First experience with model-based selection of head and neck cancer patients for proton therapy

Particle arc therapy: Status and potential

There is a rising interest in developing and utilizing arc delivery techniques with charged particle beams, e.g., proton, carbon or other ions, for clinical implementation. In this work, perspectives from the European Society for Radiotherapy and Oncology (ESTRO) 2022 physics workshop on particle arc therapy are reported. This outlook provides an outline and prospective vision for the path forward to clinically deliverable proton, carbon, and other ion arc treatments. Through the collaboration among industry, academic, and clinical research and development, the scientific landscape and outlook for particle arc therapy are presented here to help our community understand the physics, radiobiology, and clinical principles. The work is presented in three main sections: (i) treatment planning, (ii) treatment delivery, and (iii) clinical outlook.

A probabilistic evaluation of the Dutch robustness and model-based selection protocols for Head-and-Neck IMPT: A multi-institutional study

BACKGROUND AND PURPOSE

In the Netherlands, 2 protocols have been standardized for PT among the 3 proton centers: a robustness evaluation (RE) to ensure adequate CTV dose and a model-based selection (MBS) approach for IMPT patient-selection. This multi-institutional study investigates (i) inter-patient and inter-center variation of target dose from the RE protocol and (ii) the robustness of the MBS protocol against treatment errors for a cohort of head-and-neck cancer (HNC) patients treated in the 3 Dutch proton centers.

MATERIALS AND METHODS

Clinical treatment plans of 100 HNC patients were evaluated. Polynomial Chaos Expansion (PCE) was used to perform a comprehensive robustness evaluation per plan, enabling the probabilistic evaluation of 100,000 complete fractionated treatments. PCE allowed to derive scenario distributions of clinically relevant dosimetric parameters to assess CTV dose (D99.8%/D0.2%, based on a prior photon plan calibration) and tumour control probabilities (TCP) as well as the evaluation of the dose to OARs and normal tissue complication probabilities (NTCP) per center.

RESULTS

For the CTV70.00, doses from the RE protocol were consistent with the clinical plan evaluation metrics used in the 3 centers. For the CTV54.25, D99.8% were consistent with the clinical plan evaluation metrics at center 1 and 2 while, for center 3, a reduction of 1 GyRBE was found on average. This difference did not impact modelled TCP at center 3. Differences between expected and nominal NTCP were below 0.3 percentage point for most patients.

CONCLUSION

The standardization of the RE and MBS protocol lead to comparable results in terms of TCP and the NTCPs. Still, significant inter-patient and inter-center variation in dosimetric parameters remained due to clinical practice differences at each institution. The MBS approach is a robust protocol to qualify patients for PT.

Dosimetric and NTCP analyses for selecting parotid gland cancer patients for proton therapy

PURPOSE/OBJECTIVE

To perform a dosimetric and a normal tissue complication probability (NTCP) comparison between intensity modulated proton therapy and photon volumetric modulated arc therapy in a cohort of patients with parotid gland cancers in a post-operative or radical setting.

MATERIALS AND METHODS

From May 2011 to September 2021, 37 parotid gland cancers patients treated at two institutions were eligible. Inclusion criteria were as follows: patients aged ⩾ 18 years, diagnosis of parotid gland cancers candidate for postoperative radiotherapy or definitive radiotherapy, presence of written informed consent for the use of anonymous data for research purposes. Organs at risk (OARs) were retrospectively contoured. Target coverage goal was defined as D95 > 98%. Six NTCP models were selected. NTCP profiles were calculated for each patient using an internally-developed Python script in RayStation TPS. Average differences in NTCP between photon and proton plans were tested for significance with a two-sided Wilcoxon signed-rank test.

RESULTS

Seventy-four plans were generated. A lower Dmean to the majority of organs at risk (inner ear, cochlea, oral cavity, pharyngeal constrictor muscles, contralateral parotid and submandibular gland) was obtained with intensity modulated proton therapy vs volumetric modulated arc therapy with statistical significance (p < .05). Ten (27%) patients had a difference in NTCP (photon vs proton plans) greater than 10% for hearing loss and tinnitus: among them, seven qualified for both endpoints, two patients for hearing loss only, and one for tinnitus.

CONCLUSIONS

In the current study, nearly one-third of patients resulted eligible for proton therapy and they were the most likely to benefit in terms of prevention of hearing loss and tinnitus.

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.

Evaluation of an automated clinical decision system with deep learning dose prediction and NTCP model for prostate cancer proton therapy

Objective.To evaluate the feasibility of using a deep learning dose prediction approach to identify patients who could benefit most from proton therapy based on the normal tissue complication probability (NTCP) model.Approach.Two 3D UNets were established to predict photon and proton doses. A dataset of 95 patients with localized prostate cancer was randomly partitioned into 55, 10, and 30 for training, validation, and testing, respectively. We selected NTCP models for late rectum bleeding and acute urinary urgency of grade 2 or higher to quantify the benefit of proton therapy. Propagated uncertainties of predicted ΔNTCPs resulting from the dose prediction errors were calculated. Patient selection accuracies for a single endpoint and a composite evaluation were assessed under different ΔNTCP thresholds.Main results.Our deep learning-based dose prediction technique can reduce the time spent on plan comparison from approximately 2 days to as little as 5 seconds. The expanded uncertainty of predicted ΔNTCPs for rectum and bladder endpoints propagated from the dose prediction error were 0.0042 and 0.0016, respectively, which is less than one-third of the acceptable tolerance. The averaged selection accuracies for rectum bleeding, urinary urgency, and composite evaluation were 90%, 93.5%, and 93.5%, respectively.Significance.Our study demonstrates that deep learning dose prediction and NTCP evaluation scheme could distinguish the NTCP differences between photon and proton treatment modalities. In addition, the dose prediction uncertainty does not significantly influence the decision accuracy of NTCP-based patient selection for proton therapy. Therefore, automated deep learning dose prediction and NTCP evaluation schemes can potentially be used to screen large patient populations and to avoid unnecessary delays in the start of prostate cancer radiotherapy in the future.

Toxicity profile of patients treated with proton and carbon-ion therapy for primary nasopharyngeal carcinoma: A systematic review and meta-analysis

BACKGROUND

Proton and carbon-ion therapy may spare normal tissues in regions with many critical structures surrounding the target volume. As toxicity outcome data are emerging, we aimed to synthesize the published data for the toxicity outcomes of proton or carbon-ion therapy (together known as particle beam therapy [PBT]) for primary nasopharyngeal carcinoma (NPC).

MATERIALS AND METHODS

We searched PubMed and Scopus electronic databases to identify original studies reporting toxicity outcomes following PBT of primary NPC. Quality assessment was performed using NIH's Quality Assessment Tool. Reports were extracted for information on demographics, main results, and clinical and dose factors correlates. Meta-analysis was performed using the random-effects model.

RESULTS

Twelve studies were selected (six using mixed particle-photon beams, five performed comparisons to photon-based therapy). The pooled event rates for acute grade ≥2 toxicities mucositis, dermatitis, xerostomia weight loss are 46% (95% confidence interval [95% CI]-29%-64%, I2 = 87%), 47% (95% CI-28%-67%, I2 = 87%), 16% (95% CI-9%-29%, I2 = 76%), and 36% (95% CI-27%-47%, I2 = 45%), respectively. Only one late endpoint (xerostomia grade ≥2) has sufficient data for analysis with pooled event rate of 9% (95% CI-3%-29%, I2 = 77%), lower than intensity-modulated radiotherapy 27% (95% CI-10%-54%, I2 = 95%). For most endpoints with significant differences between the PBT and photon-based therapies, PBT resulted in better outcomes. In two studies where dose distribution was studied, doses to the organs at risk were independent risk factors for toxicities.

CONCLUSION

PBT may reduce the risk of acute toxicities for patients treated for primary NPC, likely due to dose reduction to critical structures. The pooled event rate for toxicities derived in this study can be a guide for patient counseling.

Essentially unedited deep-learning-based OARs are suitable for rigorous oropharyngeal and laryngeal cancer treatment planning

Quality of organ at risk (OAR) autosegmentation is often judged by concordance metrics against the human-generated gold standard. However, the ultimate goal is the ability to use unedited autosegmented OARs in treatment planning, while maintaining the plan quality. We tested this approach with head and neck (HN) OARs generated by a prototype deep-learning (DL) model on patients previously treated for oropharyngeal and laryngeal cancer. Forty patients were selected, with all structures delineated by an experienced physician. For each patient, a set of 13 OARs were generated by the DL model. Each patient was re-planned based on original targets and unedited DL-produced OARs. The new dose distributions were then applied back to the manually delineated structures. The target coverage was evaluated with inhomogeneity index (II) and the relative volume of regret. For the OARs, Dice similarity coefficient (DSC) of areas under the DVH curves, individual DVH objectives, and composite continuous plan quality metric (PQM) were compared. The nearly identical primary target coverage for the original and re-generated plans was achieved, with the same II and relative volume of regret values. The average DSC of the areas under the corresponding pairs of DVH curves was 0.97 ± 0.06. The number of critical DVH points which met the clinical objectives with the dose optimized on autosegmented structures but failed when evaluated on the manual ones was 5 of 896 (0.6%). The average OAR PQM score with the re-planned dose distributions was essentially the same when evaluated either on the autosegmented or manual OARs. Thus, rigorous HN treatment planning is possible with OARs segmented by a prototype DL algorithm with minimal, if any, manual editing.

Material decomposition maps based calibration of dual energy CT scanners for proton therapy planning: a phantom study

We introduce a new calibration method for dual energy CT (DECT) based on material decomposition (MD) maps, specifically iodine and water MD maps. The aim of this method is to provide the first DECT calibration based on MD maps. The experiments were carried out using a general electric (GE) revolution CT scanner with ultra-fast kV switching and used a density phantom by GAMMEX for calibration and evaluation. The calibration process involves several steps. First, we tested the ability of MD values to reproduce Hounsfield unit (HU) values of single energy CT (SECT) acquisitions and it was found that the errors were below 1%, validating their use for HU reproduction. Next, the different definitions of computedZvalues were compared and the robustness of the approach based on the materials' composition was confirmed. Finally, the calibration method was compared with a previous method by Bourqueet al, providing a similar level of accuracy and superior performance in terms of precision. Overall, this novel DECT calibration method offers improved accuracy and reliability in determining tissue-specific physical properties. The resulting maps can be valuable for proton therapy treatments, where precise dose calculations and accurate tissue differentiation are crucial for optimal treatment planning and delivery.

Quality of Decision Making in Radiation Oncology

High-quality decision making in radiation oncology requires the careful consideration of multiple factors. In addition to the evidence-based indications for curative or palliative radiotherapy, this article explores how, in routine clinical practice, we also need to account for many other factors when making high-quality decisions. Foremost are patient-related factors, including preference, and the complex interplay between age, frailty and comorbidities, especially with an ageing cancer population. Whilst clinical practice guidelines inform our decisions, we need to account for their applicability in different patient groups and different resource settings. With particular reference to curative-intent radiotherapy, we explore decisions regarding dose fractionation schedules, use of newer radiotherapy technologies and multimodality treatment considerations that contribute to personalised patient-centred care.

Treatment planning comparison for head and neck cancer between photon, proton, and combined proton-photon therapy - From a fixed beam line to an arc

BACKGROUND AND PURPOSE

This study investigates whether combined proton-photon therapy (CPPT) improves treatment plan quality compared to single-modality intensity-modulated radiation therapy (IMRT) or intensity-modulated proton therapy (IMPT) for head and neck cancer (HNC) patients. Different proton beam arrangements for CPPT and IMPT are compared, which could be of specific interest concerning potential future upright-positioned treatments. Furthermore, it is evaluated if CPPT benefits remain under inter-fractional anatomical changes for HNC treatments.

MATERIAL AND METHODS

Five HNC patients with a planning CT and multiple (4-7) repeated CTs were studied. CPPT with simultaneously optimized photon and proton fluence, single-modality IMPT, and IMRT treatment plans were optimized on the planning CT and then recalculated and reoptimized on each repeated CT. For CPPT and IMPT, plans with different degrees of freedom for the proton beams were optimized. Fixed horizontal proton beam line (FHB), gantry-like, and arc-like plans were compared.

RESULTS

The target coverage for CPPT without adaptation is insufficient (average V95%=88.4 %), while adapted plans can recover the initial treatment plan quality for target (average V95%=95.5 %) and organs-at-risk. CPPT with increased proton beam flexibility increases plan quality and reduces normal tissue complication probability of Xerostomia and Dysphagia. On average, Xerostomia NTCP reductions compared to IMRT are -2.7 %/-3.4 %/-5.0 % for CPPT FHB/CPPT Gantry/CPPT Arc. The differences for IMPT FHB/IMPT Gantry/IMPT Arc are + 0.8 %/-0.9 %/-4.3 %.

CONCLUSION

CPPT for HNC needs adaptive treatments. Increasing proton beam flexibility in CPPT, either by using a gantry or an upright-positioned patient, improves treatment plan quality. However, the photon component is substantially reduced, therefore, the balance between improved plan quality and costs must be further determined.

Proton Therapy in Breast Cancer: A Review of Potential Approaches for Patient Selection

Proton radiotherapy may be a compelling technical option for the treatment of breast cancer due to its unique physical property known as the "Bragg peak." This feature offers distinct advantages, promising superior dose conformity within the tumor area and reduced radiation exposure to surrounding healthy tissues, enhancing the potential for better treatment outcomes. However, proton therapy is accompanied by inherent challenges, primarily higher costs and limited accessibility when compared to well-developed photon irradiation. Thus, in clinical practice, it is important for radiation oncologists to carefully select patients before recommendation of proton therapy to ensure the transformation of dosimetric benefits into tangible clinical benefits. Yet, the optimal indications for proton therapy in breast cancer patients remain uncertain. While there is no widely recognized methodology for patient selection, numerous attempts have been made in this direction. In this review, we intended to present an inspiring summarization and discussion about the current practices and exploration on the approaches of this treatment decision-making process in terms of treatment-related side-effects, tumor control, and cost-efficiency, including the normal tissue complication probability (NTCP) model, the tumor control probability (TCP) model, genomic biomarkers, cost-effectiveness analyses (CEAs), and so on. Additionally, we conducted an evaluation of the eligibility criteria in ongoing randomized controlled trials and analyzed their reference value in patient selection. We evaluated the pros and cons of various potential patient selection approaches and proposed possible directions for further optimization and exploration. In summary, while proton therapy holds significant promise in breast cancer treatment, its integration into clinical practice calls for a thoughtful, evidence-driven strategy. By continuously refining the patient selection criteria, we can harness the full potential of proton radiotherapy while ensuring maximum benefit for breast cancer patients.

Evaluation of decentralised model-based selection of head and neck cancer patients for a proton treatment study. DAHANCA 35

INTRODUCTION

Proton treatment can potentially spare patients with H&N cancer for substantial treatment-related toxicities. The current study investigated the reproducibility of a decentralised model-based selection of patients for a proton treatment study when the selection plans were compared to the clinical treatment plans performed at the proton centre.

METHODS

Sixty-three patients were selected for proton treatment in the six Danish Head and Neck Cancer (DAHANCA) centres. The patients were selected based on normal tissue complication probability (NTCP) estimated from local photon and proton treatment plans, which showed a ΔNTCP greater than 5%-point for either grade 2 + dysphagia or grade 2 + xerostomia at six months. The selection plans were compared to the clinical treatment plans performed at the proton centre.

RESULTS

Of the 63 patients, 49 and 25 were selected based on an estimated benefit in risk of dysphagia and xerostomia, respectively. Eleven patients had a potential gain in both toxicities. The mean ΔNTCP changed from the local selection plan comparison to the clinical comparison from 6.9 to 5.3 %-points (p = 0.01) and 7.3 to 4.9 %-points (p = 0.03) for dysphagia and xerostomia, respectively. Volume differences in both CTV and OAR could add to the loss in ΔNTCP. 61 of the 63 clinical plans had a positive ΔNTCP, and 38 had a ΔNTCP of 5%-points for at least one of the two endpoints.

CONCLUSION

A local treatment plan comparison can be used to select candidates for proton treatment. The local comparative proton plan overestimates the potential benefit of the clinical proton plan. Continuous quality assurance of the delineation procedures and planning is crucial in the subsequent randomised clinical trial setting.

Considerations for study design in the DAHANCA 35 trial of protons versus photons for head and neck cancer

Proton radiotherapy offers a dosimetric advantage compared to photon therapy in sparing normal tissue, but the clinical evidence for toxicity reductions in the treatment of head and neck cancer is limited. The Danish Head and Neck Cancer Group (DAHANCA) has initiated the DAHANCA 35 randomised trial to clarify the value of proton therapy (NCT04607694). The DAHANCA 35 trial is performed in an enriched population of patients selected by an anticipated benefit of proton therapy to reduce the risk of late dysphagia or xerostomia based on normal tissue complication probability (NTCP) modelling. We present our considerations on the trial design and a test of the selection procedure conducted before initiating the randomised study.

Technical note: Evaluation of deep learning based synthetic CTs clinical readiness for dose and NTCP driven head and neck adaptive proton therapy

BACKGROUND

Adaptive proton therapy workflows rely on accurate imaging throughout the treatment course. Our centre currently utilizes weekly repeat CTs (rCTs) for treatment monitoring and plan adaptations. However, deep learning-based methods have recently shown to successfully correct CBCT images, which suffer from severe imaging artifacts, and generate high quality synthetic CT (sCT) images which enable CBCT-based proton dose calculations.

PURPOSE

To compare daily CBCT-based sCT images to planning CTs (pCT) and rCTs of head and neck (HN) cancer patients to investigate the dosimetric accuracy of CBCT-based sCTs in a scenario mimicking actual clinical practice.

METHODS

Data of 56 HN cancer patients, previously treated with proton therapy was used to generate 1.962 sCT images, using a previously developed and trained deep convolutional neural network. Clinical IMPT treatment plans were recalculated on the pCT, weekly rCTs and daily sCTs. The dosimetric accuracy of sCTs was compared to same day rCTs and the initial planning CT. As a reference, rCTs were also compared to pCTs. The dose difference between sCTs and rCTs/pCT was quantified by calculating the D98 difference for target volumes and Dmean difference for organs-at-risk. To investigate the clinical relevancy of possible dose differences, NTCP values were calculated for dysphagia and xerostomia.

RESULTS

For target volumes, only minor dose differences were found for sCT versus rCT and sCT versus pCT, with dose differences mostly within ±1.5%. Larger dose differences were observed in OARs, where a general shift towards positive differences was found, with the largest difference in the left parotid gland. Delta NTCP values for grade 2 dysphagia and xerostomia were within ±2.5% for 90% of the sCTs.

CONCLUSIONS

Target doses showed high similarity between rCTs and sCTs. Further investigations are required to identify the origin of the dose differences at OAR levels and its relevance in clinical decision making.

Dose planning study of proton versus photon radiotherapy for head and neck squamous cell carcinoma of unknown primary in the primary and recurrent setting

BACKGROUND

Patients with head and neck squamous cell carcinoma of unknown primary (HNCUP) are often treated with extensive radiotherapy (RT). Frequently, the bilateral nodal clinical target volume (nCTV) and the volumes of suspected mucosal primary sites (mCTV) of the pharynx and larynx is irradiated. This treatment is effective but toxic. New data suggest that omission of the contralateral nCTV and mCTV, results in few recurrences. The present study explores photon versus proton therapy, in the primary and recurrent setting.

MATERIAL AND METHODS

An analysis of twelve patients previously treated for HNCUP was performed. A fictitious recurrence was defined in patients treated for unilateral disease. Independently a volumetric arc photon plan and an intensity-modulated proton plan was made for all cases and scenarios.

RESULTS

Compared to the standard bilateral treatment this study shows that limiting the target to unilateral nCTV leads to a significant decrease in dysphagia of 18% and 17% and xerostomia of 4.0% and 5% for photon and protons, respectively. Comparing photon RT directly to proton RT shows a small and often insignificant gain, using protons for both bilateral and unilateral targets. Focusing on re-irradiation, benefits from using protons in both the primary setting and at re-irradiation were limited. However, using protons for re-irradiation only leads to a decrease in the tissue volume receiving a specific dose outside the target overlapping region, e.g., V90Gymean was 31, 25, and 22 cm3 for photons-photons, photons-protons, and protons-protons, respectively. For V100Gy of the ipsilateral carotid artery, no differences were observed.

CONCLUSION

Omitting contralateral nCTV irradiation and mCTV irradiation will significantly reduce toxicity. The accumulated high dose volumes can be minimised using protons for re-irradiation. However, the use of protons for primary treatment provides limited benefit in most patients.

Patient selection for proton therapy using Normal Tissue Complication Probability with deep learning dose prediction for oropharyngeal cancer

BACKGROUND

In cancer care, determining the most beneficial treatment technique is a key decision affecting the patient's survival and quality of life. Patient selection for proton therapy (PT) over conventional radiotherapy (XT) currently entails comparing manually generated treatment plans, which requires time and expertise.

PURPOSE

We developed an automatic and fast tool, AI-PROTIPP (Artificial Intelligence Predictive Radiation Oncology Treatment Indication to Photons/Protons), that assesses quantitatively the benefits of each therapeutic option. Our method uses deep learning (DL) models to directly predict the dose distributions for a given patient for both XT and PT. By using models that estimate the Normal Tissue Complication Probability (NTCP), namely the likelihood of side effects to occur for a specific patient, AI-PROTIPP can propose a treatment selection quickly and automatically.

METHODS

A database of 60 patients presenting oropharyngeal cancer, obtained from the Cliniques Universitaires Saint Luc in Belgium, was used in this study. For every patient, a PT plan and an XT plan were generated. The dose distributions were used to train the two dose DL prediction models (one for each modality). The model is based on U-Net architecture, a type of convolutional neural network currently considered as the state of the art for dose prediction models. A NTCP protocol used in the Dutch model-based approach, including grades II and III xerostomia and grades II and III dysphagia, was later applied in order to perform automatic treatment selection for each patient. The networks were trained using a nested cross-validation approach with 11-folds. We set aside three patients in an outer set and each fold consists of 47 patients in training, five in validation and five for testing. This method allowed us to assess our method on 55 patients (five patients per test times the number of folds).

RESULTS

The treatment selection based on the DL-predicted doses reached an accuracy of 87.4% for the threshold parameters set by the Health Council of the Netherlands. The selected treatment is directly linked with these threshold parameters as they express the minimal gain brought by the PT treatment for a patient to be indicated to PT. To validate the performance of AI-PROTIPP in other conditions, we modulated these thresholds, and the accuracy was above 81% for all the considered cases. The difference in average cumulative NTCP per patient of predicted and clinical dose distributions is very similar (less than 1% difference).

CONCLUSIONS

AI-PROTIPP shows that using DL dose prediction in combination with NTCP models to select PT for patients is feasible and can help to save time by avoiding the generation of treatment plans only used for the comparison. Moreover, DL models are transferable, allowing, in the future, experience to be shared with centers that would not have PT planning expertise.

PTV-based VMAT vs. robust IMPT for head-and-neck cancer: A probabilistic uncertainty analysis of clinical plan evaluation with the Dutch model-based selection

BACKGROUND AND PURPOSE

In the Netherlands, head-and-neck cancer (HNC) patients are referred for proton therapy (PT) through model-based selection (MBS). However, treatment errors may compromise adequate CTV dose. Our aims are: (i) to derive probabilistic plan evaluation metrics on the CTV consistent with clinical metrics; (ii) to evaluate plan consistency between photon (VMAT) and proton (IMPT) planning in terms of CTV dose iso-effectiveness and (iii) to assess the robustness of the OAR doses and of the risk toxicities involved in the MBS.

MATERIALS AND METHODS

Sixty HNC plans (30 IMPT/30 VMAT) were included. A robustness evaluation with 100,000 treatment scenarios per plan was performed using Polynomial Chaos Expansion (PCE). PCE was applied to determine scenario distributions of clinically relevant dosimetric parameters, which were compared between the 2 modalities. Finally, PCE-based probabilistic dose parameters were derived and compared to clinical PTV-based photon and voxel-wise proton evaluation metrics.

RESULTS

Probabilistic dose to near-minimum volume v = 99.8% for the CTV correlated best with clinical PTV-D98% and VWmin-D98%,CTV doses for VMAT and IMPT respectively. IMPT showed slightly higher nominal CTV doses, with an average increase of 0.8 GyRBE in the median of the D99.8%,CTV distribution. Most patients qualified for IMPT through the dysphagia grade II model, for which an average NTCP gain of 10.5 percentages points (%-point) was found. For all complications, uncertainties resulted in moderate NTCP spreads lower than 3 p.p. on average for both modalities.

CONCLUSION

Despite the differences between photon and proton planning, the comparison between PTV-based VMAT and robust IMPT is consistent. Treatment errors had a moderate impact on NTCPs, showing that the nominal plans are a good estimator to qualify patients for PT.

Proton therapy and oral mucositis in oral & oropharyngeal cancers: outcomes, dosimetric and NTCP benefit

INTRODUCTION

Radiation-induced oral mucositis (RIOM), is a common, debilitating, acute side effect of radiotherapy for oral cavity (OC) and oropharyngeal (OPx) cancers; technical innovations for reducing it are seldom discussed. Intensity-modulated-proton-therapy (IMPT) has been reported extensively for treating OPx cancers, and less frequently for OC cancers. We aim to quantify the reduction in the likelihood of RIOM in treating these 2 subsites with IMPT compared to Helical Tomotherapy.

MATERIAL AND METHODS

We report acute toxicities and early outcomes of 22 consecutive patients with OC and OPx cancers treated with IMPT, and compare the dosimetry and normal tissue complication probability (NTCP) of ≥ grade 3 mucositis for IMPT and HT.

RESULTS

Twenty two patients, 77% males, 41% elderly and 73% OC subsite, were reviewed. With comparable target coverage, IMPT significantly reduced the mean dose and D32, D39, D45, and D50, for both the oral mucosa (OM) and spared oral mucosa (sOM). With IMPT, there was a 7% absolute and 16.5% relative reduction in NTCP for grade 3 mucositis for OM, compared to HT. IMPT further reduced NTCP for sOM, and the benefit was maintained in OC, OPx subsites and elderly subgroup. Acute toxicities, grade III dermatitis and mucositis, were noted in 50% and 45.5% patients, respectively, while 22.7% patients had grade 3 dysphagia. Compared with published data, the hospital admission rate, median weight loss, feeding tube insertion, unplanned treatment gaps were lower with IMPT. At a median follow-up of 15 months, 81.8% were alive; 72.7%, alive without disease and 9%, alive with disease.

CONCLUSION

The dosimetric benefit of IMPT translates into NTCP reduction for grade 3 mucositis compared to Helical Tomotherapy for OPx and OC cancers and encourages the use of IMPT in their management.

The SINTART 2 Study. A phase II non-randomised controlled trial of induction chemotherapy, photon-, proton- and carbon-ion-based radiotherapy integration in patients with locally advanced unresectable sinonasal tumours

PURPOSE

Unresectable, locally advanced sinonasal epithelial tumours are rare diseases with poor prognosis. Multimodal approach is widely used, although no standard therapy has been established in prospective trials. This study assessed activity and safety of an innovative integration of multimodality treatment-induction chemotherapy (ICT), surgery and radiotherapy (RT)-modulated by histology and response to ICT.

METHODS

Patients with untreated, unresectable sinonasal epithelial tumours with selected histotypes (squamous cell carcinoma, intestinal-type adenocarcinoma, sinonasal undifferentiated and neuroendocrine carcinoma, olfactory neuroblastoma) were enroled in a single-arm, open-label, phase II, multicentre clinical trial. Patients were treated with up to 5 ICT cycles, whose regimen was selected according to histotype. Photon and/or proton/carbon-ion-based RT was employed according to disease site, stage and ICT response. Primary end-point was 5-years progression-free survival (PFS), secondary end-points were overall survival (OS), ICT objective response rate per RECIST 1.1 and safety.

RESULTS

Twenty-five patients were evaluable for primary end-point. Five-year PFS was 26.8% (95% confidence interval [CI]: 12.6-57.1), with a median PFS of 18 months. Five-year OS was 23.8% (95% CI: 9.5-59.3), with a median OS of 27 months. The overall response rate to ICT was 40%. Three-year PFS for patients achieving major volumetric partial response (mPRv) versus non-mPRv was 40% (95% CI: 13.7-100%) versus 23.1% (95% CI: 8.3-64.7%) (P = 0.318) and 3-year OS was 53.3% (95% CI: 21.4-100%) versus 37.7% (95% CI: 20.0-71.0%) (P = 0.114).

CONCLUSION

Multimodal combination of ICT and innovative RT did not provide a significant improvement in survival rates with respect to previous experiences. This finding underscores the need for future research in this rare disease, still characterised by a heavy burden and poor prognosis. We observed longer survival in subjects achieving response to ICT. The overall treatment safety is acceptable.

Global democratisation of proton radiotherapy

Proton radiotherapy is an advanced treatment option compared with conventional x-ray treatment, delivering much lower doses of radiation to healthy tissues surrounding the tumour. However, proton therapy is currently not widely available. In this Review, we summarise the evolution of proton therapy to date, together with the benefits to patients and society. These developments have led to an exponential growth in the number of hospitals using proton radiotherapy worldwide. However, the gap between the number of patients who should be treated with proton radiotherapy and those who have access to it remains large. We summarise the ongoing research and development that is contributing to closing this gap, including the improvement of treatment efficiency and efficacy, and advances in fixed-beam treatments that do not require an enormously large, heavy, and costly gantry. The ultimate goal of decreasing the size of proton therapy machines to fit into standard treatment rooms appears to be within reach, and we discuss future research and development opportunities to achieve this goal.

Evaluating the effect of setup uncertainty reduction and adaptation to geometric changes on normal tissue complication probability using online adaptive head and neck intensity modulated proton therapy

Objective. To evaluate the impact of setup uncertainty reduction (SUR) and adaptation to geometrical changes (AGC) on normal tissue complication probability (NTCP) when using online adaptive head and neck intensity modulated proton therapy (IMPT).Approach.A cohort of ten retrospective head and neck cancer patients with daily scatter corrected cone-beam CT (CBCT) was studied. For each patient, two IMPT treatment plans were created: one with a 3 mm setup uncertainty robustness setting and one with no explicit setup robustness. Both plans were recalculated on the daily CBCT considering three scenarios: the robust plan without adaptation, the non-robust plan without adaptation and the non-robust plan with daily online adaptation. Online-adaptation was simulated using an in-house developed workflow based on GPU-accelerated Monte Carlo dose calculation and partial spot-intensity re-optimization. Dose distributions associated with each scenario were accumulated on the planning CT, where NTCP models for six toxicities were applied. NTCP values from each scenario were intercompared to quantify the reduction in toxicity risk induced by SUR alone, AGC alone and SUR and AGC combined. Finally, a decision tree was implemented to assess the clinical significance of the toxicity reduction associated with each mechanism.Main results. For most patients, clinically meaningful NTCP reductions were only achieved when SUR and AGC were performed together. In these conditions, total reductions in NTCP of up to 30.48 pp were obtained, with noticeable NTCP reductions for aspiration, dysphagia and xerostomia (mean reductions of 8.25, 5.42 and 5.12 pp respectively). While SUR had a generally larger impact than AGC on NTCP reductions, SUR alone did not induce clinically meaningful toxicity reductions in any patient, compared to only one for AGC alone.SignificanceOnline adaptive head and neck proton therapy can only yield clinically significant reductions in the risk of long-term side effects when combining the benefits of SUR and AGC.

Proton Beam Radiation Therapy for Oropharyngeal Squamous Cell Carcinoma

Purpose

To discuss the role of proton beam therapy (PBT) in the treatment of patients with oropharyngeal squamous cell carcinoma (OPSCC).

Materials and Methods

A review of the pertinent literature.

Results

Proton beam therapy likely results in reduced acute and late toxicity as compared with intensity-modulated radiation therapy (IMRT). The extent of the reduced toxicity, which may be modest, depends on the endpoint and technical factors such as pencil beam versus passive scattered PBT and adaptive replanning. The disease control rates after PBT are likely similar to those after IMRT.

Conclusion

Proton beam therapy is an attractive option to treat patients with OPSCC. Whether it becomes widely available depends on access.

Planned dose of intensity modulated proton beam therapy versus volumetric modulated arch therapy to tooth-bearing regions

BACKGROUND

Intensity modulated proton beam therapy (IMPT) for head and neck cancer offers dosimetric benefits for the organs at risk when compared to photon-based volumetric modulated arch therapy (VMAT). However, limited data exists about the potential benefits of IMPT for tooth-bearing regions. The aim of this study was to compare the IMPT and VMAT radiation dosimetrics of the tooth-bearing regions in head and neck cancer patients. Also, we aimed to identify prognostic factors for a cumulative radiation dose of ≥40 Gy on the tooth-bearing areas, which is considered the threshold dose for prophylactic dental extractions.

METHODS

A total of 121 head and neck cancer patients were included in this retrospective analysis of prospectively collected data. We compared the average Dmean values of IMPT versus VMAT of multiple tooth-bearing regions in the same patients. Multivariate logistic regression analysis was performed for receiving a cumulative radiation dose of ≥40 Gy to the tooth-bearing regions (primary endpoint) in both VMAT and IMPT.

RESULTS

A lower Dmean was seen after applying IMPT to the tooth-bearing tumour regions (p < 0.001). Regarding VMAT, oral cavity tumours, T3-T4 tumours, molar regions in the mandible, and regions ipsilateral to the tumour were risk factors for receiving a cumulative radiation dose of ≥40 Gy.

CONCLUSIONS

IMPT significantly reduces the radiation dose to the tooth-bearing regions.

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.

Study of hepatic toxicity in small liver tumors after photon or proton therapy based on factors predicting the benefits of proton

OBJECTIVES

In a previous study of hepatic toxicity, the following three factors were identified to predict the benefits of proton beam therapy (PBT) for hepatocellular carcinomas (HCCs) with a maximum diameter of ≤5 cm and Child-pugh grade A (CP-A): number of tumors (1 vs ≥2), the location of tumors (hepatic hilum or others), and the sum of the diameters of lesions. The aim of this study is to analyze the association between these three factors and hepatic toxicity.

METHODS

We retrospectively reviewed patients of CP-A treated with PBT or photon stereotactic body radiotherapy (X-ray radiotherapy, XRT) for HCC ≤5 cm. For normal liver dose, the V5, V10, V20 (volumes receiving 5, 10, and 20 Gy at least), and the mean dose was evaluated. The albumin-bilirubin (ALBI) and CP score changes from the baseline were evaluated at 3 and 6 months after treatment.

RESULTS

In 89 patients (XRT: 48, PBT: 41), those with two or three (2-3) predictive factors were higher normal liver doses than with zero or one (0-1) factor. In the PBT group, the ALBI score worsened more in patients with 2-3 factors than those with 0-1 factor, at 3 months (median: 0.26 vs 0.02, p = 0.032) and at 6 months (median: 0.35 vs 0.10, p = 0.009). The ALBI score change in the XRT group and CP score change in either modality were not significantly different in the number of predictive factors.

CONCLUSION

The predictive factor numbers predicted the ALBI score change in PBT but not in XRT.

ADVANCES IN KNOWLEDGE

This study suggest that the number of predictive factors previously identified (0-1 vs 2-3) were significantly associated with dosimetric parameters of the normal liver in both modalities. In the proton group, the number of predictive factors was associated with a worsening ALBI score at 3 and 6 months, but these associations were not found in the photon SBRT group.

The relation between prediction model performance measures and patient selection outcomes for proton therapy in head and neck cancer

BACKGROUND

Normal-tissue complication probability (NTCP) models predict complication risk in patients receiving radiotherapy, considering radiation dose to healthy tissues, and are used to select patients for proton therapy, based on their expected reduction in risk after proton therapy versus photon radiotherapy (ΔNTCP). Recommended model evaluation measures include area under the receiver operating characteristic curve (AUC), overall calibration (CITL), and calibration slope (CS), whose precise relation to patient selection is still unclear. We investigated how each measure relates to patient selection outcomes.

METHODS

The model validation and consequent patient selection process was simulated within empirical head and neck cancer patient data. By manipulating performance measures independently via model perturbations, the relation between model performance and patient selection was studied.

RESULTS

Small reductions in AUC (-0.02) yielded mean changes in ΔNTCP between 0.9-3.2 %, and single-model patient selection differences between 2-19 %. Deviations (-0.2 or +0.2) in CITL or CS yielded mean changes in ΔNTCP between 0.3-1.4 %, and single-model patient selection differences between 1-10 %.

CONCLUSIONS

Each measure independently impacts ΔNTCP and patient selection and should thus be assessed in a representative sufficiently large external sample. Our suggested practical model selection approach is considering the model with the highest AUC, and recalibrating it if needed.

Comparison of intensity-modulated proton therapy (IMPT) versus intensity-modulated radiation therapy (IMRT) for the treatment of head and neck cancer based on radiobiological modelling

Aim:

The aim of our study is to retrospectively report the radiobiological aspects for intensity-modulated proton therapy (IMPT) against intensity-modulated radiation therapy (IMRT) for patients with head and neck cancer treated at our institution. A secondary goal is to reinforce current model-based approaches to head and neck cancer patient selection for IMPT.

Materials and Methods:

Eighteen patients were evaluated with prescription doses ranging from 50 to 70 Gy delivered in 2 Gy per fraction. The dose volume histograms (DVH) were used to calculate equivalent uniform dose (EUD), tumour control probability (TCP) and normal tissue complication probability (NTCP) for biophysical comparison using mechanistic mathematical dose response models. Absolute values of TCP and NTCP were then compared between IMPT and IMRT.

Results:

The dose models demonstrate a minimal radiobiological advantage for IMPT compared to IMRT in treating head and neck cancers. Absolute values of TCP were slightly higher, while absolute values of NTCP were slightly lower for IMPT versus IMRT.

Conclusions:

Further studies are needed to determine if the radiobiological advantage indeed translates to a therapeutic advantage for patients.

Hyperfractionated intensity-modulated proton therapy for pharyngeal cancer with variable relative biological effectiveness: A simulation study

BACKGROUND

The relative biological effectiveness (RBE) of proton is considered to be dependent on biological parameters and fractional dose. While hyperfractionated photon therapy was effective in the treatment of patients with head and neck cancers, its effect in intensity-modulated proton therapy (IMPT) under the variable RBE has not been investigated in detail.

PURPOSE

To study the effect of variable RBE on hyperfractionated IMPT for the treatment of pharyngeal cancer. We investigated the biologically effective dose (BED) to determine the theoretical effective hyperfractionated schedule.

METHODS

The treatment plans of three pharyngeal cancer patients were used to define the ΔBED for the clinical target volume (CTV) and soft tissue (acute and late reaction) as the difference between the BED for the altered schedule with variable RBE and conventional schedule with constant RBE. The ΔBED with several combinations of parameters (treatment days, number of fractions, and prescribed dose) was comprehensively calculated. Of the candidate schedules, the one that commonly gave a higher ΔBED for CTV was selected as the resultant schedule. The BED volume histogram was used to compare the influence of variable RBE and fractionation.

RESULTS

In the conventional schedule, compared with the constant RBE, the variable RBE resulted in a mean 2.6 and 2.7 Gy reduction of BED_mean for the CTV and soft tissue (acute reaction) of the three plans, respectively. Moreover, the BED_mean for soft tissue (late reaction) increased by 7.4 Gy, indicating a potential risk of increased RBE. Comprehensive calculation of the ΔBED resulted in the hyperfractionated schedule of 80.52 Gy (RBE = 1.1)/66 fractions in 6.5 weeks. When variable RBE was used, compared with the conventional schedule, the hyperfractionated schedule increased the BED_mean for CTV by 7.6 Gy; however, this was associated with a 7.8 Gy increase for soft tissue (acute reaction). The BED_mean for soft tissue (late reaction) decreased by 2.4 Gy.

CONCLUSION

The results indicated a potential effect of the variable RBE on IMPT for pharyngeal cancer but with the possibility that hyperfractionation could outweigh this effect. Although biological uncertainties require conservative use of the resultant schedule, hyperfractionation is expected to be an effective strategy in IMPT for pharyngeal cancer.

Pan-Canadian consensus recommendations for proton beam therapy access in Canada

PURPOSE

Proton Beam Therapy (PBT)is a treatment option for select cancer patients. It is currently not available in Canada. Assessment and referral processes for out-of-country treatment for eligible patients vary by jurisdiction, leading to variability in access to this treatment for Canadian cancer patients. The purpose of this initiative was to develop a framework document to inform consistent and equitable PBT access for appropriate patients through the creation of pan-Canadian PBT access consensus recommendations.

MATERIALS AND METHODS

A modified Delphiprocess was used to develop pan-Canadian recommendations with input from 22 PBT clinical and administrative experts across all provinces, external peer-review by provincial cancer and system partners, and feedback from a targeted community consultation. This was conducted by electronic survey and live discussion. Consensus threshold was set at 70% agreement.

RESULTS

Fourconsensus rounds resulted in a final set of 27 recommendations divided into three categories: patient eligibility (n = 9); program level (n = 10); and system level (n = 8). Patient eligibility included: anatomic site (n = 4), patient characteristics (n = 3), clinical efficacy (n = 2). Program level included: regulatory and staff requirements (n = 5), equipment and technologies (n = 4), quality assurance (n = 1). System level included: referral process (n = 5), costing, budget impact and quality adjusted life years (n = 2), eligible patient estimates (n = 1). Recommendations were released nationally in June 2021 and distributed to all 43 cancer programs in Canada.

CONCLUSION

A pan-Canadian consensus-building approach was successful in creating an evidence-based, peer-reviewed suite of recommendations thatsupportapplication of consistent clinical criteria to inform treatment options, facility set-up and access to high quality proton therapy.

Human Papillomavirus-Related Non-Metastatic Oropharyngeal Carcinoma: Current Local Treatment Options and Future Perspectives

Over the last two decades, human papillomavirus (HPV) has caused a new pandemic of cancer in many urban areas across the world. The new entity, HPV-associated oropharyngeal squamous cell carcinoma (OPSCC), has been at the center of scientific attention ever since, not only due to its distinct biological behavior, but also because of its significantly better prognosis than observed in its HPV-negative counterpart. The very good treatment outcomes of the disease after primary therapy (minimally-invasive surgery, radiation therapy with or without chemotherapy) resulted in the creation of a separate staging system, reflecting this excellent prognosis. A substantial proportion of newly diagnosed HPV-driven OPSCC is diagnosed in stage I or II, where long-term survival is observed worldwide. Deintensification of the primary therapeutic methods, aiming at a reduction of long-term toxicity in survivors, has emerged, and the quality of life of the patient after treatment has become a key-point in many clinical trials. Current treatment recommendations for the treatment of HPV-driven OPSCC do not differ significantly from HPV-negative OPSCC; however, the results of randomized trials are eagerly awaited and deemed necessary, in order to include deintensification into standard clinical practice.

Automated clinical decision support system with deep learning dose prediction and NTCP models to evaluate treatment complications in patients with esophageal cancer

BACKGROUND AND PURPOSE

This study aims to investigate how accurate our deep learning (DL) dose prediction models for intensity modulated radiotherapy (IMRT) and pencil beam scanning (PBS) treatments, when chained with normal tissue complication probability (NTCP) models, are at identifying esophageal cancer patients who are at high risk of toxicity and should be switched to proton therapy (PT).

MATERIALS AND METHODS

Two U-Net were created, for photon (XT) and proton (PT) plans, respectively. To estimate the dose distribution for each patient, they were trained on a database of 40 uniformly planned patients using cross validation and a circulating test set. These models were combined with a NTCP model for postoperative pulmonary complications. The NTCP model used the mean lung dose, age, histology type, and body mass index as predicting variables. The treatment choice is then done by using a ΔNTCP threshold between XT and PT plans. Patients with ΔNTCP ≥ 10% were referred to PT.

RESULTS

Our DL models succeed in predicting dose distributions with a mean error on the mean dose to the lungs (MLD) of 1.14 ± 0.93% for XT and 0.66 ± 0.48% for PT. The complete automated workflow (DL chained with NTCP) achieved 100% accuracy in patient referral. The average residual (ΔNTCP ground truth - ΔNTCP predicted) is 1.43 ± 1.49%.

CONCLUSION

This study evaluates our DL dose prediction models in a broader patient referral context and demonstrates their ability to support clinical decisions.

Comparison of Estimated Late Toxicities between IMPT and IMRT Based on Multivariable NTCP Models for High-Risk Prostate Cancers Treated with Pelvic Nodal Radiation

Purpose

To compare the late gastrointestinal (GI) and genitourinary toxicities (GU) estimated using multivariable normal tissue complication probability (NTCP) models, between pencil-beam scanning proton beam therapy (PBT) and helical tomotherapy (HT) in patients of high-risk prostate cancers requiring pelvic nodal irradiation (PNI) using moderately hypofractionated regimen.

Materials and Methods

Twelve consecutive patients treated with PBT at our center were replanned with HT using the same planning goals. Six late GI and GU toxicity domains (stool frequency, rectal bleeding, fecal incontinence, dysuria, urinary incontinence, and hematuria) were estimated based on the published multivariable NTCP models. The ΔNTCP (difference in absolute NTCP between HT and PBT plans) for each of the toxicity domains was calculated. A one-sample Kolmogorov-Smirnov test was used to analyze distribution of data, and either a paired t test or a Wilcoxon matched-pair signed rank test was used to test statistical significance.

Results

Proton beam therapy and HT plans achieved adequate target coverage. Proton beam therapy plans led to significantly better sparing of bladder, rectum, and bowel bag especially in the intermediate range of 15 to 40 Gy, whereas doses to penile bulb and femoral heads were higher with PBT plans. The average ΔNTCP for grade (G)2 rectal bleeding, fecal incontinence, stool frequency, dysuria, urinary incontinence, and G1 hematuria was 12.17%, 1.67%, 2%, 5.83%, 2.42%, and 3.91%, respectively, favoring PBT plans. The average cumulative ΔNTCP for GI and GU toxicities (ΣΔNTCP) was 16.58% and 11.41%, respectively, favoring PBT. Using a model-based selection threshold of any G2 ΔNTCP >10%, 67% (8 patients) would be eligible for PBT.

Conclusion

Proton beam therapy plans led to superior sparing of organs at risk compared with HT, which translated to lower NTCP for late moderate GI and GU toxicities in patients of prostate cancer treated with PNI. For two-thirds of our patients, the difference in estimated absolute NTCP values between PBT and HT crossed the accepted threshold for minimal clinically important difference.

A study on predicting cases that would benefit from proton beam therapy in primary liver tumors of less than or equal to 5 cm based on the estimated incidence of hepatic toxicity

•

An advantage of PBT is reducing the liver receiving low doses of radiation.

•

The factors predicting the benefit in PBT are different among NTCP models.

•

The tumor size, number, and location are useful in estimating the benefits of PBT.

Background

Materials and methods

Results

Conclusions

Redefine the Role of Proton Beam Therapy for the Locally-Advanced Non-Small Cell Lung Cancer Assisting the Reduction of Acute Hematologic Toxicity

Purpose

To investigate the potential clinical benefit of utilizing intensity-modulated proton therapy (IMPT) to reduce acute hematologic toxicity for locally advanced non-small cell lung cancer (LA-NSCLC) patients and explore the feasibility of a model-based patient selection approach via the normal tissue complication probability (NTCP).

Methods

Twenty patients with LA-NSCLC were retrospectively selected. Volumetric modulated arc photon therapy (VMAT) and IMPT plans were generated with a prescription dose of 60 Gy in 30 fractions. A wide range of cases with varied tumor size, location, stations of metastatic lymph nodes were selected to represent the general cancer group. Contouring and treatment planning followed RTOG-1308 protocol. Doses to thoracic vertebral bodies (TVB) and other organ at risks were compared. Risk of grade ≥ 3 acute hematologic toxicity (HT3+) were calculated based on the NTCP model, and patients with a reduction on NTCP of HT3+ from VMAT to IMPT (△NTCP_HT3+) ≥ 10% were considered to ‘significantly benefit from proton therapy.’

Results

Compared to VMAT, IMPT significantly reduced the dose to the TVB, the lung, the heart, the esophagus and the spinal cord. Tumor distance to TVB was significantly associated with △NTCP _HT3+ ≥ 10%. For the patients with tumor distance ≤ 0.7 cm to TVB, the absolute reduction of dose (mean, V30 and V40) to TVB was significantly lower than that in patients with tumor distance &gt; 0.7 cm.

Conclusion

IMPT decreased the probability of HT3+ compared to VMAT by reducing the dose to the TVB in LA-NSCLC patients. Patients with tumor distance to TVB less than 0.7 cm are likely to benefit most from proton over photon therapy.

Technical note: Optimal allocation of limited proton therapy resources using model-based patient selection

PURPOSE

We consider the following scenario: A radiotherapy clinic has a limited number of proton therapy slots available each day to treat cancer patients of a given tumor site. The clinic's goal is to minimize the expected number of complications in the cohort of all patients of that tumor site treated at the clinic, and thereby maximize the benefit of its limited proton resources.

METHODS

To address this problem, we extend the normal tissue complication probability (NTCP) model-based approach to proton therapy patient selection to the situation of limited resources at a given institution. We assume that, on each day, a newly diagnosed patient is scheduled for treatment at the clinic with some probability and with some benefit Δ N T C P $\Delta NTCP$ from protons over photons, which is drawn from a probability distribution. When a new patient is scheduled for treatment, a decision for protons or photons must be made, and a patient may wait only for a limited amount of time for a proton slot becoming available. The goal is to determine the Δ N T C P $\Delta NTCP$ thresholds for selecting a patient for proton therapy, which optimally balance the competing goals of making use of all available slots while not blocking slots with patients with low benefit. This problem can be formulated as a Markov decision process (MDP) and the optimal thresholds can be determined via a value-policy iteration method.

RESULTS

The optimal Δ N T C P $\Delta NTCP$ thresholds depend on the number of available proton slots, the average number of patients under treatment, and the distribution of Δ N T C P $\Delta NTCP$ values. In addition, the optimal thresholds depend on the current utilization of the facility. For example, if one proton slot is available and a second frees up shortly, the optimal Δ N T C P $\Delta NTCP$ threshold is lower compared to a situation where all but one slot remain blocked for longer.

CONCLUSIONS

MDP methodology can be used to augment current NTCP model-based patient selection methods to the situation that, on any given day, the number of proton slots is limited. The optimal Δ N T C P $\Delta NTCP$ threshold then depends on the current utilization of the proton facility. Although, the optimal policy yields only a small nominal benefit over a constant threshold, it is more robust against variations in patient load.

Proton Therapy in the Management of Luminal Gastrointestinal Cancers: Esophagus, Stomach, and Anorectum

While the role of proton therapy in gastric cancer is marginal, its role in esophageal and anorectal cancers is expanding. In esophageal cancer, protons are superior in sparing the organs at risk, as shown by multiple dosimetric studies. Literature is conflicting regarding clinical significance, but the preponderance of evidence suggests that protons yield similar or improved oncologic outcomes to photons at a decreased toxicity cost. Similarly, protons have improved sparing of the organs at risk in anorectal cancers, but clinical data is much more limited to date, and toxicity benefits have not yet been shown clinically. Large, randomized trials are currently underway for both disease sites.

Influence of Beam Angle on Normal Tissue Complication Probability of Knowledge-Based Head and Neck Cancer Proton Planning

Knowledge-based planning solutions have brought significant improvements in treatment planning. However, the performance of a proton-specific knowledge-based planning model in creating knowledge-based plans (KBPs) with beam angles differing from those used to train the model remains unexplored. We used a previously validated RapidPlanPT model and scripting to create nine KBPs, one with default and eight with altered beam angles, for 10 recent oropharynx cancer patients. The altered-angle plans were compared against the default-angle ones in terms of grade 2 dysphagia and xerostomia normal tissue complication probability (NTCP), mean doses of several organs at risk, and dose homogeneity index (HI). As KBP could be suboptimal, a proof of principle automatic iterative optimizer (AIO) was added with the aim of reducing the plan NTCP. There were no statistically significant differences in NTCP or HI between default- and altered-angle KBPs, and the altered-angle plans showed a <1% reduction in NTCP. AIO was able to reduce the sum of grade 2 NTCPs in 66/90 cases with mean a reduction of 3.5 ± 1.8%. While the altered-angle plans saw greater benefit from AIO, both default- and altered-angle plans could be improved, indicating that the KBP model alone was not completely optimal to achieve the lowest NTCP. Overall, the data showed that the model was robust to the various beam arrangements within the range described in this analysis.

Cardiotoxicity model-based patient selection for Hodgkin lymphoma proton therapy

INTRODUCTION

Hodgkin lymphoma (HL) is a highly curable hematological malignancy. Consolidation radiation therapy techniques have made significant progresses to improve organ-at-risk sparing in order to reduce late radiation-induced toxicity. Recent technical breakthroughs notably include intensity modulated proton therapy (IMPT), which has demonstrated a major dosimetric benefit at the cardiac level for mediastinal HL patients. However, its implementation in clinical practice is still challenging, notably due to the limited access to proton therapy facilities. In this context, the purpose of this study was to estimate the benefit of IMPT for HL proton therapy for diverse cardiac adverse events and to propose a general frame for mediastinal HL patient selection strategy for IMPT based on cardiotoxicity reduction, patient clinical factors, and IMPT treatment availability.

MATERIAL AND METHODS

This retrospective dosimetric study included 30 mediastinal HL patients treated with VMAT. IMPT plans were generated on the initial simulation scans. Dose to the heart, to the left ventricle and to the valves were retrieved to calculate the relative risk (RR) of ischemic heart disease (IHD), congestive heart failure (CHF) and valvular disease (VD). Composite relative risk reduction (cRRR) of late cardiotoxicity, between VMAT and IMPT, were calculated as the weighted mean of relative risk reduction for IHD, CHF and VD, calculated across a wide range of cardiovascular risk factor combinations. The proportion of mediastinal HL patients who could benefit from IMPT was estimated in European countries, based on the country population and on the number of active gantries, to propose country-specific cRRR thresholds for patient selection.

RESULTS

Compared with VMAT, IMPT significantly reduced average mean doses to the heart (2.36 Gy vs 0.99 Gy, p < 0.01), to the left ventricle (0.67 Gy vs 0.03, p < 0.01) and to the valves (1.29 Gy vs. 0.06, p < 0.01). For a HL patient without cardiovascular risk factor other than anthracycline-based chemotherapy, the relative risks of late cardiovascular complications were significantly lower after IMPT compared with VMAT for ischemic heart disease (1.07 vs 1.17, p < 0.01), for congestive heart failure (2.84 vs. 3.00, p < 0.01), and for valvular disease (1.01 vs. 1.06, p < 0.01). The median cRRR of cardiovascular adverse events with IMPT was 4.8%, ranging between 0.1% and 30.5%, depending on the extent of radiation fields and on the considered cardiovascular risk factors. The estimated proportion of HL patients currently treatable with IMPT in European countries with proton therapy facilities ranged between 8.0% and 100% depending on the country, corresponding to cRRR thresholds ranging from 24.0% to 0.0%.

CONCLUSION

While a statistically significant clinical benefit is theoretically expected for ischemic heart disease, cardiac heart failure and valvular disease for mediastinal HL patients with IMPT, the overall cardiotoxicity risk reduction is notable only for a minority of patients. In the context of limited IMPT availability, this study proposed a general model-based selection approach for mediastinal HL patient based on calculated cardiotoxicity reduction, taking into consideration patient clinical characteristics and IMPT facility availability.

A Patient Selection Approach Based on NTCP Models and DVH Parameters for Definitive Proton Therapy in Locally Advanced Sinonasal Cancer Patients

(1) Background: In this work, we aim to provide selection criteria based on normal tissue complication probability (NTCP) models and additional explanatory dose-volume histogram parameters suitable for identifying locally advanced sinonasal cancer patients with orbital invasion benefitting from proton therapy. (2) Methods: Twenty-two patients were enrolled, and two advanced radiation techniques were compared: intensity modulated proton therapy (IMPT) and photon volumetric modulated arc therapy (VMAT). Plans were optimized with a simultaneous integrated boost modality: 70 and 56 Gy(RBE) in 35 fractions were prescribed to the high risk/low risk CTV. Several endpoints were investigated, classified for their severity and used as discriminating paradigms. In particular, when NTCP models were already available, a first selection criterion based on the delta-NTCP was adopted. Additionally, an overall analysis in terms of DVH parameters was performed. Furthermore, a second selection criterion based on a weighted sum of the ΔNTCP and ΔDVH was adopted. (3) Results: Four patients out of 22 (18.2%) were suitable for IMPT due to ΔNTCP > 3% for at least one severe toxicity, 4 (18.2%) due to ΔNTCP > 20% for at least three concurrent intermediate toxicities and 16 (72.7%) due to the mixed sum of ΔNTCP and ΔDVH criterion. Since, for some cases, both criteria were contemporary fulfilled, globally 17/22 patients (77.3%) would benefit from IMPT. (4) Conclusions: For this rare clinical scenario, the use of a strategy including DVH parameters and NTCPs when comparing VMAT and IMPT is feasible. We showed that patients affected by sinonasal cancer could profit from IMPT compared to VMAT in terms of optical and central nervous system organs at risk sparing.

Proton Therapy for Squamous Cell Carcinoma of the Head and Neck: Early Clinical Experience and Current Challenges

Simple Summary

Proton therapy is a promising type of radiation therapy used to destroy tumor cells. It has the potential to further improve the outcomes for patients with head and neck cancer since it allows to minimize the radiation dose to vital structures around the tumor, leading to less toxicity. This paper describes the current experience worldwide with proton therapy in head and neck cancer.

Abstract

Proton therapy (PT) is a promising development in radiation oncology, with the potential to further improve outcomes for patients with squamous cell carcinoma of the head and neck (HNSCC). By utilizing the finite range of protons, healthy tissue can be spared from beam exit doses that would otherwise be irradiated with photon-based treatments. Current evidence on PT for HNSCC is limited to comparative dosimetric analyses and retrospective single-institution series. As a consequence, the recognized indications for the reimbursement of PT remain scarce in most countries. Nevertheless, approximately 100 PT centers are in operation worldwide, and initial experiences for HNSCC are being reported. This review aims to summarize the results of the early clinical experience with PT for HNSCC and the challenges that are currently faced.

Estimating the percentage of patients who might benefit from proton beam therapy instead of X-ray radiotherapy

OBJECTIVES

High-energy Proton Beam Therapy (PBT) commenced in England in 2018 and NHS England commissions PBT for 1.5% of patients receiving radical radiotherapy. We sought expert opinion on the level of provision.

METHODS

Invitations were sent to 41 colleagues working in PBT, most at one UK centre, to contribute by completing a spreadsheet. 39 responded: 23 (59%) completed the spreadsheet; 16 (41%) declined, arguing that clinical outcome data are lacking, but joined six additional site-specialist oncologists for two consensus meetings. The spreadsheet was pre-populated with incidence data from Cancer Research UK and radiotherapy use data from the National Cancer Registration and Analysis Service. 'Mechanisms of Benefit' of reduced growth impairment, reduced toxicity, dose escalation and reduced second cancer risk were examined.

RESULTS

The most reliable figure for percentage of radical radiotherapy patients likely to benefit from PBT was that agreed by 95% of the 23 respondents at 4.3%, slightly larger than current provision. The median was 15% (range 4-92%) and consensus median 13%. The biggest estimated potential benefit was from reducing toxicity, median benefit to 15% (range 4-92%), followed by dose escalation median 3% (range 0 to 47%); consensus values were 12 and 3%. Reduced growth impairment and reduced second cancer risk were calculated to benefit 0.5% and 0.1%.

CONCLUSIONS

The most secure estimate of percentage benefit was 4.3% but insufficient clinical outcome data exist for confident estimates. The study supports the NHS approach of using the evidence base and developing it through randomised trials, non-randomised studies and outcomes tracking.

ADVANCES IN KNOWLEDGE

Less is known about the percentage of patients who may benefit from PBT than is generally acknowledged. Expert opinion varies widely. Insufficient clinical outcome data exist to provide robust estimates. Considerable further work is needed to address this, including international collaboration; much is already underway but will take time to provide mature data.

The dosimetric and clinical advantages of the GTV-CTV-PTV margins reduction by 6 mm in head and neck squamous cell carcinoma: Significant acute and late toxicity reduction

PURPOSE

We aim to identify the dosimetric and clinical impact of reducing the total GTV-CTV-PTV margins in head-and-neck squamous cell carcinoma (HNSCC) treated with definitive (chemo)radiation.

MATERIALS AND METHODS

The acute and late toxicity and outcomes of 155 consecutive patients treated between February 2017 and March 2019 with GTV-CTV-PTV margins of 9 mm were compared to those of 155 consecutive patients treated with total margin of 15 mm margin, before April 2015. All patients were treated with VMAT with daily-image guidance using CBCT.

RESULTS

Reducing the GTV-CTV-PTV by 6 mm resulted in significant reduction of total irradiated volume (PTV-total) by a median of 28.1% and significant reduction of doses to all salivary glands (largest reduction ipsilateral parotid gland; median -9.6 Gy) and constrictor muscle (-6.1 Gy) with subsequent reduction of the incidence of overall acute grade 3 toxicity (47.7% for 9 mm and 66.5% for 15 mm groups, p = 0.001), grade 3 mucositis (18.1% vs. 35.5%, p < 0.001) and feeding tube-dependency at the end of treatment (24.5% vs. 40%, p = 0.005). The incidence of late grade ≥ 2 xerostomia and dysphagia were also significantly lower in the 9 mm group (31.7% vs. 58.6% p < 0.001, and 15.4% vs. 26.7%, p = 0.04). The 2-year rates of loco-regional control, disease-free and overall survival were 78.8% vs.75.8%, 70.9% vs. 64.4%, and 83.8% vs. 67.6%, (p > 0.05, all).

CONCLUSION

Reduction of the total GTV-CTV-PTV margins from 15 to 9 mm in HNSCC significantly reduced the irradiated volumes and the dose to salivary glands and constrictor muscle with significant reduction of radiation-related toxicity. The loco-regional control rates of both groups were comparable.

Proton Radiation Therapy for Nasopharyngeal Cancer Patients: Dosimetric and NTCP Evaluation Supporting Clinical Decision

(1) Background: we proposed an integrated strategy to support clinical allocation of nasopharyngeal patients between proton and photon radiotherapy. (2) Methods: intensity-modulated proton therapy (IMPT) plans were optimized for 50 consecutive nasopharyngeal carcinoma (NPC) patients treated with volumetric modulated arc therapy (VMAT), and differences in dose and normal tissue complication probability (ΔNTCPx-p) for 16 models were calculated. Patient eligibility for IMPT was assessed using a model-based selection (MBS) strategy following the results for 7/16 models describing the most clinically relevant endpoints, applying a model-specific ΔNTCPx-p threshold (15% to 5% depending on the severity of the complication) and a composite threshold (35%). In addition, a comprehensive toxicity score (CTS) was defined as the weighted sum of all 16 ΔNTCPx-p, where weights follow a clinical rationale. (3) Results: Dose deviations were in favor of IMPT (ΔD_mean ≥ 14% for cord, esophagus, brainstem, and glottic larynx). The risk of toxicity significantly decreased for xerostomia (-12.5%), brain necrosis (-2.3%), mucositis (-3.2%), tinnitus (-8.6%), hypothyroidism (-9.3%), and trismus (-5.4%). There were 40% of the patients that resulted as eligible for IMPT, with a greater advantage for T3-T4 staging. Significantly different CTS were observed in patients qualifying for IMPT. (4) Conclusions: The MBS strategy successfully drives the clinical identification of NPC patients, who are most likely to benefit from IMPT. CTS summarizes well the expected global gain.

Hadron Therapy Achievements and Challenges: The CNAO Experience

Protons and carbon ions (hadrons) have useful properties for the treatments of patients affected by oncological pathologies. They are more precise than conventional X-rays and possess radiobiological characteristics suited for treating radio-resistant or inoperable tumours. This paper gives an overview of the status of hadron therapy around the world. It focusses on the Italian National Centre for Oncological Hadron therapy (CNAO), introducing operation procedures, system performance, expansion projects, methodologies and modelling to build individualized treatments. There is growing evidence that supports safety and effectiveness of hadron therapy for a variety of clinical situations. However, there is still a lack of high-level evidence directly comparing hadron therapy with modern conventional radiotherapy techniques. The results give an overview of pre-clinical and clinical research studies and of the treatments of 3700 patients performed at CNAO. The success and development of hadron therapy is strongly associated with the creation of networks among hadron therapy facilities, clinics, universities and research institutions. These networks guarantee the growth of cultural knowledge on hadron therapy, favour the efficient recruitment of patients and present available competences for R&D (Research and Development) programmes.

Deep Learning for Radiotherapy Outcome Prediction Using Dose Data - A Review

Artificial intelligence, and in particular deep learning using convolutional neural networks, has been used extensively for image classification and segmentation, including on medical images for diagnosis and prognosis prediction. Use in radiotherapy prognostic modelling is still limited, however, especially as applied to toxicity and tumour response prediction from radiation dose distributions. We review and summarise studies that applied deep learning to radiotherapy dose data, in particular studies that utilised full three-dimensional dose distributions. Ten papers have reported on deep learning models for outcome prediction utilising spatial dose information, whereas four studies used reduced dimensionality (dose volume histogram) information for prediction. Many of these studies suffer from the same issues that plagued early normal tissue complication probability modelling, including small, single-institutional patient cohorts, lack of external validation, poor data and model reporting, use of late toxicity data without taking time-to-event into account, and nearly exclusive focus on clinician-reported complications. They demonstrate, however, how radiation dose, imaging and clinical data may be technically integrated in convolutional neural networks-based models; and some studies explore how deep learning may help better understand spatial variation in radiosensitivity. In general, there are a number of issues specific to the intersection of radiotherapy outcome modelling and deep learning, for example translation of model developments into treatment plan optimisation, which will require further combined effort from the radiation oncology and artificial intelligence communities.

A Decision Support Tool to Optimize Selection of Head and Neck Cancer Patients for Proton Therapy

Simple Summary

A decision support tool was developed to select head and neck cancer patients for proton therapy. The tool uses delineation data to predict expected toxicity risk reduction with proton therapy and can be used before a treatment plan is created. The positive predictive value of the tool is >90%. This tool significantly reduces delays in commencing treatment and avoid redundant photon vs. proton treatment plan comparison.

Abstract

Selection of head and neck cancer (HNC) patients for proton therapy (PT) using plan comparison (VMAT vs. IMPT) for each patient is labor-intensive. Our aim was to develop a decision support tool to identify patients with high probability to qualify for PT, at a very early stage (immediately after delineation) to avoid delay in treatment initiation. A total of 151 HNC patients were included, of which 106 (70%) patients qualified for PT. Linear regression models for individual OARs were created to predict the D_mean to the OARs for VMAT and IMPT plans. The predictors were OAR volume percentages overlapping with target volumes. Then, actual and predicted plan comparison decisions were compared. Actual and predicted OAR D_mean (VMAT R² = 0.953, IMPT R² = 0.975) and NTCP values (VMAT R² = 0.986, IMPT R² = 0.992) were highly correlated. The sensitivity, specificity, PPV and NPV of the decision support tool were 64%, 87%, 92% and 51%, respectively. The expected toxicity reduction with IMPT can be predicted using only the delineation data. The probability of qualifying for PT is >90% when the tool indicates a positive outcome for PT. This tool will contribute significantly to a more effective selection of HNC patients for PT at a much earlier stage, reducing treatment delay.

Fast, automated knowledge-based treatment planning for selecting patients for proton therapy based on normal tissue complication probabilities

Purpose

Selecting patients who will benefit from proton therapy is laborious and subjective. We demonstrate a novel automated solution for creating high-quality knowledge-based plans (KBPs) using proton and photon beams to identify patients for proton treatment based on their normal tissue complication probabilities (NTCP).

Methods and Materials

Two previously validated RapidPlan PT models for locally advanced head and neck cancer were used in combination with scripting to automatically create proton and photon KBPs for 72 patients with recent oropharynx cancer. NTCPs were calculated for each patient based on the KBPs, and patient selection was simulated according to the current Dutch national protocol.

Results

The photon/proton KBP exhibited good correlation between predicted and achieved organ-at-risk mean doses, with a ≤5 Gy difference in 208/196 out of 215 structures relevant for the head and neck cancer NTCP model. The proton KBPs yielded on average 7.1/6.1/7.6 Gy lower dose to salivary/swallowing structures/oral cavity than the photon KBPs. This reduced average grade 2/3 dysphagia and xerostomia by 7.1/3.3 and 5.5/2.0 percentage points, resulting in 16 of 72 patients (22%) being indicated for proton treatment. The entire automated process took <30 minutes per patient.

Conclusions

Automated support for decision making using KBP is feasible and fast. The planning solution has potential to speed up the planning and patient-selection process significantly without major compromises to the plan quality.

Current practice in proton therapy delivery in adult cancer patients across Europe

BACKGROUND AND PURPOSE

Major differences exist among proton therapy (PT) centres regarding PT delivery in adult cancer patient. To obtain insight into current practice in Europe, we performed a survey among European PT centres.

MATERIALS AND METHODS

We designed electronic questionnaires for eight tumour sites, focusing on four main topics: 1) indications and patient selection methods; 2) reimbursement; 3) on-going or planned studies, 4) annual number of patients treated with PT.

RESULTS

Of 22 centres, 19 (86%) responded. In total, 4233 adult patients are currently treated across Europe annually, of which 46% consists of patients with central nervous system tumours (CNS), 15% head and neck cancer (HNC), 15% prostate, 9% breast, 5% lung, 5% gastrointestinal, 4% lymphoma, 0.3% gynaecological cancers. CNS are treated in all participating centres (n = 19) using PT, HNC in 16 centres, lymphoma in 10 centres, gastrointestinal in 10 centres, breast in 7 centres, prostate in 6 centres, lung in 6 centres, and gynaecological cancers in 3 centres. Reimbursement is provided by national health care systems for the majority of commonly treated tumour sites. Approximately 74% of centres enrol patients for prospective data registration programs. Phase II-III trials are less frequent, due to reimbursement and funding problems. Reasons for not treating certain tumour types with PT are lack of evidence (30%), reimbursement issues (29%) and/or technical limitations (20%).

CONCLUSION

Across European PT centres, CNS tumours and HNC are the most frequently treated tumour types. Most centres use indication protocols. Lack of evidence for PT and reimbursement issues are the most reported reasons for not treating specific tumour types with PT.

A two-stage genome-wide association study of radiation-induced acute toxicity in head and neck cancer

BACKGROUND

Most head and neck cancer (HNC) patients receive radiotherapy (RT) and develop toxicities. This genome-wide association study (GWAS) was designed to identify single nucleotide polymorphisms (SNPs) associated with common acute radiation-induced toxicities (RITs) in an HNC cohort.

METHODS

A two-stage GWAS was performed in 1279 HNC patients treated with RT and prospectively scored for mucositis, xerostomia, sticky saliva, and dysphagia. The area under the curve (AUC) was used to estimate the average load of toxicity during RT. At the discovery study, multivariate linear regression was used in 957 patients, and the top-ranking SNPs were tested in 322 independent replication cohort. Next, the discovery and the replication studies were meta-analyzed.

RESULTS

A region on 5q21.3 containing 16 SNPs showed genome-wide (GW) significance association at P-value < 5.0 × 10-8 with patient-rated acute xerostomia in the discovery study. The top signal was rs35542 with an adjusted effect size of 0.17*A (95% CI 0.12 to 0.23; P-value <  = 3.78 × 10-9). The genome wide significant SNPs were located within three genes (EFNA5, FBXL17, and FER). In-silico functional analysis showed these genes may be involved in DNA damage response and co-expressed in minor salivary glands. We found 428 suggestive SNPs (P-value < 1.0 × 10-5) for other toxicities, taken to the replication study. Eleven of them showed a nominal association (P-value < 0.05).

CONCLUSIONS

This GWAS suggested novel SNPs for patient-rated acute xerostomia in HNC patients. If validated, these SNPs and their related functional pathways could lead to a predictive assay to identify sensitive patients to radiation, which may eventually allow a more individualized RT treatment.