Abstract

In this study, we assessed the differences in the dose distribution of a 4 MV photon beam among different calculation algorithms: the Acuros XB (AXB) algorithm, the analytic anisotropic algorithm (AAA), and the pencil beam convolution (PBC) algorithm (ver. 11.0.31), in phantoms and in clinical intensity‐modulated radiation therapy (IMRT) plans. Homogeneous and heterogeneous, including middle‐, low‐, and high‐density, phantoms were combined to assess the percentage depth dose and lateral dose profiles among AXB, AAA, and PBC. For the phantom containing the low‐density area, AXB was in agreement with measurement within 0.5%, while the greatest differences between the AAA and PBC calculations and measurement were 2.7% and 3.6%, respectively. AXB showed agreement with measurement within 2.5% at the high‐density area, while AAA and PBC overestimated the dose by more than 4.5% and 4.0%, respectively. Furthermore, 15 IMRT plans, calculated using AXB, for oropharyngeal, hypopharyngeal, and laryngeal carcinomas were analyzed. The dose prescription was 70 Gy to 50% of the planning target volume (PVT70). Subsequently, each plan was recalculated using AAA and PBC while maintaining the AXB‐calculated monitor units, leaf motion, and beam arrangement. Additionally, nine hypopharyngeal and laryngeal cancer patients were analyzed in terms of PTV70 for cartilaginous structures (PVT70_cartilage). The doses covering 50% to PTV70 calculated by AAA and PBC were 2.1%±1.0% and 3.7%±0.8% significantly higher than those using AXB, respectively (p<0.01). The increases in doses to PTV70_cartilage calculated by AAA and PBC relative to AXB were 3.9% and 5.3% on average, respectively, and were relatively greater than those in the entire PVT70. AXB was found to be in better agreement with measurement in phantoms in heterogeneous areas for the 4 MV photon beam. Considering AXB as the standard, AAA and PBC overestimated the IMRT dose for head and neck cancer. The dosimetric differences should not be ignored, particularly with cartilaginous structures in PTV.PACS number: 87.55.‐x, 87.55.dk, 87.55.kd

Highlights

  • Dose calculation accuracy is one of the most important steps in the radiation therapy treatment process; the dose calculation process is imperfect due to measurement uncertainties, inadequacies in beam modeling, and inherent limitations in the algorithms.To maximize the therapeutic benefit of radiation therapy, it is essential that the estimated doses to tissues are delivered accurately

  • For the phantom containing the low-density area, Acuros XB (AXB) was in agreement with measurement within 0.5%, while the greatest differences between the analytic anisotropic algorithm (AAA) and pencil beam convolution (PBC) calculations and measurement were 2.7% and 3.6%, respectively

  • Some investigations have shown that AXB could achieve comparable accuracy to Monte Carlo methods, which are widely considered the gold standard for accurate dose calculation used in radiation therapy in phantom experiments, assuming the presence of homogeneous water and heterogeneous media.[3,4]

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Summary

MV photon beam in head and neck intensity-modulated radiation therapy

For the phantom containing the low-density area, AXB was in agreement with measurement within 0.5%, while the greatest differences between the AAA and PBC calculations and measurement were 2.7% and 3.6%, respectively. AXB showed agreement with measurement within 2.5% at the high-density area, while AAA and PBC overestimated the dose by more than 4.5% and 4.0%, respectively. 15 IMRT plans, calculated using AXB, for oropharyngeal, hypopharyngeal, and laryngeal carcinomas were analyzed. The increases in doses to PTV70_cartilage calculated by AAA and PBC relative to AXB were 3.9%. AXB was found to be in better agreement with measurement in phantoms in heterogeneous areas for the 4 MV photon beam. Considering AXB as the standard, AAA and PBC overestimated the IMRT dose for head and neck cancer.

INTRODUCTION
Phantom study
Patient selection and volume definition of targets and organs at risk
Treatment planning
RESULTS
CONCLUSIONS
Full Text
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