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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 簡國龍(Kuo-Liong Chien),施庭芳(Tiffany Ting-Fang Shih) | |
dc.contributor.author | Jane Wang | en |
dc.contributor.author | 王甄 | zh_TW |
dc.date.accessioned | 2021-05-20T21:18:49Z | - |
dc.date.available | 2018-01-05 | |
dc.date.available | 2021-05-20T21:18:49Z | - |
dc.date.copyright | 2011-03-03 | |
dc.date.issued | 2011 | |
dc.date.submitted | 2011-01-05 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/10307 | - |
dc.description.abstract | 背景與目的:
乳房熱攝影是一偵測腫瘤之生理現象之檢查。我們的研究目的,是欲評估兩類熱攝影- 靜態及動態熱攝影之診斷表現,並要分析乳房熱攝影表徵與預測乳癌預後因子之相關性。這些預測乳癌預後因子包括動情激素接受體 (ER) 及黃體素接受體 (PR)、人體上皮生長因子接受體2 (HER2)、臨床分級、組織分級。 方法: 本研究為橫斷性研究,是以在乳房X光攝影或超音波有局部病灶之女性為研究對象。我們將由五種熱攝影表徵樹立靜態熱攝影評分系統。我們將把年齡及上述表徵置入模型,並以多變數邏輯式迴歸模型及接受操作特徵曲線 (Receiver operating characteristics, ROC) 來評估診斷表現。 在接受靜態及動態熱攝影之次族群,判讀表徵包括二靜態及二動態表徵。我們將由只含靜態表徵 (模型A) 及含靜態、動態表徵之年齡調整模型 (模型B),估計二種模型之接受操作特徵曲線下面積 (Area under the ROC curve, AUC)。 我們將分析靜態及動態熱攝影表徵與乳癌預後因子相關性之評估。 結果: 在靜態熱攝影方面,共有298個病灶接受分析。其適切模型之AUC為0.781 (95%信賴區間0.683-0.855)。當敏感度為94.3%時,特異度為30.4%。在171個惡性病灶中,二表徵與ER成反向相關 (P值0.010,0.037)。三表徵和PR成反向相關 (P值0.039,0.020,0.022)。Triple-negative (即ER、PR、HER2皆陰性) 之乳癌傾向有較高之熱攝影評分 (和其他類相比,P值0.029)。一表徵和臨床分級正相關 (P值0.008)。在128例侵襲性乳管癌中,一表徵和組織分級成正相關 (P值0.037)。 本研究中有56個病灶有靜態及動態熱攝影資料供分析。由模型A及B 之 AUC均為0.744 (95%信賴區間: 模型A,0.512-0.978; B,0.514-0.975)。在敏感度100%時,二模型之特異度均為33.3%。在其中之26惡性病灶中,一動態表徵和ER成反向相關 (P值0.021),二動態表徵和HER2成正相關 (P值0.015,0.033)。一靜態表徵與侵襲性乳管癌組織分級成正相關 (P值0.006,22例病灶)。 結論: 當乳房熱攝影之敏感度>90%時,特異度相對地偏低。動態熱攝影並未比靜態熱攝影更顯著地增加診斷準確度。乳房熱攝影表徵可能在將來可以做為預測乳癌預後之指標。 | zh_TW |
dc.description.abstract | Background and Objective:
Breast thermography is an examination which delineates physiological response of the tumor. The purpose of our study is to evaluate the diagnostic performance of the two types of breast thermography- steady-state and dynamic thermography, and investigate the association of thermographic signs with breast cancer prognostic indicators, including ER (estrogen receptor), PR (progesterone receptor), HER2 (human epidermal growth factor receptor 2) statuses, clinical staging, and histologic grade. Methods: We conducted a cross-sectional study, and enrolled women who had suspicious findings on mammography or breast ultrasound. We interpreted steady-state thermography using five thermographic signs and evaluated the diagnostic performance by ROC analysis (Receiver operating characteristics) from age-adjusted multiple logistic regression model For the subpopulation of women receiving both steady-state and dynamic thermography, the interpretation was determined by the two steady-state signs and two dynamic signs. The age-adjusted logistic regression models with only steady-state signs (model A) and with both steady-state and dynamic signs (model B), and the resulting AUC (Area under the ROC curve) can be derived. The association of thermographic signs and the prognostic indicators of the cancerous lesions were estimated for steady-state thermography and dynamic thermography. Results: A total of 298 breast lesions were included for steady-state thermographic study. The AUC was 0.781 for the fitted model (95% CI: 0.683-0.855). The specificity was 30.4% when the sensitivity was 94.3%. Of the 171 cancerous lesions, two thermographic signs were inversely associated with ER (P=0.010 and 0.037), and three signs were inversely associated with PR (P=0.039, 0.020, and 0.022). Triple-negative (ER, PR, and HER2 negative) cancers tended to show higher thermographic scores than other types of cancers (P =0.029). One thermographic sign was positively associated with clinical staging (P=0.008). One thermographic sign was positively associated with histologic grade of invasive ductal carcinoma (n=128; P=0.037). There were 56 lesions with both steady-state and dynamic images available. The AUC was both 0.744 for the models A and B (95% CI: model A, 0.512-0.978; B, 0.514-0.975), and the specificity was 33.3% when the sensitivity was 100% for both models. Of the 26 malignant lesions, one of the dynamic signs was inversely associated with ER (P=0.021). The two dynamic signs were positively associated with HER2 status (P=0.015 and 0.033). One steady-state sign was positively related with the histologic grade of invasive ductal carcinoma (P=0.006; n=22). Conclusion: The specificity of breast thermography was low when the sensitivity >90%. Dynamic thermography did not show additional diagnostic yield than steady-state thermography. The thermographic signs may be predictive of breast cancer prognosis. | en |
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dc.description.tableofcontents | 論文口試委員審定書 I
序言 III 中文摘要 IV 英文摘要 (Abstract) VI 內容綱要 (Table of Contents) VIII List of Tables XI List of Figures XIV 英文縮寫對照表 XVI 第一章 研究背景 1 第一節 臨床常使用之乳房疾病診斷影像工具 1 第二節 何謂熱攝影 (Thermography) 1 第三節 乳房熱攝影 (Breast thermography) 之緣起及現況 2 1.3.1 乳房熱攝影於區分良性或惡性病灶之輔助診斷角色 2 1.3.2 乳房熱攝影應用於乳癌篩檢之概況 5 1.3.3 乳房熱攝影做為未來罹癌之風險指標 6 1.3.4 乳房熱攝影於預測乳癌患者長期預後之研究 7 1.3.5 乳房熱攝影用於監測乳癌治療後之療效 7 第四節 乳房熱攝影之種類 8 1.4.1 乳房靜態熱攝影 8 1.4.2 乳房動態熱攝影 8 第五節 常用於乳房熱攝影之判讀標準 12 1.5.1 乳房靜態熱攝影之判讀標準之研究 12 1.5.2 乳房動態熱攝影之判讀標準 14 第六節 以生物醫學工程之人工智慧方式判讀乳房熱攝影 14 第七節 以ROC分析應用於乳房熱攝影 15 第八節 乳房熱攝影與乳癌病灶分子標記及預後之相關性 16 第九節 評估乳房熱攝影在臨床之運用 16 1.9.1 臨床乳房影像判讀時可能關切之問題 16 1.9.2 乳房熱攝影於臨床乳房影像可能之應用方向 18 第二章 研究假說及目的 20 第一節 研究假說 20 第二節 研究目的 20 第三章 研究方法 21 第一節 研究設計 21 第二節 受試者選取 21 3.2.1 受試者納入條件 21 3.2.2 受試者排除標準 21 3.2.3 研究贊助及倫委會核准 22 第三節 乳房熱攝影檢查之操作方法 22 3.3.1 乳房熱攝影機器介紹 22 3.3.2 乳房靜態熱攝影之做法 23 3.3.3 乳房動態熱攝影之做法 23 第四節 乳房熱攝影之影像後處理與分析 24 3.4.1 影像判讀之先決條件 24 3.4.2 乳房靜態熱攝影之判讀 24 3.4.3 乳房動態熱攝影之判讀指標 26 第五節 乳房熱攝影與乳癌病灶分子標記與預後相關性之分析 27 第六節 統計方法 29 3.6.1 受試者臨床描述性資料之分析 29 3.6.2 乳房靜態熱攝影判讀系統之分析 29 3.6.3 靜態熱攝影之樣本數 (sample size) 及檢定力 (power) 估計 32 3.6.4 動態熱攝影診斷表現之分析及評估 33 3.6.5 動態熱攝影之樣本數及檢定力估計 35 第四章 結果 37 第一節 靜態熱攝影之結果 37 4.1.1 靜態熱攝影之臨床納入流程 37 4.1.2 靜態熱攝影受試者基本資料之呈現 37 4.1.3 靜態熱攝影IR表徵之單變數分析 38 4.1.4 靜態熱攝影判讀模型之樹立 38 4.1.5 靜態熱攝影在較小病灶之診斷表現 39 4.1.6 靜態熱攝影在較低BI-RADS®分級之診斷表現 40 4.1.7 靜態熱攝影判讀一致性分析 40 4.1.8 靜態熱攝影與乳癌分子標記及預後之相關性 40 第二節 動態熱攝影之判讀結果與診斷表現 42 4.2.1 受試者納入流程 42 4.2.2 動態熱攝影受試者之描述性資料分析 42 4.2.3 動態熱攝影之判讀指標之描述性分析 43 4.2.4 動態熱攝影指標之單變數分析 43 4.2.5 動態熱攝影指標之相關性分析 44 4.2.6 動態熱攝影判讀模型之樹立 44 4.2.7 較小病灶在動態熱攝影之結果分析 45 4.2.8 較低BI-RADS®分級之病灶在動態熱攝影之結果分析 45 4.2.9 動態熱攝影和乳癌分子標記及預後之相關性 46 第五章 討論 48 第一節 乳房靜態熱攝影 48 5.1.1 靜態熱攝影判讀表徵之樹立與診斷表現 48 5.1.2 靜態熱攝影與乳癌病灶之分子標記及預後之相關性 51 第二節 乳房動態熱攝影 53 5.2.1 動態熱攝影判讀表徵之樹立與診斷表現 53 5.2.2 乳房動態熱攝影與乳癌分子標記與預後之相關性 56 第三節 總結 58 參考文獻 59 List of Tables I. Tables from Systematic review Table I-1. Systematic review of breast thermography 67 Table I-2. Ville Marie Infrared Imaging (IR) Grading Scale (modified from Keyserlingk et al., 1998) 72 Table I-3. The diagnostic performance of dynamic thermography of the breast (modified from Jurist et al., 1982) 73 Table I-4. The diagnostic performance of non-subtraction dynamic thermography and subtraction thermography of the breast (modified from Usuki et al.,1991) 74 IV. Tables of Results Table IV-1. Clinical and conventional imaging findings for women receiving steady-state thermography. 75 Table IV-2. Lesion BI-RADS® distribution in conventional imaging for women receiving steady-state thermography 76 Table IV-3. Analysis of steady-state thermographic signs and the final results by univariate analysis without and with age-adjustment………………………. 77 Table IV-4. Basic characteristics in training and validated sets in steady-state breast thermography 78 Table IV-5. Diagnostic performance of steady-state thermography of the breast 79 Table IV-6. Subgroup analysis of validated set in steady-state thermography 80 Table IV-7. Subgroup diagnostic performance of steady-state thermography of the breast 81 Table IV-8. Lesion characteristics of breast cancer in women receiving steady-state thermography 82 Table IV-9. The association of steady-state thermographic findings with ER, PR, HR, HER2 statuses, and three composite types of breast cancer 83 Table IV-10. The histologic grade and ER, PR, HR, HER2 statuses, composite types of invasive breast carcinomas on steady-state thermography 84 Table IV-11. Steady-state thermographic findings and histologic grade of invasive breast carcinomas 85 Table IV-12. Clinical and conventional imaging findings of women receiving dynamic thermography of the breast 86 Table IV-13. The BI-RADS® distribution for women receiving dynamic thermography of the breast 87 Table IV-14. Descriptive and univariate analysis of the thermographic signs in dynamic thermography 88 Table IV-15. The correlation analysis of the diagnostic signs in dynamic thermography 90 Table IV-16. Basic characteristics in training and validated sets in dynamic thermography 91 Table IV-17. Diagnostic performance of dynamic thermography 92 Table IV-18. Subgroup analysis of women receiving dynamic thermography 93 Table IV-19. The lesion characteristics of breast cancer in women receiving dynamic thermography 94 Table IV-20. The association of thermographic signs with ER, PR, HR, HER2 statuses and composite types for breast cancer in patients receiving dynamic thermography 96 Table IV-21. The histologic grade and ER, PR, HR, HER2, composite types of invasive ductal carcinomas in women receiving dynamic thermography of the breast 97 Table IV-22. The association of thermographic signs and grades of invasive ductal carcinomas in patients receiving dynamic thermography 98 List of Figures Figure 1. The presentation of breast thermographic signs (modified from Gautherie et al., 1982 and Hobbins et al., 1983). 99 Figure 2. The thermographic machine. 104 Figure 3. Flow chart of subject enrollment for steady-state thermography of the breast. 105 Figure 4. The ROC curves for the two models of the validated set (n=99) of lesions from the patients receiving steady-state mammography. 106 Figure 5. A 63-year-old woman with a grade III invasive ductal carcinoma in the right upper breast. 107 Figure 6. A 42-year-old woman with a benign lesion (fibrocystic change verified by surgical pathology) in right breast. 109 Figure 7. The distribution of IR1 scores in different composite types in malignant lesions from patients receiving steady-state thermography. 110 Figure 8. The distribution of IR2 score in different clinical staging in malignant lesions from patients receiving steady-steady thermography of the breast. 112 Figure 9. The enrollment of the lesions from patients receiving dynamic thermography of the breast. 113 Figure 10. A 64-year-old woman who received both steady-state and dynamic thermography of the breast, and with a grade III invasive ductal carcinoma in right breast proven by histopathology. 114 Figure 11. The ROC curves of lesions from validated set (n=19) of patients receiving dynamic thermography of the breast. 117 Figure 12. The distribution of tdPostmPreT values in benign and malignant lesions <=1cm from patients receiving dynamic thermography of the breast, presented as dotplot. 118 Figure 13. The distribution of tdPostmPreT values between benign and malignant lesions which were interpreted as BI-RADS 3 or 4A findings on conventional imaging. 119 Figure 14. The dotplot distribution of diagnostic signs of dynamic thermography in malignant lesions with different molecular subtypes. 120 Figure 15. The dotplot distribution of dPreT in grade I, II versus grade III invasive ductal carcinomas from patients receiving dynamic thermography. 122 | |
dc.language.iso | zh-TW | |
dc.title | 靜態熱攝影與動態熱攝影於乳癌診斷之應用 | zh_TW |
dc.title | Use of steady-state thermography and dynamic thermography in breast cancer diagnosis | en |
dc.type | Thesis | |
dc.date.schoolyear | 99-1 | |
dc.description.degree | 博士 | |
dc.contributor.oralexamcommittee | 蔡育秀,沈戊忠,李文宗,程蘊菁,郭文宏 | |
dc.subject.keyword | 乳房熱攝影,診斷表現,乳房腫瘤。, | zh_TW |
dc.subject.keyword | Breast thermography,diagnostic performance,breast neoplasms., | en |
dc.relation.page | 122 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2011-01-05 | |
dc.contributor.author-college | 公共衛生學院 | zh_TW |
dc.contributor.author-dept | 流行病學與預防醫學研究所 | zh_TW |
顯示於系所單位: | 流行病學與預防醫學研究所 |
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