Yan Zhumin,Zhang Jingqiao,Chen Xiaojian,et al.Study on the relationship between CT image texture changes of parotids and acute xerostomia during radiation treatment for head and neck cancer[J].Chinese Journal of Radiological Medicine and Protection,2019,39(4):262-267
Study on the relationship between CT image texture changes of parotids and acute xerostomia during radiation treatment for head and neck cancer
Received:December 05, 2018  
DOI:10.3760/cma.j.issn.0254-5098.2019.04.004
KeyWords:Parotid gland  Radiation-induced xerostomia  Texture  CT image  Early prediction
FundProject:河南省科技攻关项目(152102310156)
Author NameAffiliationE-mail
Yan Zhumin Department of Radiation Oncology, The Affiliated Tumor Hospital of Zhengzhou University, Zhengzhou 450008, China  
Zhang Jingqiao New York Proton Center, New York NY 10035, United States of America  
Chen Xiaojian Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee 53226, United States of America  
Hai Long Department of Radiation Oncology, The Affiliated Tumor Hospital of Zhengzhou University, Zhengzhou 450008, China  
Sun Xueming Department of Radiation Oncology, The Affiliated Tumor Hospital of Zhengzhou University, Zhengzhou 450008, China  
Wu Hui Department of Radiation Oncology, The Affiliated Tumor Hospital of Zhengzhou University, Zhengzhou 450008, China wuhui7008@126.com 
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Abstract::
      Objective To investigate the relationship between parotid image texture and acute radiation xerostomia (grade) during radiotherapy in patients with head and neck cancer. The mathematical model was established to predict the severity of radiation dry mouth in the early stage. Methods 23 patients with head and neck cancer treated with radiotherapy were observed. The degree of xerostomia was evaluated according to RTOG criteria. The weekly validated CT images of these patients during radiotherapy were collected and transmitted to the MIM system to outline the parotid gland, and an internal analysis program was developed in MATLAB (R2013a). The changes of texture features of weekly parotid CT images during radiotherapy were analyzed, including mean CT value (MCTN), standard deviation (STD), skewness, kurtosis, entropy and volume. The mathematical model was established, and the KNN method was used to optimize the model and predict the level of xerostomia. Results There was no significant correlation among the changes of MCTN, volume and the degree of xerostomia(P>0.05). However, according to the weekly changes of MCTN and volume, the model was established to predict the grade of xerostomia with an accuracy of 99%. Conclusions The changes of parotid gland MCTN and volume were significantly correlated with acute radiation xerostomia during radiotherapy for head and neck cancer, and the MCTN changes can be used to predict the severity of xerostomia in the early stage.
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