4.7 Article

Correlation of PET images of metabolism, proliferation and hypoxia to characterize tumor phenotype in patients with cancer of the oropharynx

期刊

RADIOTHERAPY AND ONCOLOGY
卷 105, 期 1, 页码 36-40

出版社

ELSEVIER IRELAND LTD
DOI: 10.1016/j.radonc.2012.09.012

关键词

Correlation; FDG; FLT; Cu-ATSM; PET

资金

  1. Genentech
  2. NIH [5T32GM08349]
  3. UW Carbone Cancer Center

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Spatial organization of tumor phenotype is of great interest to radiotherapy target definition and outcome prediction. We characterized tumor phenotype in patients with cancers of the oropharynx through voxel-based correlation of PET images of metabolism, proliferation, and hypoxia. Methods: Patients with oropharyngeal cancer received F-18-fluorodeoxyglucose (FDG) PET/CT, F-18-fluorothymidine (FLT) PET/CT, and Cu-61-diacetyl-bis(N4-methylthiosemicarbazone) (Cu-ATSM) PET/CT. Images were co-registered and standardized uptake values (SUV) were calculated for all modalities. Voxel-based correlation was evaluated With Pearson's correlation coefficient in tumor regions. Additionally, sensitivity studies were performed to quantify the effects of image segmentation, registration, noise, and segmentation on R. Results: On average, FDG PET and FLT PET images were most highly correlated (R-FDG:FLT = 0.76, range 0.53-0.85), while Cu-ATSM PET showed greater heterogeneity in correlation to other tracers (RFDG:Cu-ATSM = 0.64, range 0.51-0.79; RFLT:Cu-ATSM = 0.61, range 0.21-0.80). Of the tested parameters, correlation was most sensitive to image registration. Misregistration of one voxel lead to Delta R-FDG = 0.25, Delta R-FLT = 0.39, and Delta RCu-ATSM = 0.27. Image noise and reconstruction also had quantitative effects on correlation. No significant quantitative differences were found between GTV, expanded GTV, or CTV regions. Conclusions: Voxel-based correlation represents a first step into understanding spatial organization of tumor phenotype. These results have implications for radiotherapy target definition and provide a framework to test outcome prediction based on pretherapy distribution of phenotype. (C) 2012 Elsevier Ireland Ltd. All rights reserved. Radiotherapy and Oncology 105 (2012) 36-40

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