alexa Radiobiological Modeling Based on 18F-Fluorodeoxyglucos
ISSN: 2155-9619

Journal of Nuclear Medicine & Radiation Therapy
Open Access

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Research Article

Radiobiological Modeling Based on 18F-Fluorodeoxyglucose Positron Emission Tomography Data for Esophageal Cancer

Mariana Guerrero1*, Shan Tan1,2 and Wei Lu1

1Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, 21201, USA

2Department of Intelligent Science and Technology, School of Automation, Huazhong University of Science and Technology, Wuhan, China

*Corresponding Author:
Mariana Guerrero, PhD
Clinical Associate Professor
University of Maryland School of Medicine
Baltimore, MD 21201, USA
Tel: 410-328-7023
Fax: 410-328-2618
E-mail: [email protected]

Received date: July 28, 2014; Accepted date: September 23, 2014; Published date: September 29, 2014

Citation: Guerrero M, Tan S, Lu W (2014) Radiobiological Modeling Based on 18F-Fluorodeoxyglucose Positron Emission Tomography Data for Esophageal Cancer. J Nucl Med Radiat Ther 5:190. doi: 10.4172/2155-9619.1000190

Copyright: © 2014 Guerrero M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




Background: We investigated the relationship of standardized uptake values (SUVs) to radiobiological parameters, such a 25 s tumor control probability (TCP), to allow for quantitative prediction of tumor response based on SUVs from 18F fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) before and after treatment for esophageal cancer.
Methods: We analyzed data from 20 esophageal cancer patients treated with chemoradiotherapy (CRT) followed by surgery. Tumor pathologic response to CRT was assessed in surgical specimens. Patients underwent 18F-FDG PET imaging before and after CRT. Rigid image registration was performed between both images. Because TCP in a heterogeneous tumor is a function of average cell survival, we modeled TCP as a function of , a possible surrogate for average cell survival (=). TCP was represented by a sigmoid function with two parameters: SUVR50, the at which TCP=0.5, and γ50, the slope of the curve at SUVR50. The two parameters and their confidence intervals (CIs) were estimated using the maximum-likelihood method. The correlation between SUV before CRT and SUV change was also studied.
Results: A TCP model as a function of SUV before and after treatment was developed for esophageal cancer patients. The maximum-likelihood estimate of SUVR50 was 0.47 (90% CI, 0.30-0.61) and for γ50was 1.62 (90% CI, 0-4.2). High initial SUV and larger metabolic response (larger ) were correlated, and this correlation was stronger among responders. Conclusions: Our TCP model indicates that is a possible surrogate for cell survival in esophageal cancer patients. Although CIs are large as a result of the small patient sample, parameters for a TCP curve can be derived and an individualized TCP can be calculated for future patients. Initial SUV does not predict response, whereas a correlation is found between surrogates for initial tumor burden and cell kill during therapy.


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