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<p>This study evaluates the dosimetric impact of material and mass density misassignments in Acuros XB dose calculations using phantom simulations and clinical analysis in Eclipse TPS. The phantom study analyzed material and mass density misassignments in Acuros XB using virtual phantoms with a central insert assigned different materials and mass densities to simulate misassignment. A clinical analysis of 270 patient CT scans from three scanners assessed HU variations in sinonasal cavities, bladder, and liver. Dosimetric deviations were examined in 96 radiotherapy patients across these anatomical sites by comparing automatic and manual material assignments, with dose differences assessed using D<sub>98%</sub>, D<sub>mean</sub>, and D<sub>2%</sub> for target volumes and misclassified structures. Material misassignment caused substantial dose differences, particularly in air–lung and cartilage–bone misassignments, with 12.1% and 2.8% deviations, respectively. Mass density misassignments led to dose variations of up to 5.5% for lung–air and 2% for bone. Combined misassignments amplified differences, reaching 18% for air–lung and 5.5% for cartilage–bone. Misassignment of non-biological materials such as biological tissues resulted in dose differences from 1 to 26.5%. Clinical analysis showed HU variations frequently led to material misassignment. Sinonasal air cavities were misclassified as lung, causing dose deviations of 11.8% for D<sub>98%</sub>, 8.6% for D<sub>mean</sub>, and 2.6% for D<sub>2%</sub>. Bladder and liver were predominantly misclassified as muscle and cartilage, respectively, resulting in systematic dose deviations of approximately 1% and 0.5%. Accurate material assignment is critical for precise Acuros XB dose calculations. Material mischaracterization introduces significant dose differences, necessitating manual verification in cases where auto-assignment is prone to misassignment.</p>

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Dosimetric impact of material misassignment in linear Boltzmann transport equation-based external beam radiotherapy dose calculation

  • 期刊论文

  • 发表日期：

    2025年8月23日

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  • Perumal Murugan,
  • Ravikumar Manickam,
  • Tamilarasan Rajamanickam,
  • Sivakumar Muthu,
  • C. Dinesan,
  • Karthik Appunu,
  • Abishake Murali

摘要

This study evaluates the dosimetric impact of material and mass density misassignments in Acuros XB dose calculations using phantom simulations and clinical analysis in Eclipse TPS. The phantom study analyzed material and mass density misassignments in Acuros XB using virtual phantoms with a central insert assigned different materials and mass densities to simulate misassignment. A clinical analysis of 270 patient CT scans from three scanners assessed HU variations in sinonasal cavities, bladder, and liver. Dosimetric deviations were examined in 96 radiotherapy patients across these anatomical sites by comparing automatic and manual material assignments, with dose differences assessed using D98%, Dmean, and D2% for target volumes and misclassified structures. Material misassignment caused substantial dose differences, particularly in air–lung and cartilage–bone misassignments, with 12.1% and 2.8% deviations, respectively. Mass density misassignments led to dose variations of up to 5.5% for lung–air and 2% for bone. Combined misassignments amplified differences, reaching 18% for air–lung and 5.5% for cartilage–bone. Misassignment of non-biological materials such as biological tissues resulted in dose differences from 1 to 26.5%. Clinical analysis showed HU variations frequently led to material misassignment. Sinonasal air cavities were misclassified as lung, causing dose deviations of 11.8% for D98%, 8.6% for Dmean, and 2.6% for D2%. Bladder and liver were predominantly misclassified as muscle and cartilage, respectively, resulting in systematic dose deviations of approximately 1% and 0.5%. Accurate material assignment is critical for precise Acuros XB dose calculations. Material mischaracterization introduces significant dose differences, necessitating manual verification in cases where auto-assignment is prone to misassignment.