THE USE OF ONLINE IMAGE VERIFICATION TO ESTIMATE THE VARIATION IN RADIATION-THERAPY DOSE DELIVERY

Purpose: On-line radiotherapy imaging systems provide data that allow us to study the geometric nature of treatment variation. It is more cl inically relevant to examine the resultant dosimetric variation. In th is work, daily beam position as recorded by the on-line images is used to recalculate the treatment plan to show the effect geometric variat ion has on dose. Methods and Materials: Daily 6 MV or 18 MV x-ray port al images were acquired using a fiberoptic on-line imaging system for 12 patients with cancers in the head and neck, thoracic, and pelvic re gions. Each daily on-line portal image was aligned with the prescripti on simulation image using a template of anatomical structures defined on the latter. The outline of the actual block position was then super imposed on the prescription image. Daily block positions were cumulate d to give a summary image represented by the block overlap isofrequenc y distribution. The summary data were used to analyze the amount of ge ometric variation relative to the prescription boundary on a histogram distribution plot. Treatment plans were recalculated by considering e ach aligned portal image as an individual beam. Results: On-Line Image Verification (OLIV) data can differentiate between systematic and ran dom errors in a course of daily radiation therapy. The data emphasize that the type and magnitude of patient set-up errors are unique for in dividual patients and different clinical situations. Head and neck sit es had the least random variation (average 0-100% block overlap isofre quency distribution width = 7 mm) compared to thoracic (average 0-100% block overlap isofrequency distribution width = 12 mm) or pelvic site s (average 0-100% block overlap isofrequency distribution width = 14 m m). When treatment delivery is analyzed case by case, systematic as we ll as random errors are represented. When the data are pooled by anato mical site, individuality of variations is lost and variation appears random. Recalculated plans demonstrated dosimetric deviations from the original plans. The differences between the two dosimetric distributi ons were emphasized using a technique of plan subtraction. This allowe d quick identification of relative ''hot and cold spots'' in the recal culated plans. The magnitude and clinical significance of dosimetric v ariation was unique for each patient. Conclusions: OLIV data are usefu l to study geometric uncertainties because of the unique nature for in dividual patients. Dose recalculation is helpful to illustrate the dos imetric consequences of set-up errors.