A pre-absorber optimization technique for pencil beam scanning proton therapy treatments

Dosimetric and NTCP advantages of robust proton therapy over robust VMAT for Stage III NSCLC in the immunotherapy era

AIMS

To assess the robustness and to define the dosimetric and NTCP advantages of pencil-beam-scanning proton therapy (PBSPT) compared with VMAT for unresectable Stage III non-small lung cancer (NSCLC) in the immunotherapy era.

MATERIAL AND METHODS

10 patients were re-planned with VMAT and PBSPT using: 1) ITV-based robust optimization with 0.5 cm setup uncertainties and (for PBSPT) 3.5 % range uncertainties on free-breathing CT 2) CTV-based RO including all 4DCTs anatomies. Target coverage (TC), organs at risk dose and TC robustness (TCR), set at V95%, were compared. The NTCP risk for radiation pneumonitis (RP), 24-month mortality (24MM), G2 + acute esophageal toxicity (ET), the dose to the immune system (EDIC) and the left anterior descending (LAD) coronary artery V15 < 10 % were registered. Wilcoxon test was used.

RESULTS

Both PBSPT methods improved TC and TCR (p < 0.01). The mean lung dose and lung V20 were lower with PBSPT (p < 0.01). Median mean heart dose reduction with PBSPT was 8 Gy (p < 0.001). PT lowered median LAD V15 (p = 0.004). ΔNTCP > 5 % with PBSPT was observed for two patients for RP and for five patients for 24 MM. ΔNTCP for ≥ G2 ET was not in favor of PBSPT for all patients. PBSPT halved median EDIC (4.9/5.1 Gy for ITV/CTV-based VMAT vs 2.3 Gy for both ITV/CTV-based PBSPT, p < 0.01).

CONCLUSIONS

PBSPT is a robust approach with significant dosimetric and NTCP advantages over VMAT; the EDIC reduction could allow for a better integration with immunotherapy. A clinical benefit for a subset of NSCLC patients is expected.

Treatment planning of scanned proton beams in RayStation

The use of scanned proton beams in external beam radiation therapy has seen a rapid development over the past decade. This technique places new demands on treatment planning, as compared to conventional photon-based radiation therapy. In this article, several proton specific functions as implemented in the treatment planning system RayStation are presented. We will cover algorithms for energy layer and spot selection, basic optimization including the handling of spot weight limits, optimization of the linear energy transfer (LET) distribution, robust optimization including the special case of 4D optimization, proton arc planning, and automatic planning using deep learning. We will further present the Monte Carlo (MC) proton dose engine in RayStation to some detail, from the material interpretation of the CT data, through the beam model parameterization, to the actual MC transport mechanism. Useful tools for plan evaluation, including robustness evaluation, and the versatile scripting interface are also described. The overall aim of the paper is to give an overview of some of the key proton planning functions in RayStation, with example usages, and at the same time provide the details about the underlying algorithms that previously have not been fully publicly available.

Spot scanning proton arc therapy reduces toxicity in oropharyngeal cancer patients

BACKGROUND

Proton arc technology has recently shown dosimetric gains for various treatment indications. The increased number of beams and energy layers (ELs) in proton arc plans, increases the degrees of freedom in plan optimization and thereby flexibility to spare dose in organs at risk (OARs). A relationship exists between dosimetric plan quality, delivery efficiency, the number of ELs -and beams in a proton arc plan.

PURPOSE

This work aims to investigate the effect of the number of beams and ELs in a proton arc plan, on toxicity and delivery time for oropharyngeal cancer patients (OPC) selected for intensity modulated proton therapy (IMPT) based on the Dutch model-based approach.

METHODS

The EL reduction algorithm iteratively selects ELs from beams equidistantly spaced over a 360° arc. The beams in the final plan may contain multiple ELs, making them suited for static delivery on the studied treatment machine. The produced plans can therefore be called "step and shoot" proton arc plans. The number of beams and ELs were varied to determine the relationship with the planning cost function value, normal tissue complication probability (NTCP) and delivery time. Proton arc plans with robust target coverage and optimal energy layer reduction (ELR) settings to reduce NTCP, were generated for 10 OPC patients. Proton arc plans were compared to clinical volumetric modulated arc therapy (VMAT) and IMPT plans in terms of integral dose, OAR dose, NTCP for xerostomia and dysphagia and delivery time. Furthermore, dose-weighted average linear energy transfer (LET_d ) distributions were compared between the IMPT and proton arc plans. A dry run delivery of a plan containing 20 beams and 360 ELs was performed to evaluate delivery time and accuracy.

RESULTS

We found 360 ELs distributed over 30 beams generated proton arc plans with near minimal expected plan toxicity. Relative to corresponding IMPT and VMAT plans, an average reduction of 21 ± 3% and 58 ± 10% in integral dose was observed. D m e a n $_{mean}$ was reduced most in the pharyngeal constrictor muscle (PCM) medius structure, with on average 9.0 ± 4.2 Gy(RBE) (p = 0.0002) compared to the clinical IMPT plans. The average NTCP for grade≥2 and grade≥3 xerostomia at 6 months after treatment significantly decreased with 4.7 ± 1.8% (p = 0.002) and 1.7 ± 0.8% (p = 0.002), respectively, while the average NTCP for grade≥2 and grade≥3 dysphagia decreased with 4.4 ± 2.9% (p = 0.002) and 0.9 ± 0.4% (p = 0.002), respectively, increasing the benefit of protons relative to VMAT. For a "step and shoot" proton arc delivery with auto beam sequencing the estimated delivery time is 11 min, similar to the delivery time of a 6-field IMPT treatment. Gamma analysis between the planned and delivered dose distribution resulted in a 99.99% pass rate using 1mm/1% dose difference/distance to agreement criteria.

CONCLUSIONS

"Step and shoot" proton arc demonstrates potential to further reduce toxicity compared to IMPT and VMAT in OPC treatment. By employing 360 ELs and 30 beams in the proposed ELR method, delivery time can reach clinically acceptable levels without compromising plan toxicity when automatic beam sequencing is available.

Clinical validation of a GPU-based Monte Carlo dose engine of a commercial treatment planning system for pencil beam scanning proton therapy

PURPOSE

To perform the validation of the GPU-based (Graphical Processing Unit based) proton Monte Carlo (MC) dose engine implemented in a commercial TPS (RayStation 10B) and to report final dose calculation times for clinical cases.

MATERIALS AND METHODS

440 patients treated at the Proton Therapy Center of Trento, Italy, between 2018 and 2019 were selected for this study. 636 approved plans with 3361 beams computed with the clinically implemented CPU-MC dose engine (version 4.2 and 4.5), were used for the validation of the new algorithm. For each beam, the dose was recalculated using the new GPU-MC dose engine with the initial CPU computation settings and compared to the original CPU-MC dose. Beam dose difference distributions were studied to ensure that the two dose distributions were equal within the expected fluctuations of the MC statistical uncertainty (s) of each computation. Plan dose distributions were compared with respect to the dosimetric indices D₉₈, D₅₀ and D₁ of all ROIs defined as targets. A complete assessment of the computation time as a function of s and dose grid voxel size was done.

RESULTS

The median over all mean beam dose differences between CPU- and GPU-MC was -0.01% and the median of the corresponding standard deviations was close to (√2s) both for simulations with an s of 0.5% and 1.0% per beam. This shows that the two dose distributions can be considered equal. All the DVH indices showed an average difference below 0.04%. About half of the plans were computed with 1.0% statistical uncertainty on a 2 mm dose calculation grid, for which the median computation time was 5.2 s. The median computational speed for all plans in the study was 8.4 million protons/second.

CONCLUSION

A validation of a clinical MC algorithm running on GPU was performed on a large pool of patients treated with pencil beam scanning proton therapy. We demonstrated that the differences with the previous CPU-based MC were only due to the intrinsic statistical fluctuations of the MC method, which translated to insignificant differences on plan dose level. The significant increase in dose calculation speed is expected to facilitate new clinical workflows.

Clinical implementation of pencil beam scanning proton therapy for liver cancer with forced deep expiration breath hold

PURPOSE

To present our technique for liver cancer treatments with proton therapy in pencil beam scanning mode and to evaluate the impact of uncertainties on plan quality.

MATERIALS AND METHODS

Seventeen patients affected by liver cancer were included in this study. Patients were imaged and treated in forced breath-hold using the Active Breathing Coordinator system and monitored with an optical tracking system. Three simulation CTs were acquired to estimate the anatomical variability between breath-holds and generate an internal target volume (ITV). The treatment plans were optimized with a Single Field Optimization technique aimed at minimizing the use of range shifter. Plan robustness was tested simulating systematic range and setup uncertainties, as well as the interplay effect between breath-holds. The appropriateness of margin was further verified based on the actual positioning data acquired during treatment.

RESULTS

The dose distributions of the nominal plans achieved a satisfactory target coverage in 11 out of 17 patients, while in the remaining 6 D₉₅ to the PTV was affected by the constraint on mean liver dose. The constraints for all other organs at risk were always within tolerances. The interplay effect had a limited impact on the dose distributions: the worst case scenario showed a D₉₅ reduction in the ITV < 3.9 GyRBE and no OAR with D₁ > 105% of the prescription dose. The robustness analysis showed that for 13 out of 17 patients the ITV coverage in terms of D₉₅ was better than D₉₅ of the PTV in the nominal plan. For the remaining 4 patients, the maximum difference between ITV D₉₅ and PTV D₉₅ was ≤0.7% even for the largest simulated setup error and it was deemed clinically acceptable. Hot spots in the OARs were always lower than 105% of the prescription dose. Positioning images confirmed that the breath hold technique and the PTV margin were adequate to compensate for inter- and intra-breath-hold variations in liver position.

CONCLUSION

We designed and clinically applied a technique for the treatment of liver cancer with proton pencil beam scanning in forced deep expiration breath-hold. The initial data on plan robustness and patient positioning suggest that the choices in terms of planning technique and treatment margins are able to reach the desired balance between target coverage and organ at risk sparing.

Proton or photon radiosurgery for cardiac ablation of ventricular tachycardia? Breath and ECG gated robust optimization

PURPOSE

Ventricular tachycardia (VT) is a life-threatening heart disorder. The aim of this preliminary study is to assess the feasibility of stereotactic body radiation therapy (SBRT) photon and proton therapy (PT) plans for the treatment of VT, adopting robust optimization technique for both irradiation techniques.

METHODS

ECG gated CT images (in breath hold) were acquired for one patient. Conventional planning target volume (PTV) and robust optimized plans (25GyE in single fraction) were simulated for both photon (IMRT, 5 and 9 beams) and proton (SFO, 2 beams) plans. Robust optimized plans were obtained both for protons and photons considering in the optimization setup errors (5 mm in the three orthogonal directions), range (±3.5%) and the clinical target volume (CTV) motion due to heartbeat and breath-hold variability.

RESULTS

The photon robust optimization method, compared to PTV-based plans, showed a reduction in the average dose to the heart by about 25%; robust optimization allowed also reducing the mean dose to the left lung from 3.4. to 2.8 Gy for 9-beams configuration and from 4.1 to 2.9 Gy for 5-beams configuration. Robust optimization with protons, allowed further reducing the OAR doses: average dose to the heart and to the left lung decreased from 7.3 Gy to 5.2 GyE and from 2.9 Gy to 2.2 GyE, respectively.

CONCLUSIONS

Our study demonstrates the importance of the optimization technique adopted in the treatment planning system for VT treatment. It has been shown that robust optimization can significantly reduce the dose to healthy cardiac tissues and that PT further increases this gain.

Clinical results of active scanning proton therapy for primary liver tumors

BACKGROUND

Evidence for the efficacy of radiation therapy for primary liver cancer is growing. In this context, proton therapy (PT) can potentially improve the therapeutic ratio, as demonstrated by recent clinical studies. Here we report the first European clinical experience on the use of PT for primary liver cancer.

METHODS

All patients treated for primary liver cancer in our center entered the analysis. Patients were simulated during deep expiration breath-hold. A 15-fraction treatment schedule was adopted using active scanning PT. Clinical outcome and toxicity were retrospectively analyzed.

RESULTS

Between January 2018 and December 2019, 18 patients were treated. Fourteen patients had hepatocellular carcinoma (HCC), three patients had intrahepatic cholangiocarcinoma (ICC), and one patient had synchronous ICC-HCC. The Child-Pugh score was A5 in the majority of patients with HCC (71.4%). Median prescription dose was 58.05 Gy (range, 50.31-67.5). Median follow-up was 10 months (range, 1-19). The majority of deaths occurred from liver tumor progression. One-year overall survival (OS) was 63%. A significant correlation between worse OS and patient performance status, vascular invasion, and tumor stage was recorded. One-year local control was 90%. Toxicity was low, with a decrease in Child-Pugh score ⩾2 points detected in one patient. No cases of classic radiation-induced liver disease occurred.

CONCLUSIONS

Our initial results of active scanning PT for primary liver cancer demonstrated the feasibility, safety, and effectiveness of this advanced technique in this setting. The potential of the combination of PT with other locoregional therapies is under evaluation.

Clinical implementation in proton therapy of multi-field optimization by a hybrid method combining conventional PTV with robust optimization

To implement a robust multi-field optimization (MFO) technique compatible with the application of a Monte Carlo (MC) algorithm and to evaluate its robustness. Nine patients (three brain, five head-and-neck, one spine) underwent proton treatment generated by a novel robust MFO technique. A hybrid (hMFO) approach was implemented, planning dose coverage on isotropic PTV compensating for setup errors, whereas range calibration uncertainties are incorporated into PTV robust optimization process. hMFO was compared with single-field optimization (SFO) and full robust multi-field optimization (fMFO), both on the nominal plan and the worst-case scenarios assessed by robustness analysis. The SFO and the fMFO plans were normalized to hMFO on CTV to obtain iso-D95 coverage, and then the organs at risk (OARs) doses were compared. On the same OARs, in the normalized nominal plans the potential impact of variable relative biological effectiveness (RBE) was investigated. hMFO reduces the number of scenarios computed for robust optimization (from twenty-one in fMFO to three), making it practicable with the application of a MC algorithm. After normalizing on D95 CTV coverage, nominal hMFO plans were superior compared to SFO in terms of OARs sparing (p   <  0.01), without significant differences compared to fMFO. The improvement in OAR sparing with hMFO with respect to SFO was preserved in worst-case scenarios (p   <  0.01), confirming that hMFO is as robust as SFO to physical uncertainties, with no significant differences when compared to the worst case scenarios obtained by fMFO. The dose increase on OARs due to variable RBE was comparable to the increase due to physical uncertainties (i.e. 4-5 Gy(RBE)), but without significant differences between these techniques. hMFO allows improving plan quality with respect to SFO, with no significant differences with fMFO and without affecting robustness to setup, range and RBE uncertainties, making clinically feasible the application of MC-based robust optimization.

Improve the dosimetric outcome in bilateral head and neck cancer (HNC) treatment using spot-scanning proton arc (SPArc) therapy: a feasibility study

BACKGROUND

To explore the dosimetric improvement, delivery efficiency, and plan robustness for bilateral head and neck cancer (HNC) treatment utilizing a novel proton therapy technique - the spot-scanning proton arc (SPArc) therapy.

METHODS

We evaluated fourteen bilateral HNC patients retrospectively. Both SPArc and 3-field Intensity Modulated Proton Therapy (IMPT) plans were generated for each patient using the same robust optimization parameters. The prescription doses were 70Gy (relative biological effectiveness (RBE) for CTV_high and 60Gy[RBE] for CTV_low. Clinically significant dosimetric parameters were extracted and compared. Root-mean-square deviation dose (RMSDs) Volume Histogram(RVH) was used to evaluate the plan robustness. Total treatment delivery time was estimated based on the machine parameters.

RESULTS

The SPArc plan was able to provide equivalent or better robust target coverage while showed significant dosimetric improvements over IMPT in most of the organs at risk (OARs). More specifically, it reduced the mean dose of the ipsilateral parotid, contralateral parotid, and oral cavity by 25.8%(p = 0.001), 20.8%(p = 0.001) and 20.3%(p = 0.001) respectively compared to IMPT. This technique reduced D1 (the maximum dose covering 1% volume of a structure) of cord and brain stem by 20.8% (p = 0.009) and 10.7% (p = 0.048), respectively. SPArc also reduced the average integral dose by 17.2%(p = 0.001) and external V3Gy (the volume received 3Gy[RBE]) by 8.3%(p = 0.008) as well. RVH analysis showed that the SPArc plans reduced the dose uncertainties in most OARs compared to IMPT, such as cord: 1.1 ± 0.4Gy[RBE] vs 0.7 ± 0.3Gy[RBE](p = 0.001), brain stem: 0.9 ± 0.7Gy[RBE] vs 0.7 ± 0.7Gy[RBE](p = 0.019), contralateral parotid: 2.5 ± 0.5Gy[RBE] vs 2.2 ± 0.6Gy[RBE](p = 0.022) and ipsilateral parotid: 3.1 ± 0.7Gy[RBE] vs 2.8 ± 0.6Gy[RBE](p = 0.004) respectively. The average total estimated treatment delivery time were 283.4 ± 56.2 s, 469.2 ± 62.0 s and 1294.9 ± 106.7 s based on energy-layer-switching-time (ELST) of 0.1 s, 1 s, and 5 s respectively for SPArc plans, compared to the respective values of 328.0 ± 47.6 s(p = 0.002), 434.1 ± 52.0 s(p = 0.002), and 901.7 ± 74.8 s(p = 0.001) for 3-field IMPT plans. The potential clinical benefit of utilizing SPArc will lead to a decrease in the mean probability of salivary flow dysfunction by 31.3%(p = 0.001) compared with IMPT.

CONCLUSIONS

SPArc could significantly spare OARs while providing a similar or better robust target coverage compared with IMPT in the treatment of bilateral HNC. In the modern proton system with ELST less than 0.5 s, SPArc could potentially be implemented in the routine clinic with a practical, achievable treatment delivery efficiency.

Accurate proton treatment planning for pencil beam crossing titanium fixation implants

PURPOSE

To present a planning strategy for proton pencil-beam scanning when titanium implants need to be crossed by the beam.

METHODS

We addressed three issues: the implementation of a CT calibration curve to assign to titanium the correct stopping power; the effect of artefacts on CT images and their reduction by a dedicated algorithm; the differences in dose computation depending on the dose engine, pencil-beam vs Monte-Carlo algorithms. We performed measurement tests on a simple cylinder phantom and on a real implant. These phantoms were irradiated with three geometries (single spots, uniform mono-energetic layer and uniform box), measuring the exit dose either by radio-chromic film or multi-layer ionization chamber. The procedure was then applied on two patients treated for chordoma.

RESULTS

We had to set in the calibration curve a mass density equal to 4.37 g/cm³ to saturated Hounsfield Units, in order to have the correct stopping power assigned to titanium in TPS. CT artefact reduction algorithm allowed a better reconstruction of the shape and size of the implant. Monte-Carlo resulted accurate in computing the dose distribution whereas the pencil-beam algorithm failed due to sharp density interfaces between titanium and the surrounding material. Finally, the treatment plans obtained on two patients showed the impact of the dose engine algorithm, with 10-20% differences between pencil-beam and Monte-Carlo in small regions distally to the titanium screws.

CONCLUSION

The described combination of CT calibration, artefacts reduction and Monte-Carlo computation provides a reliable methodology to compute dose in patients with titanium implants.