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  4. Ultrasonic Tissue Characterization of Liver
 
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Ultrasonic Tissue Characterization of Liver

Date Issued
2005
Date
2005
Author(s)
Yeh, Wen-Chun
DOI
en-US
URI
http://ntur.lib.ntu.edu.tw//handle/246246/53311
Abstract
Fibrosis and steatosis are two common histological changes of the liver. Hepatic fibrosis is caused by inflammation and the degree of fibrosis may range from fibrous expansion in the portal area to cirrhosis. Detection of fibrosis status is very important. By knowing the fibrosis status, proper treatment can be given to the patients of chronic hepatitis. Hepatic steatosis – the accumulation of fat within liver cells – is another common histological finding of liver. Detection of steatosis status is also important because severe steatosis of liver may induce elevated levels of serum liver enzymes. Liver biopsy has been used to accurately identify the fibrosis and steatosis. However, the needle biopsy procedure is invasive and sometimes may cause severe complications, hence not a routine diagnostic procedure. Therefore, a non-invasive method for liver tissue characterization is desired and ultrasound may be most feasible tool. A diffuse fibrotic structure changes the mechanical properties of liver and affects characteristics of the ultrasound image. Since the elasticity of liver potentially can be measured by ultrasonic elasticity imaging and the fibrosis grade can be classified using the image features, ultrasound is very promising for tissue characterization of liver. Besides, steatosis may increase the echogenicity of the liver and change the image features as well. However, the histological changes associated with steatosis, such as distribution of fatty droplets, cannot be resolved by conventional ultrasound. High-frequency ultrasound (≧20 MHz) with higher spatial resolution has the potential to reveal more details of steatosis and achieve higher classification accuracy. In this thesis, we measure the elastic properties of fresh human liver tissues, as the first step for elasticity imaging of liver. The capability of the ultrasound in determining the liver fibrosis is evaluated by conventional ultrasound and the steatosis by high-frequency ultrasound. To evaluate the impact of fibrosis on elastic properties of human liver and to investigate potential benefits of ultrasonic elasticity imaging, 19 fresh human liver samples and one hepatic tumor (focal nodular hyperplasia) sample obtained during operation are studied. Simple 1D estimates based on the cyclic compression–relaxation method are preformed. Elastic modulus values are derived from the pre-determined strain and the stress values. Each specimen subsequently receives histological examination and a grade of liver fibrosis is scored from 0 to 5. Results show that the elastic modulus generally increases with the fibrosis grade though some discrepancies exist at the middle grades of fibrosis (score 1-3). It is concluded that severity of fibrosis has a good correlation with stiffness of liver. On the other hand, B-mode images of 16 specimens in above-mentioned study and 4 new specimens (total 20 fresh human liver samples) are also obtained to evaluate ultrasound’s ability in determining the grade of liver fibrosis. Image features derived from gray-level concurrence and nonseparable wavelet transform are extracted to classify fibrosis using a classifier known as the support vector machine. Each liver sample subsequently undergoes histological examination and liver fibrosis is graded as 0-5 (i.e., totally 6 grades). The 6 grades are then combined into 2, 3, 4 and 6 classes. Classifications using the extracted image features by the support vector machine are tested and correlated with histology. The results reveal that the best classification accuracy of 2, 3, 4 and 6 classes are 91%, 85%, 81% and 72%, respectively. Thus, liver fibrosis can be noninvasively characterized using B-mode ultrasound even though the performance declines as the number of classes increases. High-frequency B-mode ultrasound images of 19 new fresh human liver samples are also obtained to evaluate their usefulness in determining the steatosis grade. The images are acquired by a mechanically controlled 25-MHz single-crystal probe. A subsequent histological examination of each liver sample grades the steatosis from 0 to 3. The 4 grades are then combined into 2, 3 and 4 classes. The classification results are correlated with histology. The best classification accuracies of the 2, 3, and 4 classes are 90.5%, 85.8%, and 82.6%, respectively, which are markedly better than those for conventional ultrasound at 7 MHz (best classification accuracies of 81.6%, 75.8%, and 74.2%, respectively). These results indicate that liver steatosis can be more accurately characterized using high-frequency B-mode ultrasound. In conclusion, these studies demonstrate that ultrasound is a promising tool for tissue characterization of liver. The first study shows that severity of fibrosis has a good correlation with stiffness of liver and it provides a good basis for the elasticity imaging of liver in clinical use. The second study shows that liver fibrosis can also be noninvasively characterized using conventional B-mode ultrasound. In the third study, it is shown that liver steatosis needs higher spatial resolution of ultrasound for more accurate characterization. Nevertheless, clinical applications of high-frequency ultrasound for liver will not be feasible unless the penetration limitation is overcome. The main contributions of this thesis include the following pioneer works in ultrasonic tissue characterization of the liver. In the first study, we were the first group in the world to measure elastic properties of fresh human liver samples and investigated the correlation with histological findings. In the second study, we successfully applied the support vector machine to the field of ultrasonic tissue classification. In the third study, we performed pioneering work of high-frequency liver imaging and tissue characterization. These research results will be instrumental to our future work.
Subjects
肝臟彈性
彈性影像
脂肪變性
纖維化
組織特性
肝臟
灰階值共現
不可分小波轉換
支持向量機制
分類
超音波
肝臟病理
Liver elasticity
Elasticity imaging
Support vector machine
Nonseparable wavelet transform
High-frequency ultrasound
Liver pathology
Ultrasound
Classification
Fibrosis
Gray-level concurrence
Tissue characterization
Liver
Steatosis
SDGs

[SDGs]SDG3

Type
thesis

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