ObjectiveTo analyze the tumor characteristics of colorectal cancer in the current version of Database from Colorectal Cancer (DACCA).MethodsThe DACCA version was the updated version on September 26, 2019. The data items included: date of surgery, precancerous lesions, cancer family, tumor site, distance to the dentate line, morphology of tumor, size, position, happening and origination, differentiation, pathology of tumor, Ki-67 of protein, complications (included obstruction, intussusception, perforation, pain, edema, and hemorrhage) were analyzed for the characteristics of each selected data item.ResultsA total of 11 898 analyzable data rows were obtained by screening the DACCA database. Among the 11 898 pieces of data, the effective data of precancerous lesions was 1 275, including 541 (42.4%) with precancerous lesions, and 734 (57.6%) without precancerous lesions. There were 1 116 valid data on cancer families, and 761 (6.4%) had a family history of cancer. The Ki-67 index had a total of 1 893 valid data, which ranged form 0 to 95% [(59.0±20.1) %]. According to the classification of tumor occurrence, the primary colorectal cancer accounted for the vast majority (92.8%), and the metastatic colorectal cancer was the least (0.3%). According to the primary and multiple primary, respectively analysis of tumor site, distance to the dentate line, morphology of tumor, size, position, differentiation, and pathology of tumor showed that, most tumor’s position were in the rectum (76.9%, 41.9%), the most common morphology was ulcers (42.4%, 51.5%), the most tumors were located around the wall of intestine (44.6%, 35.0%), the degree of differentiation was mostly moderate (65.4%, 61.3%), most of the tumor pathologies were adenocarcinoma (77.8%, 64.0%).ConclusionA more accurate and detailed analysis of colorectal cancer tumor characteristics by the DACCA database is helpful for determining the diagnosis and treatment plan in clinical work, judging the prognosis, and so on.
Esophageal cancer is a serious threat to the health of Chinese people. The key to solve this problem is early diagnosis and early treatment, and the most important method is endoscopic screening. The rapid development of artificial intelligence (AI) technology makes its application and research in the field of digestive endoscopy growing, and it is expected to become the "right-hand man" for endoscopists in the early diagnosis of esophageal cancer. Currently, the application of multimodal and multifunctional AI systems has achieved good performance in the diagnosis of superficial esophageal squamous cell carcinoma and precancerous lesions. This study summarized and reviewed the research progress of AI in the diagnosis of superficial esophageal squamous cell carcinoma and precancerous lesions, and also explored its development direction in the future.
Esophageal cancer is an aggressive malignancy with high morbidity and poor prognosis. Symptoms of early esophageal cancer are insidious and difficult to detect, while advanced esophageal obstruction, lesion infiltration and metastasis seriously affect patients’ quality of life. Early detection and treatment can help to increase the survival chance of patients. Recently, artificial intelligence (AI) has shown remarkable success in diagnosis of esophageal cancer, highlighting the great potential of new AI-assisted diagnostic modalities. This paper aims to review recent progress of AI in the diagnosis of esophageal cancer and to prospect its clinical application.