Imaging features can be used to predict the survival of patients with liver cancer

reporter learned from the Suzhou Institute of Biomedical Engineering Technology of the Chinese Academy of Sciences that the team led by Gao Xin researchers of the institute recently studied the factors affecting the survival of patients with liver cancer through the method of tumor imaging genomics. The results showed that the imaging characteristics of the soft and hard texture of the liver and the volume of the tumor transition area were directly related to the total survival of liver cancer patients. This finding is instructive for scientific prognosis assessment of liver cancer.
emerging tumor imaging genomics is an interdisciplinary subject in the field of oncology research. It combines the non-invasive, inexpensive and repeatable characteristics of medical imaging with the advantages of molecular technology to directly explore the root causes of the disease, combining the two to study the imaging markers that can identify or diagnose tumors and what scientific explanations are available at the molecular biology level to guide the evaluation and treatment of tumors.
In this study, the research team of Suzhou Medical Institute of the Chinese Academy of Sciences, in cooperation with Shanghai University, Wake Forest University and Suzhou University Affiliated Second Hospital, selected liver cancer, which is particularly high in China, and carried out two years of research on tumor imaging genomics.
Gao Xin, the study's samples, gene expression data and total survival data from 371 patients with hepatocellular carcinoma from the U.S. Cancer Gene Map Database, as well as enhanced CT data from 38 patients in the study. Through the extraction of imaging histological characteristics, as well as the analysis of gene expression data and the total survival of patients, the researchers found that there were two imaging characteristics, which were closely related to the length of life of liver cancer patients. First, according to tumor activity from weak to strong tumor image area is divided into necrotic area, transition zone, active area, the larger the proportion of the transition area, the longer the patient's survival;
significance of this study is to find a new way to link tumor imaging to molecular mechanisms, so that clinical diagnosis and evaluation can have both intuitive and scientific basis. This method can also be extended to other disease research, we will be followed by expanded samples, to carry out glioma-related research. Gao Xin said.
research results have recently been published in the field of radiology
research. (Source: Wang Wei, Xinhua)