Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
Tóm tắt
Từ khóa
Tài liệu tham khảo
Kurland, B. F. et al. Promise and pitfalls of quantitative imaging in oncology clinical trials. Magn. Reson. Imaging 30, 1301–1312 (2012).
Buckler, A. J., Bresolin, L., Dunnick, N. R. & Sullivan, D. C. Group. A collaborative enterprise for multi-stakeholder participation in the advancement of quantitative imaging. Radiology 258, 906–914 (2011).
Buckler, A. J. et al. Quantitative imaging test approval and biomarker qualification: interrelated but distinct activities. Radiology 259, 875–884 (2011).
Lambin, P. et al. Predicting outcomes in radiation oncology—multifactorial decision support systems. Nat. Rev. Clin. Oncol. 10, 27–40 (2013).
Jaffe, C. C. Measures of response: RECIST, WHO, and new alternatives. J. Clin. Oncol. 24, 3245–3251 (2006).
Birchard, K. R., Hoang, J. K., Herndon, J. E. & Patz, E. F. Early changes in tumor size in patients treated for advanced stage nonsmall cell lung cancer do not correlate with survival. Cancer 115, 581–586 (2009).
Lambin, P. et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur. J. Cancer 48, 441–446 (2012).
Kumar, V. et al. Radiomics: the process and the challenges. Magn. Reson. Imaging 30, 1234–1248 (2012).
Zhao, B. et al. Evaluating variability in tumor measurements from same-day repeat CT scans of patients with non–small cell lung cancer. Radiology 252, 263–272 (2009).
van Baardwijk, A. et al. PET-CT-based auto-contouring in non-small-cell lung cancer correlates with pathology and reduces interobserver variability in the delineation of the primary tumor and involved nodal volumes. Int. J. Radiat. Oncol. Biol. Phys. 68, 771–778 (2007).
Harrell, F. E. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis Springer (2001).
Subramanian, A. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
Yachida, S. et al. Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature 467, 1114–1117 (2010).
Gerlinger, M. et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. New Engl. J. Med. 366, 883–892 (2012).
Gerlinger, M. & Swanton, C. How Darwinian models inform therapeutic failure initiated by clonal heterogeneity in cancer medicine. Br. J. Cancer 103, 1139–1143 (2010).
Kern, S. E. Why your new cancer biomarker may never work: recurrent patterns and remarkable diversity in biomarker failures. Cancer Res. 72, 6097–6101 (2012).
Starmans, M. H. W. et al. Independent and functional validation of a multi-tumour-type proliferation signature. Br. J. Cancer 107, 508–515 (2012).
Nair, V. S. et al. Prognostic PET 18F-FDG uptake imaging features are associated with major oncogenomic alterations in patients with resected non-small cell lung cancer. Cancer Res. 72, 3725–3734 (2012).
Diehn, M. et al. Identification of noninvasive imaging surrogates for brain tumor gene-expression modules. Proc. Natl Acad. Sci. USA 105, 5213–5218 (2008).
Segal, E. et al. Decoding global gene expression programs in liver cancer by noninvasive imaging. Nat. Biotechnol. 25, 675–680 (2007).
Tixier, F. et al. Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer. J. Nucl. Med. 52, 369–378 (2011).
Naqa El, I. et al. Exploring feature-based approaches in PET images for predicting cancer treatment outcomes. Pattern Recognit. 42, 1162–1171 (2009).
Ganeshan, B., Panayiotou, E., Burnand, K., Dizdarevic, S. & Miles, K. Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. Eur. Radiol. 22, 796–802 (2011).
Ganeshan, B., Skogen, K., Pressney, I., Coutroubis, D. & Miles, K. Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: preliminary evidence of an association with tumour metabolism, stage, and survival. Clin. Radiol. 67, 157–164 (2012).
Gevaert, O. et al. Non-small cell lung cancer: identifying prognostic imaging biomarkers by leveraging public gene expression microarray data: methods and preliminary results. Radiology 264, 387–396 (2012).