Investigation of a Novel Decision Support Metric for Head and Neck Adaptive Radiation Therapy Using a Real-Time In Vivo Portal Dosimetry System.

Abstract

In adaptive radiation therapy of head and neck cancer, any significant anatomical changes observed are used to adapt the treatment plan to maintain target coverage without elevating the risk of xerostomia. However, the additional resources required for adaptive radiation therapy pose a challenge for broad-based implementation. It is hypothesized that a change in transit fluence is associated with volumetric change in the vicinity of the target and therefore can be used as a decision support metric for adaptive radiation therapy. This was evaluated by comparing the fluence with volumetric changes in 12 patients. Transit fluence was measured by an in vivo portal dosimetry system. Weekly cone beam computed tomography was used to determine volume change in the rectangular region of interest from condyloid process to C6. The integrated transit fluence through the region of interest on the day of the cone beam computed tomography scan was calculated with the first treatment as the baseline. The correlation between fluence change and volume change was determined. A logistic regression model was also used to associate the 5% region of interest volume reduction replanning trigger point and the fluence change. The model was assessed by a chi-square test. The area under the receiver–operating characteristic curve was also determined. A total of 46 pairs of measurements were obtained. The correlation between fluence and volumetric changes was found to be −0.776 (P value <.001). The negative correlation is attributed to the increase in the photon fluence transport resulting from the volume reduction. The chi-square of the logistic regression was found to be 17.4 (P value <.001). The area under the receiver–operating characteristic curve was found to be 0.88. Results indicate the change in transit fluence, which can be measured without consuming clinical resources or requiring additional time in the treatment room, can be used as a decision support metric for adaptive therapy.