Radiomic and quantitative-semantic models of low-dose computed tomography for predicting the poorly differentiated invasive non-mucinous pulmonary adenocarcinoma
Author:
Funder
Sichuan Science and Technology Program
Chengdu Science and Technology Program
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s11547-023-01591-z.pdf
Reference58 articles.
1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A et al (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 71(3):209–249. https://doi.org/10.3322/caac.21660
2. Moreira AL, Ocampo PSS, Xia Y, Zhong H, Russell PA, Minami Y et al (2020) A grading system for invasive pulmonary adenocarcinoma: a proposal from the international association for the study of lung cancer pathology committee. J Thorac Oncol 15(10):1599–1610. https://doi.org/10.1016/j.jtho.2020.06.001
3. Deng C, Zheng Q, Zhang Y, Jin Y, Shen X, Nie X et al (2021) Validation of the novel international association for the study of lung cancer grading system for invasive pulmonary adenocarcinoma and association with common driver mutations. J Thorac Oncol 16(10):1684–1693. https://doi.org/10.1016/j.jtho.2021.07.006
4. Rokutan-Kurata M, Yoshizawa A, Ueno K, Nakajima N, Terada K, Hamaji M et al (2021) Validation study of the international association for the study of lung cancer histologic grading system of invasive lung adenocarcinoma. J Thorac Oncol 16(10):1753–1758. https://doi.org/10.1016/j.jtho.2021.04.008
5. Hou L, Wang T, Chen D, She Y, Deng J, Yang M et al (2022) Prognostic and predictive value of the newly proposed grading system of invasive pulmonary adenocarcinoma in Chinese patients: a retrospective multicohort study. Mod Pathol 35(6):749–756. https://doi.org/10.1038/s41379-021-00994-5
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