Generalized approach for radiotherapy treatment planning by optimizing projected health outcome: preliminary results for prostate radiotherapy patients

Image-based data mining applies to data collected from children

PURPOSE

Image-based data mining (IBDM) is a novel voxel-based method for analyzing radiation dose responses that has been successfully applied in adult data. Because anatomic variability and side effects of interest differ for children compared to adults, we investigated the feasibility of IBDM for pediatric analyses.

METHODS

We tested IBDM with CT images and dose distributions collected from 167 children (aged 10 months to 20 years) who received proton radiotherapy for primary brain tumors. We used data from four reference patients to assess IBDM sensitivity to reference selection. We quantified spatial-normalization accuracy via contour distances and deviations of the centers-of-mass of brain substructures. We performed dose comparisons with simplified and modified clinical dose distributions with a simulated effect, assessing their accuracy via sensitivity, positive predictive value (PPV) and Dice similarity coefficient (DSC).

RESULTS

Spatial normalizations and dose comparisons were insensitive to reference selection. Normalization discrepancies were small (average contour distance < 2.5 mm, average center-of-mass deviation < 6 mm). Dose comparisons identified differences (p < 0.01) in 81% of simplified and all modified clinical dose distributions. The DSCs for simplified doses were high (peak frequency magnitudes of 0.9-1.0). However, the PPVs and DSCs were low (maximum 0.3 and 0.4, respectively) in the modified clinical tests.

CONCLUSIONS

IBDM is feasible for childhood late-effects research. Our findings may inform cohort selection in future studies of pediatric radiotherapy dose responses and facilitate treatment planning to reduce treatment-related toxicities and improve quality of life among childhood cancer survivors.

Stray neutron radiation exposures from proton therapy: physics-based analytical models of neutron spectral fluence, kerma and absorbed dose

Objective. Patients who receive proton beam therapy are exposed to unwanted stray neutrons. Stray radiations increase the risk of late effects in normal tissues, such as second cancers and cataracts, and may cause implanted devices such as pacemakers to malfunction. Compared to therapeutic beams, little attention has been paid to modeling stray neutron exposures. In the past decade, substantial progress was made to develop semiempirical models of stray neutron dose equivalent, but models to routinely calculate neutron absorbed dose and kerma are still lacking. The objective of this work was to develop a new physics based analytical model to calculate neutron spectral fluence, kerma, and absorbed dose in a water phantom. Approach. We developed the model using dosimetric data from Monte Carlo simulations and neutron kerma coefficients from the literature. The model explicitly considers the production, divergence, scattering, and attenuation of neutrons. Neutron production was modeled for 120–250 MeV proton beams impinging on a variety of materials. Fluence, kerma and dose calculations were performed in a 30 × 180 × 44 cm3 phantom at points up to 43 cm in depth and 80 cm laterally. Main Results. Predictions of the analytical model agreed reasonably with corresponding values from Monte Carlo simulations, with a mean difference in average energy deposited of 20%, average kerma coefficient of 21%, and absorbed dose to water of 49%. Significance. The analytical model is simple to implement and use, requires less configuration data that previously reported models, and is computationally fast. This model appears potentially suitable for integration in treatment planning system, which would enable risk calculations in prospective and retrospective cases, providing a powerful tool for epidemiological studies and clinical trials.

A patient-specific hybrid phantom for calculating radiation dose and equivalent dose to the whole body

OBJECTIVE

As cancer survivorship increases, there is growing interest in minimizing the late effects of radiation therapy such as radiogenic second cancer, which may occur anywhere in the body. Assessing the risk of late effects requires knowledge of the dose distribution throughout the whole body, including regions far from the treatment field, beyond the typical anatomical extent of clinical CT scans.

APPROACH

A hybrid phantom was developed which consists of in-field patient CT images extracted from ground truth whole-body CT (WBCT) scans, out-of-field mesh phantoms scaled to basic patient measurements, and a blended transition region. Four of these hybrid phantoms were created, representing male and female patients receiving proton therapy treatment in pelvic and cranial sites. To assess the performance of the hybrid approach, we simulated treatments using the hybrid phantoms, the scaled and unscaled mesh phantoms, and the ground truth whole-body CTs. We calculated absorbed dose and equivalent dose in and outside of the treatment field, with a focus on neutrons induced in the patient by proton therapy. Proton and neutron dose was calculated using a general purpose Monte Carlo code.

MAIN RESULTS

The hybrid phantom provided equal or superior accuracy in calculated organ dose and equivalent dose values relative to those obtained using the mesh phantoms in 78% in all selected organs and calculated dose quantities. Comparatively the default mesh and scaled mesh were equal or superior to the other phantoms in 21% and 28% of cases respectively.

SIGNIFICANCE

The proposed methodology for hybrid synthesis provides a tool for whole-body organ dose estimation for individual patients without requiring CT scans of their entire body. Such a capability would be useful for personalized assessment of late effects and risk-optimization of treatment plans.