Comparative study of imaging staging and postoperative pathological staging of esophageal cancer based on smart medical big data

Abstract

Esophageal cancer has become a malignant tumor disease with high mortality worldwide. Many cases of esophageal cancer are not very serious in the beginning but become severe in the late stage, so the best treatment time is missed. Less than 20% of patients with esophageal cancer are in the late stage of the disease for 5 years. The main treatment method is surgery, which is assisted by radiotherapy and chemotherapy. Radical resection is the most effective treatment method, but a method for imaging examination of esophageal cancer with good clinical effect has yet to be developed. This study compared imaging staging of esophageal cancer with pathological staging after operation based on the big data of intelligent medical treatment. MRI can be used to evaluate the depth of esophageal cancer invasion and replace CT and EUS for accurate diagnosis of esophageal cancer. Intelligent medical big data, medical document preprocessing, MRI imaging principal component analysis and comparison and esophageal cancer pathological staging experiments were used. Kappa consistency tests were conducted to compare the consistency between MRI staging and pathological staging and between two observers. Sensitivity, specificity and accuracy were determined to evaluate the diagnostic effectiveness of 3.0T MRI accurate staging. Results showed that 3.0T MR high-resolution imaging could show the histological stratification of the normal esophageal wall. The sensitivity, specificity and accuracy of high-resolution imaging in staging and diagnosis of isolated esophageal cancer specimens reached 80%. At present, preoperative imaging methods for esophageal cancer have obvious limitations, while CT and EUS have certain limitations. Therefore, non-invasive preoperative imaging examination of esophageal cancer should be further explored.Esophageal cancer has become a malignant tumor disease with high mortality worldwide. Many cases of esophageal cancer are not very serious in the beginning but become severe in the late stage, so the best treatment time is missed. Less than 20% of patients with esophageal cancer are in the late stage of the disease for 5 years. The main treatment method is surgery, which is assisted by radiotherapy and chemotherapy. Radical resection is the most effective treatment method, but a method for imaging examination of esophageal cancer with good clinical effect has yet to be developed. This study compared imaging staging of esophageal cancer with pathological staging after operation based on the big data of intelligent medical treatment. MRI can be used to evaluate the depth of esophageal cancer invasion and replace CT and EUS for accurate diagnosis of esophageal cancer. Intelligent medical big data, medical document preprocessing, MRI imaging principal component analysis and comparison and esophageal cancer pathological staging experiments were used. Kappa consistency tests were conducted to compare the consistency between MRI staging and pathological staging and between two observers. Sensitivity, specificity and accuracy were determined to evaluate the diagnostic effectiveness of 3.0T MRI accurate staging. Results showed that 3.0T MR high-resolution imaging could show the histological stratification of the normal esophageal wall. The sensitivity, specificity and accuracy of high-resolution imaging in staging and diagnosis of isolated esophageal cancer specimens reached 80%. At present, preoperative imaging methods for esophageal cancer have obvious limitations, while CT and EUS have certain limitations. Therefore, non-invasive preoperative imaging examination of esophageal cancer should be further explored.

Keywords

• big data of intelligent medical treatment
• imaging of esophageal cancer
• pathological stage after operation
• preprocessing of medical documents