Fifty-seventh annual meeting of the American association of physicists in medicine
MO-F-CAMPUS-J-05: Using 2D Relative Gamma Analysis From EPID Image as a Predictor of Plan Deterioration Due to Anatomical Changes
One of the side effects of radiotherapy for head and neck (H&N) cancer is the patient's anatomical changes. The changes can strongly affect the planned dose distribution. In this work, our goal is to demonstrate that relative analysis of EPID images is a fast and simple method to detect anatomical changes that can have a strong dosimetric impact on the treatment plan for H&N patients.
EPID images were recorded at every beam and all fractions for 50 H&N patients. Of these, five patients that showed important anatomical changes were selected to evaluate dosimetric impacts of these changes and to correlate them with a 2D relative gamma analysis of EPID images. The planning CT and original contours were deformed onto CBCTs (one mid treatment and one at the end of treatment). By using deformable image registration, it was possible to map accurate CT numbers from the planning CT to the anatomy of the day obtained with CBCTs. Clinical treatment plan were then copied on the deformed dataset and dose was re-computed. In parallel, EPID images were analysed using the gamma index (3%3mm) relative to the first image.
It was possible to divide patients in two distinct, statistically different (p<0.001) categories using an average gamma index of 0.5 as a threshold. Below this threshold no significant dosimetric degradation of the plan are observed. Above this threshold two types of plan deterioration were seen: (1) target dose increases, but coverage remains adequate while dose to at least one OAR increases beyond tolerances; (2) the OAR doses remain low, but the target dose is reduced and coverage becomes inadequate.
Relative analysis gamma of EPID images could indeed be a fast and simple method to detect anatomical changes that can potentially deteriorates treatment plan for H&N patients.
This work was supported in part by Varian Medical System