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

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.

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 R>, a possible surrogate for average cell survival (R>=after/SUV_before>). TCP was represented by a sigmoid function with two parameters: SUV_R50, the R> at which TCP=0.5, and γ₅₀, the slope of the curve at SUV_R50. The two parameters and their confidence intervals (CIs) were estimated using the maximum-likelihood method. The correlation between SUV before CRT and SUV change before - SUV_after> was also studied.

A TCP model as a function of SUV before and after treatment was developed for esophageal cancer patients. The maximum-likelihood estimate of SUV_R50 was 0.47 (90% CI, 0.30-0.61) and for γ₅₀ was 1.62 (90% CI, 0-4.2). High initial SUV and larger metabolic response (larger before -SUV_after>) were correlated, and this correlation was stronger among responders.

Our TCP model indicates that after/SUV_before> 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.