肝臟超音波背散射訊號之一階統計值於肝纖維化偵測的應用

The Detection of Liver Fibrosis based on the First-Order Statistics of the Backscattered Ultrasonic Signal of Liver Tissue

劉至偉(Chih-Wei Tsao)

指導教授 ： 曹建和

國立臺灣大學/電機資訊學院/生醫電子與資訊學研究所/碩士(2010年)

https://doi.org/10.6342/NTU.2010.01280

摘要

肝纖維化為慢性肝炎引起的常見症狀，除了會演化成肝硬化外，亦是肝臟受損的歷程記錄，因此肝纖維化的診斷一直是監控慢性肝炎的重要指標。肝纖維化診斷的黃金標準為肝穿刺，但肝穿刺是侵入性手術，因此難以普遍施行，以致肝纖維化第一線的診療儀器還是腹部超音波影像儀器。但肝纖維化於超音波影像的診斷一直難有可靠的準確度且難以量化，因此我們希望利用超音波影像的RF訊號於工程層面輔助醫生診斷。
由前人研究知肝臟超音波影像雖為Speckle組成的影像，但Speckle並非毫無資訊。利用訊號的一階統計參數值，可以推測出散射子的狀態。而由肝纖維化的病理進程，我們發現當重度肝纖維化時，影響肝臟結構的散射特性分為兩個層面：一個是規律性的打亂；而另一個是造成散射截面的不均勻。由前人研究我們得知Nakagami分布的參數m值，對這兩個特性都能有效描述。因此我們將利用估測此參數值來偵測肝纖維化。
不過於實際肝臟超音波訊號上，訊號的統計有一些難以解決的問題，而造成統計參數估測的困難。我們發展出將影像ROI分割成許多小區塊分別做參數統計，並將所得的統計值的統計分布以眾數估測其趨勢。
我們以此方法求得的結果比對肝穿刺的結果，發現由此方法估測出的參數值，將能有效的偵測出重度纖維化。

關鍵字

肝纖維化 ； 肝小葉 ； 腹部超音波 ； 一階統計 ； Nakagami分布

並列摘要

Liver fibrosis was common symptoms caused by chronic hepatitis, in addition to evolve into liver cirrhosis, is also a course record of the liver damage, so the diagnosis of liver fibrosis in chronic hepatitis has been key indicators. The gold standard for diagnosis of liver fibrosis is liver biopsy, but liver biopsy is invasive surgery, it is difficult to universal, so that the first-line treatment of liver fibrosis is abdominal ultrasound imaging apparatus equipment. However, ultrasound imaging of liver fibrosis in the diagnosis has been difficult to have reliable accuracy and difficult to quantify, so we want to use the RF signal of ultrasound imaging assisted medical diagnosis.
Know from the previous studies, although liver ultrasonography is composed of speckle, but not without information. Using first-order statistical parameters can be inferred scattering state. By the pathological process of liver fibrosis, we found that the impact of the structure of the scattering characteristics of the severe liver fibrosis is divided into two effect: one is the upset of the regularity; while the other is caused by the uneven cross section. In previous studies we know the value of the parameter m or the parameter of the Nakagami distribution can be effectively described in these two characteristics. Therefore, we will use the estimated value of this parameter to detect liver fibrosis.
However, in practical there are some difficult issues, which lead to statistical parameter estimation problems of the real liver signal. We developed a method which makes ROI image divided into many smaller blocks were used for parameter statistics, and statistics obtained from the statistical distribution of the trend estimate.
The results obtained in this way we compared the results of liver biopsy and found that this method of estimating the parameter will be able to effectively detect severe fibrosis.

並列關鍵字

liver fibrosis ； liver lobule ； abdominal ultrasound ； first-order statistics ； Nakagami distribution

參考文獻

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