The model-based approach to clinical studies in particle radiotherapy – A new concept in evidence based radiation oncology?

A novel stochastic optimization method for handling misalignments of proton and photon doses in combined treatments

Objective. Combined proton–photon treatments, where most fractions are delivered with photons and only a few are delivered with protons, may represent a practical approach to optimally use limited proton resources. It has been shown that, when organs at risk (OARs) are located within or near the tumor, the optimal multi-modality treatment uses protons to hypofractionate parts of the target volume and photons to achieve near-uniform fractionation in dose-limiting healthy tissues, thus exploiting the fractionation effect. These plans may be sensitive to range and setup errors, especially misalignments between proton and photon doses. Thus, we developed a novel stochastic optimization method to directly incorporate these uncertainties into the biologically effective dose (BED)-based simultaneous optimization of proton and photon plans. Approach. The method considers the expected value E b and standard deviation σ b of the cumulative BED b in every voxel of a structure. For the target, a piecewise quadratic penalty function of the form b min − E b − 2 σ b + 2 is minimized, aiming for plans in which the expected BED minus two times the standard deviation exceeds the prescribed BED b min . Analogously, E b + 2 σ b − b max + 2 is considered for OARs. Main results. Using a spinal metastasis case and a liver cancer patient, it is demonstrated that the novel stochastic optimization method yields robust combined treatment plans. Tumor coverage and a good sparing of the main OARs are maintained despite range and setup errors, and especially misalignments between proton and photon doses. This is achieved without explicitly considering all combinations of proton and photon error scenarios. Significance. Concerns about range and setup errors for safe clinical implementation of optimized proton–photon radiotherapy can be addressed through an appropriate stochastic planning method.

Consolidative active scanning proton therapy for mediastinal lymphoma: selection criteria, treatment implementation and clinical feasibility

AIMS

Proton therapy (PT) represents an advanced form of radiotherapy with unique physical properties which could be of great advantage in reducing long-term radiation morbidity for cancer survivors. Here, we aim to describe the whole process leading to the clinical implementation of consolidative active scanning proton therapy treatment (PT) for mediastinal lymphoma.

METHODS

The process included administrative, technical and clinical issues. Authorization of PT is required in all cases as mediastinal lymphoma is currently not on the list of diseases reimbursable by the Italian National Health Service. Technically, active scanning PT treatment for mediastinal lymphoma is complex, due to the interaction between actively scanned protons and the usually irregular and large volumes to be irradiated, the nearby healthy tissues and the target motion caused by breathing. A road map to implement the technical procedures was prepared. The clinical selection of patients was of utmost importance and took into account both patient and tumor characteristics.

RESULTS

The first mediastinal lymphoma was treated at our PT center in 2018, four years after the start of the clinical activities. The treatment technique implementation included mechanical deep inspiration breath-hold simulation computed tomography (CT), clinical target volume (CTV)-based multifield optimization planning and plan robustness analysis. The ultimate authorization rate was 93%. In 4 cases a proton-photon plan comparison was required. Between May 2018 and February, 2021, 14 patients were treated with consolidative PT. The main clinical reasons for choosing PT over photons was a bulky disease in 8 patients (57%), patient's age in 11 patients (78%) and the proximity of the lymphoma to cardiac structures in 10 patients (71%). With a median follow-up of 15 months (range, 1-33 months) all patients but one (out-of-field relapse) are without evidence of disease, all are alive and no late toxicities were observed during the follow-up period.

CONCLUSIONS

The clinical implementation of consolidative active scanning PT for mediastinal lymphoma required specific technical procedures and a prolonged experience with PT treatments. An accurate selection of patients for which PT could be of advantage in comparison with photons is mandatory.

Optimal Allocation of Proton Therapy Slots in Combined Proton-Photon Radiation Therapy

PURPOSE

Proton therapy is a limited resource that is not available to all patients who may benefit from it. We investigated combined proton-photon treatments, in which some fractions are delivered with protons and the remaining fractions with photons, as an approach to maximize the benefit of limited proton therapy resources at a population level.

METHODS AND MATERIALS

To quantify differences in normal-tissue complication probability (NTCP) between protons and photons, we considered a cohort of 45 patients with head and neck cancer for whom intensity modulated radiation therapy and intensity modulated proton therapy plans were previously created, in combination with NTCP models for xerostomia and dysphagia considered in the Netherlands for proton patient selection. Assuming limited availability of proton slots, we developed methods to optimally assign proton fractions in combined proton-photon treatments to minimize the average NTCP on a population level. The combined treatments were compared with patient selection strategies in which patients are assigned to single-modality proton or photon treatments.

RESULTS

There is a benefit of combined proton-photon treatments compared with patient selection, owing to the nonlinearity of NTCP functions; that is, the initial proton fractions are the most beneficial, whereas additional proton fractions have a decreasing benefit when a flatter part of the NTCP curve is reached. This effect was small for the patient cohort and NTCP models considered, but it may be larger if dose-response relationships are better known. In addition, when proton slots are limited, patient selection methods face a trade-off between leaving slots unused and blocking slots for future patients who may have a larger benefit. Combined proton-photon treatments with flexible proton slot assignment provide a method to make optimal use of all available resources.

CONCLUSIONS

Combined proton-photon treatments allow for better use of limited proton therapy resources. The benefit over patient selection schemes depends on the NTCP models and the dose differences between protons and photons.

Assessment of the confidence interval in the multivariable normal tissue complication probability model for predicting radiation-induced liver disease in primary liver cancer

We developed a confidence interval-(CI) assessing model in multivariable normal tissue complication probability (NTCP) modeling for predicting radiation-induced liver disease (RILD) in primary liver cancer patients using clinical and dosimetric data. Both the mean NTCP and difference in the mean NTCP (ΔNTCP) between two treatment plans of different radiotherapy modalities were further evaluated and their CIs were assessed. Clinical data were retrospectively reviewed in 322 patients with hepatocellular carcinoma (n = 215) and intrahepatic cholangiocarcinoma (n = 107) treated with photon therapy. Dose-volume histograms of normal liver were reduced to mean liver dose (MLD) based on the fraction size-adjusted equivalent uniform dose. The most predictive variables were used to build the model based on multivariable logistic regression analysis with bootstrapping. Internal validation was performed using the cross-validation leave-one-out method. Both the mean NTCP and the mean ΔNTCP with 95% CIs were calculated from computationally generated multivariate random sets of NTCP model parameters using variance-covariance matrix information. RILD occurred in 108/322 patients (33.5%). The NTCP model with three clinical and one dosimetric parameter (tumor type, Child-Pugh class, hepatitis infection status and MLD) was most predictive, with an area under the receiver operative characteristics curve (AUC) of 0.79 (95% CI 0.74-0.84). In eight clinical subgroups based on the three clinical parameters, both the mean NTCP and the mean ΔNTCP with 95% CIs were able to be estimated computationally. The multivariable NTCP model with the assessment of 95% CIs has potential to improve the reliability of the NTCP model-based approach to select the appropriate radiotherapy modality for each patient.

Clinical practice vs. state-of-the-art research and future visions: Report on the 4D treatment planning workshop for particle therapy - Edition 2018 and 2019

The 4D Treatment Planning Workshop for Particle Therapy, a workshop dedicated to the treatment of moving targets with scanned particle beams, started in 2009 and since then has been organized annually. The mission of the workshop is to create an informal ground for clinical medical physicists, medical physics researchers and medical doctors interested in the development of the 4D technology, protocols and their translation into clinical practice. The 10th and 11th editions of the workshop took place in Sapporo, Japan in 2018 and Krakow, Poland in 2019, respectively. This review report from the Sapporo and Krakow workshops is structured in two parts, according to the workshop programs. The first part comprises clinicians and physicists review of the status of 4D clinical implementations. Corresponding talks were given by speakers from five centers around the world: Maastro Clinic (The Netherlands), University Medical Center Groningen (The Netherlands), MD Anderson Cancer Center (United States), University of Pennsylvania (United States) and The Proton Beam Therapy Center of Hokkaido University Hospital (Japan). The second part is dedicated to novelties in 4D research, i.e. motion modelling, artificial intelligence and new technologies which are currently being investigated in the radiotherapy field.

Integrating Mathematical Modeling into the Roadmap for Personalized Adaptive Radiation Therapy

In current radiation oncology practice, treatment protocols are prescribed based on the average outcomes of large clinical trials, with limited personalization and without adaptations of dose or dose fractionation to individual patients based on their individual clinical responses. Predicting tumor responses to radiation and comparing predictions against observed responses offers an opportunity for novel treatment evaluation. These analyses can lead to protocol adaptation aimed at the improvement of patient outcomes with better therapeutic ratios. We foresee the integration of mathematical models into radiation oncology to simulate individual patient tumor growth and predict treatment response as dynamic biomarkers for personalized adaptive radiation therapy (RT).

What Conditions Make Proton Beam Therapy Financially Viable in Western Canada?

Background

Proton beam therapy (PBT) is available in many western and Asian countries, but there is no clinical, gantry-based PBT facility in Canada.

Methods

A cost analysis was conducted from the Alberta Ministry of Health perspective with a 15-year horizon. Estimated costs were: PBT unit, facility development as part of an ongoing capital project, electricity, maintenance contract, and staffing. Revenues were: savings from stopping USA referrals, avoiding the costs of standard radiation therapy (RT) for Albertans receiving PBT instead, and cost-recovery charges for out-of-province patients.

Results

The Ministry of Health funded 15 Albertans for PBT in the USA in the 2014/15 fiscal year (mean CAD$ 237,348/patient). A single-vault, compact PBT unit operating 10 hours/day could treat 250 patients annually. A 100 Albertans, with accepted indications, such as the curative-intent treatment of chordomas, ocular melanomas, and selected pediatric cancers, would likely benefit annually from PBT’s improved conformality and/or reduced integral dose compared to RT. The estimated capital cost was $40 million for a single beamline built within an ongoing capital project. Operating costs were $4.8 million/year at capacity. With 50% capacity reserved for non-Albertans at a cost recovery of $45,000/patient, a Western Canadian PBT facility would achieve net positive cash flow by year eight of clinical operations, assuming Alberta-to-USA referrals reach 21 patients/year by 2024 and increase at 3%/year thereafter. Sensitivity analysis indicates the lifetime net savings is robust to the assumptions made.

Conclusion

This business case, based on Canadian costing data and estimates, demonstrates the potential for a financially viable PBT facility in Western Canada.

"Radiobiology of Proton Therapy": Results of an international expert workshop

The physical properties of proton beams offer the potential to reduce toxicity in tumor-adjacent normal tissues. Toward this end, the number of proton radiotherapy facilities has steeply increased over the last 10-15 years to currently around 70 operational centers worldwide. However, taking full advantage of the opportunities offered by proton radiation for clinical radiotherapy requires a better understanding of the radiobiological effects of protons alone or combined with drugs or immunotherapy on normal tissues and tumors. This report summarizes the main results of the international expert workshop "Radiobiology of Proton Therapy" that was held in November 2016 in Dresden. It addresses the major topics (1) relative biological effectiveness (RBE) in proton beam therapy, (2) interaction of proton radiobiology with radiation physics in current treatment planning, (3) biological effects in proton therapy combined with systemic treatments, and (4) testing biological effects of protons in clinical trials. Finally, important research avenues for improvement of proton radiotherapy based on radiobiological knowledge are identified. The clinical distribution of radiobiological effectiveness of protons alone or in combination with systemic chemo- or immunotherapies as well as patient stratification based on biomarker expressions are key to reach the full potential of proton beam therapy. Dedicated preclinical experiments, innovative clinical trial designs, and large high-quality data repositories will be most important to achieve this goal.

Mathematical Modelling for Patient Selection in Proton Therapy

Proton beam therapy (PBT) is still relatively new in cancer treatment and the clinical evidence base is relatively sparse. Mathematical modelling offers assistance when selecting patients for PBT and predicting the demand for service. Discrete event simulation, normal tissue complication probability, quality-adjusted life-years and Markov Chain models are all mathematical and statistical modelling techniques currently used but none is dominant. As new evidence and outcome data become available from PBT, comprehensive models will emerge that are less dependent on the specific technologies of radiotherapy planning and delivery.

Proton therapy in paediatric oncology: an Irish perspective

BACKGROUND

Proton therapy (PT) is a radiotherapy treatment modality that uses protons, rather than conventional photons. PT is often used in paediatric oncology due to its reported capability to reduce acute and late adverse treatment effects. As PT is unavailable in Ireland, patients are referred abroad for treatment.

AIMS

To: (1) produce a descriptive study of Irish children referred abroad for PT, and (2) discuss the case for PT in general.

METHODS

A retrospective review of all children referred for PT before October 2015 was performed. Information was gathered regarding demographics, diagnosis, referral timeline, adverse effects attributable to PT, current status and cost. A review of the relevant literature was performed.

RESULTS

Seventeen children treated in Ireland have been referred abroad for PT. The largest number was in the 0-4 year old group. At initial diagnosis the median age was 4.8 years. The average cost per child was €37,312. Two patients suffered disease relapse. Four have encountered PT-related adverse effects.

CONCLUSION

Despite the fact that >100,000 patients worldwide have been treated with PT, the level of published evidence to support superiority over conventional treatment remains low. It is debated that randomised control trials in this area would be inconsistent with the principle of clinical equipoise. In contrast, there is a call for level 1 evidence to justify drastic changes in patient care, particularly in light of recent reports of unexpected toxicities. In time, careful evaluation, follow-up and clinical trials will likely support the preferential use of PT in children.

Development and evaluation of an online three-level proton vs photon decision support prototype for head and neck cancer - Comparison of dose, toxicity and cost-effectiveness

To quantitatively assess the effectiveness of proton therapy for individual patients, we developed a prototype for an online platform for proton decision support (PRODECIS) comparing photon and proton treatments on dose metric, toxicity and cost-effectiveness levels. An evaluation was performed with 23 head and neck cancer datasets.

A simulation study on proton computed tomography (CT) stopping power accuracy using dual energy CT scans as benchmark

BACKGROUND

Accurate stopping power estimation is crucial for treatment planning in proton therapy, and the uncertainties in stopping power are currently the largest contributor to the employed dose margins. Dual energy x-ray computed tomography (CT) (clinically available) and proton CT (in development) have both been proposed as methods for obtaining patient stopping power maps. The purpose of this work was to assess the accuracy of proton CT using dual energy CT scans of phantoms to establish reference accuracy levels.

MATERIAL AND METHODS

A CT calibration phantom and an abdomen cross section phantom containing inserts were scanned with dual energy and single energy CT with a state-of-the-art dual energy CT scanner. Proton CT scans were simulated using Monte Carlo methods. The simulations followed the setup used in current prototype proton CT scanners and included realistic modeling of detectors and the corresponding noise characteristics. Stopping power maps were calculated for all three scans, and compared with the ground truth stopping power from the phantoms.

RESULTS

Proton CT gave slightly better stopping power estimates than the dual energy CT method, with root mean square errors of 0.2% and 0.5% (for each phantom) compared to 0.5% and 0.9%. Single energy CT root mean square errors were 2.7% and 1.6%. Maximal errors for proton, dual energy and single energy CT were 0.51%, 1.7% and 7.4%, respectively.

CONCLUSION

Better stopping power estimates could significantly reduce the range errors in proton therapy, but requires a large improvement in current methods which may be achievable with proton CT.

Concept for individualized patient allocation: ReCompare--remote comparison of particle and photon treatment plans

Background

Identifying those patients who have a higher chance to be cured with fewer side effects by particle beam therapy than by state-of-the-art photon therapy is essential to guarantee a fair and sufficient access to specialized radiotherapy. The individualized identification requires initiatives by particle as well as non-particle radiotherapy centers to form networks, to establish procedures for the decision process, and to implement means for the remote exchange of relevant patient information. In this work, we want to contribute a practical concept that addresses these requirements.

Methods

We proposed a concept for individualized patient allocation to photon or particle beam therapy at a non-particle radiotherapy institution that bases on remote treatment plan comparison. We translated this concept into the web-based software tool ReCompare (REmote COMparison of PARticlE and photon treatment plans).

Results

We substantiated the feasibility of the proposed concept by demonstrating remote exchange of treatment plans between radiotherapy institutions and the direct comparison of photon and particle treatment plans in photon treatment planning systems. ReCompare worked with several tested standard treatment planning systems, ensured patient data protection, and integrated in the clinical workflow.

Conclusions

Our concept supports non-particle radiotherapy institutions with the patient-specific treatment decision on the optimal irradiation modality by providing expertise from a particle therapy center. The software tool ReCompare may help to improve and standardize this personalized treatment decision. It will be available from our website when proton therapy is operational at our facility.