Non-invasive Imaging for Lung Cancer Grading
Author Information
Author(s): Feng Jinbao, Shao Xiaonan, Gao Jianxiong, Ge Xinyu, Sun Yan, Shi Yunmei, Wang Yuetao
Primary Institution: Department of Nuclear Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, China
Hypothesis
Can non-invasive imaging methods accurately predict the new IASLC grading of lung invasive non-mucinous adenocarcinoma?
Conclusion
The new IASLC grading system significantly improves prognostic accuracy for lung invasive non-mucinous adenocarcinoma, and non-invasive imaging methods can effectively predict this grading.
Supporting Evidence
- The new IASLC grading system has been adopted by the 2021 WHO classification of thoracic tumors.
- Studies indicate that the new IASLC grading system can accurately predict patient prognosis.
- Non-invasive imaging methods are increasingly being studied for their ability to predict lung INMA grading.
Takeaway
Doctors can use special imaging techniques to see how serious a lung cancer is without needing to do surgery first.
Methodology
This review summarizes the establishment and clinical value of the IASLC grading system and discusses the application of non-invasive imaging techniques in predicting lung INMA grading.
Limitations
Many studies are single-center and retrospective, which may limit the generalizability of the results.
Digital Object Identifier (DOI)
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