Intra-operative extracorporeal irradiation of tumour-invaded craniotomy bone flap in meningioma: a case series.

BACKGROUND: Extracorporeal irradiation of tumorous calvaria (EITC) can be performed to restore function and form of the skull after resection of bone-invasive meningioma. We sought to examine the rate of tumour recurrence and other selected outcomes in patients undergoing meningioma resection and EITC. METHODS: Retrospective single-centre study of adult patients undergoing meningioma resection and EITC between January 2015 and November 2022 at a tertiary neurosurgical centre. Patient demographics, surgery data, tumour data, use of adjuvant therapy, surgical complications, and tumour recurrences were collected. RESULTS: Eighteen patients with 11 (61%) CNS WHO grade 1, 6 (33%) grade 2, and 1 (6%) grade 3 meningiomas were included. Median follow-up was 42 months (range 3-88). Five (28%) patients had a recurrence, but none were associated with the bone flap. Two (11%) wound infections requiring explant surgery occurred. Six (33%) patients required a further operation. Two operations were for recurrences, one was for infection, one was a washout and wound exploration but no evidence of infection was found, one patient requested the removal of a small titanium implant, and one patient required a ventriculoperitoneal shunt for a persistent CSF collection. There were no cases of bone flap resorption and cosmetic outcome was not routinely recorded. CONCLUSION: EITC is feasible and fast to perform with good outcomes and cost-effectiveness compared to other reconstructive methods. We observed similar recurrence rates and lower infection rates requiring explant compared to the largest series of cranioplasty in meningioma. Cosmetic outcome is universally under-reported and should be reported in future studies.

Sub-regional analysis of the parotid glands: model development for predicting late xerostomia with radiomics features in head and neck cancer patients.

BACKGROUND: The irradiation of sub-regions of the parotid has been linked to xerostomia development in patients with head and neck cancer (HNC). In this study, we compared the xerostomia classification performance of radiomics features calculated on clinically relevant and de novo sub-regions of the parotid glands of HNC patients. MATERIAL AND METHODS: All patients (N = 117) were treated with TomoTherapy in 30-35 fractions of 2-2.167 Gy per fraction with daily mega-voltage-CT (MVCT) acquisition for image-guidance purposes. Radiomics features (N = 123) were extracted from daily MVCTs for the whole parotid gland and nine sub-regions. The changes in feature values after each complete week of treatment were considered as predictors of xerostomia (CTCAEv4.03, grade ≥ 2) at 6 and 12 months. Combinations of predictors were generated following the removal of statistically redundant information and stepwise selection. The classification performance of the logistic regression models was evaluated on train and test sets of patients using the Area Under the Curve (AUC) associated with the different sub-regions at each week of treatment and benchmarked with the performance of models solely using dose and toxicity at baseline. RESULTS: In this study, radiomics-based models predicted xerostomia better than standard clinical predictors. Models combining dose to the parotid and xerostomia scores at baseline yielded an AUCtest of 0.63 and 0.61 for xerostomia prediction at 6 and 12 months after radiotherapy while models based on radiomics features extracted from the whole parotid yielded a maximum AUCtest of 0.67 and 0.75, respectively. Overall, across sub-regions, maximum AUCtest was 0.76 and 0.80 for xerostomia prediction at 6 and 12 months. Within the first two weeks of treatment, the cranial part of the parotid systematically yielded the highest AUCtest. CONCLUSION: Our results indicate that variations of radiomics features calculated on sub-regions of the parotid glands can lead to earlier and improved prediction of xerostomia in HNC patients.

The suitability of micronuclei as markers of relative biological effect.

Micronucleus (MN) formation is routinely used as a biodosimeter for radiation exposures and has historically been used as a measure of DNA damage in cells. Strongly correlating with dose, MN are also suggested to indicate radiation quality, differentiating between particle and photon irradiation. The "gold standard" for measuring MN formation is Fenech's cytokinesis-block micronucleus (CBMN) cytome assay, which uses the cytokinesis blocking agent cytochalasin-B. Here, we present a comprehensive analysis of the literature investigating MN induction trends in vitro, collating 193 publications, with 2476 data points. Data were collected from original studies that used the CBMN assay to quantify MN in response to ionizing radiation in vitro. Overall, the meta-analysis showed that individual studies mostly have a linear increase of MN with dose [85% of MN per cell (MNPC) datasets and 89% of percentage containing MN (PCMN) datasets had an R2 greater than 0.90]. However, there is high variation between studies, resulting in a low R2 when data are combined (0.47 for MNPC datasets and 0.60 for PCMN datasets). Particle type, species, cell type, and cytochalasin-B concentration were suggested to influence MN frequency. However, variation in the data meant that the effects could not be strongly correlated with the experimental parameters investigated. There is less variation between studies when comparing the PCMN rather than the number of MNPC. Deviation from CBMN protocol specified timings did not have a large effect on MN induction. However, further analysis showed less variation between studies following Fenech's protocol closely, which provided more reliable results. By limiting the cell type and species as well as only selecting studies following the Fenech protocol, R2 was increased to 0.64 for both measures. We therefore determine that due to variation between studies, MN are currently a poor predictor of radiation-induced DNA damage and make recommendations for futures studies assessing MN to improve consistency between datasets.

Radiogenomics: the search for genetic predictors of radiotherapy response.

'Radiogenomics' is the study of genetic variation associated with response to radiotherapy. Radiogenomics aims to uncover the genes and biologic pathways responsible for radiotherapy toxicity that could be targeted with radioprotective agents and; identify genetic markers that can be used in risk prediction models in the clinic. The long-term goal of the field is to develop single nucleotide polymorphism-based risk models that can be used to stratify patients to more precisely tailored radiotherapy protocols. The field has evolved over the last two decades in parallel with advances in genomics, moving from narrowly focused candidate gene studies to large, collaborative genome-wide association studies. Several confirmed genetic variants have been identified and the field is making progress toward clinical translation.

Radiotherapy intensification for atypical and malignant meningiomas: A systematic review.

Background: The outcomes of nonbenign (WHO Grades 2 and 3 [G2, G3]) meningiomas are suboptimal and radiotherapy (RT) dose intensification strategies have been investigated. The purpose of this review is to report on clinical practice and outcomes with particular attention to RT doses and techniques. Methods: The PICO criteria (Population, Intervention, Comparison, and Outcomes) were used to frame the research question, directed at outlining the clinical outcomes in patients with G2-3 meningiomas treated with RT. The same search strategy was run in Embase and MEDLINE and, after deduplication, returned 1 807 records. These were manually screened for relevance and 25 were included. Results: Tumor outcomes and toxicities are not uniformly reported in the selected studies since different endpoints and time points have been used by different authors. Many risk factors for worse outcomes are described, the most common being suboptimal RT. This includes no or delayed RT, low doses, and older techniques. A positive association between RT dose and progression-free survival (PFS) has been highlighted by analyzing the studies in this review (10/25) that report the same endpoint (5y-PFS). Conclusions: This literature review has shown that standard practice RT leads to suboptimal tumor control rates in G2-3 meningiomas, with a significant proportion of disease recurring after a relatively short follow-up. Randomized controlled trials are needed in this setting to define the optimal RT approach. Given the increasing data to suggest a benefit of higher RT doses for high-risk meningiomas, novel RT technologies with highly conformal dose distributions are preferential to achieve optimal target coverage and organs at risk sparing.

Independent validation of genes and polymorphisms reported to be associated with radiation toxicity: a prospective analysis study.

BACKGROUND: Several studies have reported associations between radiation toxicity and single nucleotide polymorphisms (SNPs) in candidate genes. Few associations have been tested in independent validation studies. This prospective study aimed to validate reported associations between genotype and radiation toxicity in a large independent dataset. METHODS: 92 (of 98 attempted) SNPs in 46 genes were successfully genotyped in 1613 patients: 976 received adjuvant breast radiotherapy in the Cambridge breast IMRT trial (ISRCTN21474421, n=942) or in a prospective study of breast toxicity at the Christie Hospital, Manchester, UK (n=34). A further 637 received radical prostate radiotherapy in the MRC RT01 multicentre trial (ISRCTN47772397, n=224) or in the Conventional or Hypofractionated High Dose Intensity Modulated Radiotherapy for Prostate Cancer (CHHiP) trial (ISRCTN97182923, n=413). Late toxicity was assessed 2 years after radiotherapy with a validated photographic technique (patients with breast cancer only), clinical assessment, and patient questionnaires. Association tests of genotype with overall radiation toxicity score and individual endpoints were undertaken in univariate and multivariable analyses. At a type I error rate adjusted for multiple testing, this study had 99% power to detect a SNP, with minor allele frequency of 0·35, associated with a per allele odds ratio of 2·2. FINDINGS: None of the previously reported associations were confirmed by this study, after adjustment for multiple comparisons. The p value distribution of the SNPs tested against overall toxicity score was not different from that expected by chance. INTERPRETATION: We did not replicate previously reported late toxicity associations, suggesting that we can essentially exclude the hypothesis that published SNPs individually exert a clinically relevant effect. Continued recruitment of patients into studies within the Radiogenomics Consortium is essential so that sufficiently powered studies can be done and methodological challenges addressed. FUNDING: Cancer Research UK, The Royal College of Radiologists, Addenbrooke's Charitable Trust, Breast Cancer Campaign, Cambridge National Institute of Health Research (NIHR) Biomedical Research Centre, Experimental Cancer Medicine Centre, East Midlands Innovation, the National Cancer Institute, Joseph Mitchell Trust, Royal Marsden NHS Foundation Trust, Institute of Cancer Research NIHR Biomedical Research Centre for Cancer.

The use of radiotherapy, surgery and chemotherapy in the curative treatment of cancer: results from the FORTY (Favourable Outcomes from RadioTherapY) project.

OBJECTIVES: Radiotherapy, surgery and chemotherapy play key roles in the curative treatment of cancer, alone and in combination. Quantifying their roles is essential for equipment provision and workforce planning. The estimate that 40% of cancer patients are cured by RT has been used extensively to inform and influence policy but is relatively old and warrants review. METHODS: Patient, tumour and treatment event data was obtained for the 5 year period from 2009 to 2013, allowing a further 5 years for survival outcomes to be known. We analysed patient-level data on utilisation of surgery, radiotherapy, and chemotherapy in cancer patients in England. Data were sourced from Public Health England, using National Cancer Registrations, the National Radiotherapy Dataset (RTDS) and the Systemic Anti-Cancer Therapy Dataset (SACT). All tumour sites (excluding C44) and ages were included. We analysed three cohorts: all patients [n = 1,029,569], patients who survived 5 years or more [n = 537,970] and patients who survived <5 years [n = 491,599]. RESULTS: Overall cancer-specific 5-year survival was 52%, and in those patients, surgery was the most common curative treatment, with 80% receiving surgery, alone or in combination; radiotherapy was delivered to 39% and chemotherapy to 29%; 45% received two and 13% all three modalities. CONCLUSIONS: The high proportion receiving multi-modality treatment emphasises the importance of integrated, resourced, multidisciplinary cancer care. Radiotherapy was delivered to almost 40% of patients who survived 5 years which underlines its importance in cancer management. ADVANCES IN KNOWLEDGE: The results are essential in planning cancer services. They also inform the public health narrative.

Machine-learning with region-level radiomic and dosimetric features for predicting radiotherapy-induced rectal toxicities in prostate cancer patients.

BACKGROUND AND PURPOSE: This study aims to build machine learning models to predict radiation-induced rectal toxicities for three clinical endpoints and explore whether the inclusion of radiomic features calculated on radiotherapy planning computerised tomography (CT) scans combined with dosimetric features can enhance the prediction performance. MATERIALS AND METHODS: 183 patients recruited to the VoxTox study (UK-CRN-ID-13716) were included. Toxicity scores were prospectively collected after 2 years with grade ≥ 1 proctitis, haemorrhage (CTCAEv4.03); and gastrointestinal (GI) toxicity (RTOG) recorded as the endpoints of interest. The rectal wall on each slice was divided into 4 regions according to the centroid, and all slices were divided into 4 sections to calculate region-level radiomic and dosimetric features. The patients were split into a training set (75%, N = 137) and a test set (25%, N = 46). Highly correlated features were removed using four feature selection methods. Individual radiomic or dosimetric or combined (radiomic + dosimetric) features were subsequently classified using three machine learning classifiers to explore their association with these radiation-induced rectal toxicities. RESULTS: The test set area under the curve (AUC) values were 0.549, 0.741 and 0.669 for proctitis, haemorrhage and GI toxicity prediction using radiomic combined with dosimetric features. The AUC value reached 0.747 for the ensembled radiomic-dosimetric model for haemorrhage. CONCLUSIONS: Our preliminary results show that region-level pre-treatment planning CT radiomic features have the potential to predict radiation-induced rectal toxicities for prostate cancer. Moreover, when combined with region-level dosimetric features and using ensemble learning, the model prediction performance slightly improved.

Assessing the generalisability of radiomics features previously identified as predictive of radiation-induced sticky saliva and xerostomia.

Background and purpose: While core to the scientific approach, reproducibility of experimental results is challenging in radiomics studies. A recent publication identified radiomics features that are predictive of late irradiation-induced toxicity in head and neck cancer (HNC) patients. In this study, we assessed the generalisability of these findings. Materials and Methods: The procedure described in the publication in question was applied to a cohort of 109 HNC patients treated with 50-70 Gy in 20-35 fractions using helical radiotherapy although there were inherent differences between the two patient populations and methodologies. On each slice of the planning CT with delineated parotid and submandibular glands, the imaging features that were previously identified as predictive of moderate-to-severe xerostomia and sticky saliva 12 months post radiotherapy (Xer12m and SS12m) were calculated. Specifically, Short Run Emphasis (SRE) and maximum CT intensity (maxHU) were evaluated for improvement in prediction of Xer12m and SS12m respectively, compared to models solely using baseline toxicity and mean dose to the salivary glands. Results: None of the associations previously identified as statistically significant and involving radiomics features in univariate or multivariate models could be reproduced on our cohort. Conclusion: The discrepancies observed between the results of the two studies delineate limits to the generalisability of the previously reported findings. This may be explained by the differences in the approaches, in particular the imaging characteristics and subsequent methodological implementation. This highlights the importance of external validation, high quality reporting guidelines and standardisation protocols to ensure generalisability, replication and ultimately clinical implementation.

Large-scale meta-genome-wide association study reveals common genetic factors linked to radiation-induced acute toxicities across cancer types.

BACKGROUND: This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity across 4 cancer types (prostate, head and neck, breast, and lung). METHODS: A genome-wide association study meta-analysis was performed using 19 cohorts totaling 12 042 patients. Acute standardized total average toxicity (STATacute) was modelled using a generalized linear regression model for additive effect of genetic variants, adjusted for demographic and clinical covariates (rSTATacute). Linkage disequilibrium score regression estimated shared single-nucleotide variation (SNV-formerly SNP)-based heritability of rSTATacute in all patients and for each cancer type. RESULTS: Shared SNV-based heritability of STATacute among all cancer types was estimated at 10% (SE = 0.02) and was higher for prostate (17%, SE = 0.07), head and neck (27%, SE = 0.09), and breast (16%, SE = 0.09) cancers. We identified 130 suggestive associated SNVs with rSTATacute (5.0 × 10‒8 < P < 1.0 × 10‒5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size ‒0.17; P = 1.7 × 10‒7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified 'RNA splicing via endonucleolytic cleavage and ligation' (P = 5.1 × 10‒6, P = .079 corrected) as the top gene set associated with rSTATacute among all patients. In silico gene expression analysis showed that the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed P = .004 corrected; sun exposed P = .026 corrected). CONCLUSIONS: There is shared SNV-based heritability for acute radiation-induced toxicity across and within individual cancer sites. Future meta-genome-wide association studies among large radiation therapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.

Predicting radiotherapy-induced xerostomia in head and neck cancer patients using day-to-day kinetics of radiomics features.

Background and purpose: The images acquired during radiotherapy for image-guidance purposes could be used to monitor patient-specific response to irradiation and improve treatment personalisation. We investigated whether the kinetics of radiomics features from daily mega-voltage CT image-guidance scans (MVCT) improve prediction of moderate-to-severe xerostomia compared to dose/volume parameters in radiotherapy of head-and-neck cancer (HNC). Materials and Methods: All included HNC patients (N = 117) received 30 or more fractions of radiotherapy with daily MVCTs. Radiomics features were calculated on the contra-lateral parotid glands of daily MVCTs. Their variations over time after each complete week of treatment were used to predict moderate-to-severe xerostomia (CTCAEv4.03 grade ≥ 2) at 6, 12 and 24 months post-radiotherapy. After dimensionality reduction, backward/forward selection was used to generate combinations of predictors.Three types of logistic regression model were generated for each follow-up time: 1) a pre-treatment reference model using dose/volume parameters, 2) a combination of dose/volume and radiomics-based predictors, and 3) radiomics-based predictors. The models were internally validated by cross-validation and bootstrapping and their performance evaluated using Area Under the Curve (AUC) on separate training and testing sets. Results: Moderate-to-severe xerostomia was reported by 46 %, 33 % and 26 % of the patients at 6, 12 and 24 months respectively. The selected models using radiomics-based features extracted at or before mid-treatment outperformed the dose-based models with an AUCtrain/AUCtest of 0.70/0.69, 0.76/0.74, 0.86/0.86 at 6, 12 and 24 months, respectively. Conclusion: Our results suggest that radiomics features calculated on MVCTs from the first half of the radiotherapy course improve prediction of moderate-to-severe xerostomia in HNC patients compared to a dose-based pre-treatment model.

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.

No Association Between Polygenic Risk Scores for Cancer and Development of Radiation Therapy Toxicity.

PURPOSE: Our aim was to test whether updated polygenic risk scores (PRS) for susceptibility to cancer affect risk of radiation therapy toxicity. METHODS AND MATERIALS: Analyses included 9,717 patients with breast (n=3,078), prostate (n=5,748) or lung (n=891) cancer from Radiogenomics and REQUITE Consortia cohorts. Patients underwent potentially curative radiation therapy and were assessed prospectively for toxicity. Germline genotyping involved genome-wide single nucleotide polymorphism (SNP) arrays with nontyped SNPs imputed. PRS for each cancer were generated by summing literature-identified cancer susceptibility risk alleles: 352 breast, 136 prostate, and 24 lung. Weighted PRS were generated using log odds ratio (ORs) for cancer susceptibility. Standardized total average toxicity (STAT) scores at 2 and 5 years (breast, prostate) or 6 to 12 months (lung) quantified toxicity. Primary analysis tested late STAT, secondary analyses investigated acute STAT, and individual endpoints and SNPs using multivariable regression. RESULTS: Increasing PRS did not increase risk of late toxicity in patients with breast (OR, 1.000; 95% confidence interval [CI], 0.997-1.002), prostate (OR, 0.99; 95% CI, 0.98-1.00; weighted PRS OR, 0.93; 95% CI, 0.83-1.03), or lung (OR, 0.93; 95% CI, 0.87-1.00; weighted PRS OR, 0.68; 95% CI, 0.45-1.03) cancer. Similar results were seen for acute toxicity. Secondary analyses identified rs138944387 associated with breast pain (OR, 3.05; 95% CI, 1.86-5.01; P = 1.09 × 10-5) and rs17513613 with breast edema (OR, 0.94; 95% CI, 0.92-0.97; P = 1.08 × 10-5). CONCLUSIONS: Patients with increased polygenic predisposition to breast, prostate, or lung cancer can safely undergo radiation therapy with no anticipated excess toxicity risk. Some individual SNPs increase the likelihood of a specific toxicity endpoint, warranting validation in independent cohorts and functional studies to elucidate biologic mechanisms.

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.

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.

50 years of radiotherapy research: Evolution, trends and lessons for the future.

Rapid and relentless technological advances in an ever-more globalized world have shaped the field of radiation oncology in which we practise today. These developments have drastically modified the habitus1 of health professionals and researchers at an individual and organisational level. In this article we present an analysis of trends in radiation oncology research over the last half a century. To do so, the data from >350,000 scientific publications pertaining to a yearly search of the PubMed database with the keywords cancer radiotherapy was analysed. This analysis revealed that, over the years, radiotherapy research output has declined relative to alternative cancer therapies, representing 64% in 1970 it decreased to 31% in 2019. Also, the pace of research has significantly accelerated with, in the last 15 years, a doubling in the number of articles published by the 10% most productive researchers. Researchers are also facing stronger competition today with a proportion of first authors that will never get to publish as a last author increasing steadily from 58% in 1970 to 84% in 2000. Additionally, radiotherapy research output is extremely unequally distributed in the world, with Africa and South America contributing to ∼3% of radiotherapy articles in 2019 while representing 23% of the world's population. This disparity, reflecting economic situations and radiotherapy capabilities, has a knock-on effect for the provision of routine clinical treatment. Since research activity is inherent to delivery of high quality clinical care, this contributes to the global inequity of radiotherapy services. Learning from these trends is crucial for the future not only of radiation oncology research but also for effective and equitable cancer care.

Does the uncertainty in relative biological effectiveness affect patient treatment in proton therapy?

Clinical treatment with protons uses the concept of relative biological effectiveness (RBE) to convert the absorbed dose into an RBE-weighted dose that equals the dose for radiotherapy with photons causing the same biological effect. Currently, in proton therapy a constant RBE of 1.1 is generically used. However, empirical data indicate that the RBE is not constant, but increases at the distal edge of the proton beam. This increase in RBE is of concern, as the clinical impact is still unresolved, and clinical studies demonstrating a clinical effect of an increased RBE are emerging. Within the European Particle Therapy Network (EPTN) work package 6 on radiobiology and RBE, a workshop was held in February 2020 in Manchester with one day of discussion dedicated to the impact of proton RBE in a clinical context. Current data on RBE effects, patient outcome and modelling from experimental as well as clinical studies were presented and discussed. Furthermore, representatives from European clinical proton therapy centres, who were involved in patient treatment, laid out their current clinical practice on how to consider the risk of a variable RBE in their centres. In line with the workshop, this work considers the actual impact of RBE issues on patient care in proton therapy by reviewing preclinical data on the relation between linear energy transfer (LET) and RBE, current clinical data sets on RBE effects in patients, and applied clinical strategies to manage RBE uncertainties. A better understanding of the variability in RBE would allow development of proton treatments which are safer and more effective.

Update of the EPTN atlas for CT- and MR-based contouring in Neuro-Oncology.

BACKGROUND AND PURPOSE: To update the digital online atlas for organs at risk (OARs) delineation in neuro-oncology based on high-quality computed tomography (CT) and magnetic resonance (MR) imaging with new OARs. MATERIALS AND METHODS: In this planned update of the neurological contouring atlas published in 2018, ten new clinically relevant OARs were included, after thorough discussion between experienced neuro-radiation oncologists (RTOs) representing 30 European radiotherapy-oncology institutes. Inclusion was based on daily practice and research requirements. Consensus was reached for the delineation after critical review. Contouring was performed on registered CT with intravenous (IV) contrast (soft tissue & bone window setting) and 3 Tesla (T) MRI (T1 with gadolinium & T2 FLAIR) images of one patient (1 mm slices). For illustration purposes, delineation on a 7 T MRI without IV contrast from a healthy volunteer was added. OARs were delineated by three experienced RTOs and a neuroradiologist based on the relevant literature. RESULTS: The presented update of the neurological contouring atlas was reviewed and approved by 28 experts in the field. The atlas is available online and includes in total 25 OARs relevant to neuro-oncology, contoured on CT and MRI T1 and FLAIR (3 T & 7 T). Three-dimensional (3D) rendered films are also available online. CONCLUSION: In order to further decrease inter- and intra-observer OAR delineation variability in the field of neuro-oncology, we propose the use of this contouring atlas in photon and particle therapy, in clinical practice and in the research setting. The updated atlas is freely available on www.cancerdata.org.

A mathematical model of brain tumour response to radiotherapy and chemotherapy considering radiobiological aspects.

Glioblastoma is the most frequent and malignant brain tumour. For many years, the conventional treatment has been maximal surgical resection followed by radiotherapy (RT), with a median survival time of less than 10 months. Previously, the use of adjuvant chemotherapy (given after RT) has failed to demonstrate a statistically significant survival advantage. Recently, a randomized phase III trial has confirmed the benefit of temozolomide (TMZ) and has defined a new standard of care for the treatment of patients with high-grade brain tumours. The results showed an increase of 2.5 months in median survival, and 16.1% in 2 year survival, for patients receiving RT with TMZ compared with RT alone. It is not clear whether the major benefit of TMZ comes from either concomitant administration of TMZ with RT, or from six cycles of adjuvant TMZ, or both. The objectives were to develop our original model, which addressed survival after RT, to construct a new module to assess the potential role of TMZ from clinical data, and to explore its synergistic contribution in addition to radiation. The model has been extended to include radiobiological parameters. The addition of the linear quadratic equation to describe cellular response to treatment has enabled us to quantify the effects of radiation and TMZ in radiobiological terms. The results indicate that the model achieves an excellent fit to the clinical data, with the assumption that TMZ given concomitantly with RT synergistically increases radiosensitivity. The alternative, that the effect of TMZ is due only to direct cell killing, does not fit the clinical data so well. The addition of concomitant TMZ appears to change the radiobiological parameters. This aspect of our results suggests possible treatment developments. Our observations need further evaluations in real clinical trials, may suggest treatment strategies for new trials, and inform their design.

Associations between voxel-level accumulated dose and rectal toxicity in prostate radiotherapy.

BACKGROUND AND PURPOSE: Associations between dose and rectal toxicity in prostate radiotherapy are generally poorly understood. Evaluating spatial dose distributions to the rectal wall (RW) may lead to improvements in dose-toxicity modelling by incorporating geometric information, masked by dose-volume histograms. Furthermore, predictive power may be strengthened by incorporating the effects of interfraction motion into delivered dose calculations.Here we interrogate 3D dose distributions for patients with and without toxicity to identify rectal subregions at risk (SRR), and compare the discriminatory ability of planned and delivered dose. MATERIAL AND METHODS: Daily delivered dose to the rectum was calculated using image guidance scans, and accumulated at the voxel level using biomechanical finite element modelling. SRRs were statistically determined for rectal bleeding, proctitis, faecal incontinence and stool frequency from a training set (n = 139), and tested on a validation set (n = 47). RESULTS: SRR patterns differed per endpoint. Analysing dose to SRRs improved discriminative ability with respect to the full RW for three of four endpoints. Training set AUC and OR analysis produced stronger toxicity associations from accumulated dose than planned dose. For rectal bleeding in particular, accumulated dose to the SRR (AUC 0.76) improved upon dose-toxicity associations derived from planned dose to the RW (AUC 0.63). However, validation results could not be considered significant. CONCLUSIONS: Voxel-level analysis of dose to the RW revealed SRRs associated with rectal toxicity, suggesting non-homogeneous intra-organ radiosensitivity. Incorporating spatial features of accumulated delivered dose improved dose-toxicity associations. This may be an important tool for adaptive radiotherapy in the future.