PURPOSE: To compare (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging characteristics in non-small cell lung cancer (NSCLC) with or without epidermal growth factor receptor (EGFR) mutations. METHODS: We retrospectively identified NSCLC patients who underwent EGFR mutation testing and pretreatment FDG-PET and CT scans. The maximum standard uptake value (SUV(max)) of the primary tumor and any metastases was measured and normalized to the SUV of blood in the pulmonary artery. We compared normalized SUV(max) values between EGFR-mutant and wild-type patients and modeled radiographic and clinical predictors of EGFR mutation status. Receiver operator characteristic (ROC) curves were used to identify potential SUV cutoffs predictive of genotype. RESULTS: We included 100 patients (24 EGFR-mutant and 76 wild-type). There was a trend for higher normalized SUV(max) in the primary tumors among patients with EGFR-wild-type versus mutant (median, 3.4; range, 0.6-12.8; versus median, 2.9; range, 0.4-5.0; p = .09). Normalized SUV(max) of nodal and distant metastases, and CT characteristics were not associated with genotype. On multivariate analysis, low normalized SUV(max) of the primary tumor was predictive for EGFR mutation (odds ratio, 0.72; 95% confidence interval, 0.53-0.98; p = .034). ROC curve analyses yielded an area under the curve of 0.62, and identified a potential cutoff of ≥ 5.0 to distinguish wild-type from mutant tumors. CONCLUSIONS: In this retrospective study, high FDG avidity (normalized SUV(max) ≥ 5) correlated with EGFR-wild-type genotype. Although genotyping remains the gold standard, further work to validate FDG-PET as a surrogate for tumor genotype may provide useful information in patients without available tumor tissue.
PURPOSE: To compare (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging characteristics in non-small cell lung cancer (NSCLC) with or without epidermal growth factor receptor (EGFR) mutations. METHODS: We retrospectively identified NSCLCpatients who underwent EGFR mutation testing and pretreatment FDG-PET and CT scans. The maximum standard uptake value (SUV(max)) of the primary tumor and any metastases was measured and normalized to the SUV of blood in the pulmonary artery. We compared normalized SUV(max) values between EGFR-mutant and wild-type patients and modeled radiographic and clinical predictors of EGFR mutation status. Receiver operator characteristic (ROC) curves were used to identify potential SUV cutoffs predictive of genotype. RESULTS: We included 100 patients (24 EGFR-mutant and 76 wild-type). There was a trend for higher normalized SUV(max) in the primary tumors among patients with EGFR-wild-type versus mutant (median, 3.4; range, 0.6-12.8; versus median, 2.9; range, 0.4-5.0; p = .09). Normalized SUV(max) of nodal and distant metastases, and CT characteristics were not associated with genotype. On multivariate analysis, low normalized SUV(max) of the primary tumor was predictive for EGFR mutation (odds ratio, 0.72; 95% confidence interval, 0.53-0.98; p = .034). ROC curve analyses yielded an area under the curve of 0.62, and identified a potential cutoff of ≥ 5.0 to distinguish wild-type from mutant tumors. CONCLUSIONS: In this retrospective study, high FDG avidity (normalized SUV(max) ≥ 5) correlated with EGFR-wild-type genotype. Although genotyping remains the gold standard, further work to validate FDG-PET as a surrogate for tumor genotype may provide useful information in patients without available tumor tissue.
Authors: Rebecca L Elstrom; Daniel E Bauer; Monica Buzzai; Robyn Karnauskas; Marian H Harris; David R Plas; Hongming Zhuang; Ryan M Cinalli; Abass Alavi; Charles M Rudin; Craig B Thompson Journal: Cancer Res Date: 2004-06-01 Impact factor: 12.701
Authors: Monica Buzzai; Daniel E Bauer; Russell G Jones; Ralph J Deberardinis; Georgia Hatzivassiliou; Rebecca L Elstrom; Craig B Thompson Journal: Oncogene Date: 2005-06-16 Impact factor: 9.867
Authors: William Pao; Vincent Miller; Maureen Zakowski; Jennifer Doherty; Katerina Politi; Inderpal Sarkaria; Bhuvanesh Singh; Robert Heelan; Valerie Rusch; Lucinda Fulton; Elaine Mardis; Doris Kupfer; Richard Wilson; Mark Kris; Harold Varmus Journal: Proc Natl Acad Sci U S A Date: 2004-08-25 Impact factor: 11.205
Authors: J Guillermo Paez; Pasi A Jänne; Jeffrey C Lee; Sean Tracy; Heidi Greulich; Stacey Gabriel; Paula Herman; Frederic J Kaye; Neal Lindeman; Titus J Boggon; Katsuhiko Naoki; Hidefumi Sasaki; Yoshitaka Fujii; Michael J Eck; William R Sellers; Bruce E Johnson; Matthew Meyerson Journal: Science Date: 2004-04-29 Impact factor: 47.728
Authors: Thomas J Lynch; Daphne W Bell; Raffaella Sordella; Sarada Gurubhagavatula; Ross A Okimoto; Brian W Brannigan; Patricia L Harris; Sara M Haserlat; Jeffrey G Supko; Frank G Haluska; David N Louis; David C Christiani; Jeff Settleman; Daniel A Haber Journal: N Engl J Med Date: 2004-04-29 Impact factor: 91.245
Authors: Laura E MacConaill; Elizabeth Garcia; Priyanka Shivdasani; Matthew Ducar; Ravali Adusumilli; Marc Breneiser; Mark Byrne; Lawrence Chung; Jodie Conneely; Lauren Crosby; Levi A Garraway; Xin Gong; William C Hahn; Charlie Hatton; Philip W Kantoff; Michael Kluk; Frank Kuo; Yonghui Jia; Ruchi Joshi; Janina Longtine; Allison Manning; Emanuele Palescandolo; Nematullah Sharaf; Lynette Sholl; Paul van Hummelen; Jacqueline Wade; Bruce M Wollinson; Dimity Zepf; Barrett J Rollins; Neal I Lindeman Journal: J Mol Diagn Date: 2014-08-23 Impact factor: 5.568
Authors: Jian Guan; Nan J Xiao; Min Chen; Wen L Zhou; Yao W Zhang; Shuang Wang; Yong M Dai; Lu Li; Yue Zhang; Qin Y Li; Xiang Z Li; Mi Yang; Hu B Wu; Long H Chen; Lai Y Liu Journal: Medicine (Baltimore) Date: 2016-07 Impact factor: 1.889
Authors: Carlos Caicedo; Maria Jose Garcia-Velloso; Maria Dolores Lozano; Tania Labiano; Carmen Vigil Diaz; Jose Maria Lopez-Picazo; Alfonso Gurpide; Javier J Zulueta; Javier Zulueta; Jose Angel Richter Echevarria; Jose Luis Perez Gracia Journal: Eur J Nucl Med Mol Imaging Date: 2014-07-03 Impact factor: 9.236
Authors: Stephen S F Yip; John Kim; Thibaud P Coroller; Chintan Parmar; Emmanuel Rios Velazquez; Elizabeth Huynh; Raymond H Mak; Hugo J W L Aerts Journal: J Nucl Med Date: 2016-09-29 Impact factor: 10.057