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系統識別號 U0026-2208201723263300
論文名稱(中文) 以超音波逆散射訊號和統計模型對活體內肝組織纖維化之定量分析
論文名稱(英文) In vivo Quantitative Assessment of Hepatic Fibrosis by Ultrasonic Backscattering and Statistical Model
校院名稱 成功大學
系所名稱(中) 資訊工程學系
系所名稱(英) Institute of Computer Science and Information Engineering
學年度 105
學期 2
出版年 106
研究生(中文) 黃柏諺
研究生(英文) Bo-Yen Huang
學號 P76041425
學位類別 碩士
語文別 英文
論文頁數 59頁
口試委員 指導教授-王士豪
口試委員-孫永年
口試委員-江青芬
口試委員-方佑華
口試委員-吳佳慶
中文關鍵字 Nakagami 統計模型  超音波逆散射訊號  參數成像  肝臟纖維化  活體實驗 
英文關鍵字 Nakagami statistical model  ultrasonic backscattering signal  parametric imaging  liver fibrosis  in vivo experiment 
學科別分類
中文摘要 肝臟穿刺是臨床上最準確的評估肝臟纖維化程度或肝硬化的方法,但為侵入式的評估,有造成氣胸、出血、感染或死亡的風險。除此之外,大鼠常被應用在肝臟研究當中,實驗中需要犧牲大量的大鼠來驗證或評估其肝纖維化程度或降低取樣誤差。而本研究的目的為利用醫療用超音波和IB、Nakagami統計參數,以活體實驗和非侵入式的方式評估肝臟纖維化。Sprague Drawley大鼠將被使用於實驗當中,實驗組使用四氯化碳進行肝纖維化的誘發,另有控制組對照,並使用7.5MHz的單振源換能器、Nakagami 統計參數和IB,對健康、輕度和嚴重的肝臟纖維化做定量評估。B-mode影像上,輕度纖維化和嚴重纖維化的影像亮度明顯大於控制組,輕度纖維化和嚴重纖維化的影像上並沒有顯著的差異。在IB方面控制組為–131.9±3.3dB,在輕度纖維化為–117.3±0.8dB和控制組間的p-value小於0.01,在嚴重纖維化的IB為–114.0±2.5dB和輕度纖維化的IB間的p-value小於0.05。但IB為逆散射訊號強度,容易受到系統設定和入射波角度等等的影響,Nakagami統計參數則是利用逆散射訊號的包封訊號分析散射子在生物組織中的特性。在控制組的Nakagami參數為0.58±0.03表示為前雷利分布,輕度纖維化的Nakagami參數為0.78±0.02表示為前雷利分布且散射子數量及濃度多於控制組,控制組和輕度纖維化的Nakagami參數間的p-value小於0.01。在嚴重纖維化的Nakagami參數為0.83±0.02表示為前雷利分布且散射子數量及濃度多於輕度纖維化的組別,且輕度纖維化和嚴重纖維化的Nakagami統計參數間的p-value小於0.05。在Nakagami影像中,可以在影像中得知區域性的散射子特性,像是區域性的散射子分布、濃度和數量。最後,因為傳統灰階B-mode影像目前還是廣泛使用於醫療當中,在未來可以把Nakagami影像中的區域性散射子特性加入傳統B-mode影像當中,增加肝臟纖維化在影像上的不同程度上的辨識度。
英文摘要 In general, the liver biopsy is the most accurate method to assess liver fibrosis. The liver biopsy is a procedure to remove a small piece from liver tissue and it is invasive that can cause many complications. Besides, rats are widely used in liver fibrosis experiments and a lot of rats are sacrificed to verify, assess the liver fibrosis level and reduced the sampling errors. Therefore, ultrasound and statistical parameters were used to assess the liver fibrosis as a non-invasive method in this study. Sprague Dawley rats were induced liver fibrosis by CCl4. A 7.5MHz single element transducer was used in ultrasound system. Nakagami parameter and IB were used to quantitatively assess the liver fibrosis as a non-invasive method. B-mode images of mild and severe groups were significantly brighter than control group, but the difference of brightness between mild and severe groups were not significant. IB of control group was –131.9±3.3dB, mild group was –117.3±0.8dB, and severe group was –114.0±2.5dB. The p-value of IB between control group and mild group was small than 0.01 when the p-value of IB between mild group and severe group was small than 0.05. IB was the strength of backscattering signals, which was easily affected by ultrasound system and the angle of incident signals. Nakagami statistical parameter could indicate the scatterer properties by ultrasonic backscattering signals. Nakagami parameter of control group was 0.58±0.03, mild group was 0.78±0.02, and severe group was 0.83±0.02. The scatterer distribution of control group, mild group, and severe group were pre-Rayleigh distribution. The p-value of Nakagami parameter between control group and mild group was small than 0.01 when the p-value of Nakagami parameter was small than 0.05. Nakagami images could show the local scatterer properties which B-mode images could not. In the end, B-mode images are still widely used in medical field, so the Nakagami images can provide the local information to B-mode images and make the more accurate assessment of liver fibrosis stages.
論文目次 摘要……………………………………………………………………………………I
Abstract …………………………………………………………………………….III
誌謝…………………………………………………………………………………...V
Table of Contents VI
List of Tables VIII
List of Figures VIII
Chapter 1: Introduction 1
1.1 Ultrasound 1
1.2 Liver fibrosis 2
1.3 Quantitative analysis of ultrasound 2
1.4 Ultrasonic Statistical models 3
1.5 Research Motivation and Objectives 4
Chapter 2: Theoretical Background 6
2.1 Theory of Ultrasonic Wave Propagation 6
2.1.1 Reflection and Refraction 8
2.1.2 Attenuation and Absorption 10
2.1.3 Ultrasonic Scattering 11
2.1.4 Ultrasonic Transducers 16
2.1.5 Sound Field 19
2.2 Statistical Models for Ultrasonic Backscattering signals 20
Chapter 3: Materials and Methods 29
3.1 Animal model 29
3.2 Experimental Arrangement 29
Chapter 4: Results 36
4.1 Ultrasonic statistical model 36
4.2 Histological Sections 48
Chapter 5: Discussion 49
Chapter 6: Conclusions and Future Works 51
6.1 Conclusions 51
6.2 Future Works 52
References 53
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