Retrospective Estimation of Linear Energy Transfer Distributions within Pediatric Patients Treated with Passive Scattering Proton Therapy
Abstract
Purpose
The NCI Pediatric Proton and Photon Therapy Comparison Cohort aims to compare the risk of second malignancies in patients treated with proton versus photon radiotherapy. Using Monte Carlo (MC) simulations, normal tissue dose estimates were retrospectively calculated. Late effects depend not only on the physical dose, but also on radiation quality. In proton therapy, the primary proton beam and secondary particles deposit dose through charged particle interactions. The relative biological effectiveness of cancer induction may be linked to the density of these ionizing interactions, quantified as the linear energy transfer (LET). This pilot study develops a workflow to estimate LET for patients treated with passive scattering proton therapy to support future analyses of treatment-related outcomes.
Methods
Data from thirty patients undergoing passive scattering proton radiotherapy were incorporated into a MC workflow to reconstruct patient-specific normal tissue dose estimates. Fifteen patients were treated intracranially and fifteen received craniospinal irradiation (CSI). For patients with limited imaging, the workflow extended partial-body into whole-body anatomy with automatically contoured tissues. MC simulations were performed using TOPAS, and the distribution of dose-averaged LET (LETd) within the patient was calculated using the built-in ProtonLET scorer.
Results
LETd and LETd-volume estimates provide insight into radiation quality of the organ absorbed dose and dose-volume received from these treatment techniques. In general, near-field and out-of-field organs received dose with higher LETd than organs partially or fully in-field. For example, one patient treated with CSI received a mean absorbed dose of 3.87 Gy to the near-field esophagus and 3.19 Gy to the partially in-field right kidney; the mean LETd of these two organs were 10.33 and 4.82 keV/um, respectively.
Conclusion
This work establishes a MC-based workflow for estimating patient-specific LETd in passive scattering proton therapy. These data enable future cohort analyses to incorporate radiation quality when evaluating treatment-related health risks.