A method to verify sections of arc during intrafraction portal dosimetry for prostate VMAT

Abstract

Abstract This study investigates the use of a running sum of images during segment-resolved intrafraction portal dosimetry for volumetric modulated arc therapy (VMAT), so as to alert the operator to an error before it becomes irremediable. At the time of treatment planning, predicted portal images were created for each segment of the VMAT arc, and at the time of delivery, intrafraction monitoring software polled the portal imager to read new images as they became available. The predicted and measured images were compared and displayed on a segment basis. In particular, a running sum of images from ten segments (a ‘section’) was investigated, with mean absolute difference between predicted and measured images being quantified. Images for 13 prostate patients were used to identify appropriate tolerance values for this statistic. Errors in monitor units of 2%–10%, field size of 2–10 mm, field position of 2–10 mm and path length of 10–50 mm were deliberately introduced into the treatment plans and delivered to a water-equivalent phantom and the sensitivity of the method to these errors was investigated. Gross errors were also considered for one case. The patient images show considerable variability from segment to segment, but when using a section of the arc the variability is reduced, so that the maximum value of mean absolute difference between predicted and measured images is reduced to below 12%, after excluding the first 10% of segments. This tolerance level is also found to be applicable for delivery of the plans to a water-equivalent phantom. Using this as a tolerance level for the error plans, a 10% increase in monitor units is detected, 4 mm increase or shift in multileaf collimator settings can be detected, and an air gap of dimensions 40 mm  ×  50 mm is detected. Gross errors can also be detected instantly after the first 10% of segments. The running difference between predicted and measured images over ten segments is able to identify errors at specific regions of the arc, as well as in the overall treatment.