臺灣博碩士論文加值系統

評估放射治療後誘發二次致癌風險對於小兒病人尤為重要，因為小兒的組織處於生長期與治癒後存活期較長，而目前的質子治療計畫系統對於照野外的器官劑量，並無考量質子所誘發中子輻射所造成的影響，另外文獻中亦缺乏合併考慮照野內外的輻射誘發癌症風險，鑑於上述三點，本研究目的是開發一個針對照野內外不同劑量範圍，選用各自適用的風險評估模型的臨床風險計算系統，並用其評估小兒腦瘤以擾動式質子治療後的二次致癌風險。
通過人體試驗委員會許可後，取得11位病人DICOM資料，擷取病患資訊並重建危急器官(Organ at risk, OAR)與射束之間的相對位置用以定義OAR屬於照野內或照野外。照野內外分別使用各自適用的風險評估模型，照野內由質子所造成高劑量區，使用學者Schneider開發的器官等價劑量模型(Organ equivalent dose, OED)，照野外由散射光子、質子與二次中子所造成的低劑量區，則參考BEIR VII報告中建立的線性風險模型。將照野內外的OAR致癌風險通過台灣人口背景生存機率的加權，計算累積至台灣平均壽命80歲的可歸因性終生危險度(Life attributable risk, LAR)作為風險分析標的。最後使用本風險計算系統評估11位臨床小兒腦瘤病患的二次致癌風險，分別比對其在擾動式質子技術與光子技術的治療計畫下，二次致癌風險的情況。
本研究所開發的臨床風險計算系統建構完成後，先根據已發表文獻比對驗證其可行性，再將此系統用於計算臨床小兒腦瘤病例。計算結果顯示小兒腦部OAR的LAR落在0~9 %之間，每個案例的LAR分布情形與PTV的體積大小與位置有關係。針對小兒腦瘤病患的風險評估比較質子計畫與光子計畫結果，在PTV偏離頭部中心或體積較小的群組裡，可明顯發現擾動式質子治療的風險低於光子治療。

Evaluating the risk of secondary cancer induction after radiation therapy is especially important in pediatric patients because the tissue of the child is in the growth phase and the survival period is longer after the cure, and the current proton therapy does not take into account the dose effects of proton-induced neutron radiation outside the field. In addition, there is also a lack of consideration in the literature to assess the conbination risk of induced cancer by inside and outside the field. Due to the above three points, the purpose of this study is to develop a suitable risk assessment module for different dose ranges inside and outside the field, using their respective risk assessment models, and to assess the secondary risk of pediatric brain tumors after wobbling proton therapy.
After approval by Institutional Review Board(IRB), 11 patients' DICOM data were obtained. Patient information was extracted and the relative position between the Organ at risk (OAR) and the beam was reconstructed to define whether the OAR in the field or out of the field. Select the appropriate risk assessment model inside and outside the field respectively. For high-dose areas(in field), use the Organ equivalent dose(OED) method developed by Uwe Schneider. For low-dose areas(out-of-field) deposited dose by scattered photon, proton and second neutron, refer to the linear risk model established in the BEIR VII report. The OAR radiation-induced cancer risk inside and outside the field was weighted by the survival probability of Taiwan's Life Table, and the life attributable risk(LAR) accumulated to the average life expectancy of Taiwan was calculated as the risk analysis target. Finally, this risk calculation system was used to evaluate the secondary carcinogenic risk of 11 clinical pediatric brain tumor patients, respectively, compared with the secondary cancer risk under the treatment plan of wobbling proton and photon technology.
After the construction of the clinical risk calculation system developed in this study, the feasibility of the system was verified based on the published literature, and the system was used to calculate clinical pediatric brain tumor cases. The calculation results show that the LAR of the pediatric brain OAR is between 0 % and 9 %. The LAR distribution in each case is related to the volume and location of PTV. For the risk assessment of pediatric brain tumor patients, the results of the proton and the photon treatment planning were compared. In the group which PTV locates in the out-of-center of the head or is smaller volume, the risk of wobbling proton therapy was significantly lower than that of photon therapy.

摘要 i
Abstract ii
致謝 iv
目錄 v
表目錄 viii
圖目錄 ix
第一章 緒論 1
1.1 研究目的及動機 1
1.2 研究方法與步驟 2
1.3 研究範圍與限制 4
1.4 名詞解釋 5
第二章 介紹與文獻回顧 9
2.1 擾動式質子治療 9
2.1.1 質子治療的發展 9
2.1.2 質子治療技術分類與原理 12
2.1.3 擾動式質子治療技術原理 15
2.2 輻射致癌評估 18
2.2.1 細胞對游離輻射的反應 18
2.2.2 輻射致癌機轉 20
2.2.3 輻射劑量反應調查報告 24
2.2.4 輻射致癌評估模型 29
第三章 研究設計與方法 33
3.1 輻射致癌計算模型 33
3.1.1 高劑量模型 33
3.1.2 低劑量模型 42
3.1.3 未列表之特定器官 45
3.2 臨床風險計算系統建構 47
3.2.1 臨床病例取得與篩選 47
3.2.2 治療計畫 49
3.2.3 治療計畫檔案處理 51
3.2.4 器官位置定義 53
3.2.5 劑量數據 61
3.2.6 計算風險值 69
3.3 程式碼架構 72
第四章 結果與討論 80
4.1 系統驗證 80
4.2 風險結果 85
4.3 總覽與討論 103
第五章 結論與未來工作 107
5.1 研究結論 107
5.2 未來工作 108
參考資料 110
附錄 119
I. Matlab程式碼I：Export data 119
II. Matlab程式碼II：Initialization 123
III. Matlab程式碼III：Process data 126
IV. Matlab程式碼IV：Risk calculation 128