The first goal of this paper is to clarify the reference conditions for the reference dosimetry of clinical proton beams. A clear distinction is made between proton beam delivery systems which should be calibrated with a spread-out Bragg peak field and those that should be calibrated with a (pseudo-)monoenergetic proton beam. For the latter, this paper also compares two independent dosimetry techniques to calibrate the beam monitor chambers: absolute dosimetry (of the number of protons exiting the nozzle) with a Faraday cup and reference dosimetry (i.e. determination of the absorbed dose to water under IAEA TRS-398 reference conditions) with an ionization chamber. To compare the two techniques, Monte Carlo simulations were performed to convert dose-to-water to proton fluence. A good agreement was found between the Faraday cup technique and the reference dosimetry with a plane-parallel ionization chamber. The differences-of the order of 3%-were found to be within the uncertainty of the comparison. For cylindrical ionization chambers, however, the agreement was only possible when positioning the effective point of measurement of the chamber at the reference measurement depth-i.e. not complying with IAEA TRS-398 recommendations. In conclusion, for cylindrical ionization chambers, IAEA TRS-398 reference conditions for monoenergetic proton beams led to a systematic error in the determination of the absorbed dose to water, especially relevant for low-energy proton beams. To overcome this problem, the effective point of measurement of cylindrical ionization chambers should be taken into account when positioning the reference point of the chamber. Within the current IAEA TRS-398 recommendations, it seems advisable to use plane-parallel ionization chambers-rather than cylindrical chambers-for the reference dosimetry of pseudo-monoenergetic proton beams.

We propose a method of creating and validating a Monte Carlo (MC) model of a proton Pencil Beam Scanning (PBS) machine using only commissioning measurements and avoiding the nozzle modeling. Measurements with a scintillating screen coupled with a CCD camera, ionization chamber and a Faraday Cup were used to model the beam in TOPAS without using any machine parameter information but the virtual source distance from the isocenter. Then the model was validated on simple Spread Out Bragg Peaks (SOBP) delivered in water phantom and with six realistic clinical plans (many involving 3 or more fields) on an anthropomorphic phantom. In particular the behavior of the moveable Range Shifter (RS) feature was investigated and its modeling has been proposed. The gamma analysis (3%,3 mm) was used to compare MC, TPS (XiO-ELEKTA) and measured 2D dose distributions (using radiochromic film). The MC modeling proposed here shows good results in the validation phase, both for simple irradiation geometry (SOBP in water) and for modulated treatment fields (on anthropomorphic phantoms). In particular head lesions were investigated and both MC and TPS data were compared with measurements. Treatment plans with no RS always showed a very good agreement with both of them (γ-Passing Rate (PR) > 95%). Treatment plans in which the RS was needed were also tested and validated. For these treatment plans MC results showed better agreement with measurements (γ-PR > 93%) than the one coming from TPS (γ-PR < 88%). This work shows how to simplify the MC modeling of a PBS machine for proton therapy treatments without accounting for any hardware components and proposes a more reliable RS modeling than the one implemented in our TPS. The validation process has shown how this code is a valid candidate for a completely independent treatment plan dose calculation algorithm. This makes the code an important future tool for the patient specific QA verification process.

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BackgroundA multidisciplinary and multi-institutional working group applied the Failure Mode and Effects Analysis (FMEA) approach to the actively scanned proton beam radiotherapy process implemented at CNAO (Centro Nazionale di Adroterapia Oncologica), aiming at preventing accidental exposures to the patient.MethodsFMEA was applied to the treatment planning stage and consisted of three steps: i) identification of the involved sub-processes; ii) identification and ranking of the potential failure modes, together with their causes and effects, using the risk probability number (RPN) scoring system, iii) identification of additional safety measures to be proposed for process quality and safety improvement. RPN upper threshold for little concern of risk was set at 125.ResultsThirty-four sub-processes were identified, twenty-two of them were judged to be potentially prone to one or more failure modes. A total of forty-four failure modes were recognized, 52% of them characterized by an RPN score equal to 80 or higher. The threshold of 125 for RPN was exceeded in five cases only. The most critical sub-process appeared related to the delineation and correction of artefacts in planning CT data. Failures associated to that sub-process were inaccurate delineation of the artefacts and incorrect proton stopping power assignment to body regions. Other significant failure modes consisted of an outdated representation of the patient anatomy, an improper selection of beam direction and of the physical beam model or dose calculation grid. The main effects of these failures were represented by wrong dose distribution (i.e. deviating from the planned one) delivered to the patient. Additional strategies for risk mitigation, easily and immediately applicable, consisted of a systematic information collection about any known implanted prosthesis directly from each patient and enforcing a short interval time between CT scan and treatment start. Moreover, (i) the investigation of dedicated CT image reconstruction algorithms, (ii) further evaluation of treatment plan robustness and (iii) implementation of independent methods for dose calculation (such as Monte Carlo simulations) may represent novel solutions to increase patient safety.ConclusionsFMEA is a useful tool for prospective evaluation of patient safety in proton beam radiotherapy. The application of this method to the treatment planning stage lead to identify strategies for risk mitigation in addition to the safety measures already adopted in clinical practice.

Clinically relevant intensity modulated proton therapy (IMPT) treatment plans were measured in a newly developed anthropomorphic phantom (i) to assess plan accuracy in the presence of high heterogeneity and (ii) to measure plan robustness in the case of treatment uncertainties (range and spatial). The new phantom consists of five different tissue substitute materials simulating different tissue types and was cut into sagittal planes so as to facilitate the verification of co-planar proton fields. GafChromic films were positioned in the different planes of the phantom, and 3D-IMPT and distal edge tracking (DET) plans were delivered to a volume simulating a skull base chordoma. In addition, treatments planned on CTs of the phantom with HU units modified were delivered to simulate systematic range uncertainties (range-error treatments). Finally, plans were delivered with the phantom rotated to simulate spatial errors. Results show excellent agreement between the calculated and the measured dose distribution: >99% and 98% of points with a gamma value <1 (3%/3 mm) for the 3D-IMPT and the DET plan, respectively. For both range and spatial errors, the 3D-IMPT plan was more robust than the DET plan. Both plans were more robust to range than to the spatial uncertainties. Finally, for range error treatments, measured distributions were compared to a model for predicting delivery errors in the treatment planning system. Good agreement has been found between the model and the measurements for both types of IMPT plan.

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A commercial Monte Carlo (MC) algorithm (RayStation version 6.0.024) for the treatment of brain tumors with pencil beam scanning (PBS) proton therapy is validated and compared via measurements and analytical calculations in clinically realistic scenarios. For the measurements a 2D ion chamber array detector (MatriXX PT) was placed underneath the following targets: (1) an anthropomorphic head phantom (with two different thicknesses) and (2) a biological sample (i.e. half a lamb's head). In addition, we compared the MC dose engine versus the RayStation pencil beam (PB) algorithm clinically implemented so far, in critical conditions such as superficial targets (i.e. in need of a range shifter (RS)), different air gaps, and gantry angles to simulate both orthogonal and tangential beam arrangements. For every plan the PB and MC dose calculations were compared to measurements using a gamma analysis metrics (3%, 3 mm). For the head phantom the gamma passing rate (GPR) was always >96% and on average >99% for the MC algorithm; the PB algorithm had a GPR of  ⩽90% for all the delivery configurations with a single slab (apart 95% GPR from the gantry of 0° and small air gap) and in the case of two slabs of the head phantom the GPR was >95% only in the case of small air gaps for all three (0°, 45°, and 70°) simulated beam gantry angles. Overall the PB algorithm tends to overestimate the dose to the target (up to 25%) and underestimate the dose to the organ at risk (up to 30%). We found similar results (but a bit worse for the PB algorithm) for the two targets of the lamb's head where only two beam gantry angles were simulated. Our results suggest that in PBS proton therapy a range shifter (RS) needs to be used with caution when planning a treatment with an analytical algorithm due to potentially great discrepancies between the planned dose and the dose delivered to the patient, including in the case of brain tumors where this issue could be underestimated. Our results also suggest that a MC evaluation of the dose has to be performed every time the RS is used and, mostly, when it is used with large air gaps and beam directions tangential to the patient surface.

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