Technical Note: A Monte Carlo study of magnetic-field-induced radiation dose effects in mice

DeepMC: a deep learning method for efficient Monte Carlo beamlet dose calculation by predictive denoising in magnetic resonance-guided radiotherapy

Emerging magnetic resonance (MR) guided radiotherapy affords significantly improved anatomy visualization and, subsequently, more effective personalized treatment. The new therapy paradigm imposes significant demands on radiation dose calculation quality and speed, creating an unmet need for the acceleration of Monte Carlo (MC) dose calculation. Existing deep learning approaches to denoise the final plan MC dose fail to achieve the accuracy and speed requirements of large-scale beamlet dose calculation in the presence of a strong magnetic field for online adaptive radiotherapy planning. Our deep learning dose calculation method, DeepMC, addresses these needs by predicting low-noise dose from extremely noisy (but fast) MC-simulated dose and anatomical inputs, thus enabling significant acceleration. DeepMC simultaneously reduces MC sampling noise and predicts corrupted dose buildup at tissue-air material interfaces resulting from MR-field induced electron return effects. Here we demonstrate our model's ability to accelerate dose calculation for daily treatment planning by a factor of 38 over traditional low-noise MC simulation with clinically meaningful accuracy in deliverable dose and treatment delivery parameters. As a post-processing approach, DeepMC provides compounded acceleration of large-scale dose calculation when used alongside established MC acceleration techniques in variance reduction and graphics processing unit-based MC simulation.

Comparison of dose distributions between transverse magnetic fields of 0.35 T and 1.5 T for radiotherapy in lung tumor using Monte Carlo calculation

We investigated the impact of the transverse magnetic fields of 0.35 T and 1.5 T on the dose distributions for a 6 MV beam, by using a thorax phantom with a lung tumor. First, the dose distributions in the magnetic flux densities of 0 T, 0.35 T, and 1.5 T were compared by increasing the number of irradiation fields. Next, the dose distributions for stereotactic body radiotherapy (SBRT) with 5-fields for an isolated lung tumor was compared in transverse magnetic fields. All dose distributions were calculated by the Monte Carlo method. The prescription doses for SBRT with 5-fields was 48 Gy for D₉₅ (dose covering 95% volume) in the planning target volume (PTV). The dose distributions were analyzed by the dose difference map (DD map), dose volume histogram (DVH), and dose indices. For the 1-field, the dose distributions were more affected at 1.5 T rather than 0.35 T. The DVHs for PTV at 1.5 T almost agreed with those at 0 T for more than 5-fields. In contrast, the D₉₈ in the PTV at 0.35 T reduced constantly by 6.0% with more than 5-fields. The D₉₅ in PTV for SBRT with 5-fields was 9.0% lower at 0.35 T and 2.5% higher at 1.5 T, in comparison with that at 0 T. For dispersed irradiation angles of more than 5-fields, it is more desirable to use the magnetic flux density of 1.5 T than 0.35 T for the radiotherapy in the lung tumor.

Measurement validation of treatment planning for a MR-Linac

Purpose

The magnetic field can cause a nonnegligible dosimetric effect in an MR‐Linac system. This effect should be accurately accounted for by the beam models in treatment planning systems (TPS). The purpose of the study was to verify the beam model and the entire treatment planning and delivery process for a 1.5 T MR‐Linac based on comprehensive dosimetric measurements and end‐to‐end tests.

Material and methods

Dosimetry measurements and end‐to‐end tests were performed on a preclinical MR‐Linac (Elekta AB) using a multitude of detectors and were compared to the corresponding beam model calculations from the TPS for the MR‐Linac. Measurement devices included ion chambers (IC), diamond detector, radiochromic film, and MR‐compatible ion chamber array and diode array. The dose in inhomogeneous phantom was also verified. The end‐to‐end tests include the generation, delivery, and comparison of 3D and IMRT plan with measurement.

Results

For the depth dose measurements with Farmer IC, micro IC and diamond detector, the absolute difference between most measurement points and beam model calculation beyond the buildup region were <1%, at most 2% for a few measurement points. For the beam profile measurements, the absolute differences were no more than 1% outside the penumbra region and no more than 2.5% inside the penumbra region. Results of end‐to‐end tests demonstrated that three 3D static plans with single 5 × 10 cm² fields (at gantry angle 0°, 90° and 270°) and two IMRT plans successfully passed gamma analysis with clinical criteria. The dose difference in the inhomogeneous phantom between the calculation and measurement was within 1.0%.

Conclusions

Both relative and absolute dosimetry measurements agreed well with the TPS calculation, indicating that the beam model for MR‐Linac properly accounts for the magnetic field effect. The end‐to‐end tests verified the entire treatment planning process.

Radiation-induced lung toxicity in mice irradiated in a strong magnetic field

Strong magnetic fields affect radiation dose deposition in MRI-guided radiation therapy systems, particularly at interfaces between tissues of differing densities such as those in the thorax. In this study, we evaluated the impact of a 1.5 T magnetic field on radiation-induced lung damage in C57L/J mice. We irradiated 140 mice to the whole thorax with parallel-opposed Co-60 beams to doses of 0, 9.0, 10.0, 10.5, 11.0, 12.0, or 13.0 Gy (20 mice per dose group). Ten mice per dose group were irradiated while a 1.5 T magnetic field was applied transverse to the radiation beam and ten mice were irradiated with the magnetic field set to 0 T. We compared survival and noninvasive assays of radiation-induced lung damage, namely respiratory rate and metrics derived from thoracic cone-beam CTs, between the two sets of mice. We report two main results. First, the presence of a transverse 1.5 T field during irradiation had no impact on survival of C57L/J mice. Second, there was a small but statistically significant effect on noninvasive assays of radiation-induced lung damage. These results provide critical safety data for the clinical introduction of MRI-guided radiation therapy systems.

Biological effects of static magnetic field exposure in the context of MR-guided radiotherapy

The clinical introduction of MRI-guided radiotherapy has prompted consideration of the potential impact of the static magnetic field on biological responses to radiation. This review provides an introduction to the mechanisms of biological interaction of radiation and magnetic fields individually, in addition to a description of the magnetic field effects on megavoltage photon beams at the macroscale, microscale and nanoscale arising from the Lorentz force on secondary charged particles. A relatively small number of scientific studies have measured the impact of combined static magnetic fields and ionising radiation on biological endpoints of relevance to radiotherapy. Approximately, half of these investigations found that static magnetic fields in combination with ionising radiation produced a significantly different outcome compared with ionising radiation alone. strength static magnetic fields appear to modestly influence the radiation response via a mechanism distinct from modification to the dose distribution. This review intends to serve as a reference for future biological studies, such that understanding of static magnetic field plus ionising radiation synergism may be improved, and if necessary, accounted for in MRI-guided radiotherapy treatment planning.

Remote Cherenkov imaging-based quality assurance of a magnetic resonance image-guided radiotherapy system

PURPOSE

Tools to perform regular quality assurance of magnetic resonance image-guided radiotherapy (MRIgRT) systems should ideally be independent of interference from the magnetic fields. Remotely acquired optical Cherenkov imaging-based dosimetry measurements in water were investigated for this purpose, comparing measures of dose accuracy, temporal dynamics, and overall integrated IMRT delivery.

METHODS

A 40 × 30.5 × 37.5 cm3 water tank doped with 1 g/L of quinine sulfate was imaged using an intensified charge-coupled device (ICCD) to capture the Cherenkov emission while being irradiated by a commercial MRIgRT system (ViewRay™). The ICCD was placed down-bore at the end of the couch, 4 m from treatment isocenter and behind the 5-Gauss line of the 0.35-T MRI. After establishing optimal camera acquisition settings, square beams of increasing size (4.2 × 4.2 cm2 , 10.5 × 10.5 cm2 , and 14.7 × 14.7 cm2 ) were imaged at 0.93 frames per second, from an individual cobalt-60 treatment head, to develop projection measures related to percent depth dose (PDD) curves and cross beam profiles (CPB). These Cherenkov-derived measurements were compared to ionization chamber (IC) and radiographic film dosimetry data, as well as simulation data from the treatment planning system (TPS). An intensity-modulated radiotherapy (IMRT) commissioning plan from AAPM TG-119 (C4:C-Shape) was also imaged at 2.1 frames per second, and the single linear sum image from 509 s of plan delivery was compared to the dose volume prediction generated by the TPS using gamma index analysis.

RESULTS

Analysis of standardized test target images (1024 × 1024 pixels) yielded a pixel resolution of 0.37 mm/pixel. The beam width measured from the Cherenkov image-generated projection CBPs was within 1 mm accuracy when compared to film measurements for all beams. The 502 point measurements (i.e., pixels) of the Cherenkov image-based projection percent depth dose curves (pPDDs) were compared to pPDDs simulated by the treatment planning system (TPS), with an overall average error of 0.60%, 0.56%, and 0.65% for the 4.2, 10.5, and 14.7 cm square beams, respectively. The relationships between pPDDs and central axis PDDs derived from the TPS were used to apply a weighting factor to the Cherenkov pPDD, so that the Cherenkov data could be directly compared to IC PDDs (average error of -0.07%, 0.10%, and -0.01% for the same sized beams, respectively). Finally, the composite image of the TG-119 C4 treatment plan achieved a 95.1% passing rate using 4%/4 mm gamma index agreement criteria between Cherenkov intensity and TPS dose volume data.

CONCLUSIONS

This is the first examination of Cherenkov-generated pPDDs and pCBPs in an MR-IGRT system. Cherenkov imaging measurements were fast to acquire, and minimal error was observed overall. Cherenkov imaging also provided novel real-time data for IMRT QA. The strengths of this imaging are the rapid data capture ability providing real-time, high spatial resolution data, combined with the remote, noncontact nature of imaging. The biggest limitation of this method is the two-dimensional (2D) projection-based imaging of three-dimensional (3D) dose distributions through the transparent water tank.