Abstract The mortality rate of lung cancer is relatively high and the incidence of lung cancer has been increased year by year. Consequently, early screening and diagnosis plays a crucial role. The traditional screening method is biopsy, which has multiple defects. Radiomics can resolve these limitations and improve the diagnosis and prognosis of lung cancer in a noninvasive and low-cost manner, assisting the clinicians to make decisions in clinical practice. In this paper, the process and application, prospects and challenges of radiomics in the screening of lung cancer were introduced, aiming to promote the development of radiomics.
[1] Jemal A,Bray F,Center MM,et al. Global cancer statistics[J].CA:Cancer J Clinicians,61(1):69-90.DOI:10.3322/caac.20107. [2] Siegel R, Jemal A. Cancer facts& figures 2015[J]. Am Cancer Soc,2015, 65(1):5-29. [3] Canadian Cancer Society′s Advisory Committee. Canadian cancer statistics 2015[R].Can Cancer Soc,2015:1-151.DOI:10.1126/science.251.4994.623-e. [4] 张乐,黄筱.我国会不会成为第一肺癌大国？[J].环球经济,2014(Z2):49-49. Zhang L,Huang Y.Will China become the first big lung cancer country?[J].Global Economy,2014(Z2):49-49. [5] Madeleine S, Evelyn E, Janna E,et al. Radiomics applied to lung cancer:a review[J].Transl Cancer Res,2016,5(4):398-409. DOI:10.21037/tcr.2016.06.18. [6] Burton,A.RECIST:right time to renovate?[J].Lancet Oncol,2007(8):464-465.DOI:10.1016/S1470-2045(07)70155-9. [7] Birchard,K,Hoang R,Herndon JK,et al. Early changes in tumor size in patients treated for advanced stage nonsmall cell lung cancer do not correlate with survival[J].Cancer,2009,115(3),581-586.DOI:10.1001/cncr.24060. [8] Stephen S,Hugo J.Applications and limitation of radiomics[J].Phys Med Biol,2016,61(1):150-166. DOI:10.1088/0031-9155/61/13/R150. [9] Philippe L.Radiomics:Extracting more information form medical images using advanced feature analysis[J].European J Cancer,2012,48(4):441-446. DOI:10.1016/j.ejca.2011.11.036. [10] Hatt M,Tixier F,Visvikis D,et al. Radiomics in PET/CT:More than meets the eye?[J].J Nucl Med,2017,58(3):365. DOI:10.2967/jnumed.116.184655. [11] Kumar V, Gu YH, Basu S,et al. Radiomics:the process and the challenges[J].Magn Reson Imag,2012,30(9),1234-1248. DOI:10.1016/j.mri.2012.06.010. [12] Fave X,Zhang L,Yang J,et al. Delta-radiomics features for the prediction of patient outcomes in non–small cell lung cancer[J].Scient Rep,2017(7):588. DOI:10.1038/s41598-017-00665-z. [13] 贾田颖,余雯,傅小龙.影像组学在非小细胞肺癌精准治疗中的应用进展[J].中华放射医学与防护杂志,2016,36(12):947-950. DOI:10.3760/cma.j.issn.0254-5098.2016.12.015. Jia TY,Yu W,Fu XL. Progress in the application of imaging in precision treatment of non-small cell lung cancer[J]. Chin J Radiol Med Protect,2016,36(12):947-950.DOI:10.3760/cma.j.issn.0254-5098.2016.12.015. [14] Yu DD,Zang YL,Dong D,et al. Developing a radiomics framework for classifying non-small cell lung carcinoma subtypes[J].Spie Med Imag,2017:1013426. DOI:10.1117/12.2253923. [15] Emaminejad N,Wang Y,Qian W,et al. Applying a radiomics approach to predict prognosis of lung cancer patients[J].Med Imag Comput Aid Diag,2016,9785:97851E. DOI:10.1117/12.2214672. [16] Coroller TP,Agrawal V,Narayan V,et al. Radiomic phenotype features predict pathological response in non-small cell lung cancer[J].Radiother Oncol,2016,119(3):480-486. DOI:10.1016/j.radonc.2016.04.004. [17] Moran A,Daly ME,Ssf Y,et al. Radiomics-based assessment of radiation-induced lung injury after stereotactic body radiotherapy[J].Clin Lung Cancer,2017,18(6):e425-2431. DOI:10.1016/j,cllc.2017.05.014. [18] Wang J,X Liu X, Dong D,et al. Prediction of malignant and benign of lung tumor using a quantitative radiomic method[J].Int Conf IEEE Eng Med Biol Soc,2016,1272. DOI:10.1109/EMBC.2016.7590938. [19] Yip SS,Aerts HJ.Application and limitations of radiomics[J].Phys Med Biol,2016,61(13):150-166. DOI:10.1088/0031-9155/61/13/R150. [20] Scrivener M, Jong EECD, Timmeren JEV,et al. Radiomics applied to lung cancer:a review[J].Tran Cancer Res,2016,5(4):398-409.DOI:10.21037/tcr.2016.01.18.
2019, Vol. 28 
