目的 分析食管癌前病变反流性食管炎(RE)及Barrett食管的舌象转化规律.方法 基于食管癌高发区人群筛查,通过倾向性评分匹配方法以1∶2分别匹配轻度、中重度反流性食管炎及Barrett食管人群,匹配因素包括人群一般特征、生活习惯及相关疾病,采用多因素Logistic回归及倾向性评分匹配方法(PSM)匹配后舌象特征分布规律及食管炎癌转化过程中舌象特征变化规律.结果 经过一般特征、生活习惯、相关疾病PSM匹配,组间各变量间均衡可比(|d| ＞0.25),匹配后组间各变量之间基本均衡,PS进一步校正通过多因素Logistic回归分析,轻度RE与灰黑苔[OR=1.540 (1.120,2.119)]、绛舌[OR=1.529 (1.028,2.275)]、暗红舌[OR=1.291 (1.128,1.479)]、紫舌[OR=1.532 (1.237,1.896)]明显相关;中重度RE与紫舌[OR=1.681 (1.068,2.648)]及灰黑苔[OR=4.719(1.858,11.987)]明显相关;Barrett食管与紫舌[OR =3.447 (1.206,9.853)]相关. 结论 紫舌是RE向Barrett食管转变的危险舌象.

Esophageal cancer is a common malignant carcinoma that occurs in the digestive tract and leads to around three million deaths worldwide.Patients commonly present with symptoms, such as dysphagia, cough, hoarseness, and pain in the esophagus. According to researches, smoking,alcohol consumption, exposure to radiation,contaminated food, chronic throat irritation,

ObjectiveTo differentiate patients with esophageal cancer or premalignant lesions from the high-risk population for preliminary screening of esophageal cancer using a feature index determined by a computer-aided tongue information acquisition and processing system (DS01-B).MethodsTotally, 213 patients diagnosed with esophageal cancer or premalignant lesions and 2,840 normal subjects were collected including primarily screened and reexamined, all of them were confirmed with histological examinations. Their tongue color space values and manifestation features were extracted by DS01-B and analyzed. Firstly, the analysis of variance was performed to differentiate normal subjects from patients with esophageal cancer and premalignant lesions. Secondly, the logistic regression was conducted using 10 features and gender, age to get a predictive equation of the possibility of esophageal cancer or premalignant lesions. Lastly, the equation was tested by subjects undergoing primary screening.ResultsSaturation (S) values in the HSV color space showed significant differences between patients with esophageal cancer and normal subjects or those with mild atypical hyperplasia (P<0.05); blue-to-yellow (b) values in the Lab color space showed significant differences between patients with esophageal cancer or premalignant lesions and normal subjects (P<0.05). Logistic regression analysis showed that the computer-aided tongue inspection approach had an accuracy of 72.3% (2008/2776) in identifying patients with esophageal cancer or premalignant lesions for preliminary screening in high-risk population.ConclusionComputer-aided tongue inspection, with descriptive and quantitative profile as described in this study, could be applied as a cost- and timeefficient, non-invasive approach for preliminary screening of esophageal cancer in high-risk population.

e15579 Background: More than 50% esophageal cancer cases of the world are in China. The main causative factors that contribute to extremely high incidence of esophageal cancer (9.15/ million) in certain rural areas of China has not yet been elucidated. Screening and diagnosis of precancerous lesions and early stage cancer are main neasures of decreasing incidence rate and mortality rate. Methods: High-risk population (40-69 years old) in high risk areas of esophageal cancer, Cixian and Yangcheng were screened, and 4742 cases were included. They were divided into 4 groups: normal group, esophagitis/gastritis, esophageal neoplasia low-level group and esophageal neoplasia high-level group, according to pathology and electronic gastroscope diagnosis. Diagnostic testing lingual information collection system (DS01-B) was used and tongue image were collected, including tongue color, coating color, fur character, tongue shape, local ecchymosis, et al. Difference of tongue image information was analyzed by multi-factor logistic regression using SPSS and R statistical software. Results: Logistic regression analysis showed that dark purplish tongue colour, and tongue local ecchymosis were correlated to precancerous lesions and early stage cancer (P < 0.01 or P < 0.05). Red and crimson tongue, yellow and white coated tongue, spotted tongue and tongue local ecchymosis were correlated to esophagitis and gastritis(P < 0.01 or P < 0.05). Logistic regression model had diagnostic total coincidence rate (69.4%) for early esophageal cancer screening. Conclusions: Multi-factor logistic regression model based on tongue image information has clinical value of prediction esophageal precancerous lesion.