CT纹理分析对吉非替尼治疗肺腺癌疗效评估的应用

目的:探讨CT纹理分析在吉非替尼治疗肺腺癌疗效评估中的应用价值。材料与方法:回顾性分析21例经吉非替尼治疗3个月后，依据实体肿瘤疗效评价标准（RECIST）（Version 1.1）进行疗效评估为部分缓解（PR）的肺腺癌患者，对治疗前CT基线平扫图像及治疗3个月时复查的CT平扫图像进行纹理分析，获得灰度直方图及灰度共生矩阵相关的纹理参数，比较治疗前后纹理参数的差异，并且对无进展生存期（PFS）进行了亚组分析，对PFS≥1年及PFS <1年的两个亚组治疗前后纹理参数的变化值进行比较。结果:21例经吉非替尼治疗3个月后评价为PR的肺腺癌患者，病灶经治疗后的平均灰度值、偏度和峰度、熵低于治疗前（P<0.05），治疗后标准差、角二阶矩和逆差矩高于治疗前（P<0.05），但治疗前后的对比度无统计学差异（P>0.05）。对PFS进行亚组分析的结果显示，Δ逆差矩在两组间差异有统计学意义（P<0.05）。结论:CT纹理分析有助于评价吉非替尼治疗肺腺癌的近期疗效且能够预测患者的PFS。 

CT Texture Analysis on the Response Evaluation of Lung Adenocarcinoma Treated by Gifitinib

Objective:To investigate the value of CT texture analysis in the evaluation of response to gefitinib-based treatment in patients with lung adenocarcinoma. Materials and Methods:Twenty-one patients with lung adenocarcinoma who received a treatment of gefitinib were retrospectively analyzed, and were evaluated as partial response(PR) after 3 months treatment based on RECIST 1.1(Response Evaluation Criteria in Solid Tumors, Version 1.1). We obtained and compared the quantitative texture parameters of gray histograms and GLCM on CT scan images before and after 3 months of treatment, respectively. A subgroup analysis of progression-free survival(PFS) of no less than 1 year and less than 1 year, were conducted to compare the changes in texture parameters before and after treatment. Results:Twenty-one patients with lung adenocarcinoma were evaluated as PR after 3 months of treatment with gefitinib. There were significant decreases in the mean gray value, skewness, kurtosis and entropy of the lesions, while there were significant increases in the standard deviation, angular second moment, and inverse difference moment of the lesions after the treatment(P < 0.05). There was no significant difference in contrast between pre-and posttreatment(P > 0.05). A subgroup analysis of PFS showed a significant difference in Δ inverse between the two groups(P < 0.05). Conclusion:CT texture analysis may be helpful for the evaluation of short-term effect to gefitinib-based treatment and the prediction of PFS in patients with lung adenocarcinoma.