院 (1998) 肺癌診治共識.
5. Oncology R (2013) Radiation pneumonitis: occurrence, prediction, prevention and treatment. 7:105–110.
6. Choi YW, Munden RF, Erasmus JJ, et al. (2004) Effects of radiation therapy on the lung: radiologic appearances and differential diagnosis. Radiographics 24:985–97; discussion 998. doi: 10.1148/rg.244035160
7. Aoki T, Nagata Y, Negoro Y, et al. (2004) Evaluation of lung injury after three-dimensional conformal stereotactic radiation therapy for solitary lung tumors: CT appearance. Radiology 230:101–8. doi: 10.1148/radiol.2301021226
8. Wang W, Xu Y, Schipper M, et al. (2013) Effect of normal lung definition on lung dosimetry and lung toxicity prediction in radiation therapy treatment planning. Int J Radiat Oncol Biol Phys 86:956–63. doi: 10.1016/j.ijrobp.2013.05.003
9. Vaidya M, Creach KM, Frye J, et al. (2012) Combined PET/CT image characteristics for radiotherapy tumor response in lung cancer. Radiother Oncol 102:239–45. doi: 10.1016/j.radonc.2011.10.014
10. Ma J, Zhang J, Zhou S, et al. (2010) Regional lung density changes after radiation therapy for tumors in and around thorax. Int J Radiat Oncol Biol Phys 76:116–22. doi: 10.1016/j.ijrobp.2009.01.025
11. Phernambucq ECJ, Palma DA, Vincent A, et al. (2011) Time and dose-related changes in radiological lung density after concurrent chemoradiotherapy for lung cancer. Lung Cancer 74:451–6. doi: 10.1016/j.lungcan.2011.05.010
12. Bernchou U, Schytte T, Bertelsen A, et al. (2013) Time evolution of regional CT density changes in normal lung after IMRT for NSCLC. Radiother Oncol 109:89–94. doi: 10.1016/j.radonc.2013.08.041
13. Graham M, Purdy J, Emami B (1999) Clinical dose–volume histogram analysis for pneumonitis after 3D treatment for non-small cell lung cancer (NSCLC). Int J … 45:323–329. doi: 10.1016/S0360-3016(99)00183-2
14. Rodrigues G, Lock M, D’Souza D, et al. (2004) Prediction of radiation pneumonitis by dose - volume histogram parameters in lung cancer--a systematic review. Radiother Oncol 71:127–38. doi: 10.1016/j.radonc.2004.02.015
15. Marks LB, Bentzen SM, Deasy JO, et al. (2010) Radiation dose-volume effects in the lung. Int J Radiat Oncol Biol Phys 76:S70–6. doi: 10.1016/j.ijrobp.2009.06.091
16. De Ruysscher D, Faivre-Finn C, Nestle U, et al. (2010) European Organisation for Research and Treatment of Cancer recommendations for planning and delivery of high-dose, high-precision radiotherapy for lung cancer. J Clin Oncol 28:5301–10. doi: 10.1200/JCO.2010.30.3271
17. Ghobadi G, Hogeweg LE, Faber H, et al. (2010) Quantifying local radiation-induced lung damage from computed tomography. Int J Radiat Oncol Biol Phys 76:548–56. doi: 10.1016/j.ijrobp.2009.08.058
18. Mah K, Van Dyk J (1988) Quantitative measurement of changes in human lung density following irradiation. Radiother Oncol 11:169–179. doi: 10.1016/0167-8140(88)90253-8
19. Wennberg B, Gagliardi G, Sundbom L, et al. (2002) Early response of lung in breast cancer irradiation: radiologic density changes measured by CT and symptomatic radiation pneumonitis. Int J Radiat Oncol 52:1196–1206. doi: 10.1016/S0360-3016(01)02770-5
20. Palma DA, van Sornsen de Koste JR, Verbakel WF a R, Senan S (2011) A new approach to quantifying lung damage after stereotactic body radiation therapy. Acta Oncol 50:509–17. doi: 10.3109/0284186X.2010.541934
21. Palma DA, Senan S, Haasbeek CJA, et al. (2011) Radiological and Clinical Pneumonitis After Stereotactic Lung Radiotherapy: A Matched Analysis of Three-Dimensional Conformal and Volumetric-modulated Arc Therapy Techniques. Int J Radiat Oncol 80:506–513.
22. Otsu N (1975) A threshold selection method from gray-level histograms. Automatica 11:23–27.
23. Zhang J, Yan C-H, Chui C-K, Ong S-H (2010) Fast segmentation of bone in CT images using 3D adaptive thresholding. Comput Biol Med 40:231–6. doi: 10.1016/j.compbiomed.2009.11.020
24. Berger JO (1985) Statistical Decision Theory and Bayesian Analysis. J Am Stat Assoc 83:266. doi: 10.2307/2288950
25. Matsopoulos GK, Delibasis KK, Mouravliansky N a, et al. (2003) CT-MRI automatic surface-based registration schemes combining global and local optimization techniques. Technol Health Care 11:219–32.
26. Ingber L (1993) Simulated annealing: Practice versus theory. Math Comput Model 18:29–57. doi: 10.1016/0895-7177(93)90204-C
27. Fritzke B (1995) A Growing Neural Gas Network Learns Topologies. Adv Neural Inf Process Syst 7 7:625–632. doi: 10.1.1.31.4273
28. Martinetz T (1993) Competitive Hebbian learning rule forms perfectly topology preserving maps. ICANN’93. Springer, pp 427–434
29. Myronenko A, Song X (2010) Point set registration: coherent point drift. IEEE Trans Pattern Anal Mach Intell 32:2262–75. doi: 10.1109/TPAMI.2010.46
30. Myronenko A, Song X, Carreira-Perpinan MA (2006) Non-rigid point set registration: Coherent point drift. Adv. Neural Inf. Process. Syst. pp 1009–1016
31. Murphy K, van Ginneken B, Reinhardt JM, et al. (2011) Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge. IEEE Trans Med Imaging 30:1901–20. doi: 10.1109/TMI.2011.2158349


QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top