良性肺结节与肺癌患者舌象特征的相关性分析

Tongue image feature correlation analysis in benign lung nodules and lung cancer

  • 摘要:
    目的 分析良性肺结节患者和肺癌患者舌象指标相关性的差异。
    方法 在2020年7月1日至2022年3月31日期间,分别于上海中医药大学附属龙华医院的肿瘤科以及上海中医药大学附属曙光医院的体检中心,收集肺癌患者和肺结节患者的临床信息。利用TFDA-1型数字舌诊仪获取良性肺结节及肺癌患者的舌象图片,并运用TDAS V2.0软件对舌象图像进行分析,提取包括舌质(TB)和舌苔(TC)的Lab色彩空间指标(TB/TC-L、TB/TC-a、TB/TC-b)、纹理指标 TB/TC-对比度(CON)、TB/TC-角二阶矩(ASM)、TB/TC-熵(ENT)、TB/TC-MEAN 以及舌苔参数指标(perAll、perPart)。通过Pearson或Spearman相关性分析,对舌质和舌苔特征的双变量进行相关性分析,并采用典型相关分析(CCA)分析其整体相关性。
    结果 在排除异常值和离群值后,研究共纳入了307例良性肺结节患者和276例肺癌患者。简单相关性分析表明,肺癌组在TB-L与TC-L的相关性、TB-b与TC-b的相关性以及TB-b与perAll的相关性均高于良性肺结节组,良性肺结节组在TB-a与TC-a的相关性、TB-a与perAll的相关性以及舌质纹理参数(TB-CON、TB-ASM、TB-ENT、TB-MEAN)与舌苔纹理参数(TC-CON、TC-ASM、TC-ENT、TC-MEAN)的相关性均高于肺癌组。典型相关分析进一步揭示,肺癌组舌质与舌苔指标之间存在较强的相关性,良性肺结节组的第一、第二对典型变量的相关系数分别为0.918和0.817(P < 0.05),肺癌组则分别为0.940和0.822(P < 0.05)。
    结论 良性肺结节与肺癌患者在舌质和舌苔的L值、a值、b值,舌苔的perAll值和舌质与舌苔的纹理参数(TB/TC-CON、TB/TC-ASM、TB/TC-ENT、TB/TC-MEAN),以及两组人群舌质与舌苔的整体相关性方面均存在相关性差异。舌诊客观化指标能有效辅助良性肺结节与肺癌的诊断,从而为肺癌的早发现、早诊断、早治疗提供科学依据。

     

    Abstract:
    Objective To analyze the differences in the correlation of tongue image indicators among patients with benign lung nodules and lung cancer.
    Methods From July 1, 2020 to March 31, 2022, clinical information of lung cancer patients and benign lung nodules patients was collected at the Oncology Department of Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine and the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, respectively. We obtained tongue images from patients with benign lung nodules and lung cancer using the TFDA-1 digital tongue diagnosis instrument, and analyzed these images with the TDAS V2.0 software. The extracted indicators included color space parameters in the Lab system for both the tongue body (TB) and tongue coating (TC) (TB/TC-L, TB/TC-a, and TB/TC-b), textural parameters TB/TC-contrast (CON), TB/TC-angular second moment (ASM), TB/TC-entropy (ENT), and TB/TC-MEAN, as well as TC parameters (perAll and perPart). The bivariate correlation of TB and TC features was analyzed using Pearson’s or Spearman’s correlation analysis, and the overall correlation was analyzed using canonical correlation analysis (CCA).
    Results Samples from 307 patients with benign lung nodules and 276 lung cancer patients were included after excluding outliers and extreme values. Simple correlation analysis indicated that the correlation of TB-L with TC-L, TB-b with TC-b, and TB-b with perAll in lung cancer group was higher than that in benign nodules group. Moreover, the correlation of TB-a with TC-a, TB-a with perAll, and the texture parameters of the TB (TB-CON, TB-ASM, TB-ENT, and TB-MEAN) with the texture parameters of the TC (TC-CON, TC-ASM, TC-ENT, and TC-MEAN) in benign nodules group was higher than lung cancer group. CCA further demonstrated a strong correlation between the TB and TC parameters in lung cancer group, with the first and second pairs of typical variables in benign nodules and lung cancer groups indicating correlation coefficients of 0.918 and 0.817 (P < 0.05), and 0.940 and 0.822 (P < 0.05), respectively.
    Conclusion Benign lung nodules and lung cancer patients exhibited differences in correlation in the L, a, and b values of the TB and TC, as well as the perAll value of the TC, and the texture parameters (TB/TC-CON, TB/TC-ASM, TB/TC-ENT, and TB/TC-MEAN) between the TB and TC. Additionally, there were differences in the overall correlation of the TB and TC between the two groups. Objective tongue diagnosis indicators can effectively assist in the diagnosis of benign lung nodules and lung cancer, thereby providing a scientific basis for the early detection, diagnosis, and treatment of lung cancer.

     

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