Journal of International Oncology

Journal of International Oncology››2019,Vol. 46››Issue (3): 141-146.doi:10.3760/cma.j.issn.1673-422X.2019.03.003

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Study of texture analysis based on CT images to predict radiochemotherapy sensitivity in patients with esophageal squamous cell carcinoma

Yi Minghui1,4,5, Li Zhenjiang2, Cao Qiang3, Li Baosheng4,5

  1. 1School of Medicine and Life Sciences, University of JinanShandong Academy of Medical Sciences, Jinan 250022, China; 2Department of Radiation Physics, Shandong Cancer Hospital Affiliated to Shandong University, Jinan 250117, China; 3Shandong Medical Imaging and Radiotherapy Engineering Center, Jinan 250117, China; 4Department of Radiation Therapy, Shandong Cancer Hospital Affiliated to Shandong University, Jinan 250117, China; 5Shandong Academy of Medical Sciences, Jinan 250062, China
  • Online:2019-03-08Published:2019-05-17
  • Contact:Li Baosheng E-mail:baoshli1963@163.com
  • Supported by:

    National Natural Science Foundation of China (81874224); Key Research and Development Program of Shandong Province of China (2017CXZC1206)

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Abstract:ObjectiveTo investigate the relationship between texture features based on CT and radiochemotherapy sensitivity in patients with esophageal squamous cell carcinoma (ESCC). MethodsA total of 92 ESCC patients treated at Shandong Cancer Hospital Affiliated to Shandong University between January 2014 and December 2017 were retrospectively collected. All patients were divided into responders (complete response + partial response) and nonresponders (stable disease + progression disease) according to therapeutic sensitivity. The texture features were extracted from CT images for positioning. And the patients were divided into training set (46 patients) and test set (46 patients) using traintestsplit, training set for establishing predictive model and test set for model validation. ResultsThere were 31 responders and 15 nonresponders in the training set, and the portion of responders was 67.4%. Univariate analyses showed that the histogram matrix (HISTO)sknewess was significantly different between the two groups (Z=2.097, P=0.036) and the area under the curve (AUC) was 0.692 with 95%CI of 0.5390.820. Sknewess ≤-2.58 intended to be responders. Binary logistic regression of sknewess (Z=2.097, P=0.036) in HISTO, high gray level zone emphasis (HGZE) (Z=1.722, P=0.085) and small zone high gray level emphasis (SZHGE) (Z=1.640, P=0.101) in gray level zonelength matrix (GLZLM) showed that sknewess was the independent influence factor of sensitivity (OR=0.558, 95%CI: 0.3380.923, P=0.023), and the AUC of logistic regression model was 0.718 with 95%CI of 0.5500.886, which indicted that the model had the ability to predict treatment response of ESCC patients. The model was validated by using test set and the AUC was 0.706, and the sensitivity of the model was 70.6% while the specificity was 69.0%. It showed that the model had certain ability in predicting treatment response. ConclusionCT texture analysis can predict the radiochemotherapy sensitivity in patients with ESCC to some extent.

Key words:Esophageal neoplasms,Radiotherapy,Chemotherapy, adjuvant,Treatment effect,Texture analysis