Gang Liu, Yihua Cheng

(Lanzhou University)

Abstract：

Lung cancer is one of the malignant tumors with the fastest growth in incidence rate and mortality in the world and the greatest threat to human health and life. Once diagnosed with lung cancer, patients are often in the advanced stage of lung cancer, with a five-year survival rate of only 18% for advanced lung cancer patients and only 5% for patients with distant metastasis. However, the five-year survival rate for stage I non-small cell lung cancer patients is as high as 77.9%, therefore, with the rapid development of detection technology and the continuous improvement of medical level, early diagnosis of lung cancer has become the key to improving the effectiveness of lung cancer treatment. Raman spectroscopy technology collects Raman spectral information at each pixel point in space, presents molecular information in space, and qualitatively, quantitatively, and spatially analyzes substance molecules to observe substance composition and structure information in image form, accurately revealing the biochemical characteristics of biological tissues. As a non-invasive detection technique, Raman spectroscopy can detect molecular level structural differences between cancerous and normal tissues. Therefore, it has the advantages of rich information, simple sample preparation, high sensitivity, and high accuracy for early clinical diagnosis of asymptomatic lung cancer with tissue changes. By using Raman spectroscopy technology to detect lung tissue sections, lung cells, and other samples, changes in biological molecular components such as proteins, lipids, nucleotides, etc. within tissue cells can be observed at the microscopic level, enabling qualitative and quantitative diagnosis of lung cancer. This article reviews the application and research progress of Raman spectroscopy technology in lung cancer diagnosis based on different lung cancer detection samples in recent years, and looks forward to the future use of Raman spectroscopy technology to assist in early treatment of lung cancer, in order to provide reference for clinical doctors and researchers.

Key Words：

lung cancer; diagnosis; Raman spectroscopy; imaging