EP04.01-07 Optimal Predictors for Lung Cancer Using High-Resolution CT

H. Notsuda, H. Oshio,K. Onodera,T. Watanabe,Y. Watanabe, T. Suzuki,H. Oishi,H. Niikawa, M. Noda,Y. Okada

Journal of Thoracic Oncology(2023)

引用 0|浏览2
暂无评分
摘要
Since the developments of low-dose helical computed tomography (HRCT) screening for early detection and early treatment of lung cancer, small-sized lung cancers with low density area on CT tend to be found. In particular, part-solid GGNs, which partially contain a solid component, have a high probability of being lung cancer and often require surgical treatment. However, these tumors, especially small-sized, are difficult to diagnose prior to surgical treatment. Based on the results of JCOG0802 and 0804 studies, reduction surgery for part-solid GGN has been selected, and the importance of preoperative diagnosis in determining the surgical method has increased.
更多
查看译文
关键词
lung cancer,optimal predictors,high-resolution
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要