Acute esophagitis (AE) is a common dose-limiting toxicity in radiotherapy (RT) of locally advanced non-small cell lung cancer (LA-NSCLC). We developed an early AE prediction model from weekly accumulated esophagus dose and its associated local volumetric change.
51 LA-NSCLC patients were treated via IMRT to 60Gy in 2 Gy-fractions with concurrent chemotherapy and had weekly cone-beam CTs (CBCTs). Twenty-eight patients (55%) developed ≥grade2 AE (≥AE2) at a median of 4 weeks post-RT start. For early ≥AE2 prediction, esophagus on CBCTs of the first two weeks were deformably registered to the planning CTs and weekly esophagus dose was accumulated. Week1-to-week2 esophagus volume changes including maximum esophagus expansion (MEex%) and volumes with ≥x% local expansions (VEx%; x=5, 10, 15) were calculated from the Jacobian map of deformation vector field gradients. Logistic regression model with 5-fold cross-validation was built using combinations of the accumulated Mean Esophagus Doses (MED) and the esophagus change parameters with the lowest p-value in univariate analysis. The model was validated on additional 18 and 11 patients with weekly CBCTs and MRIs, respectively, and compared to models using only planned mean dose (MED). Performance was assessed using AUC and Hosmer-Lemeshow test (P).
Univariately, w1→w2 VE10% (p=0.004), VE5% (p=0.01) and MEex% (p=0.02) significantly predicted ≥AE2. A model combining MED and w1→w2 VE10% had the best performance (AUC=0.80; P=0.43), while the MED model had a lower accuracy (AUC=0.67; P=0.26). The combined model also showed high accuracy in the CBCT (AUC=0.78) and MRI validations (AUC=0.75).
A CBCT-based cross-validated and internally validated model on MRI with a combination of accumulated esophagus dose and local volume change from the first two weeks of chemo-RT significantly improved the AE prediction compared to conventional models using only the planned dose. This model could inform plan adaptation early to lower the risk of esophagitis.

Published by Elsevier Inc.