Analytical investigation of magnetic field effects on Proton lateral deflection and penetrating depth in the water phantom: A relativistic approach

Converging Proton Minibeams with Magnetic Fields for Optimized Radiation Therapy: A Proof of Concept

Proton MiniBeam Radiation Therapy (pMBRT) is a novel strategy that combines the benefits of minibeam radiation therapy with the more precise ballistics of protons to further optimize the dose distribution and reduce radiation side effects. The aim of this study is to investigate possible strategies to couple pMBRT with dipole magnetic fields to generate a converging minibeam pattern and increase the center-to-center distance between minibeams. Magnetic field optimization was performed so as to obtain the same transverse dose profile at the Bragg peak position as in a reference configuration with no magnetic field. Monte Carlo simulations reproducing realistic pencil beam scanning settings were used to compute the dose in a water phantom. We analyzed different minibeam generation techniques, such as the use of a static multislit collimator or a dynamic aperture, and different magnetic field positions, i.e., before or within the water phantom. The best results were obtained using a dynamic aperture coupled with a magnetic field within the water phantom. For a center-to-center distance increase from 4 mm to 6 mm, we obtained an increase of peak-to-valley dose ratio and decrease of valley dose above 50%. The results indicate that magnetic fields can be effectively used to improve the spatial modulation at shallow depth for enhanced healthy tissue sparing.

Dosimetric evaluation of synthetic CT generated with GANs for MRI-only proton therapy treatment planning of brain tumors

PURPOSE

The purpose of this study was to address the dosimetric accuracy of synthetic computed tomography (sCT) images of patients with brain tumor generated using a modified generative adversarial network (GAN) method, for their use in magnetic resonance imaging (MRI)-only treatment planning for proton therapy.

METHODS

Dose volume histogram (DVH) analysis was performed on CT and sCT images of patients with brain tumor for plans generated for intensity-modulated proton therapy (IMPT). All plans were robustly optimized using a commercially available treatment planning system (RayStation, from RaySearch Laboratories) and standard robust parameters reported in the literature. The IMPT plan was then used to compute the dose on CT and sCT images for dosimetric comparison, using RayStation analytical (pencil beam) dose algorithm. We used a second, independent Monte Carlo dose calculation engine to recompute the dose on both CT and sCT images to ensure a proper analysis of the dosimetric accuracy of the sCT images.

RESULTS

The results extracted from RayStation showed excellent agreement for most DVH metrics computed on the CT and sCT for the nominal case, with a mean absolute difference below 0.5% (0.3 Gy) of the prescription dose for the clinical target volume (CTV) and below 2% (1.2 Gy) for the organs at risk (OARs) considered. This demonstrates a high dosimetric accuracy for the generated sCT images, especially in the target volume. The metrics obtained from the Monte Carlo doses mostly agreed with the values extracted from RayStation for the nominal and worst-case scenarios (mean difference below 3%).

CONCLUSIONS

This work demonstrated the feasibility of using sCT generated with a GAN-based deep learning method for MRI-only treatment planning of patients with brain tumor in intensity-modulated proton therapy.