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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 張允中(Yeun-Chung Chang) | |
dc.contributor.author | Ning Chien | en |
dc.contributor.author | 簡寧 | zh_TW |
dc.date.accessioned | 2021-06-17T08:44:54Z | - |
dc.date.available | 2019-08-27 | |
dc.date.copyright | 2019-08-27 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-08-06 | |
dc.identifier.citation | 衛生署福利部國民健康署105年癌症登記年報
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X., and M. M. Cheung. 2010. 'MR diffusion kurtosis imaging for neural tissue characterization', NMR Biomed, 23: 836-48. Yabuuchi, Hidetake, Yoshio Matsuo, Takeshi Kamitani, Taro Setoguchi, Takashi Okafuji, Hiroyasu Soeda, Shuji Sakai, Masamitsu Hatakenaka, Makoto Kubo, Eriko Tokunaga, Hidetaka Yamamoto, and Hiroshi Honda. 2010. 'Non-mass-like enhancement on contrast-enhanced breast MR imaging: Lesion characterization using combination of dynamic contrast-enhanced and diffusion-weighted MR images', European Journal of Radiology, 75: e126-e32. Zahra, M. A., K. G. Hollingsworth, E. Sala, D. J. Lomas, and L. T. Tan. 2007. 'Dynamic contrast-enhanced MRI as a predictor of tumour response to radiotherapy', Lancet Oncol, 8: 63-74. Zhang, S. X., Q. J. Jia, Z. P. Zhang, C. H. Liang, W. B. Chen, Q. H. Qiu, and H. Li. 2014. 'Intravoxel incoherent motion MRI: emerging applications for nasopharyngeal carcinoma at the primary site', Eur Radiol, 24: 1998-2004. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74598 | - |
dc.description.abstract | 背景
乳癌乃本國女性新診斷癌症之首,過去文獻指出乳房磁振造影對於協助診斷乳房病灶擁有較乳房攝影更高的敏感度,然而其特異性與對於乳房病灶之診斷效度仍有進步空間。 目的 本研究目的希望透過分析多項新穎磁振造影參數以探討並提升乳房病灶辨別之準確性。本研究透過探討磁振造影之 1)擴散係數影像 (Diffusion-weighted Imaging, DWI)、2) 擴散峰度影像 (Diffusion Kurtosis Imaging, DKI ) 、 3) 內體素不相干運動(Intravoxel Incoherent motion, IVIM) 、 4) 動態對比增強磁振造影(Dynamic Contrast-enhanced MRI; DCE-MRI)等四項技術所衍生之參數,與比較各參數之差異性以尋求辨別乳房病灶之最佳影像工具。 研究方法 本研究為前瞻性研究,研究對象為臨床乳房超音波發現可疑乳房腫瘤且須切片之病患,於病患接受切片前執行磁振造影,單一次造影過程中收集DWI、DKI、IVIM及DCE-MRI等影像,並計算其定量參數。各參數在良惡腫瘤之間的統計差異性使用Student t-test檢定,而各參數辨別乳房病灶良惡性之效度則以接收者操作特徵曲線(Receiver Operating Characteristic curves, ROC curves)作為評量基準。 結果與討論 本研究總共分析來自於57名病人之61個乳房病灶(22個良性病灶與39個惡性腫瘤)。於各類別參數中,DCE-MRI的kep, ve、DWI之ADC、DKI之D與K、以及IVIM之D*等指標,均顯示在良惡性乳房腫瘤間有顯著差異(p<0.05)。其中從DKI所得之參數D(平均擴散係數)為最準確的診斷指標(AUC=0.957),同時特異性高達100%。DCE-MRI之Ktrans與IVIM之f則在良惡性乳房腫瘤之間沒有顯著差異。 結論 本研究採用一合併新穎擴散磁振成像技術與動態對比增強磁振造影之模型作為分析乳房腫瘤之工具,並比較各種定量參數之診斷效度。結果發現由擴散峰度影像與內體素不相干運動所計算出之定量參數診斷效度優於動態對比增強造影之定量參數。 | zh_TW |
dc.description.abstract | Abstract
Background Breast cancer is the most commonly diagnosed cancer among women in Taiwan. Breast magnetic resonance imaging (MRI) is a sensitive imaging technique to assess breast cancer but its effectiveness still remains to be improved. Objectives Our study aim was to assess MRI diagnostic accuracy for breast lesions by comparing quantitative parameters derived from 1) diffusion-weighted imaging (DWI), 2) diffusion kurtosis imaging (DKI), 3) intravoxel incoherent motion (IVIM) and 4) dynamic contrast-enhanced MRI (DCE-MRI) and to explore an optimal model for breast tumor differentiation. Methods This was a prospective study performed on patients with suspicious breast lesions found on breast sonography prior to biopsy. All MR experiments were conducted on a 3-T MRI scanner. Quantitative parameters from DWI (apparent diffusion coefficient, ADC; fractional anisotropy, FA), DKI (mean diffusivity, D; mean kurtosis, K), IVIM (pseudo-diffusion coefficient, D*; perfusion fraction, f) and DCE-MRI (Ktrans, kep, ve and vp) were derived and compared between malignant and benign lesions. These parameters in benign and malignant lesions were compared by GEE. (Generalized estimating equations). Area under the receiver-operating characteristic (ROC) curve (AUC) analysis was used to evaluate diagnostic accuracy among parameters. Results and Discussion Total 61 suspicious breast lesions from 57 patients were evaluated in this prospective study. The quantitative parameters, including kep and ve from DCE-MRI, ADC, D, DSTD, DMINIMUM, K, KSTD and KMINIMUM from DKI between benign and malignant lesions were significantly different (p<0.05). DMINIMUM derived from DKI demonstrated the largest AUC (0.93) and had the highest specificity (95.45%). The Ktrans from DCE-MRI and those parameters derived from IVIM were shown to be not significantly different between benign and malignant lesions. Conclusion In this study, we investigated the effectiveness of differentiating malignant breast tumors from benign ones by using a DKI-IVIM approach. The quantitative parameters derived from DKI and IVIM have been proved to be more accurate than perfusion parameters derived from DCE-MRI and conventional ADC. Key Words: MRI, breast tumors, breast cancer, DCE, DKI, IVIM, diffusion, kurtosis, intravoxel incoherent motion | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T08:44:54Z (GMT). No. of bitstreams: 1 ntu-108-P06421012-1.pdf: 1896053 bytes, checksum: d9a4c5a78157ec0a07f19cffb3c23820 (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | Table of contents
摘要 1 Abstract 2 Objectives 2 Methods 2 Results and Discussion 2 Conclusion 3 Abbreviations 3 1. Introduction 5 1.1 Dynamic Contrast-Enhanced MRI (DCE-MRI) 5 1.2 Diffusion-Weighted Imaging (DWI) 6 1.3 Diffusion Kurtosis Imaging (DKI) 7 1.4 Intravoxel Incoherent Motion (IVIM) 9 2 Materials and Methods 12 2.1 Patient selection and data collection 12 2.2 MRI sequences 13 2.3 DCE parameters 14 2.4 DWI parameters 14 2.5 DKI parameters 15 2.6 IVIM parameters 16 2.7 Image analysis 16 2.8 Histogram Analysis 17 2.9 Statistical analysis 17 3 Results 19 3.1 Pathological types of the lesions 19 3.2 Diagnostic performance of the DCE parameters 20 3.3 Diagnostic performance of the DWI parameters 20 3.4 Diagnostic performance of the DKI parameters for benign and malignant lesions 21 3.5 Diagnostic performance of the IVIM parameters for benign and malignant lesions 21 3.6 Comparison among different parameters 22 4 Discussions 24 5 Outlook 32 6 Summary 34 7 Reference 36 Table 1 Clinical Data of Patients and lesions 43 Table 2 Association Between Quantitiative Parameters and Pathologic Diagnosis 44 Table 3 Comparison of diagnostic accuracy among parameters 47 Table 4-1 Comparison of DCE parameter features in benign and different grades of malignancy 50 Table 4-2 Comparison of DKI parameter features in benign and different grades of malignancy 52 Table 4-3 Comparison of IVIM parameter features in benign and different grades of malignancy 53 Figure 1-1 Boxplot of ADC and DCE parameters 54 Figure 1-2 Boxplots of ADC, DKI and IVIM parameters 55 Figure 2-1 Receiver operating characteristic curves to assess performance of ADC and DCE parameters for discriminating malignant and benign lesions. 57 Figure 2-2 Receiver operating characteristic curves to assess performance of the parameters from ADC and DKI for discriminating malignant and benign lesions. 58 Figure 2-3 Receiver operating characteristic curves to assess performance of the parameters from ADC and IVIM for discriminating malignant and benign lesions. 59 Figure 2-4 Receiver operating characteristic curves to assess performance of the parameters from ADC and the most accurate parameters from each group for discriminating malignant and benign lesions. 60 Figure 3 MR color multiparameteric images in a case of invasive ductal carcinoma 61 Figure 4 MR color multiparameteric images in a case of fibroadenoma 62 | |
dc.language.iso | en | |
dc.title | 乳房腫瘤在磁振造影擴散係數上之特性分析:擴散峰度影像與內體素不相干運動之比較 | zh_TW |
dc.title | Characterization of Breast Tumors: Comparison among Diffusion Kurtosis Imaging (DKI) and Intravoxel Incoherent Motion (IVIM) | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 郭立威(Li-Wei Kuo),楊偉勛(Wei-Shiung Yang) | |
dc.subject.keyword | 磁振造影,乳房腫瘤,乳癌,動態顯影,擴散峰度影像,內體素不相干運動, | zh_TW |
dc.subject.keyword | MRI,breast tumors,breast cancer,DCE,DKI,IVIM,diffusion,kurtosis,intravoxel incoherent motion, | en |
dc.relation.page | 60 | |
dc.identifier.doi | 10.6342/NTU201902542 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2019-08-07 | |
dc.contributor.author-college | 醫學院 | zh_TW |
dc.contributor.author-dept | 臨床醫學研究所 | zh_TW |
顯示於系所單位: | 臨床醫學研究所 |
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