Room: Exhibit Hall
Purpose: To access the risk of second tumor induction in radiotherapy, the whole-body dose is needed. Via API-interface, we included an out-of-field dose model for external radiotherapy into the Eclipse-TPS to render the dose (photons and neutrons) clinically available within an accuracy of (0±20)% (one sigma). One problem in calculating the whole-body dose is the missing anatomy in partial body CT of the patient in the out-of-field region. Sophisticated computational human phantoms (CHPs) are available which can be fused with the limited patient CT resulting in a whole-body representation. In this study we quantified the effect of patient substitutes in terms of the accuracy in out-of-field dose calculation.
Methods: An anthropomorphic Alderson phantom was assumed to be the patient. For an IMRT treatment of a rhabdomyosarcoma located in the prostate, the whole-body dose of the patient was calculated and measured using ~400 TLDs. The patient was virtually split in two parts: pelvis where the tumor was located, and upper-body. A mismatch between the patient and a CHP (NCI) substitute was simulated by systematically displacing the upper-body 5cm either lateral, coronal, or sagittal and fusing it with the pelvis. Furthermore, CHPs of different hights (160-180cm) and weights (55-105kg) were fused with the pelvis of the patient. For the resulting whole-body representations of the patient, the dose was recalculated and compared to the original-calculated and measured dose.
Results: The deviation between the recalculated whole-body doses and the measured TLD point doses was (5±15)%. Compared to the original-calculated whole-body dose, the biggest deviation of the mean organ doses was noticed for the largest sagittal displacement.
Conclusion: A lateral or coronal mismatch and a difference in the thickness between the patient and the CHP leads to a small error in out-of-field dose. A sagittal shift of the organs strongly influences the mean organ dose.
TH- External beam- photons: out of field dosimetry/risk analysis