Xia C, Dong X, Li H, Cao M, Solar D, He S, Yang F, Yan X, Zhang S, Li N, et al. Most cancers statistics in China and United States, 2022: profiles, developments, and determinants. Chin Med J (Engl). 2022;135(5):584–90.
Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. International Most cancers statistics 2020: GLOBOCAN estimates of incidence and Mortality Worldwide for 36 cancers in 185 international locations. CA Most cancers J Clin. 2021;71(3):209–49.
Sands J, Tammemagi MC, Couraud S, Baldwin DR, Borondy-Kitts A, Yankelevitz D, Lewis J, Grannis F, Kauczor HU, von Stackelberg O, et al. Lung screening advantages and challenges: a overview of the info and description for implementation. J Thorac Oncol. 2021;16(1):37–53.
Houston KA, Henley SJ, Li J, White MC, Richards TB. Patterns in lung most cancers incidence charges and developments by histologic kind in america, 2004–2009. Lung Most cancers. 2014;86(1):22–8.
Santabarbara G, Maione P, Rossi A, Palazzolo G, Gridelli C. The function of pembrolizumab within the therapy of superior non-small cell lung most cancers. Ann Transl Med. 2016;4(11):215.
Herbst RS, Morgensztern D, Boshoff C. The biology and administration of non-small cell lung most cancers. Nature. 2018;553(7689):446–54.
Rizvi H, Sanchez-Vega F, La Okay, Chatila W, Jonsson P, Halpenny D, Plodkowski A, Lengthy N, Sauter JL, Rekhtman N, et al. Molecular determinants of response to Anti-programmed Cell loss of life (PD)-1 and anti-programmed death-ligand 1 (PD-L1) blockade in sufferers with non-small-cell Lung Most cancers profiled with focused next-generation sequencing. J Clin Oncol. 2018;36(7):633–41.
Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF, Powderly JD, Carvajal RD, Sosman JA, Atkins MB, et al. Security, exercise, and immune correlates of anti-PD-1 antibody in most cancers. N Engl J Med. 2012;366(26):2443–54.
Garon EB, Ciuleanu TE, Arrieta O, Prabhash Okay, Syrigos KN, Goksel T, Park Okay, Gorbunova V, Kowalyszyn RD, Pikiel J, et al. Ramucirumab plus Docetaxel versus placebo plus docetaxel for second-line therapy of stage IV non-small-cell lung most cancers after illness development on platinum-based remedy (REVEL): a multicentre, double-blind, randomised section 3 trial. Lancet. 2014;384(9944):665–73.
Kluger HM, Zito CR, Turcu G, Baine MK, Zhang H, Adeniran A, Sznol M, Rimm DL, Kluger Y, Chen L, et al. PD-L1 research throughout Tumor sorts, its Differential expression and predictive worth in sufferers handled with Immune Checkpoint inhibitors. Clin Most cancers Res. 2017;23(15):4270–9.
Shi WJ, Zhao W. Biomarkers or components for predicting the efficacy and hostile results of immune checkpoint inhibitors in lung most cancers: achievements and potential. Chin Med J (Engl). 2020;133(20):2466–75.
Aerts HJ, Velazquez ER, Leijenaar RT, Parmar C, Grossmann P, Carvalho S, Bussink J, Monshouwer R, Haibe-Kains B, Rietveld D, et al. Decoding tumour phenotype by noninvasive imaging utilizing a quantitative radiomics method. Nat Commun. 2014;5:4006.
Liu Y, Balagurunathan Y, Atwater T, Antic S, Li Q, Walker RC, Smith GT, Massion PP, Schabath MB, Gillies RJ. Radiological picture traits Predictive of Most cancers Standing in Pulmonary nodules. Clin Most cancers Res. 2017;23(6):1442–9.
Ehteshami Bejnordi B, Veta M, van Johannes P, van Ginneken B, Karssemeijer N, Litjens G, van der Laak J, the, Hermsen CC, Manson M et al. QF : Diagnostic Evaluation of Deep Studying Algorithms for Detection of Lymph Node Metastases in Ladies With Breast Most cancers. JAMA 2017, 318(22):2199–2210.
Ardila D, Kiraly AP, Bharadwaj S, Choi B, Reicher JJ, Peng L, Tse D, Etemadi M, Ye W, Corrado G, et al. Finish-to-end lung most cancers screening with three-dimensional deep studying on low-dose chest computed tomography. Nat Med. 2019;25(6):954–61.
Christodoulidis S, Anthimopoulos M, Ebner L, Christe A, Mougiakakou S. Multisource switch studying with convolutional neural networks for lung sample evaluation. IEEE J Biomed Well being Inf. 2017;21(1):76–84.
Zheng Y-m, Che J-y, Yuan M-g, Wu Z-j, Pang J, Zhou R-z, Li X-l, Dong C. A CT-Based mostly Deep Studying Radiomics Nomogram to foretell histological grades of Head and Neck squamous cell carcinoma. Acad Radiol. 2023;30(8):1591–9.
Zeng Q, Li H, Zhu Y, Feng Z, Shu X, Wu A, Luo L, Cao Y, Tu Y, Xiong J et al. Growth and validation of a predictive mannequin combining scientific, radiomics, and deep switch studying options for lymph node metastasis in early gastric most cancers. Entrance Med 2022, 9.
Zhang Y, Ko C-C, Chen J-H, Chang Okay-T, Chen T-Y, Lim S-W, Tsui Y-Okay, Su M-Y. Radiomics Method for Prediction of Recurrence in Non-functioning Pituitary Macroadenomas. Entrance Oncol. 2020;10:590083.
Zhu F, Yang C, Xia Y, Wang J, Zou J, Zhao L, Zhao Z. CT-based radiomics fashions might predict the early efficacy of microwave ablation in malignant lung tumors. Most cancers Imaging: Official Publication Int Most cancers Imaging Soc. 2023;23(1):60.
Wang Y, Bi Q, Deng Y, Yang Z, Tune Y, Wu Y, Wu Okay. Growth and validation of an MRI-based Radiomics Nomogram for Assessing Deep Myometrial Invasion in Early Stage Endometrial Adenocarcinoma. Acad Radiol. 2023;30(4):668–79.
Halligan S, Menu Y, Mallett S. Why did European Radiology reject my radiomic biomarker paper? Find out how to accurately consider imaging biomarkers in a scientific setting. Eur Radiol. 2021;31(12):9361–8.
He J, Hu Y, Hu M, Li B. Growth of PD-1/PD-L1 pathway in Tumor Immune Microenvironment and Remedy for Non-small Cell Lung Most cancers. Sci Rep. 2015;5:13110.
Steven A, Fisher SA, Robinson BW. Immunotherapy for lung most cancers. Respirology. 2016;21(5):821–33.
Herbst RS, Giaccone G, de Marinis F, Reinmuth N, Vergnenegre A, Barrios CH, Morise M, Felip E, Andric Z, Geater S, et al. Atezolizumab for First-Line therapy of PD-L1-Chosen sufferers with NSCLC. N Engl J Med. 2020;383(14):1328–39.
Gadgeel S, Rodriguez-Abreu D, Speranza G, Esteban E, Felip E, Domine M, Hui R, Hochmair MJ, Clingan P, Powell SF, et al. Up to date evaluation from KEYNOTE-189: Pembrolizumab or Placebo Plus Pemetrexed and Platinum for beforehand untreated metastatic nonsquamous non-small-cell Lung Most cancers. J Clin Oncol. 2020;38(14):1505–17.
Rittmeyer A, Barlesi F, Waterkamp D, Park Okay, Ciardiello F, von Pawel J, Gadgeel SM, Hida T, Kowalski DM, Dols MC, et al. Atezolizumab versus Docetaxel in sufferers with beforehand handled non-small-cell lung most cancers (OAK): a section 3, open-label, multicentre randomised managed trial. Lancet. 2017;389(10066):255–65.
Herbst RS, Baas P, Kim DW, Felip E, Perez-Gracia JL, Han JY, Molina J, Kim JH, Arvis CD, Ahn MJ, et al. Pembrolizumab versus Docetaxel for beforehand handled, PD-L1-positive, superior non-small-cell lung most cancers (KEYNOTE-010): a randomised managed trial. Lancet. 2016;387(10027):1540–50.
Borghaei H, Paz-Ares L, Horn L, Spigel DR, Steins M, Prepared NE, Chow LQ, Vokes EE, Felip E, Holgado E, et al. Nivolumab versus Docetaxel in Superior Nonsquamous Non-small-cell Lung Most cancers. N Engl J Med. 2015;373(17):1627–39.
McGranahan N, Furness AJ, Rosenthal R, Ramskov S, Lyngaa R, Saini SK, Jamal-Hanjani M, Wilson GA, Birkbak NJ, Hiley CT, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. 2016;351(6280):1463–9.
Shur JD, Doran SJ, Kumar S, Ap Dafydd D, Downey Okay, O’Connor JPB, Papanikolaou N, Messiou C, Koh DM, Orton MR. Radiomics in Oncology: a sensible information. Radiographics. 2021;41(6):1717–32.
Wen Q, Yang Z, Zhu J, Qiu Q, Dai H, Feng A, Xing L. Pretreatment CT-Based mostly Radiomics Signature as a possible imaging Biomarker for Predicting the expression of PD-L1 and CD8 + TILs in ESCC. Onco Targets Ther. 2020;13:12003–13.
Solar R, Limkin EJ, Vakalopoulou M, Dercle L, Champiat S, Han SR, Verlingue L, Brandao D, Lancia A, Ammari S, et al. A radiomics method to evaluate tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort examine. Lancet Oncol. 2018;19(9):1180–91.
Tian Y, Komolafe TE, Zheng J, Zhou G, Chen T, Zhou B, Yang X. Assessing PD-L1 expression degree through Preoperative MRI in HCC primarily based on integrating Deep Studying and Radiomics options. Diagnostics (Basel). 2021;11(10):1875.
Jiang M, Solar D, Guo Y, Guo Y, Xiao J, Wang L, Yao X. Assessing PD-L1 expression degree by Radiomic options from PET/CT in Nonsmall Cell Lung Most cancers sufferers: an preliminary outcome. Acad Radiol. 2020;27(2):171–9.
Solar Z, Hu S, Ge Y, Wang J, Duan S, Tune J, Hu C, Li Y. Radiomics examine for predicting the expression of PD-L1 in non-small cell lung most cancers primarily based on CT pictures and clinicopathologic options. J Xray Sci Technol. 2020;28(3):449–59.
Chen H, Li S, Zhang Y, Liu L, Lv X, Yi Y, Ruan G, Ke C, Feng Y. Deep learning-based computerized segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation utilizing radiomic options: a multicentre examine. Eur Radiol. 2022;32(10):7248–59.
Wang S, Shi J, Ye Z, Dong D, Yu D, Zhou M, Liu Y, Gevaert O, Wang Okay, Zhu Y et al. Predicting EGFR mutation standing in lung adenocarcinoma on computed tomography picture utilizing deep studying. Eur Respir J 2019, 53(3).
Tian P, He B, Mu W, Liu Okay, Liu L, Zeng H, Liu Y, Jiang L, Zhou P, Huang Z, et al. Assessing PD-L1 expression in non-small cell lung most cancers and predicting responses to immune checkpoint inhibitors utilizing deep studying on computed tomography pictures. Theranostics. 2021;11(5):2098–107.
Zhu Y, Man C, Gong L, Dong D, Yu X, Wang S, Fang M, Wang S, Fang X, Chen X, et al. A deep studying radiomics mannequin for preoperative grading in meningioma. Eur J Radiol. 2019;116:128–34.
