Scientific Publications Database

Article Title: Quantitative texture analysis on pre-treatment computed tomography predicts local recurrence in stage I non-small cell lung cancer following stereotactic radiation therapy
Authors: Dennie, Carole; Thornhill, Rebecca; Souza, Carolina A.; Odonkor, Cecilia; Pantarotto, Jason R.; MacRae, Robert; Cook, Graham
Journal: QUANTITATIVE IMAGING IN MEDICINE AND SURGERY Volume 7 Issue 6
Date of Publication:2017
Abstract:
Background: The prediction of local recurrence (LR) of stage I non-small cell lung cancer (NSCLC) after definitive stereotactic body radiotherapy (SBRT) remains elusive. The purpose of this study was to assess whether quantitative imaging features on pre-treatment computed tomography (CT) can predict LR beyond 18 (F-18) fluorodeoxyglucose (F-18-FDG) positron emission tomography (PET)/CT maximum standard uptake value (SUVmax).Methods: This retrospective study evaluated 36 patients with 37 stage I NSCLC who had local tumor control (LC; n=19) and (LR; n=18). Textural features were extracted on pre-treatment CT. Mann-Whitney U tests were used to compare LC and LR groups. Receiver-operating characteristic (ROC) curves were constructed and the area under the curve (AUC) calculated with LR as outcome.Results: Gray-level correlation and sum variance were greater in the LR group, compared with the LC group (P=0.02 and P=0.04, respectively). Gray-level difference variance was lower in the LR group (P=0.004). The logistic regression model generated using gray-level correlation and difference variance features resulted in AUC (SE) 0.77 (0.08) (P=0.0007). The addition of 18F-FDG PET/CT SUVmax did not improve the AUC (P=0.75).Conclusions: CT textural features were found to be predictors of LR of early stage NSCLC on baseline CT prior to SBRT.