Machine learning improves early detection of liver fibrosis by quantitative ultrasound radiomics.
Machine learning improves early detection of liver fibrosis by quantitative ultrasound radiomics.
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DOI：
10.1109/ius54386.2022.9957180
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发表时间：
2022-10
期刊：
影响因子：
--
通讯作者：
Sehgal, Chandra M.
中科院分区：
文献类型：
--
作者：
Al-Hasani, Maryam;Sultan, Laith R.;Sagreiya, Hersh;Cary, Theodore W.;Karmacharya, Mrigendra B.;Sehgal, Chandra M.
肝纤维化发展为肝硬化是一个严重的不可逆过程，是发生肝细胞癌和肝功能衰竭最关键的危险因素之一。因此，早期发现肝纤维化对于更好地管理患者至关重要。超声（US）成像可以提供一种非侵入性的替代活检。本研究评估定量美国纹理特征，以提高早期和晚期肝纤维化的检测。采用157张早期和晚期肝纤维化大鼠不同肝叶的b型超声图像进行分析。在每张图像上放置5-6个感兴趣的区域。从图像中提取12个描述肝脏纹理变化的定量特征，包括一阶直方图、行程长度（RL）和灰度共生矩阵（GLCM）。单个特征的诊断效能较高，AUC范围为0.80 ~ 0.94。使用逻辑回归和留一交叉验证来评估组合特征的性能。综合所有特征，AUC = 0.95，灵敏度= 96.8%，特异性= 93.7%，表现出轻微改善。定量的超声质构特征可以高精度地表征肝纤维化的变化，并能区分早期和晚期疾病。定量超声，如果在未来的临床研究中得到验证，可以在识别不容易通过视觉超声图像评估检测到的纤维化变化方面发挥潜在作用。
Progression of liver fibrosis to cirrhosis, a severe non-reversible process, is one of the most critical risk factors in developing hepatocellular carcinoma and liver failure. Detection of liver fibrosis at an early stage is therefore essential for better patient management. Ultrasound (US) imaging can provide a noninvasive alternative to biopsies. This study evaluates quantitative US texture features to improve early-stage versus advanced liver fibrosis detection. 157 B-mode US images of different liver lobes acquired from early and advanced fibrosis rat cases were used for analysis. 5-6 regions of interest were placed on each image. Twelve quantitative features that describe liver texture changes were extracted from the images, including first-order histogram, run length (RL), and gray level co-occurrence matrix (GLCM). The diagnostic performance of individual features was high with AUC ranging from 0.80 to 0.94. Logistic regression with leave-one-out cross-validation was used to evaluate the performance of the combined features. All features combined showed a slight improvement in performance with AUC = 0.95, sensitivity = 96.8%, and specificity = 93.7%. Quantitative US texture features characterize liver fibrosis changes with high accuracy and can differentiate early from advanced disease. Quantitative ultrasound, if validated in future clinical studies, can have a potential role in identifying fibrosis changes that are not easily detected by visual US image assessments.
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影响因子：
9.8
作者：
Regev, A;Berho, M;Schiff, ER
通讯作者：
Schiff, ER
影响因子：
4.5
作者：
Mathiesen, UL;Franzén, LE;Bodemar, G
通讯作者：
Bodemar, G
影响因子：
105.7
作者：
Tapper, Elliot B.;Parikh, Neehar D.
通讯作者：
Parikh, Neehar D.
影响因子：
5
作者：
Strauss, Simon;Gavish, Ella;Katsnelson, Ludmila
通讯作者：
Katsnelson, Ludmila
DOI：
10.1007/bf02235164
发表时间：
1971-01-01
期刊：
AMERICAN JOURNAL OF DIGESTIVE DISEASES
影响因子：
--
作者：
SOLOWAY, RD;SCHOENFIELD, LJ;BAGGENSTOSS, AH
通讯作者：
BAGGENSTOSS, AH