Zeitschrift fur Medizinische Physik最新文献

The SSRMP recommendations on reference dosimetry in kilovolt beams as used in radiation therapy were revised to establish current practice in Switzerland.

The recommendations specify the dosimetry formalism, reference class dosimeter systems and conditions used for the calibration of low and medium energy x-ray beams. Practical guidance is provided on the determination of the beam quality specifier and all corrections required for converting instrument readings to absorbed dose to water. Guidance is also provided on the determination of relative dose under non-reference conditions and on the cross calibration of instruments.

The effect of lack of electron equilibrium and influence of contaminant electrons when using thin window plane parallel chambers at x-ray tube potentials higher than 50 kV is elaborated in an appendix. In Switzerland the calibration of the reference system used for dosimetry is regulated by law. METAS and IRA are the authorities providing this calibration service to the radiotherapy departments. The last appendix of these recommendations summarise this calibration chain.

Objective

To develop and validate a versatile Monte Carlo (MC)-based dose calculation engine to support MC-based dose verification of treatment planning systems (TPSs) and quality assurance (QA) workflows in proton therapy.

Methods

The GATE MC toolkit was used to simulate a fixed horizontal active scan-based proton beam delivery (SIEMENS IONTRIS). Within the nozzle, two primary and secondary dose monitors have been designed to enable the comparison of the accuracy of dose estimation from MC simulations with respect to physical QA measurements. The developed beam model was validated against a series of commissioning measurements using pinpoint chambers and 2D array ionization chambers (IC) in terms of lateral profiles and depth dose distributions. Furthermore, beam delivery module and treatment planning has been validated against the literature deploying various clinical test cases of the AAPM TG‐119 (c-shape phantom) and a prostate patient.

Results

MC simulations showed excellent agreement with measurements in the lateral depth-dose parameters and spread-out Bragg peak (SOBP) characteristics within a maximum relative error of 0.95 mm in range, 1.83% in entrance to peak ratio, 0.27% in mean point-to-point dose difference, and 0.32% in peak location. The mean relative absolute difference between MC simulations and measurements in terms of absorbed dose in the SOBP region was 0.93% ± 0.88%. Clinical phantom studies showed a good agreement compared to research TPS (relative error for TG-119 planning target volume PTV-D₉₅ ∼ 1.8%; and for prostate PTV-D₉₅ ∼ −0.6%).

Conclusion

We successfully developed a MC model for the pencil beam scanning system, which appears reliable for dose verification of the TPS in combination with QA information, prior to patient treatment.

Purpose

To evaluate the dosimetric accuracy for small field proton irradiation relevant for pre-clinical in vivo studies using clinical infrastructure and technology. In this context additional beam collimation and range reduction was implemented.

Methods and materials

The clinical proton beam line employing pencil beam scanning (PBS) was adapted for the irradiation of small fields at shallow depths. Cylindrical collimators with apertures of 15, 12, 7 and 5 mm as well as two different range shifter types, placed at different distances relative to the target, were tested: a bolus range shifter (BRS) attached to the collimator and a clinical nozzle mounted range shifter (CRS) placed at a distance of 72 cm from the collimator. The Monte Carlo (MC) based dose calculation engine implemented in the clinical treatment planning system (TPS) was commissioned for these two additional hardware components. The study was conducted with a phantom and cylindrical target sizes between 2 and 25 mm in diameter following a dosimetric end-to-end test concept.

Results

The setup with the CRS provided a uniform dose distribution across the target. An agreement of better than 5% between the planned dose and the measurements was obtained for a target with 3 mm diameter (collimator 5 mm). A 2 mm difference between the collimator and the target diameter (target being 2 mm smaller than the collimator) sufficed to cover the whole target with the planned dose in the setup with CRS. Using the BRS setup (target 8 mm, collimator 12 mm) resulted in non-homogeneous dose distributions, with a dose discrepancy of up to 10% between the planned and measured doses.

Conclusion

The clinical proton infrastructure with adequate beam line adaptations and a state-of-the-art TPS based on MC dose calculations enables small animal irradiations with a high dosimetric precision and accuracy for target sizes down to 3 mm.

Purpose

The precision of the dose delivery in radiation therapy with high-field MR-linacs is challenging due to the substantial variation in the beam attenuation of the patient positioning system (PPS) (the couch and coils) as a function of the gantry angle. This work aimed to compare the attenuation of two PPSs located at two different MR-linac sites through measurements and calculations in the treatment planning system (TPS).

Methods

Attenuation measurements were performed at every 1° gantry angle at the two sites with a cylindrical water phantom with a Farmer chamber inserted along the rotational axis of the phantom. The phantom was positioned with the chamber reference point (CRP) at the MR-linac isocentre. A compensation strategy was applied to minimise sinusoidal measurement errors due to, e.g. air cavity or setup. A series of tests were performed to assess the sensitivity to measurement uncertainties. The dose to a model of the cylindrical water phantom with the PPS added was calculated in the TPS (Monaco v5.4 as well as in a development version Dev of an upcoming release), for the same gantry angles as for the measurements. The TPS PPS model dependency of the dose calculation voxelisation resolution was also investigated.

Results

A comparison of the measured attenuation of the two PPSs yielded differences of less than 0.5% for most gantry angles. The maximum deviation between the attenuation measurements for the two different PPSs exceeded ±1% at two specific gantry angles 115° and 245°, where the beam traverses the most complex PPS structures. The attenuation increases from 0% to 25% in 15° intervals around these angles. The measured and calculated attenuation, as calculated in v5.4, was generally within 1-2% with a systematic overestimation of the attenuation for gantry angles around 180°, as well as a maximum error of 4-5% for a few discrete angles in 10° gantry angle intervals around the complex PPS structures. The PPS modelling was improved compared to v5.4 in Dev, especially around 180°, and the results of those calculations were within ±1%, but with a similar 4% maximum deviation for the most complex PPS structures.

Conclusions

Generally, the two tested PPS structures exhibit very similar attenuation as a function of the gantry angle, including the angles with a steep change in attenuation. Both TPS versions, v5.4 and Dev delivered clinically acceptable accuracy of the calculated dose, as the differences in the measurements were overall better than ±2%. Additionally, Dev improved the accuracy of the dose calculation to ±1% for gantry angles around 180°.

Introduction

Background field removal (BFR) is a critical step required for successful quantitative susceptibility mapping (QSM). However, eliminating the background field in brains containing significant susceptibility sources, such as intracranial hemorrhages, is challenging due to the relatively large scale of the field induced by these pathological susceptibility sources.

Method

This study proposes a new deep learning-based method, BFRnet, to remove the background field in healthy and hemorrhagic subjects. The network is built with the dual-frequency octave convolutions on the U-net architecture, trained with synthetic field maps containing significant susceptibility sources. The BFRnet method is compared with three conventional BFR methods and one previous deep learning method using simulated and in vivo brains from 4 healthy and 2 hemorrhagic subjects. Robustness against acquisition field-of-view (FOV) orientation and brain masking are also investigated.

Results

For both simulation and in vivo experiments, BFRnet led to the best visually appealing results in the local field and QSM results with the minimum contrast loss and the most accurate hemorrhage susceptibility measurements among all five methods. In addition, BFRnet produced the most consistent local field and susceptibility maps between different sizes of brain masks, while conventional methods depend drastically on precise brain extraction and further brain edge erosions. It is also observed that BFRnet performed the best among all BFR methods for acquisition FOVs oblique to the main magnetic field.

Conclusion

The proposed BFRnet improved the accuracy of local field reconstruction in the hemorrhagic subjects compared with conventional BFR algorithms. The BFRnet method was effective for acquisitions of tilted orientations and retained whole brains without edge erosion as often required by traditional BFR methods.

Proton irradiation is a well-established method to treat deep-seated tumors in radio oncology. Usually, an X-ray computed tomography (CT) scan is used for treatment planning. Since proton therapy is based on the precise knowledge of the stopping power describing the energy loss of protons in the patient tissues, the Hounsfield units of the planning CT have to be converted. This conversion introduces range errors in the treatment plan, which could be reduced, if the stopping power values were extracted directly from an image obtained using protons instead of X-rays. Since protons are affected by multiple Coulomb scattering, reconstruction of the 3D stopping power map results in limited image quality if the curved proton path is not considered. This work presents a substantial code extension of the open-source toolbox TIGRE for proton CT (pCT) image reconstruction based on proton radiographs including a curved proton path estimate. The code extension and the reconstruction algorithms are GPU-based, allowing to achieve reconstruction results within minutes. The performance of the pCT code extension was tested with Monte Carlo simulated data using three phantoms (Catphan® high resolution and sensitometry modules and a CIRS patient phantom). In the simulations, ideal and non-ideal conditions for a pCT setup were assumed. The obtained mean absolute percentage error was found to be below 1% and up to 8 lp/cm could be resolved using an idealized setup. These findings demonstrate that the presented code extension to the TIGRE toolbox offers the possibility for other research groups to use a fast and accurate open-source pCT reconstruction.