HYpofractionated, dose-redistributed RAdiotherapy with protons and photons to combat radiation-induced immunosuppression in head and neck squamous cell carcinoma: study protocol of the phase I HYDRA trial.

BACKGROUND: Radiotherapy (RT) is the standard of care for most advanced head and neck squamous cell carcinoma (HNSCC) and results in an unfavorable 5-year overall survival of 40%. Despite strong biological rationale, combining RT with immune checkpoint inhibitors does not result in a survival benefit. Our hypothesis is that the combination of these individually effective treatments fails because of radiation-induced immunosuppression and lymphodepletion. By integrating modern radiobiology and innovative radiotherapy concepts, the patient's immune system could be maximally retained by (1) increasing the dose per fraction so that the total dose and number of fractions can be reduced (HYpofractionation), (2) redistributing the radiation dose towards a higher peak dose within the tumor center and a lowered elective lymphatic field dose (Dose-redistribution), and (3) using RAdiotherapy with protons instead of photons (HYDRA). METHODS: The primary aim of this multicenter study is to determine the safety of HYDRA proton- and photon radiotherapy by conducting two parallel phase I trials. Both HYDRA arms are randomized with the standard of care for longitudinal immune profiling. There will be a specific focus on actionable immune targets and their temporal patterns that can be tested in future hypofractionated immunoradiotherapy trials. The HYDRA dose prescriptions (in 20 fractions) are 40 Gy elective dose and 55 Gy simultaneous integrated boost on the clinical target volume with a 59 Gy focal boost on the tumor center. A total of 100 patients (25 per treatment group) will be recruited, and the final analysis will be performed one year after the last patient has been included. DISCUSSION: In the context of HNSCC, hypofractionation has historically only been reserved for small tumors out of fear for late normal tissue toxicity. To date, hypofractionated radiotherapy may also be safe for larger tumors, as both the radiation dose and volume can be reduced by the combination of advanced imaging for better target definition, novel accelerated repopulation models and high-precision radiation treatment planning and dose delivery. HYDRA's expected immune-sparing effect may lead to improved outcomes by allowing for future effective combination treatment with immunotherapy. TRIAL REGISTRATION: The trial is registered at ClinicalTrials.gov; NCT05364411 (registered on May 6th, 2022).

LINAC based stereotactic radiosurgery for multiple brain metastases: guidance for clinical implementation.

Introduction: Stereotactic radiosurgery (SRS) is a promising treatment option for patients with multiple brain metastases (BM). Recent technical advances have made LINAC based SRS a patient friendly technique, allowing for accurate patient positioning and a short treatment time. Since SRS is increasingly being used for patients with multiple BM, it remains essential that SRS be performed with the highest achievable quality in order to prevent unnecessary complications such as radionecrosis. The purpose of this article is to provide guidance for high-quality LINAC based SRS for patients with BM, with a focus on single isocenter non-coplanar volumetric modulated arc therapy (VMAT). Methods: The article is based on a consensus statement by the study coordinators and medical physicists of four trials which investigated whether patients with multiple BM are better palliated with SRS instead of whole brain radiotherapy (WBRT): A European trial (NCT02353000), two American trials and a Canadian CCTG lead intergroup trial (CE.7). This manuscript summarizes the quality assurance measures concerning imaging, planning and delivery. Results: To optimize the treatment, the interval between the planning-MRI (gadolinium contrast-enhanced, maximum slice thickness of 1.5 mm) and treatment should be kept as short as possible (< two weeks). The BM are contoured based on the planning-MRI, fused with the planning-CT. GTV-PTV margins are minimized or even avoided when possible. To maximize efficiency, the preferable technique is single isocenter (non-)coplanar VMAT, which delivers high doses to the target with maximal sparing of the organs at risk. The use of flattening filter free photon beams ensures a lower peripheral dose and shortens the treatment time. To bench mark SRS treatment plan quality, it is advisable to compare treatment plans between hospitals. Conclusion: This paper provides guidance for quality assurance and optimization of treatment delivery for LINAC-based radiosurgery for patients with multiple BM.

Improved effectiveness of stereotactic radiosurgery in large brain metastases by individualized isotoxic dose prescription: an in silico study.

INTRODUCTION: In large brain metastases (BM) with a diameter of more than 2 cm there is an increased risk of radionecrosis (RN) with standard stereotactic radiosurgery (SRS) dose prescription, while the normal tissue constraint is exceeded. The tumor control probability (TCP) with a single dose of 15 Gy is only 42%. This in silico study tests the hypothesis that isotoxic dose prescription (IDP) can increase the therapeutic ratio (TCP/Risk of RN) of SRS in large BM. MATERIALS AND METHODS: A treatment-planning study with 8 perfectly spherical and 46 clinically realistic gross tumor volumes (GTV) was conducted. The effects of GTV size (0.5-4 cm diameter), set-up margins (0, 1, and 2 mm), and beam arrangements (coplanar vs non-coplanar) on the predicted TCP using IDP were assessed. For single-, three-, and five-fraction IDP dose-volume constraints of V12Gy = 10 cm3, V19.2 Gy = 10 cm3, and a V20Gy = 20 cm3, respectively, were used to maintain a low risk of radionecrosis. RESULTS: In BM of 4 cm in diameter, the maximum achievable single-fraction IDP dose was 14 Gy compared to 15 Gy for standard SRS dose prescription, with respective TCPs of 32 and 42%. Fractionated SRS with IDP was needed to improve the TCP. For three- and five-fraction IDP, a maximum predicted TCP of 55 and 68% was achieved respectively (non-coplanar beams and a 1 mm GTV-PTV margin). CONCLUSIONS: Using three-fraction or five-fraction IDP the predicted TCP can be increased safely to 55 and 68%, respectively, in large BM with a diameter of 4 cm with a low risk of RN. Using IDP, the therapeutic ratio of SRS in large BM can be increased compared to current SRS dose prescription.

Survival after whole brain radiotherapy for brain metastases from lung cancer and breast cancer is poor in 6325 Dutch patients treated between 2000 and 2014.

BACKGROUND: Whole brain radiotherapy (WBRT) is considered standard of care for patients with multiple brain metastases or unfit for radical treatment modalities. Recent studies raised discussion about the expected survival after WBRT. Therefore, we analysed survival after WBRT for brain metastases 'in daily practice' in a large nationwide multicentre retrospective cohort. METHODS: Between 2000 and 2014, 6325 patients had WBRT (20 Gy in 4 Gy fractions) for brain metastases from non-small cell lung cancer (NSCLC; 4363 patients) or breast cancer (BC; 1962 patients); patients were treated in 15 out of 21 Dutch radiotherapy centres. Survival was calculated by the Kaplan-Meier method from the first day of WBRT until death as recorded in local hospital data registration or the Dutch Municipal Personal Records Database. FINDINGS: The median survival was 2.7 months for NSCLC and 3.7 months for BC patients (p < .001). For NSCLC patients aged <50, 50-60, 60-70 and >70 years, survival was 4.0, 3.0, 2.8 and 2.1 months, respectively (p < .001). For BC patients, survival was 4.5, 3.8, 3.2 and 2.9 months, respectively (p = .047). In multivariable analyses, higher age was related to poorer survival with hazard ratios (HR) for patients aged 50-60, 60-70 and >70 years being 1.05, 1.19 and 1.34, respectively. Primary BC (HR: 0.83) and female sex (HR: 0.85) were related to better survival (p < .001). INTERPRETATION: The survival of patients after WBRT for brain metastases from NSCLC treated in Dutch 'common radiotherapy practice' is poor, in breast cancer and younger patients it is disappointingly little better. These results are in line with the results presented in the QUARTZ trial and we advocate a much more restrictive use of WBRT. In patients with a more favourable prognosis the optimal treatment strategy remains to be determined. Prospective randomized trials and individualized prognostic models are needed to identify these patients and to tailor treatment.

Use of Systemic Therapy Concurrent With Cranial Radiotherapy for Cerebral Metastases of Solid Tumors.

The incidence of brain metastases of solid tumors is increasing. Local treatment of brain metastases is generally straightforward: cranial radiotherapy (e.g., whole-brain radiotherapy or stereotactic radiosurgery) or resection when feasible. However, treatment becomes more complex when brain metastases occur while other metastases, outside of the central nervous system, are being controlled with systemic therapy (chemotherapeutics, molecular targeted agents, or monoclonal antibodies). It is known that some anticancer agents can increase the risk for neurotoxicity when used concurrently with radiotherapy. Increased neurotoxicity decreases quality of life, which is undesirable in this predominantly palliative patient group. Therefore, it is of utmost importance to identify the compounds that should be temporarily discontinued when cranial radiotherapy is needed.This review summarizes the (neuro)toxicity data for combining systemic therapy (chemotherapeutics, molecular targeted agents, or monoclonal antibodies) with concurrent radiotherapy of brain metastases. Because only a limited amount of high-level data has been published, a risk assessment of each agent was done, taking into account the characteristics of each compound (e.g., lipophilicity) and the microenvironment of brain metastasis. The available trials suggest that only gemcitabine, erlotinib, and vemurafenib induce significant neurotoxicity when used concurrently with cranial radiotherapy. We conclude that for most systemic therapies, the currently available literature does not show an increase in neurotoxicity when these therapies are used concurrently with cranial radiotherapy. However, further studies are needed to confirm safety because there is no high-level evidence to permit definitive conclusions. The Oncologist 2017;22:222-235Implications for Practice: The treatment of symptomatic brain metastases diagnosed while patients are receiving systemic therapy continues to pose a dilemma to clinicians. Will concurrent treatment with cranial radiotherapy and systemic therapy (chemotherapeutics, molecular targeted agents, and monoclonal antibodies), used to control intra- and extracranial tumor load, increase the risk for neurotoxicity? This review addresses this clinically relevant question and evaluates the toxicity of combining systemic therapies with cranial radiotherapy, based on currently available literature, in order to determine the need to and interval to interrupt systemic treatment.

Whole brain radiotherapy versus stereotactic radiosurgery for 4-10 brain metastases: a phase III randomised multicentre trial.

BACKGROUND: Maintenance of quality of life is the primary goal during treatment of brain metastases (BM). This is a protocol of an ongoing phase III randomised multicentre study. This study aims to determine the exact additional palliative value of stereotactic radiosurgery (SRS) over whole brain radiotherapy (WBRT) in patients with 4-10 BM. METHODS: The study will include patients with 4-10 BM from solid primary tumours diagnosed on a high-resolution contrast-enhanced MRI scan with a maximum lesional diameter of 2.5 cm in any direction and a maximum cumulative lesional volume of 30 cm3. Patients will be randomised between WBRT in five fractions of 4 Gy to a total dose of 20 Gy (standard arm) and single dose SRS to the BMs (study arm) in the range of 15-24 Gy. The largest BM or a localisation in the brainstem will determine the prescribed SRS dose. The primary endpoint is difference in quality of life (EQ5D EUROQOL score) at 3 months after radiotherapy with regard to baseline. Secondary endpoints are difference in quality of life (EQ5D EUROQOL questionnaire) at 6, 9 and 12 months after radiotherapy with regard to baseline. Other secondary endpoints are at 3, 6, 9 and 12 months after radiotherapy survival, Karnofsky ≥ 70, WHO performance status, steroid use (mg), toxicity according to CTCAE V4.0 including hair loss, fatigue, brain salvage during follow-up, type of salvage, time to salvage after randomisation and Barthel index. Facultative secondary endpoints are neurocognition with the Hopkins verbal learning test revised, quality of life EORTC QLQ-C30, quality of life EORTC BN20 brain module and fatigue scale EORTC QLQ-FA13. DISCUSSION: Worldwide, most patients with more than 4 BM will be treated with WBRT. Considering the potential advantages of SRS over WBRT, i.e. limiting radiation doses to uninvolved brain and a high rate of local tumour control by just a single treatment with fewer side effects, such as hair loss and fatigue, compared to WBRT, SRS might be a suitable alternative for patients with 4-10 BM. TRIAL REGISTRATION: Trial registration number: NCT02353000 , trial registration date 15th January 2015, open for accrual 1st July 2016, nine patients were enrolled in this trial on 14th April 2017.

Modern clinical research: How rapid learning health care and cohort multiple randomised clinical trials complement traditional evidence based medicine.

BACKGROUND: Trials are vital in informing routine clinical care; however, current designs have major deficiencies. An overview of the various challenges that face modern clinical research and the methods that can be exploited to solve these challenges, in the context of personalised cancer treatment in the 21st century is provided. AIM: The purpose of this manuscript, without intending to be comprehensive, is to spark thought whilst presenting and discussing two important and complementary alternatives to traditional evidence-based medicine, specifically rapid learning health care and cohort multiple randomised controlled trial design. Rapid learning health care is an approach that proposes to extract and apply knowledge from routine clinical care data rather than exclusively depending on clinical trial evidence, (please watch the animation: http://youtu.be/ZDJFOxpwqEA). The cohort multiple randomised controlled trial design is a pragmatic method which has been proposed to help overcome the weaknesses of conventional randomised trials, taking advantage of the standardised follow-up approaches more and more used in routine patient care. This approach is particularly useful when the new intervention is a priori attractive for the patient (i.e. proton therapy, patient decision aids or expensive medications), when the outcomes are easily collected, and when there is no need of a placebo arm. DISCUSSION: Truly personalised cancer treatment is the goal in modern radiotherapy. However, personalised cancer treatment is also an immense challenge. The vast variety of both cancer patients and treatment options makes it extremely difficult to determine which decisions are optimal for the individual patient. Nevertheless, rapid learning health care and cohort multiple randomised controlled trial design are two approaches (among others) that can help meet this challenge.

Differences in the association of time to treatment initiation and survival according to various head and neck cancer sites in a nationwide cohort.

OBJECTIVES: To assess whether there are differences in the effects of time to treatment interval (TTI) on patient survival for head and neck cancer (HNC) sites in order to provide evidence that can support decision-making regarding prioritizing treatment. MATERIALS AND METHODS: Patients in the Netherlands with a first primary HNC without distant metastasis between 2010 and 2014 were included for analysis (N = 10,486). TTI was defined as the time from pathologic diagnosis to the start of initial treatment. Overall survival (OS), cox regression analyses and cubic spline hazard models were calculated and visualized. RESULTS: Overall, the hazard of dying was higher (HR = 1.003; 95 % CI 1.001-1.005) with each additional day until treatment initiation. The pattern, as visualized in cubic spline graphs, differed by site the hazard increased more steeply with increasing TTI for oral cavity cancer. For oropharyngeal and laryngeal cancer, a slight increase commenced after a longer TTI than for oral cavity cancer, while there was hardly an increase in hazard with increasing TTI for hypopharyngeal cancer. CONCLUSION: The relationship between longer TTI and decreased survival was confirmed, but slight variations in the pattern of the hazard of dying by TTI by tumour site were observed. These findings could support decisions on prioritizing treatment. However, other aspects such as extent of treatment and quality of life should be investigated further so this can also be included.

External validation of the lung-molGPA to predict survival in patients treated with stereotactic radiotherapy for brain metastases of non-small cell lung cancer.

BACKGROUND: In the era of personalized medicine, individualized prognostic models with tumor characteristics are needed to inform patients about survival. Before clinical use, external validation of such models by an independent group is needed. An updated version of the graded prognostic assessment (GPA) estimates survival in patients with brain metastases (BMs) of non-small cell lung cancer (NSCLC). This is the first external validation of the updated Lung-molGPA in patients treated with stereotactic radiotherapy (SRT) for one or more BMs. MATERIALS AND METHODS: Patients treated with SRT for BMs from NSCLC adenocarcinoma were retrospectively included. GPA score was calculated for each patient based on six prognostic factors including age, Karnofsky Performance Status, number of BMs, extracranial metastases, EGFR/ALK status, and PD-L1 expression. Kaplan-Meier analysis evaluated survival probability. Impact of individual prognostic factors on survival was assessed by univariate and multivariate analyses using the Cox proportional hazard model. Predictive performance was evaluated using discrimination (C-statistic) and calibration (Brier test). RESULTS: The cohort (n = 241) was divided into four prognostic groups. Overall median survival was 15 months. Predicted and observed median survival were similar between the original and validation cohorts, apart from the most favorable prognostic group. With adequate C-statistics and Brier scores, the Lung-molGPA provided accurate survival predictions. CONCLUSION: The Lung-molGPA accurately predicted survival in our European population, except for an overestimation of survival in the small most favorable prognostic group. This prognostic model was externally validated and is therefore useful for counseling of patients with BMs of NSCLC adenocarcinoma.

Recursive partitioning analysis for the prediction of stereotactic radiosurgery brain metastases lesion control.

PURPOSE: The objective of this investigation was to identify independent pretreatment factors that predict for control of local brain metastases (BM) in a large single-institution series of patients receiving stereotactic radiosurgery (SRS). Recursive partitioning analysis was used to potentially identify a class of patients with durable lesion control characteristics. METHODS: A retrospective SRS database containing baseline characteristics, treatment details, and follow-up data of newly diagnosed patients with 1-3 BM (on magnetic resonance imaging) treated with linear accelerator-based SRS was created. Three study endpoints were used: time to progression (primary endpoint, individual lesion progression; n = 536), time to first progression (secondary endpoint, first lesion progression on an individual patient basis; n = 380), and overall survival (secondary endpoint; n = 380). Recursive partitioning analysis (RPA) was performed to identify predictors of time to progression. RESULTS: Multivariable analysis demonstrated that lesion aspect/phenotype and radiotherapy schedule were independent factors associated with both progression outcomes. Presence of tumor necrosis was found to be associated with a significant hazard of progression (hazard ratio >3), whereas use of the most intense radiotherapy fractionation schedule (21 Gy in one fraction) was associated with significant reductions in progression (hazard ratio <0.3). RPA using SRS dose and lesion aspect/phenotype was created and described three distinct prognostic groups. CONCLUSIONS: RPA of a large retrospective database of patients receiving SRS confirmed previous observations regarding the importance of SRS dose and lesion aspect/phenotype in lesion control and overall survival. The SRS lesion analysis may help to stratify future clinical trials and better define patient care options and prognosis.

Predicting stereotactic radiosurgery outcomes with multi-observer qualitative appearance labelling versus MRI radiomics.

Qualitative observer-based and quantitative radiomics-based analyses of T1w contrast-enhanced magnetic resonance imaging (T1w-CE MRI) have both been shown to predict the outcomes of brain metastasis (BM) stereotactic radiosurgery (SRS). Comparison of these methods and interpretation of radiomics-based machine learning (ML) models remains limited. To address this need, we collected a dataset of n = 123 BMs from 99 patients including 12 clinical features, 107 pre-treatment T1w-CE MRI radiomic features, and BM post-SRS progression scores. A previously published outcome model using SRS dose prescription and five-way BM qualitative appearance scoring was evaluated. We found high qualitative scoring interobserver variability across five observers that negatively impacted the model's risk stratification. Radiomics-based ML models trained to replicate the qualitative scoring did so with high accuracy (bootstrap-corrected AUC = 0.84-0.94), but risk stratification using these replicated qualitative scores remained poor. Radiomics-based ML models trained to directly predict post-SRS progression offered enhanced risk stratification (Kaplan-Meier rank-sum p = 0.0003) compared to using qualitative appearance. The qualitative appearance scoring enabled interpretation of the progression radiomics-based ML model, with necrotic BMs and a subset of heterogeneous BMs predicted as being at high-risk of post-SRS progression, in agreement with current radiobiological understanding. Our study's results show that while radiomics-based SRS outcome models out-perform qualitative appearance analysis, qualitative appearance still provides critical insight into ML model operation.

Dual-center validation of using magnetic resonance imaging radiomics to predict stereotactic radiosurgery outcomes.

Background: MRI radiomic features and machine learning have been used to predict brain metastasis (BM) stereotactic radiosurgery (SRS) outcomes. Previous studies used only single-center datasets, representing a significant barrier to clinical translation and further research. This study, therefore, presents the first dual-center validation of these techniques. Methods: SRS datasets were acquired from 2 centers (n = 123 BMs and n = 117 BMs). Each dataset contained 8 clinical features, 107 pretreatment T1w contrast-enhanced MRI radiomic features, and post-SRS BM progression endpoints determined from follow-up MRI. Random decision forest models were used with clinical and/or radiomic features to predict progression. 250 bootstrap repetitions were used for single-center experiments. Results: Training a model with one center's dataset and testing it with the other center's dataset required using a set of features important for outcome prediction at both centers, and achieved area under the receiver operating characteristic curve (AUC) values up to 0.70. A model training methodology developed using the first center's dataset was locked and externally validated with the second center's dataset, achieving a bootstrap-corrected AUC of 0.80. Lastly, models trained on pooled data from both centers offered balanced accuracy across centers with an overall bootstrap-corrected AUC of 0.78. Conclusions: Using the presented validated methodology, radiomic models trained at a single center can be used externally, though they must utilize features important across all centers. These models' accuracies are inferior to those of models trained using each individual center's data. Pooling data across centers shows accurate and balanced performance, though further validation is required.

Early and late contrast enhancing lesions after photon radiotherapy for IDH mutated grade 2 diffuse glioma.

OBJECTIVE: The interpretation of new enhancing lesions after radiotherapy for diffuse glioma remains a clinical challenge. We sought to characterize and classify new contrast enhancing lesions in a historical multicenter cohort of patients with IDH mutated grade 2 diffuse glioma treated with photon therapy. METHODS: We reviewed all follow-up MRI's of all patients treated with radiotherapy for histologically confirmed, IDH mutated diffuse grade 2 glioma between 1-1-2007 and 31-12-2018 in two tertiary referral centers. Disease progression (PD) was defined in accordance with the RANO criteria for progressive disease in low grade glioma. Pseudoprogression (psPD) was defined as any transient contrast-enhancing lesion between the end of radiotherapy and PD, or any new contrast-enhancing lesion that remained stable over a period of 12 months in patients who did not exhibit PD. RESULTS: A total of 860 MRI's of 106 patients were reviewed. psPD was identified in 24 patients (23%) on 76 MRI's. The cumulative incidence of psPD was 13% at 1 year, 22% at 5 years, and 28% at 10 years. The mean of the observed maximal volume of psPD was 2.4 cc. The median Dmin in psPD lesions was 50.1 Gy. The presence of an 1p/19q codeletion was associated with an increased risk of psPD (subhazard ratio 2.34, p = 0.048). psPD was asymptomatic in 83% of patients. CONCLUSION: The cumulative incidence of psPD in grade 2 diffuse glioma increases over time. Consensus regarding event definition and statistical analysis is needed for comparisons between series investigating psPD.

Performance sensitivity analysis of brain metastasis stereotactic radiosurgery outcome prediction using MRI radiomics.

Recent studies have used T1w contrast-enhanced (T1w-CE) magnetic resonance imaging (MRI) radiomic features and machine learning to predict post-stereotactic radiosurgery (SRS) brain metastasis (BM) progression, but have not examined the effects of combining clinical and radiomic features, BM primary cancer, BM volume effects, and using multiple scanner models. To investigate these effects, a dataset of n = 123 BMs from 99 SRS patients with 12 clinical features, 107 pre-treatment T1w-CE radiomic features, and BM progression determined by follow-up MRI was used with a random decision forest model and 250 bootstrapped repetitions. Repeat experiments assessed the relative accuracy across primary cancer sites, BM volume groups, and scanner model pairings. Correction for accuracy imbalances across volume groups was investigated by removing volume-correlated features. We found that using clinical and radiomic features together produced the most accurate model with a bootstrap-corrected area under the receiver operating characteristic curve of 0.77. Accuracy also varied by primary cancer site, BM volume, and scanner model pairings. The effect of BM volume was eliminated by removing features at a volume-correlation coefficient threshold of 0.25. These results show that feature type, primary cancer, volume, and scanner model are all critical factors in the accuracy of radiomics-based prognostic models for BM SRS that must be characterised and controlled for before clinical translation.

Development and evaluation of an automated EPTN-consensus based organ at risk atlas in the brain on MRI.

BACKGROUND AND PURPOSE: During radiotherapy treatment planning, avoidance of organs at risk (OARs) is important. An international consensus-based delineation guideline was recently published with 34 OARs in the brain. We developed an MR-based OAR autosegmentation atlas and evaluated its performance compared to manual delineation. MATERIALS AND METHODS: Anonymized cerebral T1-weighted MR scans (voxel size 0.9 × 0.9 × 0.9 mm3) were available. OARs were manually delineated according to international consensus. Fifty MR scans were used to develop the autosegmentation atlas in a commercially available treatment planning system (Raystation®). The performance of this atlas was tested on another 40 MR scans by automatically delineating 34 OARs, as defined by the 2018 EPTN consensus. Spatial overlap between manual and automated delineations was determined by calculating the Dice similarity coefficient (DSC). Two radiation oncologists determined the quality of each automatically delineated OAR. The time needed to delineate all OARs manually or to adjust automatically delineated OARs was determined. RESULTS: DSC was ≥ 0.75 in 31 (91 %) out of 34 automated OAR delineations. Delineations were rated by radiation oncologists as excellent or good in 29 (85 %) out 34 OAR delineations, while 4 were rated fair (12 %) and 1 was rated poor (3 %). Interobserver agreement between the radiation oncologists ranged from 77-100 % per OAR. The time to manually delineate all OARs was 88.5 minutes, while the time needed to adjust automatically delineated OARs was 15.8 minutes. CONCLUSION: Autosegmentation of OARs enables high-quality contouring within a limited time. Accurate OAR delineation helps to define OAR constraints to mitigate serious complications and helps with the development of NTCP models.

Pre-treatment visualization of predicted radiation-induced acute alopecia in brain tumour patients.

BACKGROUND AND PURPOSE: Temporary alopecia is a common side-effect in brain tumour patients receiving cranial radiotherapy with a significant psychological burden for the affected patient. The purpose of this study was to generate a method in our treatment planning system (TPS) to visualize the expected radiation-induced alopecia 4 weeks after treatment, in order to inform the patients thereupon before the start of radiotherapy. MATERIAL AND METHODS: A pilot study was conducted in ten patients receiving hypo- (HF) or conventionally fractionated (CF) photon beam Volumetric Modulated Arc Therapy (VMAT) for an intracranial lesion. Dose calculations were correlated to visible alopecia four weeks after the end of treatment to create a structure predictive of alopecia in our TPS. These alopecia structures for both fractionation schedules were validated in two cohorts of 69 HF and 78 CF patients undergoing radiotherapy between 2016 and 2019. RESULTS: In the pilot cohort, a total physical dose of 4 Gy for HF and 12.6 Gy for CF radiotherapy were found to be predictive of alopecia 4 weeks after treatment. Applying these doses to our validation cohort, we found an accurate prediction of alopecia in 59/69 (86%) HF and 73/78 (96%) CF patients. For the total patient group of 147 patients, the predicted amount of alopecia was accurate in 90% of the cases. All inaccurate predictions overestimated the expected extent of alopecia. CONCLUSION: The presented straightforward method to visualize predicted alopecia 4 weeks after treatment has proven to predict the extent alopecia highly accurate in the vast majority of patients. Sharing these results with the patients pre-treatment may result in stress reduction before cranial irradiation.

Quality of life among patients with 4 to 10 brain metastases after treatment with whole-brain radiotherapy vs. stereotactic radiotherapy: a phase III, randomized, Dutch multicenter trial.

BACKGROUND: Stereotactic radiotherapy (SRT) is an attractive treatment option for patients with brain metastases (BM), sparing healthy brain tissue and likely controlling local tumors. Most previous studies have focused on radiological response or survival. Our randomized trial (NCT02353000) investigated whether quality of life (QoL) is better preserved using SRT than whole-brain radiotherapy (WBRT) for patients with multiple BM. Recently, we published our trial's primary endpoints. The current report discusses the study's secondary endpoints. METHODS: Patients with 4 to 10 BM were randomly assigned to a standard-arm WBRT (20 Gy in 5 fractions) or SRT group (1 fraction of 15-24 Gy or 3 fractions of 8 Gy). QoL endpoints-such as EQ5D domains post-treatment, the Barthel index, the European Organisation for Research and Treatment of Cancer (EORTC) questionnaires, and the neurocognitive Hopkins Verbal Learning Test-were evaluated. RESULTS: Due to poor accrual resulting from patients' and referrers' preference for SRT, this study closed prematurely. The other endpoints' results were published recently. Twenty patients were available for analysis (n=10 vs. n=10 for the two groups, respectively). Significant differences were observed 3 months post-treatment for the mobility (P=0.041), self-care (P=0.028), and alopecia (P=0.014) EQ5D domains, favoring SRT. This self-care score also persisted compared to the baseline (P=0.025). Multiple EORTC categories reflected significant differences, favoring SRT-particularly physical functioning and social functioning. CONCLUSIONS: For patients with multiple BM, SRT alone led to persistently higher QoL than treatment with WBRT. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02353000.

The European Particle Therapy Network (EPTN) consensus on the follow-up of adult patients with brain and skull base tumours treated with photon or proton irradiation.

PURPOSE: Treatment-related toxicity after irradiation of brain tumours has been underreported in the literature. Furthermore, there is considerable heterogeneity on how and when toxicity is evaluated. The aim of this European Particle Network (EPTN) collaborative project is to develop recommendations for uniform follow-up and toxicity scoring of adult brain tumour patients treated with radiotherapy. METHODS: A Delphi method-based consensus was reached among 24 international radiation-oncology experts in the field of neuro-oncology concerning the toxicity endpoints, evaluation methods and time points. RESULTS: In this paper, we present a basic framework for consistent toxicity scoring and follow-up, using multiple levels of recommendation. Level I includes all recommendations that are considered minimum of care, whereas level II and III are optional evaluations in the advanced clinical or research setting, respectively. Per outcome domain, the clinical endpoints and evaluation methods per level are listed. Where relevant, the organ at risk threshold doses for recommended referral to specific organ specialists are defined. CONCLUSION: These consensus-based recommendations for follow-up will enable the collection of uniform toxicity data of brain tumour patients treated with radiotherapy. With adoptation of this standard, collaboration will be facilitated and we can further propel the research field of radiation-induced toxicities relevant for these patients. An online tool to implement this guideline in clinical practice is provided at www.cancerdata.org.

Model based patient pre-selection for intensity-modulated proton therapy (IMPT) using automated treatment planning and machine learning.

BACKGROUND AND PURPOSE: Patient selection for intensity modulated proton therapy (IMPT), using comparative photon therapy planning, is workload-intensive and time-consuming. Pre-selection aims at avoidance of manual IMPT planning for patients that are in the end ineligible. We investigated the use of machine learning together with automated IMPT treatment planning for pre-selection of head and neck cancer patients, and validated the methodology for the Dutch model based selection (MBS) approach. MATERIALS & METHODS: For forty-five head and neck patients with a previous MBS, an IMPT plan was generated with non-clinical, fully-automated planning. Dosimetric differences of these plans with the corresponding previously generated photon plans, and the outcomes of the former MBS, were used to train a Gaussian naïve Bayes classifier for MBS outcome prediction. During training, strong emphasis was placed on avoiding misclassification of IMPT eligible patients (i.e. false negatives). RESULTS: Pre-selection with the classifier resulted in 0 false negatives, 12 (27%) true negatives, 27 (60%) true positives, and only 6 (13%) false positive predictions. Using this pre-selection, the number of formal selection procedures with involved manual IMPT planning that resulted in a negative outcome could be reduced by 67%. CONCLUSION: With pre-selection, using machine learning and automated treatment planning, the percentage of patients with unnecessary manual IMPT planning for MBS could be drastically reduced, thereby saving costs, labor and time. With the developed approach, larger patient populations can be screened, and likely bias in pre-selection of patients can be mitigated by assisting the physician during patient pre-selection.

Quality of Automated Stereotactic Radiosurgery Plans in Patients with 4 to 10 Brain Metastases.

The purpose was to compare linac-based stereotactic radiosurgery and hypofractionated radiotherapy plan quality of automated planning, intensity modulated radiotherapy (IMRT) and manual dynamic conformal arc (DCA) plans as well as single- and multiple-isocenter techniques for multiple brain metastases (BM). For twelve patients with four to ten BM, seven non-coplanar linac-based plans were created: a manually planned DCA plan with a separate isocenter for each metastasis, a single-isocenter dynamic IMRT plan, an automatically generated single-isocenter volumetric modulated arc radiotherapy (VMAT) plan, four automatically generated single-isocenter DCA plans with three or five couch angles, with high or low sparing of normal tissue. Paddick conformity index, gradient index (GI), mean dose, total V12Gy and V5Gy of uninvolved brain, number of monitor units (MUs), irradiation time and pass rate were compared. The GI was significantly higher for VMAT than for separate-isocenter, IMRT, and all automatically generated plans. The number of MUs was lowest for VMAT, followed by automatically generated DCA and IMRT plans and highest for manual DCA plans. Irradiation time was the shortest for automatically planned DCA plans. Automatically generated linac-based single-isocenter plans for multiple BM reduce the number of MUs and irradiation time with at least comparable GI and V5Gy relative to the reference separate-isocenter DCA plans.