T2WI序列图像纹理分析对肝硬化浸润性肝癌和局灶性融合性纤维化的鉴别诊断价值

肝脏 ›› 2022, Vol. 27 ›› Issue (9): 986-989.

T2WI序列图像纹理分析对肝硬化浸润性肝癌和局灶性融合性纤维化的鉴别诊断价值

胡维杰, 陈小萍, 吴荣刚, 马臻雏

215101 江苏苏州市中西医结合医院影像科

收稿日期:2021-11-30 出版日期:2022-09-30 发布日期:2022-10-27
基金资助:
苏州市科技局民生科技(科技示范工程)(SS201815)

The value of T2WI sequence image texture analysis in the differential diagnosis of hepatic infiltrating hepatocellular carcinoma and focal fusion fibrosis

HU Wei-jie, CHEN Xiao-ping, WU Rong-gang, MA Zhen-chu

Department of Radiology, Suzhou Hospital of Integrated Traditional Chinese and Western Medicine, Jiangsu 215101, China

Received:2021-11-30 Online:2022-09-30 Published:2022-10-27

摘要/Abstract

摘要： 目的研究T2加权图像(T2WI)序列图像纹理分析对肝硬化浸润性肝癌和肝脏局灶性融合性纤维化的鉴别诊断价值。方法回顾性分析2018年8月至2021年8月苏州市中西医结合医院收治的肝硬化浸润性肝癌患者50例和肝脏局灶性融合性纤维化患者32例的临床资料。所有患者均于手术标本病理诊断前1周行MRI检查,并接受T2WI序列纹理分析。选取病灶最大层面轴位T2WI图像,并经Image J图像处理软件手动勾画感兴趣区(ROI),提取空间灰度共生矩阵(GLCM)纹理参数(熵、能量、相关性、对比度、逆差距)和直方图(Histogram)纹理参数(平均值、峰度、偏度)。对两组GLCM和Histogram纹理参数进行比较,并采用受试者工作特性曲线(ROC)评价其对肝硬化浸润性肝癌与肝脏局灶性融合性纤维化的鉴别诊断效能。结果肝硬化浸润性肝癌组熵为7.04±0.29,高于局灶性融合性纤维化组的(6.70±0.60),能量和相关性分别为(15.30±7.19)×10^-4和(15.41±7.28)×10^-4,低于局灶性融合性纤维化组的(25.02±11.37)×10^-4和(33.65±14.40)×10^-4,差异均有统计学意义(P<0.05);两组对比度、逆差距、平均值、峰度、偏度差异无统计学意义(P>0.05)。熵、能量、相关性对肝硬化浸润性肝癌与肝脏局灶性融合性纤维化均有一定鉴别诊断效能,曲线下面积(AUC)分别为0.672、0.701、0.812。结论 GLCM纹理参数熵、能量、相关性可以鉴别肝硬化浸润性肝癌与肝脏局灶性融合性纤维化,值得临床进一步验证。

关键词: T2加权图像, 纹理分析, 肝硬化浸润性肝癌, 局灶性融合性纤维化

Abstract: Objective To study on the differential diagnosis value of T2 weighted image (T2WI) sequence image texture analysis (TA) of magnetic resonance imaging (MRI) in the differential diagnosis of hepatic infiltrative hepatocellular carcinoma (iHCC) and hepatic focal fusion fibrosis (FFF). Methods Fifty cirrhotic patients with invasive liver cancer were enrolled in the iHCC group. Thirty-two patients with focal fusion fibrosis with complete preoperative magnetic resonance imaging (MRI) data and pathological confirmation of their surgical specimens were enrolled in the FFF group. The clinical data of both groups of patients were collected and retrospectively analyzed. All patients underwent MRI examination and TA sequence analysis on T2WI at one week before the operation. The maximum axial T2WI images of the lesion were selected, and the region of interest (ROI) was manually sketched by Image J Image processing software. The spatial gray co-occurrence matrix (GLCM) texture parameters (entropy, energy, correlation, contrast, deficit distance) and Histogram texture parameters (mean, kurtosis, skewness) were extracted. GLCM and Histogram texture parameters were compared between the two groups. Receiver operating characteristic curve (ROC) was used to evaluate their efficiencies in differential diagnosis of invasive liver cancer and focal hepatic fusion fibrosis. Results The entropy was 7.04±0.29 in iHCC group, which was significantly higher than that of 6.70±0.60 in FFF group (P<0.05). The energy and correlation of the iHCC group were (15.30±7.19) ×10^-4 and (15.41±7.28) ×10^-4, which were significantly lower than those of (25.02±11.37) ×10^-4 and (33.65±14.40) ×10^-4 in FFF group, respectively (P<0.05). There were no significant difference in contrast, deficit distance, mean, kurtosis and skewness parameters between the two groups (P>0.05). The entropy, energy and correlation parameters have had certain efficiencies in the differential diagnosis of invasive liver cancer and liver focal fusion fibrosis, and the areas under curves (AUC) were 0.672, 0.701 and 0.812, respectively. Conclusion The entropy, energy and correlation of GLCM texture parameters under T2WI TA are useful in distinguishing infiltrating liver cancer and focal fusion liver fibrosis, which are worthy of further clinical verification.

Key words: T2-weighted image, Texture analysis, liver cirrhosis with infiltrative hepatocellular carcinoma, Focal fusion fibrosis

胡维杰, 陈小萍, 吴荣刚, 马臻雏. T2WI序列图像纹理分析对肝硬化浸润性肝癌和局灶性融合性纤维化的鉴别诊断价值[J]. 肝脏, 2022, 27(9): 986-989.

HU Wei-jie, CHEN Xiao-ping, WU Rong-gang, MA Zhen-chu. The value of T2WI sequence image texture analysis in the differential diagnosis of hepatic infiltrating hepatocellular carcinoma and focal fusion fibrosis[J]. Chinese Hepatolgy, 2022, 27(9): 986-989.

参考文献

[1] Smith A, Baumgartner K, Bositis C. Cirrhosis: diagnosis and management. Am Fam Physician, 2019, 100(12):759-770.
[2] Wu L, Shen Y, Li F. Non-invasive diagnosis of liver fibrosis: a review of current imaging modalities. Gastroenterol Hepatol, 2020, 43(4):211-221.
[3] 曹怡, 方向军, 代月黎. 普美显MRI增强扫描鉴别肝硬化结节与肝癌应用价值. 中南医学科学杂志, 2020, 48(1):76-79.
[4] 宋文龙, 郭大静, 陈倩羽, 等. 基于MR增强图像肝细胞癌直方图纹理分析. 放射学实践, 2019, 34(12):1348-1353.
[5] Schawkat K, Ciritsis A, von Ulmenstein S, et al. Diagnostic accuracy of texture analysis and machine learning for quantification of liver fibrosis in MRI: correlation with MR elastography and histopathology. Eur Radiol, 2020, 30(8):4675-4685.
[6] 罗月, 薛宏伟, 王培军. 应重视肝纤维化的影像学研究进展及应用. 中华医学杂志, 2019, 99(7):481-483.
[7] Shu Z, Fang S, Ye Q, et al. Prediction of efficacy of neoadjuvant chemoradiotherapy for rectal cancer: the value of texture analysis of magnetic resonance images. Abdom Radiol (NY), 2019, 44(11):3775-3784.
[8] Xu J, Cui X, Wang B, et al. Texture analysis of early cerebral tissue damage in magnetic resonance imaging of patients with lung cancer. Oncol Lett, 2020, 19(4):3089-3100.
[9] Thomas JV, Abou Elkassem AM, Ganeshan B, et al. MR imaging texture analysis in the abdomen and pelvis. Magn Reson Imaging Clin N Am, 2020, 28(3):447-456.
[10] Yu JY, Zhang HP, Tang ZY, et al. Value of texture analysis based on enhanced MRI for predicting an early therapeutic response to transcatheter arterial chemoembolisation combined with high-intensity focused ultrasound treatment in hepatocellular carcinoma. Clin Radiol, 2018, 73(8):758-766.
[11] Cannella R, Rangaswamy B, Minervini MI, et al. Value of texture analysis on gadoxetic acid-enhanced MRI for differentiating hepatocellular adenoma from focal nodular hyperplasia. AJR Am J Roentgenol, 2019, 212(3):538-546.
[12] 翁炜, 吕秀玲, 张倩倩, 等. 基于磁共振影像组学技术对肝癌经肝动脉化疗栓塞术后短期疗效的预后价值分析. 中华医学杂志, 2020, 100(11):828-832.
[13] 黄伟康, 成东亮, 刘恺, 等. 基于T2WI序列的纹理分析在鉴别肝细胞癌分化程度的应用研究. 临床放射学杂志, 2018, 37(9):1484-1487.
[14] 武明辉, 谭红娜, 吴青霞, 等. 肝脏磁共振T2WI图像纹理特征预测肝细胞癌患者微血管侵犯的价值. 中国癌症杂志, 2018, 28(3):191-196.
[15] 钟熹, 方伟军, 麦慧, 等. 常规T2WI序列纹理分析鉴别肝硬化背景的小肝癌和增生结节的价值. 临床放射学杂志, 2019, 38(3):448-451.
[16] 张衡, 张慧慧, 舒政, 等. MRI T2WI图像纹理分析预测甲状腺乳头状癌颈部淋巴结转移的诊断价值. 中国临床医学影像杂志, 2020, 31(8):568-571.
[17] Ta D, Khan M, Ishaque A, et al. Reliability of 3D texture analysis: a multicenter MRI study of the brain. J Magn Reson Imaging, 2020, 51(4):1200-1209.