The predictive value of [18F]FDG PET/CT radiomics combined with clinical features for EGFR mutation status in different clinical staging of lung adenocarcinoma

Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73:17–48.

Article  PubMed  Google Scholar 

Xia C, Dong X, Li H, Cao M, Sun D, He S, et al. Cancer statistics in China and United States, 2022: profiles, trends, and determinants. Chin Med J (Engl). 2022;135:584–90.

Article  PubMed  Google Scholar 

Herbst RS, Morgensztern D, Boshoff C. The biology and management of non-small cell lung cancer. Nature. 2018;553:446–54.

Article  CAS  PubMed  Google Scholar 

Li X, Yin G, Zhang Y, Dai D, Liu J, Chen P, et al. Predictive power of a radiomic signature based on (18)F-FDG PET/CT images for EGFR mutational status in NSCLC. Front Oncol. 2019;9:1062.

Article  PubMed  PubMed Central  Google Scholar 

Zhang J, Zhao X, Zhao Y, Zhang J, Zhang Z, Wang J, et al. Value of pre-therapy (18)F-FDG PET/CT radiomics in predicting EGFR mutation status in patients with non-small cell lung cancer. Eur J Nucl Med Mol Imaging. 2020;47:1137–46.

Article  CAS  PubMed  Google Scholar 

Shi Y, Au JS, Thongprasert S, Srinivasan S, Tsai CM, Khoa MT, et al. A prospective, molecular epidemiology study of EGFR mutations in Asian patients with advanced non-small-cell lung cancer of adenocarcinoma histology (PIONEER). J Thorac Oncol. 2014;9:154–62.

Article  CAS  PubMed  PubMed Central  Google Scholar 

McLoughlin EM, Gentzler RD. Epidermal growth factor receptor mutations. Thorac Surg Clin. 2020;30:127–36.

Article  PubMed  Google Scholar 

Recondo G, Facchinetti F, Olaussen KA, Besse B, Friboulet L. Making the first move in EGFR-driven or ALK-driven NSCLC: First-generation or next-generation TKI? Nat Rev Clin Oncol. 2018;15:694–708.

Article  CAS  PubMed  Google Scholar 

Tan CS, Gilligan D, Pacey S. Treatment approaches for EGFR-inhibitor-resistant patients with non-small-cell lung cancer. Lancet Oncol. 2015;16:e447–59.

Article  CAS  PubMed  Google Scholar 

Devarakonda S, Morgensztern D, Govindan R. Genomic alterations in lung adenocarcinoma. Lancet Oncol. 2015;16:e342-351.

Article  CAS  PubMed  Google Scholar 

Zhang Y, Chang L, Yang Y, Fang W, Guan Y, Wu A, et al. Intratumor heterogeneity comparison among different subtypes of non-small-cell lung cancer through multi-region tissue and matched ctDNA sequencing. Mol Cancer. 2019;18:7.

Article  PubMed  PubMed Central  Google Scholar 

Li Z, Zhang Y, Bao W, Jiang C. Insufficiency of peripheral blood as a substitute tissue for detecting EGFR mutations in lung cancer: a meta-analysis. Target Oncol. 2014;9:381–8.

Article  PubMed  Google Scholar 

Hur JY, Kim HJ, Lee JS, Choi CM, Lee JC, Jung MK, et al. Extracellular vesicle-derived DNA for performing EGFR genotyping of NSCLC patients. Mol Cancer. 2018;17:15.

Article  PubMed  PubMed Central  Google Scholar 

Moding EJ, Diehn M, Wakelee HA. Circulating tumor DNA testing in advanced non-small cell lung cancer. Lung Cancer. 2018;119:42–7.

Article  PubMed  Google Scholar 

Ettinger DS, Wood DE, Aisner DL, Akerley W, Bauman JR, Bharat A, et al. Non-small cell lung cancer, version 3.2022, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2022;20:497–530.

Article  PubMed  Google Scholar 

Eberhardt WE, De Ruysscher D, Weder W, Le Pechoux C, De Leyn P, Hoffmann H, et al. 2nd ESMO Consensus Conference in Lung Cancer: locally advanced stage III non-small-cell lung cancer. Ann Oncol. 2015;26:1573–88.

Article  CAS  PubMed  Google Scholar 

Vansteenkiste J, Crino L, Dooms C, Douillard JY, Faivre-Finn C, Lim E, et al. 2nd ESMO Consensus Conference on Lung Cancer: early-stage non-small-cell lung cancer consensus on diagnosis, treatment and follow-up. Ann Oncol. 2014;25:1462–74.

Article  CAS  PubMed  Google Scholar 

Mayerhoefer ME, Materka A, Langs G, Haggstrom I, Szczypinski P, Gibbs P, et al. Introduction to radiomics. J Nucl Med. 2020;61:488–95.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Liu Q, Sun D, Li N, Kim J, Feng D, Huang G, et al. Predicting EGFR mutation subtypes in lung adenocarcinoma using (18)F-FDG PET/CT radiomic features. Transl Lung Cancer Res. 2020;9:549–62.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Nair JKR, Saeed UA, McDougall CC, Sabri A, Kovacina B, Raidu BVS, et al. Radiogenomic models using machine learning techniques to predict EGFR mutations in non-small cell lung cancer. Can Assoc Radiol J. 2021;72:109–19.

Article  PubMed  Google Scholar 

Jiang M, Zhang Y, Xu J, Ji M, Guo Y, Guo Y, et al. Assessing EGFR gene mutation status in non-small cell lung cancer with imaging features from PET/CT. Nucl Med Commun. 2019;40:842–9.

Article  CAS  PubMed  Google Scholar 

Li H, Gao C, Sun Y, Li A, Lei W, Yang Y, et al. Radiomics analysis to enhance precise identification of epidermal growth factor receptor mutation based on positron emission tomography images of lung cancer patients. J Biomed Nanotechnol. 2021;17:691–702.

Article  CAS  PubMed  Google Scholar 

Huang W, Wang J, Wang H, Zhang Y, Zhao F, Li K, et al. PET/CT based EGFR mutation status classification of NSCLC using deep learning features and radiomics features. Front Pharmacol. 2022;13: 898529.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Li S, Li Y, Zhao M, Wang P, Xin J. Combination of (18)F-Fluorodeoxyglucose PET/CT radiomics and clinical features for predicting epidermal growth factor receptor mutations in lung adenocarcinoma. Korean J Radiol. 2022;23:921–30.

Article  PubMed  PubMed Central  Google Scholar 

Ruan D, Fang J, Teng X. Efficient 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography-based machine learning model for predicting epidermal growth factor receptor mutations in non-small cell lung cancer. Q J Nucl Med Mol Imaging. 2022. https://doi.org/10.23736/s1824-4785.22.03441-0.

Article  PubMed  Google Scholar 

Zhao HY, Su YX, Zhang LH, Fu P. Prediction model based on 18F-FDG PET/CT radiomic features and clinical factors of EGFR mutations in lung adenocarcinoma. Neoplasma. 2022;69:233–41.

Article  PubMed  Google Scholar 

Yang L, Xu P, Li M, Wang M, Peng M, Zhang Y, et al. PET/CT radiomic features: a potential biomarker for EGFR mutation status and survival outcome prediction in NSCLC patients treated with TKIs. Front Oncol. 2022;12: 894323.

Article  PubMed  PubMed Central  Google Scholar 

Shiri I, Amini M, Nazari M, Hajianfar G, Haddadi Avval A, Abdollahi H, et al. Impact of feature harmonization on radiogenomics analysis: prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images. Comput Biol Med. 2022;142: 105230.

Article  CAS  PubMed  Google Scholar 

Chang C, Zhou S, Yu H, Zhao W, Ge Y, Duan S, et al. A clinically practical radiomics-clinical combined model based on PET/CT data and nomogram predicts EGFR mutation in lung adenocarcinoma. Eur Radiol. 2021;31:6259–68.

Article  CAS  PubMed  Google Scholar 

Yang B, Ji HS, Zhou CS, Dong H, Ma L, Ge YQ, et al. (18)F-fluorodeoxyglucose positron emission tomography/computed tomography-based radiomic features for prediction of epidermal growth factor receptor mutation status and prognosis in patients with lung adenocarcinoma. Transl Lung Cancer Res. 2020;9:563–74.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Shiri I, Maleki H, Hajianfar G, Abdollahi H, Ashrafinia S, Hatt M, et al. Next-generation radiogenomics sequencing for prediction of EGFR and KRAS mutation status in NSCLC patients using multimodal imaging and machine learning algorithms. Mol Imaging Biol. 2020;22:1132–48.

Article  CAS  PubMed  Google Scholar 

Koyasu S, Nishio M, Isoda H, Nakamoto Y, Togashi K. Usefulness of gradient tree boosting for predicting histological subtype and EGFR mutation status of non-small cell lung cancer on (18)F FDG-PET/CT. Ann Nucl Med. 2020;34:49–57.

Article  CAS  PubMed  Google Scholar 

Zhang H, Cai W, Wang Y, Liao M, Tian S. CT and clinical characteristics that predict risk of EGFR mutation in non-small cell lung cancer: a systematic review and meta-analysis. Int J Clin Oncol. 2019;24:649–59.

Article  CAS  PubMed  Google Scholar 

Yang X, Dong X, Wang J, Li W, Gu Z, Gao D, et al. Computed tomography-based radiomics signature: a potential indicator of epidermal growth factor receptor mutation in pulmonary adenocarcinoma appearing as a subsolid nodule. Oncologist. 2019;24:e1156–64.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cheng B, Deng H, Zhao Y, Xiong J, Liang P, Li C, et al. Predicting EGFR mutation status in lung adenocarcinoma presenting as ground-glass opacity: utilizing radiomics model in clinical translation. Eur Radiol. 2022;32:5869–79.

Article  CAS  PubMed  Google Scholar 

留言 (0)

沒有登入
gif