Ultrasound-guided intraoperative electron beam radiation therapy: A phantom study

Fitting Monte Carlo simulation results with an empirical model of megavoltage x-ray beams for rapid depth dose calculations in water

Objective. The purpose of this study was to assess a method of accelerating Monte Carlo simulations for modeling depth dose distributions from megavoltage x-ray beams by fitting them to an empirically-derived function.Approach. Using Geant4, multiple simulations of a typical medical linear accelerator beam in water and in water with an air cavity were conducted with varying numbers of initial electrons. The resulting percent depth dose curves were compared to published data from actual linear accelerator measurements. Two methods were employed to reduce computation time for this modeling process. First, an empirical function derived from measurements at a particular linear accelerator energy, source-to-surface distance, and field size was used to directly fit the simulated data. Second, a linear regression was performed to predict the empirical function's parameters for simulations with more initial electrons.Main results. Fitting simulated depth dose curves with the empirical function yielded significant improvements in either accuracy or computation time, corresponding to the two methods described. When compared to published measurements, the maximum error for the largest simulation was 5.58%, which was reduced to 2.01% with the best fit of the function. Fitting the empirical function around the air cavity heterogeneity resulted in errors less than 2.5% at the interfaces. The linear regression prediction modestly improved the same simulation with a maximum error of 4.22%, while reducing the required computation time from 66.53 h to 43.75 h.Significance. This study demonstrates the effective use of empirical functions to expedite Monte Carlo simulations for a range of applications from radiation protection to food sterilization. These results are particularly impactful in radiation therapy treatment planning, where time and accuracy are especially valuable. Employing these methods may improve patient outcomes by ensuring that dose delivery more accurately matches the prescription or by shortening the preparation time before treatment in Monte Carlo-based treatment planning systems.

Dosimetric verification of four dose calculation algorithms for spine stereotactic body radiotherapy

The applications of Type B [anisotropic analytical algorithm (AAA) and collapsed cone (CC)] and Type C [Acuros XB (AXB) and photon Monte Carlo (PMC)] dose calculation algorithms in spine stereotactic body radiotherapy (SBRT) were evaluated. Water- and bone-equivalent phantoms were combined to evaluate the percentage depth dose and dose profile. Subsequently, 48 consecutive patients with clinical spine SBRT plans were evaluated. All treatment plans were created using AXB in Eclipse. The prescription dose was 24 Gy in two fractions at a 10 MV FFF on TrueBeam. The doses were then recalculated with AAA, CC and PMC while maintaining the AXB-calculated monitor units and beam arrangement. The dose index values obtained using the four dose calculation algorithms were then compared. The AXB and PMC dose distributions agreed with the bone-equivalent phantom measurements (within ±2.0%); the AAA and CC values were higher than those in the bone-equivalent phantom region. For the spine SBRT plans, PMC, AAA and CC were overestimated compared with AXB in terms of the near minimum and maximum doses of the target and organ at risk, respectively; the mean dose difference was within 4.2%, which is equivalent with within 1 Gy. The phantom study showed that the results from AXB and PMC agreed with the measurements within ±2.0%. However, the mean dose difference ranged from 0.5 to 1 Gy in the spine SBRT planning study when the dose calculation algorithms changed. Users should incorporate a clinical introduction that includes an awareness of these differences.

Evaluation of RADIANCE Monte Carlo algorithm for treatment planning in electron based Intraoperative Radiotherapy (IOERT)

PURPOSE

To perform experimental as well as independent Monte Carlo (MC) evaluation of the MC algorithm implemented in RADIANCE version 4.0.8, a dedicated treatment planning system (TPS) for 3D electron dose calculations in intraoperative radiation therapy (IOERT).

METHODS AND MATERIALS

The MOBETRON 2000 (IntraOp Medical Corporation, Sunnyvale, CA) IOERT accelerator was employed. PDD and profiles for five cylindrical plastic applicators with 50-90 mm diameter and 0°, 30° beveling were measured in a water phantom, at nominal energies of 6, 9 and 12 MeV. Additional PDD measurements were performed for all the energies without applicator. MC modeling of the MOBETRON was performed with the user code BEAMnrc and egs_chamber of the MC simulation toolkit EGSnrc. The generated phase space files of the two 0°-bevel applicators (50 mm, 80 mm) and three energies in both RADIANCE and BEAMnrc, were used to determine PDD and profiles in various set-ups of virtual water phantoms with air and bone inhomogeneities. 3D dose distributions were also calculated in image data sets of an anthropomorphic tissue-equivalent pelvis phantom. Image acquisitions were realized with a CT scanner (Philips Big Bore CT, Netherlands). Gamma analysis was applied to quantify the deviations of the RADIANCE calculations to the measurements and EGSnrc calculations. Gamma criteria normalized to the global maximum were investigated between 2%, 2 mm and 3%, 3 mm.

RESULTS

RADIANCE MC calculations satisfied the gamma criteria of 3%, 3 mm with a tolerance limit of 85% passing rate compared to in- water phantom measurements, except for the dose profiles of the 30° beveled applicators. Mismatches lay in surface doses, in umbra regions and in the beveled end of the 30° applicators. A very good agreement to the EGSnrc calculations in heterogeneous media was observed. Deviations were more pronounced for the larger applicator diameter and higher electron energy. In 3D dose comparisons in the anthropomorphic phantom, gamma passing rates were higher than 96 % for both simulated applicators.

CONCLUSIONS

RADIANCE MC algorithm agrees within 3%, 3 mm criteria with in-water phantom measurements and EGSnrc MC dose distributions in heterogeneous media for 0°-bevel applicators. The user should be aware of missing scattering components and the 30° beveled applicators should be used with attention.

Evaluations of patient-specific bolus fabricated by mold-and-cast method using computer numerical control machine tools†

The patient-specific bolus fabricated by a mold-and-cast method using a 3D printer (3DP) and silicon rubber has been adopted in clinical practices. Manufacturing a mold using 3DP, however, can cause time delays due to failures during the 3D printing process. Thereby, we investigated an alternative method of the mold fabrication using computer numerical control (CNC) machine tools. Treatment plans were conducted concerning a keloid scar formed on the ear and nose. The bolus structures were determined in a treatment planning system (TPS), and the molds were fabricated using the same structure file but with 3DP and CNC independently. Boluses were then manufactured using each mold with silicone rubbers. We compared the geometrical difference between the boluses and the planned structure using computed tomography (CT) images of the boluses. In addition, dosimetric differences between the two measurements using each bolus and the differences between the measured and calculated dose from TPS were evaluated using an anthropomorphic head phantom. Geometrically, the CT images of the boluses fabricated by the 3DP mold and the CNC mold showed differences compared to the planned structure within 2.6 mm of Hausdorff distance. The relative dose difference between the measurements using either bolus was within 2.3%. In conclusion, the bolus made by the CNC mold benefits from a stable fabricating process, retaining the performance of the bolus made by the 3DP mold.

Validating a double Gaussian source model for small proton fields in a commercial Monte-Carlo dose calculation engine

PURPOSE

The primary fluence of a proton pencil beam exiting the accelerator is enveloped by a region of secondaries, commonly called "spray". Although small in magnitude, this spray may affect dose distributions in pencil beam scanning mode e.g., in the calculation of the small field output, if not modelled properly in a treatment planning system (TPS). The purpose of this study was to dosimetrically benchmark the Monte Carlo (MC) dose engine of the RayStation TPS (v.10A) in small proton fields and systematically compare single Gaussian (SG) and double Gaussian (DG) modeling of initial proton fluence providing a more accurate representation of the nozzle spray.

METHODS

The initial proton fluence distribution for SG/DG beam modeling was deduced from two-dimensional measurements in air with a scintillation screen with electronic readout. The DG model was either based on direct fits of the two Gaussians to the measured profiles, or by an iterative optimization procedure, which uses the measured profiles to mimic in-air scan-field factor (SF) measurements. To validate the DG beam models SFs, i.e. relative doses to a 10 × 10 cm2 field, were measured in water for three different initial proton energies (100MeV, 160MeV, 226.7MeV) and square field sizes from 1×1cm2 to 10×10cm2 using a small field ionization chamber (IBA CC01) and an IBA ProteusPlus system (universal nozzle). Furthermore, the dose to the center of spherical target volumes (diameters: 1cm to 10cm) was determined using the same small volume ionization chamber (IC). A comprehensive uncertainty analysis was performed, including estimates of influence factors typical for small field dosimetry deduced from a simple two-dimensional analytical model of the relative fluence distribution. Measurements were compared to the predictions of the RayStation TPS.

RESULTS

SFs deviated by more than 2% from TPS predictions in all fields <4×4cm2 with a maximum deviation of 5.8% for SG modeling. In contrast, deviations were smaller than 2% for all field-sizes and proton energies when using the directly fitted DG model. The optimized DG model performed similarly except for slightly larger deviations in the 1×1cm2 scan-fields. The uncertainty estimates showed a significant impact of pencil beam size variations (±5%) resulting in up to 5.0% standard uncertainty. The point doses within spherical irradiation volumes deviated from calculations by up to 3.3% for the SG model and 2.0% for the DG model.

CONCLUSION

Properly representing nozzle spray in RayStation's MC-based dose engine using a DG beam model was found to reduce the deviation to measurements in small spherical targets to below 2%. A thorough uncertainty analysis shows a similar magnitude for the combined standard uncertainty of such measurements.

Delivery of intensity-modulated electron therapy by mechanical scanning: An algorithm study

Purpose

In principle, intensity-modulated electron therapy (IMET) can be delivered through mechanical scanning, with a robotic arm mounting a linac.

Materials and methods

Here is a scanning algorithm to identify the back-and-forth, top-to-bottom (zigzag) pattern scan sequence. The algorithm includes generating beam positions with a uniform resolution according to the applicator size; adopting discrete energies to achieve the depth of 90% dose by compositing energies; selecting energy by locating the target's distal edge; and employing the energy-by-energy scan strategy for step-and-shoot discrete scanning. After a zigzag scan sequence is obtained, the delivery order of the scan spots is optimized by fast simulated annealing (FSA) to minimize the path length. For algorithm evaluation, scan sequences were generated using the computed tomography data of 10 patients with pancreatic cancer undergoing intraoperative radiotherapy, and the results were compared between the zigzag path and an optimized path. A simple calculation of the treatment delivery time, which comprises the irradiation time, the total robotic arm moving time, the time for energy switch, and the time to stop and restart the beam, was also made.

Results

In these clinical cases, FSA optimization shortened the path lengths by 12%-43%. Assuming the prescribed dose was 15 Gy, machine dose rate was 15 Gy/s, energy switch time was 2 s, stop and restart beam time was 20 ms, and robotic arm move speed was 50 mm/s, the average delivery time was 124±38 s. The largest reduction in path length yielded an approximately 10% reduction in the delivery time, which can be further reduced by increasing the machine dose rate and the robotic arm speed, decreasing the time for energy switch, and/or developing more efficient algorithms.

Conclusion

Mechanically scanning IMET is potentially feasible and worthy of further exploration.

A probabilistic approach for determining Monte Carlo beam source parameters: II. Impact of beam modeling uncertainties on dosimetric functions and treatment plans

Objective. The Monte Carlo method is recognized as a valid approach for the evaluation of dosimetric functions for clinical use. This procedure requires the accurate modeling of the considered linear accelerator. In Part I, we propose a new method to extract the probability density function of the beam model physical parameters. The aim of this work is to evaluate the impact of beam modeling uncertainties on Monte Carlo evaluated dosimetric functions and treatment plans in the context of small fields. Approach. Simulations of output factors, output correction factors, dose profiles, percent-depth doses and treatment plans are performed using the CyberKnife M6 model developed in Part I. The optimized pair of electron beam energy and spot size, and eight additional pairs of beam parameters representing a 95% confidence region are used to propagate the uncertainties associated to the source parameters to the dosimetric functions. Main results. For output factors, the impact of beam modeling uncertainties increases with the reduction of the field size and confidence interval half widths reach 1.8% for the 5 mm collimator. The impact on output correction factors cancels in part, leading to a maximum confidence interval half width of 0.44%. The impact is less significant for percent-depth doses in comparison to dose profiles. For these types of measurement, in absolute terms and in comparison to the reference dose, confidence interval half widths less than or equal to 1.4% are observed. For simulated treatment plans, the impact is more significant for the treatment delivered with a smaller field size with confidence interval half widths reaching 2.5% and 1.4% for the 5 and 20 mm collimators, respectively. Significance. Results confirm that AAPM TG-157's tolerances cannot apply to the field sizes studied. This study provides an insight on the reachable dose calculation accuracy in a clinical setup.

Beam modeling and commissioning for Monte Carlo photon beam on an Elekta Versa HD LINAC

PURPOSE

This study aims at analyzing beam data commissioning along with verifying Monte Carlo-based treatment planning system on the basis of the manufacturer guidelines for Elekta Versa HD Linear Accelerator. Moreover, evaluating the beam match process in terms of quality index, photon profile and multi leaf collimator (MLC) offset is aimed as well.

MATERIALS AND METHODS

The process of collecting beam data for Monaco 5.51 Treatment Planning System commissioning was done based on the instructions provided by the manufacturer as well as AAPM TG-106. Monte Carlo analysis was done for output factors in water, percent depth dose and beam profiles. A set of eight static and intensity modulated radiation therapy fields were used to verify the MLC parameters.

RESULTS

The difference between the measured and modeled penetrative quality (D₁₀) was achieved to be 0.54%. The output factors for 6 MV photon energy were measured and the difference between the measured and Monte Carlo output results was smaller than 1% for all the fields. The average percentage of passing the gamma criteria for commissioning test fields was (95+-4)%, however, the minimum agreement was 87.5% belonging to "7SEGA". Additionally, the agreement between both LINAC is 96%, however, the second LINAC reveals a positive offset in the point of approximately -4 cm on the x-axis at the crossplane.

CONCLUSION

Test commissioning was successfully verified using a homogeneous phantom for point dose measurements, post modelling MLC parameters and patient QA plans. All plan parameters pass the gamma criteria. 6 MV photon beam was successfully commissioned for Elekta VersaHD LINAC and is ready for clinical implementation.

Can a ToF-PET photon attenuation reconstruction test stopping-power estimations in proton therapy? A phantom study

Objective. The aim of the phantom study was to validate and to improve the computed tomography (CT) images used for the dose computation in proton therapy. It was tested, if the joint reconstruction of activity and attenuation images of time-of-flight PET (ToF-PET) scans could improve the estimation of the proton stopping-power.Approach. The attenuation images, i.e. CT images with 511 keV gamma-rays (γCTs), were jointly reconstructed with activity maps from ToF-PET scans. Theβ⁺activity was produced with FDG and in a separate experiment with proton-induced radioactivation. The phantoms contained slabs of tissue substitutes. The use of theγCTs for the prediction of the beam stopping in proton therapy was based on a linear relationship between theγ-ray attenuation, the electron density, and the stopping-power of fast protons.Main results. The FDG based experiment showed sufficient linearity to detect a bias of bony tissue in the heuristic look-up table, which maps between x-ray CT images and proton stopping-power.γCTs can be used for dose computation, if the electron density of one type of tissue is provided as a scaling factor. A possible limitation is imposed by the spatial resolution, which is inferior by a factor of 2.5 compared to the one of the x-ray CT.γCTs can also be derived from off-line, ToF-PET scans subsequent to the application of a proton field with a hypofractionated dose level.Significance. γCTs are a viable tool to support the estimation of proton stopping with radiotracer-based ToF-PET data from diagnosis or staging. This could be of higher potential relevance in MRI-guided proton therapy.γCTs could form an alternative approach to make use of in-beam or off-line PET scans of proton-inducedβ⁺activity with possible clinical limitations due to the low number of coincidence counts.

Evaluation of Acuros® XB accuracy for static small fields dose calculations based on the IAEA/AAPM TRS-483 recommendation

PURPOSE

Evaluate Acuros® XB dose calculation accuracy following TRS-483 recommendations in small static fields for flattened and un-flattened 6 MV X-ray beams.

METHODS

Field output factors were measured following TRS-483 recommendations using four radiation detectors. Two sets of field output factors were measured. One set was used to configure the beam model into Acuros® XB down to a jaw-defined field size of 1.0 cm × 1.0 cm. The second set was used to evaluate the differences between calculated and measured field output factors for MLC-fields down to a field size of 0.5 cm × 0.5 cm.

RESULTS

Acuros® XB showed an accuracy within 1.5% down to an MLC-field of 1.0 cm × 1.0 cm, for a focal spot size of 1.0 and 0.0 mm in the cross and in-plane directions. For an MLC-field of 0.5 cm × 0.5 cm, an agreement was found within 3% between calculated and measured field output factors. These results were addressed by optimizing the focal spot size to minimize the differences between calculated and measured dose profiles.

CONCLUSIONS

By optimizing the focal spot size, Acuros® XB showed an acceptable agreement within 3% down to an MLC-field of 0.5 cm × 0.5 cm. The results of this work suggest that if static and modulated delivery of very small targets is planned, then a field output factor table down to a field size of 1.0 cm is required in the beam configuration model.

The status of medical physics in radiotherapy in China

PURPOSE

To present an overview of the status of medical physics in radiotherapy in China, including facilities and devices, occupation, education, research, etc. MATERIALS AND METHODS: The information about medical physics in clinics was obtained from the 9-th nationwide survey conducted by the China Society for Radiation Oncology in 2019. The data of medical physics in education and research was collected from the publications of the official and professional organizations.

RESULTS

By 2019, there were 1463 hospitals or institutes registered to practice radiotherapy and the number of accelerators per million population was 1.5. There were 4172 medical physicists working in clinics of radiation oncology. The ratio between the numbers of radiation oncologists and medical physicists is 3.51. Approximately, 95% of medical physicists have an undergraduate or graduate degrees in nuclear physics and biomedical engineering. 86% of medical physicists have certificates issued by the Chinese Society of Medical Physics. There has been a fast growth of publications by authors from mainland of China in the top international medical physics and radiotherapy journals since 2018.

CONCLUSIONS

Demand for medical physicists in radiotherapy increased quickly in the past decade. The distribution of radiotherapy facilities in China became more balanced. High quality continuing education and training programs for medical physicists are deficient in most areas. The role of medical physicists in the clinic has not been clearly defined and their contributions have not been fully recognized by the community.