Integrated MRI-guided proton therapy planning: accounting for the full MRI field in a perpendicular system

The impact of motion on onboard MRI-guided pencil beam scanned proton therapy treatments

Objective.Online magnetic resonance imaging (MRI) guidance could be especially beneficial for pencil beam scanned (PBS) proton therapy of tumours affected by respiratory motion. For the first time to our knowledge, we investigate the dosimetric impact of respiratory motion on MRI-guided proton therapy compared to the scenario without magnetic field.Approach.A previously developed analytical proton dose calculation algorithm accounting for perpendicular magnetic fields was extended to enable 4D dose calculations. For two geometrical phantoms and three liver and two lung patient cases, static treatment plans were optimised with and without magnetic field (0, 0.5 and 1.5 T). Furthermore, plans were optimised using gantry angle corrections (0.5 T +5° and 1.5 T +15°) to reproduce similar beam trajectories compared to the 0 T reference plans. The effect of motion was then considered using 4D dose calculations without any motion mitigation and simulating 8-times volumetric rescanning, with motion for the patient cases provided by 4DCT(MRI) data sets. Each 4D dose calculation was performed for different starting phases and the CTV dose coverageV95%and homogeneityD5%-D95%were analysed.Main results.For the geometrical phantoms with rigid motion perpendicular to the beam and parallel to the magnetic field, a comparable dosimetric effect was observed independent of the magnetic field. Also for the five 4DCT(MRI) cases, the influence of motion was comparable for all magnetic field strengths with and without gantry angle correction. On average, the motion-induced decrease in CTVV95%from the static plan was 17.0% and 18.9% for 1.5 T and 0.5 T, respectively, and 19.9% without magnetic field.Significance.For the first time, this study investigates the combined impact of magnetic fields and respiratory motion on MR-guided proton therapy. The comparable dosimetric effects irrespective of magnetic field strength indicate that the effects of motion for future MR-guided proton therapy may not be worse than for conventional PBS proton therapy.

Proton dosimetry in a magnetic field: Measurement and calculation of magnetic field correction factors for a plane-parallel ionization chamber

BACKGROUND

The combination of magnetic resonance imaging and proton therapy offers the potential to improve cancer treatment. The magnetic field (MF)-dependent change in the dosage of ionization chambers in magnetic resonance imaging-integrated proton therapy (MRiPT) is considered by the correction factork B ⃗ , M , Q $k_{\vec{B},M,Q}$ , which needs to be determined experimentally or computed via Monte Carlo (MC) simulations.

PURPOSE

In this study,k B ⃗ , M , Q $k_{\vec{B},M,Q}$ was both measured and simulated with high accuracy for a plane-parallel ionization chamber at different clinical relevant proton energies and MF strengths.

MATERIAL AND METHODS

The dose-response of the Advanced Markus chamber (TM34045, PTW, Freiburg, Germany) irradiated with homogeneous 10 × $\times$ 10 cm2 $^2$ quasi mono-energetic fields, using 103.3, 128.4, 153.1, 223.1, and 252.7 MeV proton beams was measured in a water phantom placed in the MF of an electromagnet with MF strengths of 0.32, 0.5, and 1 T. The detector was positioned at a depth of 2 g/cm2 $^2$ in water, with chamber electrodes parallel to the MF lines and perpendicular to the proton beam incidence direction. The measurements were compared with TOPAS MC simulations utilizing COMSOL-calculated 0.32, 0.5, and 1 T MF maps of the electromagnet.k B ⃗ , M , Q $k_{\vec{B},M,Q}$ was calculated for the measurements for all energies and MF strengths based on the equation:k B ⃗ , M , Q = M Q M Q B ⃗ $k_{\vec{B},M,Q}=\frac{M_\mathrm{Q}}{M_\mathrm{Q}^{\vec{B}}}$ , whereM Q B ⃗ $M_\mathrm{Q}^{\vec{B}}$ andM Q $M_\mathrm{Q}$ were the temperature and air-pressure corrected detector readings with and without the MF, respectively. MC-based correction factors were determined ask B ⃗ , M , Q = D det D det B ⃗ $k_{\vec{B},M,Q}=\frac{D_\mathrm{det}}{D_\mathrm{det}^{\vec{B}}}$ , whereD det B ⃗ $D_\mathrm{det}^{\vec{B}}$ andD det $D_\mathrm{det}$ were the doses deposited in the air cavity of the ionization chamber model with and without the MF, respectively. Furthermore, MF effects on the chamber dosimetry are studied using MC simulations, examining the impact on the absorbed dose-to-water (D W $D_{W}$ ) and the shift in depth of the Bragg peak.

RESULTS

The detector showed a reduced dose-response for all measured energies and MF strengths, resulting in experimentally determinedk B ⃗ , M , Q $k_{\vec{B},M,Q}$ values larger than unity. For all energies and MF strengths examined,k B ⃗ , M , Q $k_{\vec{B},M,Q}$ ranged between 1.0065 and 1.0205. The dependence on the energy and the MF strength was found to be non-linear with a maximum at 1 T and 252.7 MeV. The MC simulatedk B ⃗ , M , Q $k_{\vec{B},M,Q}$ values agreed with the experimentally determined correction factors within their standard deviations with a maximum difference of 0.6%. The MC calculated impact onD W $D_{W}$ was smaller 0.2 %.

CONCLUSION

For the first time, measurements and simulations were compared for proton dosimetry within MFs using an Advanced Markus chamber. Good agreement ofk B ⃗ , M , Q $k_{\vec{B},M,Q}$ was found between experimentally determined and MC calculated values. The performed benchmarking of the MC code allows for calculatingk B ⃗ , M , Q $k_{\vec{B},M,Q}$ for various ionization chamber models, MF strengths and proton energies to generate the data needed for a proton dosimetry protocol within MFs and is, therefore, a step towards MRiPT.

A fast analytical dose calculation approach for MRI-guided proton therapy

Objective.Magnetic resonance (MR) is an innovative technology for online image guidance in conventional radiotherapy and is also starting to be considered for proton therapy as well. For MR-guided therapy, particularly for online plan adaptations, fast dose calculation is essential. Monte Carlo (MC) simulations, however, which are considered the gold standard for proton dose calculations, are very time-consuming. To address the need for an efficient dose calculation approach for MRI-guided proton therapy, we have developed a fast GPU-based modification of an analytical dose calculation algorithm incorporating beam deflections caused by magnetic fields.Approach.Proton beams (70-229 MeV) in orthogonal magnetic fields (0.5/1.5 T) were simulated using TOPAS-MC and central beam trajectories were extracted to generate look-up tables (LUTs) of incremental rotation angles as a function of water-equivalent depth. Beam trajectories are then reconstructed using these LUTs for the modified ray casting dose calculation. The algorithm was validated against MC in water, different materials and for four example patient cases, whereby it has also been fully incorporated into a treatment plan optimisation regime.Main results.Excellent agreement between analytical and MC dose distributions could be observed with sub-millimetre range deviations and differences in lateral shifts <2 mm even for high densities (1000 HU). 2%/2 mm gamma pass rates were comparable to the 0 T scenario and above 94.5% apart for the lung case. Further, comparable treatment plan quality could be achieved regardless of magnetic field strength.Significance.A new method for accurate and fast proton dose calculation in magnetic fields has been developed and successfully implemented for treatment plan optimisation.

Monte Carlo simulation for proton dosimetry in magnetic fields: Fano test and magnetic field correction factorskBfor Farmer-type ionization chambers

Objective. In this contribution we present a special Fano test for charged particles in presence of magnetic fields in the MC code TOol for PArticle Simulation (TOPAS), as well as the determination of magnetic field correction factorskBfor Farmer-type ionization chambers using proton beams.Approach. Customized C++ extensions for TOPAS were implemented to model the special Fano tests in presence of magnetic fields for electrons and protons. The Geant4-specific transport parameters,DRoverRandfinalRange,were investigated to optimize passing rate and computation time. ThekBwas determined for the Farmer-type PTW 30013 ionization chamber, and 5 custom built ionization chambers with same geometry but varying inner radius, testing magnetic flux density ranging from 0 to 1.0 T and two proton beam energies of 157.43 and 221.05 MeV.Main results. Using the investigated parameters, TOPAS passed the Fano test within 0.39 ± 0.15% and 0.82 ± 0.42%, respectively for electrons and protons. The chamber response (kB,M,Q) gives a maximum at different magnetic flux densities depending of the chamber size, 1.0043 at 1.0 T for the smallest chamber and 1.0051 at 0.2 T for the largest chamber. The local dose differencecBremained ≤ 0.1% for both tested energies. The magnetic field correction factorkB, for the chamber PTW 30013, varied from 0.9946 to 1.0036 for both tested energies.Significance. The developed extension for the special Fano test in TOPAS MC code with the adjusted transport parameters, can accurately transport electron and proton particles in magnetic field. This makes TOPAS a valuable tool for the determination ofkB. The ionization chambers we tested showed thatkBremains small (≤0.72%). To the best of our knowledge, this is the first calculations ofkBfor proton beams. This work represents a significant step forward in the development of MRgPT and protocols for proton dosimetry in presence of magnetic field.

Quality assurance and temporal stability of a 1.5 T MRI scanner for MR-guided Photon and Particle Therapy

PURPOSE

To describe performance measurements, adaptations and time stability over 20 months of a diagnostic MR scanner for integration into MR-guided photon and particle radiotherapy.

MATERIAL AND METHODS

For realization of MR-guided photon and particle therapy (MRgRT/MRgPT), a 1.5 T MR scanner was installed at the Heidelberg Ion Beam Therapy Center. To integrate MRI into the treatment process, a flat tabletop and dedicated coil holders for flex coils were used, which prevent deformation of the patient external contour and allow for the use of immobilization tools for reproducible positioning. The signal-to-noise ratio (SNR) was compared for the diagnostic and therapy-specific setup using the flat couch top and flexible coils for the a) head & neck and b) abdominal region as well as for different bandwidths and clinical pulse sequences. Additionally, a quality assurance (QA) protocol with monthly measurements of the ACR phantom and measurement of geometric distortions for a large field-of-view (FOV) was implemented to assess the imaging quality parameters of the device over the course of 20 months.

RESULTS

The SNR measurements showed a decreased SNR for the RT-specific as compared to the diagnostic setup of (a) 26% to 34% and (b) 11% to 33%. No significant bandwidth dependency for this ratio was found. The longitudinal assessment of the image quality parameters with the ACR and distortion phantom confirmed the long-term stability of the MRI device.

CONCLUSION

A diagnostic MRI was commissioned for use in MR-guided particle therapy. Using a radiotherapy specific setup, a high geometric accuracy and signal homogeneity was obtained after some adaptions and the measured parameters were shown to be stable over a period of 20 months.

Image-Guided Proton Therapy: A Comprehensive Review

Image guidance for radiation therapy can improve the accuracy of the delivery of radiation, leading to an improved therapeutic ratio. Proton radiation is able to deliver a highly conformal dose to a target due to its advantageous dosimetric properties, including the Bragg peak. Proton therapy established the standard for daily image guidance as a means of minimizing uncertainties associated with proton treatment. With the increasing adoption of the use of proton therapy over time, image guidance systems for this modality have been changing. The unique properties of proton radiation present a number of differences in image guidance from photon therapy. This paper describes CT and MRI-based simulation and methods of daily image guidance. Developments in dose-guided radiation, upright treatment, and FLASH RT are discussed as well.

Commissioning a beam line for MR-guided particle therapy assisted by in silico methods

BACKGROUND

Radiation therapy is continuously moving towards more precise dose delivery. The combination of online MR imaging and particle therapy, for example, radiation therapy using protons or carbon ions, could enable the next level of precision in radiotherapy. In particle therapy, research towards a combination of MR and particle therapy is well underway, but still far from clinical systems. The combination of high magnetic fields with particle therapy delivery poses several challenges for treatment planning, treatment workflow, dose delivery, and dosimetry.

PURPOSE

To present a workflow for commissioning of a light ion beam line with an integrated dipole magnet to perform MR-guided particle therapy (MRgPT) research, producing not only basic beam data but also magnetic field maps for accurate dose calculation. Accurate dose calculation in magnetic field environments requires high-quality magnetic field maps to compensate for magnetic-field-dependent trajectory changes and dose perturbations.

METHODS

The research beam line at MedAustron was coupled with a resistive dipole magnet positioned at the isocenter. Beam data were measured for proton and carbon ions with and without an applied magnetic field of 1 T. Laterally integrated depth-dose curves (IDC) as well as beam profiles were measured in water while beam trajectories were measured in air. Based on manufacturer data, an in silico model of the magnet was created, allowing to extract high-quality 3D magnetic field data. An existing GATE/Geant4 Monte Carlo (MC) model of the beam line was extended with the generated magnetic field data and benchmarked against experimental data.

RESULTS

A 3D magnetic field volume covering fringe fields until 50 mT was found to be sufficient for an accurate beam trajectory modeling. The effect on particle range retraction was found to be 2.3 and 0.3 mm for protons and carbon ions, respectively. Measured lateral beam offsets in water agreed within 0.4 and -0.5 mm with MC simulations for protons and carbon ions, respectively. Experimentally determined in-air beam trajectories agreed within 0.4 mm in the homogeneous magnetic field area.

CONCLUSION

The presented approach based on in silico modeling and measurements allows to commission a beam line for MRgPT while providing benchmarking data for the magnetic field modeling, required for state-of-the art dose calculation methods.

Target Definition in MR-Guided Adaptive Radiotherapy for Head and Neck Cancer

In recent years, MRI-guided radiotherapy (MRgRT) has taken an increasingly important position in image-guided radiotherapy (IGRT). Magnetic resonance imaging (MRI) offers superior soft tissue contrast in anatomical imaging compared to computed tomography (CT), but also provides functional and dynamic information with selected sequences. Due to these benefits, in current clinical practice, MRI is already used for target delineation and response assessment in patients with head and neck squamous cell carcinoma (HNSCC). Because of the close proximity of target areas and radiosensitive organs at risk (OARs) during HNSCC treatment, MRgRT could provide a more accurate treatment in which OARs receive less radiation dose. With the introduction of several new radiotherapy techniques (i.e., adaptive MRgRT, proton therapy, adaptive cone beam computed tomography (CBCT) RT, (daily) adaptive radiotherapy ensures radiation dose is accurately delivered to the target areas. With the integration of a daily adaptive workflow, interfraction changes have become visible, which allows regular and fast adaptation of target areas. In proton therapy, adaptation is even more important in order to obtain high quality dosimetry, due to its susceptibility for density differences in relation to the range uncertainty of the protons. The question is which adaptations during radiotherapy treatment are oncology safe and at the same time provide better sparing of OARs. For an optimal use of all these new tools there is an urgent need for an update of the target definitions in case of adaptive treatment for HNSCC. This review will provide current state of evidence regarding adaptive target definition using MR during radiotherapy for HNSCC. Additionally, future perspectives for adaptive MR-guided radiotherapy will be discussed.