PURPOSE: To evaluate the accuracy of previously reported superposition/convolution (SC) dosimetric results by comparing with Monte Carlo (MC) dose calculations for head-and-neck intensity-modulated radiation therapy (IMRT) patients treated with the simultaneous integrated boost technique. METHODS AND MATERIALS: Thirty-one plans from 24 patients previously treated on a phase I/II head-and-neck squamous cell carcinoma simultaneous integrated boost IMRT protocol were used. Clinical dose distributions, computed with an SC algorithm, were recomputed using an EGS4-based MC algorithm. Phantom-based dosimetry quantified the fluence prediction accuracy of each algorithm. Dose-volume indices were used to compare patient dose distributions. RESULTS AND DISCUSSION: The MC algorithm predicts flat-phantom measurements better than the SC algorithm. Average patient dose indices agreed within 2.5% of the local dose for targets; 5.0% for parotids; and 1.9% for cord and brainstem. However, only 1 of 31 plans agreed within 3% for all indices; 4 of 31 agreed within 5%. In terms of the prescription dose, 4 of 31 plans agreed within 3% for all indices, whereas 28 of 31 agreed within 5%. CONCLUSIONS: Average SC-computed doses agreed with MC results in the patient geometry; however deviations >5% were common. The fluence modulation prediction is likely the major source of the dose discrepancy. The observed dose deviations can impact dose escalation protocols, because they would result in shifting patients to higher dose levels.
PURPOSE: To evaluate the accuracy of previously reported superposition/convolution (SC) dosimetric results by comparing with Monte Carlo (MC) dose calculations for head-and-neck intensity-modulated radiation therapy (IMRT) patients treated with the simultaneous integrated boost technique. METHODS AND MATERIALS: Thirty-one plans from 24 patients previously treated on a phase I/II head-and-neck squamous cell carcinoma simultaneous integrated boost IMRT protocol were used. Clinical dose distributions, computed with an SC algorithm, were recomputed using an EGS4-based MC algorithm. Phantom-based dosimetry quantified the fluence prediction accuracy of each algorithm. Dose-volume indices were used to compare patient dose distributions. RESULTS AND DISCUSSION: The MC algorithm predicts flat-phantom measurements better than the SC algorithm. Average patient dose indices agreed within 2.5% of the local dose for targets; 5.0% for parotids; and 1.9% for cord and brainstem. However, only 1 of 31 plans agreed within 3% for all indices; 4 of 31 agreed within 5%. In terms of the prescription dose, 4 of 31 plans agreed within 3% for all indices, whereas 28 of 31 agreed within 5%. CONCLUSIONS: Average SC-computed doses agreed with MC results in the patient geometry; however deviations >5% were common. The fluence modulation prediction is likely the major source of the dose discrepancy. The observed dose deviations can impact dose escalation protocols, because they would result in shifting patients to higher dose levels.
Authors: Vladimir Feygelman; Kujtim Latifi; Mark Bowers; Kevin Greco; Eduardo G Moros; Max Isacson; Agnes Angerud; Jimmy Caudell Journal: J Appl Clin Med Phys Date: 2022-02-25 Impact factor: 2.243
Authors: Nesrin Dogan; Ivaylo Mihaylov; Yan Wu; Paul J Keall; Jeffrey V Siebers; Michael P Hagan Journal: Radiat Oncol Date: 2009-06-15 Impact factor: 3.481