FRoG—A New Calculation Engine for Clinical Investigations with Proton and Carbon Ion Beams at CNAO

Abstract

A fast and accurate dose calculation engine for hadrontherapy is critical for both routine clinical and advanced research applications. FRoG is a graphics processing unit (GPU)-based forward calculation tool developed at CNAO (Centro Nazionale di Adroterapia Oncologica) and at HIT (Heidelberg Ion Beam Therapy Center) for fast and accurate calculation of both physical and biological dose. FRoG calculation engine adopts a triple Gaussian parameterization for the description of the lateral dose distribution. FRoG provides dose, dose-averaged linear energy transfer, and biological dose-maps, -profiles, and -volume-histograms. For the benchmark of the FRoG calculation engine, using the clinical settings available at CNAO, spread-out Bragg peaks (SOBPs) and patient cases for both proton and carbon ion beams have been calculated and compared against FLUKA Monte Carlo (MC) predictions. In addition, FRoG patient-specific quality assurance (QA) has been performed for twenty-five proton and carbon ion fields. As a result, for protons, biological dose values, using a relative biological effectiveness (RBE) of 1.1, agree on average with MC within ~1% for both SOBPs and patient plans. For carbon ions, RBE-weighted dose (D_RBE) agreement against FLUKA is within ~2.5% for the studied SOBPs and patient plans. Both MKM (Microdosimetric Kinetic Model) and LEM (Local Effect Model) D_RBE are implemented and tested in FRoG to support the NIRS (National Institute of Radiological Sciences)-based to LEM-based biological dose conversion. FRoG matched the measured QA dosimetric data within ~2.0% for both particle species. The typical calculation times for patients ranged from roughly 1 to 4 min for proton beams and 3 to 6 min for carbon ions on a NVIDIA^® GeForce^® GTX 1080 Ti. This works demonstrates FRoG’s potential to bolster clinical activity with proton and carbon ion beams at CNAO.

1. Introduction

Radiation therapy requires dose computation on computed tomography (CT) images for each patient with high accuracy and fast calculation time. A clinical treatment planning system (TPS) for proton and carbon ions typically uses an analytical algorithm for dose calculation on a central processing unit (CPU). Recently, graphics processing unit (GPU)-based clinical TPSs have been made available (e.g., Raystation, RaySearch Laboratories, Stockholm, Sweden), promising enhanced calculation speeds for the even more time-consuming Monte Carlo (MC) codes [1]. The benefit of improved precision is clear for the more technologically demanding modalities such as particle therapy. In the near future, compact high-performance systems will become commonplace in the clinic, making routine integration of advanced physical and biophysical models feasible [1,2,3].

Presently, the commercial TPS used during clinical operation at CNAO (Centro Nazionale Adroterapia Oncologica [4]), Syngo-VC13 (Siemens AG, Mannheim, Germany), is a CPU-based system. Syngo-VC13 calculates biological dose by applying a fixed relative biological effectiveness (RBE) of 1.1 [5] for proton beams and the biological model LEM I (Local Effect Model [6]) for carbon ion beams. Syngo, as well as the other analytical systems, in comparison to MC approaches, has limitations in handling patient heterogeneities and small fields with and without the range shifter (RS) especially with proton beams [7]. Additionally, calculation features for clinically relevant biophysical quantities are often missing from such programs, such as dose-averaged linear energy transfer (LET_d) distributions in water for proton beams or RBE-weighted dose (D_RBE) for carbon ions with other biological models including the modified MKM (Microdosimetric Kinetic Model [8]). The modified MKM is applied at the carbon ion therapy facility NIRS (National Institute of Radiological Sciences) in Japan for carbon ion therapy planning [9]. At CNAO, the fractionation scheme used at NIRS has been employed requiring the introduction of a conversion between NIRS-based to LEM-based D_RBE, as calculated by Syngo [10,11].

In order to overcome these limitations, we have introduced a new calculation platform, FRoG (Fast Recalculation on GPU), to perform fast physical and biological calculations for proton and carbon ion beam therapy. The FRoG project is a collaborative effort between the CNAO facility in Pavia, Italy, and the Heidelberg Ion Beam Therapy Center (HIT) [12] in Heidelberg, Germany. FRoG was designed to perform fast and accurate calculations, applying an analytical pencil beam algorithm on GPU to calculate physical/biological dose and LET_d distributions. For proton beams, clinicians and medical physicists can assess both dose and LET_d distributions (and eventually D_RBE applying variable RBE scheme [13,14]) to further scrutinize plans for acceptance or potential re-planning purposes within minutes. For carbon ions, the user can quickly access MKM-based D_RBE values and compare them with the converted LEM-based D_RBE predictions by the use of a scaling factor introduced in Fossati et al. [10]. In presence of large hot or cold spots in the tumor, the plan can be readily re-optimized taking into account the FRoG MKM-based D_RBE values.

In this work, the benchmarks performed are presented for both proton and carbon ions in preparation for FRoG’s integration into clinical activity. SOBPs and patient cases have been calculated and compared against FLUKA MC predictions [15,16,17], which serves as the reference MC code at CNAO and was used to generate the physical database of Syngo [18,19,20,21]. Various LET_d maps and LEM vs. MKM D_RBE distributions for patients treated with proton and carbon ion beams, respectively, are presented. Prior to patient treatment, the plan from Syngo is verified dosimetrically by performing field-specific quality assurance (QA) [18]. In this work, we have used twenty-five field-specific QA for each beam modality and we have compared them against FRoG predictions.

2. Results

2.1. Comparison of FLUKA- and FRoG-Calculated Spread Out Bragg Peaks

Syngo-optimized SOBPs without beam modifiers (i.e., range shifter), have been calculated with FRoG and compared against FLUKA predictions. For protons, the results are summarized in

Table 1. Percent RBE-weighted dose (D_RBE) difference comparison for RBE-weighted dose-volume histogram (D_RBEVH) between FRoG and Monte Carlo (MC) for proton beams.

Percent Difference of	Target Volume	3 cm	12 cm	21 cm
DRBE,50	27 cm3 216 cm3	0.67% 0.59%	0.59% 0.61%	0.88% 0.71%
DRBE,2	27 cm3 216 cm3	0.91% −0.60%	−0.09% 0.08%	0.47% 0.73%
DRBE,98	27 cm3 216 cm3	0.52% 0.46%	0.43% 1.10%	1.07% 0.47%

in terms of percent D_RBE difference of the RBE-weighted dose-volume histogram (D_RBEVH) parameters D_RBE,50, D_RBE,2, and D_RBE,98 for an SOBP with equal sides of 3 cm (target volume 27 cm³) and 6 cm (target volume of 216 cm³) at different depths: 3 cm, 12 cm, and 21 cm. For a definition of these parameters see Section 4.2.1. The RBE was assumed to be 1.1.

FRoG matches well with the MC predictions. Considering all resultant values (D_RBE,50, D_RBE,2, and D_RBE,98), in terms of absolute variation, FRoG reproduces FLUKA results within 0.7% on average. The observed maximum variation was 1.1% for D_RBE,98 for an SOBP of side 3 cm at 21 cm depth and for an SOBP of side 6 cm at 12 cm depth.

Carbon ions D_RBEVH statistics for the target volume for the six studied SOBPs are summarized in

Table 2. Percent D_RBE difference comparison for Local Effect Model (LEM) D_RBEVH between FRoG and MC for ¹²C ions.

Percent Difference of	Target Volume	3 cm	12 cm	21 cm
DRBE,50	27 cm3 216 cm3	0.93% 0.58%	0.39% 0.64%	−0.01% 1.02%
DRBE,2	27 cm3 216 cm3	−1.01% −1.14%	−2.45% −0.65%	−2.27% 0.02%
DRBE,98	27 cm3 216 cm3	−2.19% 2.14%	−0.18% 2.95%	2.03% 0.78%

and

Table 3. Percent D_RBE difference comparison for Microdosimetric Kinetic Model (MKM) D_RBEVH between FRoG and MC for ¹²C ions.

Percent Difference of	Target Volume	3 cm	12 cm	21 cm
DRBE,50	27 cm3 216 cm3	−1.13% −0.46%	−2.10% −0.41%	−2.97% −0.26%
DRBE,2	27 cm3 216 cm3	−0.19% −0.68%	−0.90% −1.41%	−2.11% −2.48%
DRBE,98	27 cm3 216 cm3	0.81% −0.30%	−2.38% 1.91%	−3.86% −0.84%

for LEM and MKM, respectively. For 27 cm³ (216 cm³) target volumes, applying the LEM model, percent D_RBE differences for D_RBE,50, D_RBE,2, and D_RBE,98 are 0.4% (0.7%), −1.9% (−0.6%), and −0.1% (2.0%), respectively. These results are obtained by averaging over the three SOBP depths.

For 27 cm³ (216 cm³) target volumes, applying the MKM model, percent D_RBE differences for D_RBE,50, D_RBE,2, and D_RBE,98 are −1.1% (−0.4%), −2.2% (−1.5%), and −1.7% (0.3%), respectively. Overall, the FRoG biological dose calculations with the studied SOBPs match FLUKA predictions within 2.5%. However, variations larger than or close to 3% have been found for LEM D_RBE,98 at 12 cm (216 cm³ target volume) and MKM D_RBE,98 at 21 cm (27 cm³ target volume).

2.2. Comparison of FLUKA- and FRoG-Calculated Patient Cases

2.2.1. Proton Beams

For proton beams, fifteen CNAO patient cases have been recalculated with FRoG and FLUKA: five head and neck (H&N) without RS, five H&N with RS, and five pelvic cases without RS. The FRoG and FLUKA D_RBE predictions (RBE = 1.1) have been compared in terms of variation of D_RBE,50, D_RBE,2, and D_RBE,98 in the target volume and in terms of γ-analysis [22,23]. In Figure 1 and Figure 2, D_RBE distributions and D_RBEVH comparisons between FLUKA and FRoG are presented for a H&N case without RS and a pelvic case, respectively.

A summary of variations in target D_RBE,50, D_RBE,2, and D_RBE,98, with respect to MC calculations for proton patient cases is reported in

Table 4. Average percent variation of target D_RBE,50, D_RBE,2, and D_RBE,98, with respect to MC calculations for proton patient cases. The values represent the mean ± standard error of the mean.

Percent Difference of	Total	H&N No RS	H&N with RS	Pelvic
DRBE,50	0.68% ± 0.21%	1.05% ± 0.32%	0.34% ± 0.50%	0.65% ± 0.31%
DRBE,2	−0.57% ± 0.41%	−0.91% ± 0.55%	−0.84% ± 1.05%	0.02% ± 0.67%
DRBE,98	0.41% ± 0.56%	1.25% ± 0.42%	−0.79% ± 1.55%	0.77% ± 0.81%

. Average percent D_RBEVH differences between FLUKA simulation and FRoG over the whole patient set were within ~0.7%. γ-pass rates, i.e., percent of points for which the γ-index is ≤1, were 98.4%, 96.0%, and 97.2% for the H&N without RS, H&N with RS, and pelvic patient cases, respectively. The overall γ-pass rate was 97.2%.

The average calculation time for the ten H&N cases was approximately 90 s ± 22 s, with a maximum of 3 min and 57 s (PTV of 300 cm³, three beams with RS) and minimum of 44 s (PTV of 15.5 cm³, three beams with RS). For the pelvic cases, the average calculation time was approximately 175 s ± 60 s ranging from a maximum of 6 min and 35 s (PTV of 2134 cm³, two beams) to a minimum of 1 min and 2 s (PTV of 91 cm³, two beams). The reported runtime also includes calculating LET_d (as well as RBE) distributions which are typically unavailable in a commercial TPS.

In Figure 3, LET_d maps and LET_d-volume-histograms (LET_dVH) calculated by FRoG and FLUKA for the two patients of Figure 1 and Figure 2 are shown. For the head case, the left temporal lobe was examined in order to quantify the high LET_d component found, as expected, in the distal region of the field. For the PTV, FRoG and FLUKA LET_d values match within 0.05 keV/µm. The FRoG calculated mean LET_d is approximately 3.0 keV/µm while the LET_d,2 is 5.7 keV/µm, where LET_d,2 is the LET_d received by 2% of the volume. For the other ROIs, LET_d,2 are 6.4 keV/µm, 3.0 keV/µm, and 9.5 keV/µm, for the brainstem and the right and left temporal lobe, respectively. These values agree with the FLUKA predictions within ~0.3 keV/ µm. For the pelvic case, the mean LET_d for the CTV is 2.5 keV/µm while the LET_d,2 is 4.0 keV/µm. For the bladder, LET_d,2 is 4.1 keV/µm while for the lower value of LET_d,2 for the femurs is ~1.2 keV/µm. These values agree with the FLUKA predictions within ~0.2 keV/µm for organs at risk (OAR) and ~0.05 keV/µm for the CTV.

2.2.2. Carbon Ion Beams

For carbon ion beams, ten Syngo LEM-optimized CNAO patient cases were recalculated using FRoG and FLUKA: five H&N and five pelvic cases. The H&N cases include fields with and without RS. Resultant FLUKA and FRoG LEM/MKM-based D_RBE distributions are compared. In Figure 4 and in Figure 5, FLUKA and FRoG LEM/MKM D_RBE distributions and D_RBEVH comparisons for a H&N case and a pelvic case, respectively, are shown. In

Table 5. Average percent variation of target D_RBE,50, D_RBE,2, and D_RBE,98, with respect to MC calculations for carbon ion patient cases applying LEM and MKM biological models. The values represent the mean ± standard error of the mean.

Percent Difference of	Biological Model	Total	H&N	Pelvic
DRBE,50	LEM MKM	0.96% ± 0.33% 1.46% ± 0.30%	0.52% ± 0.52% 1.23% ± 0.30%	1.40% ± 0.38% 1.69% ± 0.50%
DRBE,2	LEM MKM	0.97% ± 0.30% 1.81% ± 0.46%	0.93% ± 0.62% 2.57% ± 0.78%	1.01% ± 0.32% 1.05% ± 0.36%
DRBE,98	LEM MKM	2.23% ± 0.34% 2.36% ± 0.30%	2.80% ± 0.65% 2.93% ± 0.46%	1.67% ± 0.18% 1.79% ± 0.23%

, percent D_RBEVH differences between FLUKA MC simulations and FRoG for the target in terms of D_RBE,2, D_RBE,50, and D_RBE,98 are reported for both MKM and LEM D_RBE values. Average percent differences over the whole patient set were within 2.5% for both LEM and MKM-based D_RBE, respectively. γ-pass rates were ~99% for both LEM and MKM in both H&N and pelvic cases.

The average calculation time including absorbed dose, LEM and MKM D_RBE for the five H&N cases was about 388 s ± 91 s, ranging from 4 min and 11 s (PTV of 25 cm³, 2 beams) to 11 min and 30 s (PTV of 204 cm³, two beams). For the pelvic cases, the average calculation time was about 205 s ± 60 s, ranging from 1 min and 33 s (PTV of 40 cm³, one beam) to 5 min and 50 s (PTV of 172 cm³, one beam).

2.3. Comparison against Dosimetric Data

For patient QA, FRoG dose calculations showed a high level of agreement, with the mean and standard deviation of the difference between calculated and measured dose over the twenty-five fields of 1.96% ± 0.79% and 2.21% ± 0.92%, for p and ¹²C, respectively. The Syngo-calculated values were 2.71% ± 1.25% and 2.57% ± 0.84%, for p and ¹²C, respectively. The improved agreement compared to Syngo is due to the employment of a triple Gaussian parameterization in FRoG instead of a double Gaussian model as in Syngo [24] and an improved handling of the RS for proton beams. In FRoG, facility-specific triple Gaussian parameterizations were implemented taking into account RS thickness and RS distance from the patients (or phantoms) entry point. Conversely, as explained previously [7], Syngo numerically accounts for the corresponding water equivalent thickness for radiological depth calculation, but the beam widening due to the RS is only covered by a single Gaussian scattering model [25]. For carbon ions, Syngo neglects the additional scattering of the beams in the RS while FRoG considers a beam energy-dependent parameterization of the beam widening due to the RS. The typical calculation time for a patient QA field is roughly 1 to 2 min depending on particle type, depth, and target volume.

3. Discussion

In this paper, benchmarks of FRoG against MC predictions for protons and carbon ions have been performed in both homogeneous (SOBP in water) and heterogeneous scenarios (patient cases). In general, on average discrepancies in terms of D_RBE values have been found to be within 1% and 2.5% for proton and carbon ions, respectively. For carbon ions, variations larger than or close to 3% have been found for LEM and for MKM. The steep dose gradients of carbon ions make D_RBE,98 a less robust metric in the evaluation of the target coverage. Additionally, we have analyzed the D_RBE,95 (biological dose received by 95% of the PTV) and found an improved agreement with a variation of 1.94% for LEM D_RBE,95 at 12 cm (side 6 cm) and −1.20% MKM D_RBE,95 at 21 cm (side 3 cm). In general, the worsening of the agreement in the case of carbon ions is due to the limitations of handling the lateral dose distributions with a simple triple Gaussian approach [24] as well as the assumption that, for biological calculations, lateral variations of the mixed radiation field are not explicitly considered [26]. In order to overcome the latter, an approach similar to the one suggested by Inaniwa and Kanematsu [26] could be implemented. Nevertheless, the FRoG agreement with the MC has been considered highly satisfactorily keeping in mind the larger discrepancies, up to 5–10%, found using commercial TPS [7,27].

In terms of physical dose distributions for carbon ions, FRoG and FLUKA match on average within 1.4% for SOBPs and within 1.6% for patient cases (see Supplementary Material Table S1), in line with results presented previously [24] where calculations of SOBPs in homogenous settings using FRoG were within 1.3% of FLUKA calculations, while analysis of patient case calculations exhibited net deviations in the target within about 1.5%.

For the proton H&N patient cases, presence of the RS marginally reduces the agreement, with the γ-pass rate decreasing from 98.4% to 96.0% with use of the RS. Nonetheless, the high level of agreement found confirms that the RS handling in FRoG is sound, as described in Section 2.3.

For proton beams, LET_d values have been found matching the MC predictions within 0.3 keV/µm in both target and organs at risk. This agreement is important when using FRoG for a retrospective study of clinical outcomes in proton therapy. A FRoG user could efficiently perform the analysis carried out in a previous paper [28], determining, for example, if areas of normal tissue damage indicated by post-treatment image changes are associated with increased LET_d values.

Regarding the carbon ion biological dose, a conversion scheme is implemented at CNAO allowing to plan a NIRS-based median biological dose to the target starting from a prescribed LEM-based biological dose [10,11]. This, however, does not assure a satisfactory coverage in certain cases resulting in hot or cold spots in the biological dose distributions due to the different particle type, LET and tissue dependencies of the two biological models. As an example, in the left panel of Figure 6, the ratio between FRoG-calculated MKM D_RBE and LEM D_RBE, multiplied by the clinical scaling value for the patient shown in Figure 4, is displayed only in the region of the CTV. For this patient, the FRoG-calculated scaling factor (D_RBE,LEM,50/D_RBE,MKM,50 for the CTV) is 1.12 which matches the expected one of about 1.10 for 4.3 Gy (RBE) LEM per fraction scheme [10]. If a constant scaling factor were enough to modulate LEM-based biological dose to MKM-based biological dose, the ratio values reported in the left panel of Figure 6 should be close to 1. Instead, hot and cold spots have been found in the CTV as summarized in the D_RBEVH shown in the right panel of Figure 6. In this context, the accessibility within few minutes of a FRoG MKM-based biological dose could help medical physicists in adjusting the LEM-based constraints, resulting in a more homogenous MKM biological dose mitigating hot and cold spots in the target.

For the studied patient cases, FRoG’s total calculation time was approximately 2 min for proton beams and 5 min for carbon ion beams. Further improvements could be made to FRoG’s calculation speed by upgrading the hardware and optimizing the code structure. For our calculations, we have used a consumer grade GPU card (NVIDIA Corporation, Santa Clara, CA, USA NVIDIA^® GeForce^® GTX 1080 Ti) as available at CNAO. For understanding the impact of upgrading the GPU card on the calculation time reduction, we have run the most time-consuming case presented in this work, i.e., a H&N carbon ion case (total time: 11 min and 30 s, PTV of 204 cm³, two beams) with a high-end graphics card (NVIDIA Corporation, Santa Clara, CA, USA NVIDIA^® Tesla^® V100) available at HIT. The time reduction was approximately 3.5-fold with a new total calculation time of about 3 min and 20 s.

In terms of dosimetric comparisons, considering both protons and carbon ions, FRoG agreed with measurements better than Syngo, with a 0.56% improvement, on average, in reproducing patient-specific QA measurements. The additional differences of about 2% found with respect to the experimental data could be due to uncertainties involved in the dose delivery process and in the water phantom positioning as described previously [18].

Here, the FRoG platform has been introduced at CNAO and it has been benchmarked successfully against MC prediction and dosimetric measurements for proton and carbon ion beams. Due to its accuracy and fast calculation time in comparison to the MC code, FRoG could be used for retrospective study of large patient cohorts as well as in clinical treatment planning workflow taking into account LET_d distributions in proton plans and MKM-based D_RBE in carbon ion plans. Organs at risk constraints resulting from toxicity studies of the long-term follow up of Japanese treatments were adopted at CNAO without any correction for the RBE model. This approach is overly conservative and it is currently under evaluation for critical structures such as the optic nerve, brainstem, and rectum.

4. Materials and Methods

4.1. FRoG Workflow and Design Information

In regard to the input physics database, FRoG handles depth dose distributions and lateral dose parametrizations generated with FLUKA simulated data [18,19,20,29]. As described previously [24], physical and biophysical quantities were simulated and scored depth-wise in water. For the physical dose, lateral evolution was additionally scored radially. Subsequently, lateral dose evolution parameterization as a function of depth using a triple Gaussian model was performed using the MINUIT package [30] in ROOT [31], as described previously [32].

For biological calculations, MC-derived depth-dependent databases for LET_d, z*_mix, alpha and beta are available. For carbon ions, z*_mix is used for MKM-based calculations [8,33] while alpha and beta for LEM ones [6,34]. Alpha and beta are the dose-averaged linear (alpha) and quadratic (beta) parameters necessary for the LEM while z*_mix is the dose-averaged saturation-corrected dose-mean specific energy of the domain delivered in a single event needed by the MKM. FRoG’s depth-dependent database for physical and biological calculations with carbon ion beams at CNAO are shown in Figure 7. The physical and biological input parameters employed for generating the database are explained in detail in previous works [33,34].

FRoG employs a pencil beam algorithm with GPU optimized raytracing [35]. Raytracing is performed with the resolution of the planning CT, whereas dose can be calculated on a downsized grid, following the clinical procedure at CNAO. For head treatments with proton beams, dose calculation is performed on a 2 × 2 × 2 mm³ grid with a 0.98 × 0.98 × 2 mm³ CT resolution, while for pelvic treatments, dose calculation is performed on a 3 × 3 × 3 mm³ grid with a 0.98 × 0.98 × 2 mm³ CT resolution. For carbon ions, for the studied cases, dose calculation is performed on a 2 × 2 × 2 mm³ grid with a 0.98 × 0.98 × 2 mm³ CT resolution. Pencil beam splitting was incorporated into FRoG’s framework following the mathematical procedures of beamlet superposition [36] handling variable lateral dose evolution in the presence of anatomical heterogeneity. In a two-dimensional grid space, the splitting method involves a superposition of N equally-spaced sub-Gaussians (bounded by ±3.5 σ) with equivalent FWHM but variable weighting. For protons ~350 subsplits were used while for carbon ions, ~350 and ~100 subsplits, were applied for patient cases in the H&N and in the pelvic region, respectively. In case of calculations in water phantoms, no splitting is needed. For each beam spot in the patient plan, source-to-surface distance was calculated and full width at half maximum (FWHM) in air projected to the entrance were interpolated using experimentally measured FWHM values for each ion, beam energy, foci, and treatment room as in clinical practice at CNAO using Syngo [20].

The FRoG dose calculation engine adopts a triple Gaussian distribution model for handling lateral dose distribution as a function of the water equivalent depth [24]. For carbon ion therapy, there are two biological models applied clinically, the modified MKM and LEM I. These models are implemented in FRoG and the two D_RBE distributions are calculated at the same time of the physical dose. The implementation of the LEM and MKM biological calculations have been performed following the approaches described in the literature [6,8,9,27,33,34]. For proton beams, dose-averaged LET in water is calculated as described previously [27] but weighting only primary protons and secondary protons, deuterons, and tritons. This allows to quickly access D_RBE values applying LET-based RBE models [13].

4.2. Benchmark of the FRoG Predictions with Proton and Carbon Ion Beams

4.2.1. Comparison against FLUKA Predictions

Six SOBPs for both proton and carbon ions have been optimized with Syngo using RBE = 1.1 for protons and LEM-based optimization for carbon ions [6,7]. The target volumes had cubic shapes with sides of 3 cm or 6 cm. They were contoured in water with the proximal face positioned at a depth of 6 cm, 12 cm, and 21 cm. The optimization goal was homogeneous target coverage to 2 Gy (RBE) for both proton and carbon ions. The results are analyzed in terms of percent D_RBE difference of D_RBE,50, D_RBE,2, and D_RBE,98. D_RBE,50, D_RBE,2, and D_RBE,98 represent the biological dose received by 50%, 2%, and 98% of the planning target volume (PTV) in the cumulative D_RBEVH, respectively. To evaluate the capability of FRoG in handling heterogeneities in clinically relevant scenarios, twenty-five patients previously treated at CNAO have been recalculated. Fifteen patients treated with proton beams (10 H&N, five pelvic cases) and ten with carbon ions (five H&N, five pelvic cases). We have included the most clinically representative targets and beam configurations. Five proton H&N patients have been selected with 3 cm RW3 range shifter, always positioned at 10 cm distance from the patient’s skin. In this way, we could quantify the FRoG predictions when an RS for proton beams was employed. γ-values have been calculated for the regions in the D_RBE distributions with a 10% low-dose threshold of the maximum MC D_RBE. The chosen criteria were 2 mm as distance-to-agreement (DTA) and 2% as D_RBE difference.

The FLUKA MC code [15,16,17] was selected to perform forward plan recalculations to benchmark FRoG predictions. FLUKA represents the gold standard for clinical calculations in particle therapy at CNAO [18,19,20].

Patients records were obtained with informed consent and handled following the Helsinki Declaration. All methods were approved and followed applicable guidelines and regulations of CNAO. Considering the retrospective nature of the study, clearing from the ethical review committee was not required. All records were anonymized prior to the study.

4.2.2. Comparison against Dosimetric Data

For experimentally validating FRoG results, dosimetric verification of patient plans in water for proton and carbon ion beams has been performed following the same procedure as for patient quality assurance at CNAO [18]. Twenty-five fields of patient-specific QA for each beam modality have been acquired and compared against FRoG predictions. The measurements were performed using a water phantom (MP3-P T41029, PTW, Freiburg, Germany). The dosimetric system consists of a three-dimensional stack of pin point ionization chambers (ICS, PinPoint Ionization Chambers, TM31015, PTW, Freiburg, Germany), mounted on a robotic arm and positioned inside the water phantom [37]. The position of the block with the ICs can be remotely controlled with a step size of 0.1 mm. The dose distribution for each beam has been measured using 12 ICs simultaneously with the ICs connected to a 12-channel electrometer (MULTIDOS^®, PTW, Freiburg, Germany). According to the CNAO QA protocol, results are accepted if the mean and the standard deviation of [(measured dose − calculated dose)/maximum field dose] over a data set of 12 points are both within ±5% and below 5%, respectively [18].

5. Conclusions

Through a multi-institutional collaboration, we introduce a unique software, FRoG, for rapid and robust dose calculation on GPU for protons and carbon ions at CNAO. As opposed to the commercial TPS used in the clinic, FRoG is a sandbox environment for radiation therapy research, providing the means to develop and evaluate sophisticated models for effective dose (e.g.,: MKM and LEM), as well as physical quantities such as LET_d. Benchmark tests for the FRoG dose calculation engine using both SOBPs and patient cases were performed against FLUKA MC and dosimetric data, demonstrating satisfactorily agreement. Future efforts with FRoG include retrospective analysis of a large patient cohort to investigate clinical outcome, as well refinement of both physical and biological models in hadrontherapy.