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[Predicting Invasive Non-mucinous Lung Adenocarcinoma IASLC Grading: 
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Kaibo Zhu1, Liangna Deng2, Yue Hou3

  • 1Department of Radiology, Lanzhou University Second Hospital, the Second Clinical Medical School, Lanzhou University, Key 
Laboratory of Medical Imaging of Gansu Province, Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China.

Zhongguo Fei AI Za Zhi = Chinese Journal of Lung Cancer
|October 29, 2025
PubMed
Summary

This study developed a nomogram using dual-energy CT scans and clinical data to predict the International Association for the Study of Lung Cancer (IASLC) grade for invasive non-mucinous pulmonary adenocarcinomas (INMA). The model accurately assesses INMA IASLC grading noninvasively before surgery.

Keywords:
International Association for the Study of Lung Cancer classificationInvasive non-mucinous pulmonary adenocarcinomasLung neoplasmsNomogramSpectral computed tomography

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