93 Background: 18-F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) is currently the imaging method of choice in assessing response of neoadjuvant chemoradiotherapy (nCRT) in esophageal cancer (EC) patients. PET/CT derived texture analysis is potentially more useful than common PET/CT measurements in response assessment and might also be of predictive value in different cancer types. The aim of this study was to develop a model to predict response to nCRT in EC based on pretreatment FDG-PET derived textural features in combination with clinical parameters. Methods: We reviewed 80 locally advanced EC patients who underwent pretreatment FDG-PET/CT and radiation planning CT scans between 2009 and 2015. Patients received nCRT according to the CROSS regimen (carboplatin/paclitaxel/41.4Gy) followed by esophagectomy. We analyzed 7 clinical, 16 geometry-based, and 87 different texture features derived from pretreatment FDG-PET images of the radiotherapy gross tumor volume. Ordinal logistic regression analysis was performed to construct a prediction model for treatment response, which was pathologically classified in complete, partial and no response on the Mandard tumor regression grade (1 vs. 2-3 vs. 4-5). The performance of this model was estimated by comparison with clinical outcome. Results: Pathologic examination revealed 16 (20.0%) complete, 46 (57.5%) partial, and 18 (22.5%) non- responders. Response analysis yielded the following independent predictive textural features: SUVmin, small zone low gray level emphasis, and contrast; and the independent predictive clinical parameters: nodal stage, endoscopic tumor length, and gender. The model has a sensitivity/specificity, positive/negative predictive value, and accuracy of 69%/97%, 85%/93%, and 91% for the prediction of complete response and 61%/79%, 46%/88%, and 75% for non-response, respectively. Conclusions: The prediction model constructed in this study, shows a good overall performance level in predicting response to nCRT in EC patients, but requires further external validation and refinement before it can be used for clinical decision making.
Predicting Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer with Textural Features Derived from Pretreatment18F-FDG PET/CT Imaging