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Background/purpose: Post radiation mucosal ulcers (PRMU) after treatment for oropharyngeal squamous cell carcinoma (OPSCC) can have a huge negative impact on patients’ quality of life, but little is known concerning risk factors and the impact of fraction size. Therefore, the goal of this study was to determine the pattern of PRMU development and to identify risk factors after a hypofractionated stereotactic body radiotherapy boost (SBRT) compared to conventionally fractionated radiotherapy for OPSCC. Material and methods: We performed a retrospective cohort study (N = 332) of OPSCC patients with ≥ 1-year disease-free survival, treated with 46 Gy Intensity Modulated Radiotherapy (IMRT) (2 Gy fractions) followed by either an SBRT boost of 16.5 Gy (5.5 Gy fractions) (N = 180), or 24 Gy IMRT (2 Gy fractions) (N = 152). PRMU (grade ≥ 2) was scored when observed > three months after the last radiotherapy (RT) fraction (CTCAE v5.0). Potential risk factors were analyzed with Cox regression models using death as competing risk. Dose at the PRMU site was calculated by projecting delineated PRMU on the planning CT. Results: All cases of PRMU (N = 64) occurred within 24 months; all were grade 2. The cumulative incidence at 2 years in the SBRT boost group was 26% (N = 46) vs. 12% (N = 18) for conventional fractionation (p = 0.003). Most PRMU developed within nine months (N = 48). PRMU occurring > nine months (N = 16) were mainly observed in the SBRT boost group (N = 15). Sex (p = 0.048), acute tube feeding (p = < 0.001), tumor subsite tonsil (p = 0.001), and N stage (p = 0.017) were associated with PRMU risk at multivariable regression in the hypofractionated SBRT boost group. All 25 delineated PRMU were located within the high dose regions. Conclusion: The risk of PRMU should be included in the cost benefit analysis when considering future research using a hypofractionated SBRT boost for OPSCC patients.

BACKGROUND AND PURPOSE: Diversity, Equity and Inclusion (DEI) in the medical workforce is linked to improved patient care and innovation, as well as employee retention and engagement. The European Society for Radiotherapy and Oncology launched a survey to provide a benchmark of DEI and engagement among radiation oncology (RO) professionals in Europe.METHODS: An anonymous survey was disseminated among RO professionals in Europe. The survey collected demographics and professional information, and participants were asked if they felt they belonged to a minority group. A DEI and workforce engagement questionnaire by Person et al. evaluated 8 inclusion factors. A favourable score was calculated by adding the percentage of "strongly agreed" or "agreed" answers.RESULTS: A total of 812 complete responses were received from 35 European countries. 21% of respondents felt they belonged to a minority group, mostly based on race/ethnicity (5.9%), nationality (4.8%) and age (4.3%). Compared to benchmark data from the United States, scores were lower for most inclusion factors, and to a greater extent for minority groups. The overall favourable score was 58% for those belonging to a minority group, significantly lower than for other respondents (71%, pCONCLUSIONS: Our work indicates that actions to improve DEI and workforce engagement among RO professionals in Europe are urgently needed, in particular among minority groups. This would potentially improve employee wellbeing and retention, promoting high quality care and innovation.

Perfusion MRI is promising for the assessment, prediction, and monitoring of radiation toxicity in organs at risk in head and neck cancer. Arterial spin labeling (ASL) may be an attractive alternative for conventional perfusion MRI, that does not require the administration of contrast agents. However, currently, little is known about the characteristics and performance of ASL in healthy tissues in the head and neck region. Therefore, the purpose of this study was to optimize and evaluate multidelay pseudocontinuous ASL (pCASL) for the head and neck region and to explore nominal values and measurement repeatability for the blood flow (BF), and the transit time and T1 values needed for BF quantification in healthy tissues. Twenty healthy volunteers underwent a scan session consisting of four repeats of multidelay pCASL (postlabel delays: 1000, 1632, 2479 ms). Regions of interest were defined in the parotid glands, submandibular glands, tonsils, and the cerebellum (as a reference). Nominal values of BF were calculated as the average over four repeats per volunteer. The repeatability coefficient and within-subject coefficient of repeatability (wCV) of BF were calculated. The effect of T1 (map vs. cohort average) and transit time correction on BF was investigated. The mean BF (+/- SE) was 55.7 +/- 3.1 ml/100 g/min for the parotid glands, 41.2 +/- 2.8 ml/100 g/min for the submandibular glands, and 32.3 +/- 2.2 ml/100 g/min for the tonsils. The best repeatability was found in the parotid glands (wCV = 13.3%-16.1%), followed by the submandibular glands and tonsils (wCV = 20.0%-24.6%). On average, the effect of T1 and transit time correction on BF was limited, although substantial bias occurred in individual acquisitions. In conclusion, we demonstrated the feasibility of BF measurements in the head and neck region using multidelay pCASL and reported on nominal BF values, BF repeatability, the effect of T1, and transit time in various tissues in the head and neck region.

Background and purpose: Quality of automatic contouring is generally assessed by comparison with manual delineations, but the effect of contour differences on the resulting dose distribution remains unknown. This study evaluated dosimetric differences between treatment plans optimized using various organ-at-risk (OAR) contouring methods. Materials and methods: OARs of twenty lung cancer patients were manually and automatically contoured, after which user-adjustments were made. For each contour set, an automated treatment plan was generated. The dosimetric effect of intra-observer contour variation and the influence of contour variations on treatment plan evaluation and generation were studied using dose-volume histogram (DVH)-parameters for thoracic OARs. Results: Dosimetric effect of intra-observer contour variability was highest for Heart Dmax (3.4 ± 6.8 Gy) and lowest for Lungs-GTV Dmean (0.3 ± 0.4 Gy). The effect of contour variation on treatment plan evaluation was highest for Heart Dmax (6.0 ± 13.4 Gy) and Esophagus Dmax (8.7 ± 17.2 Gy). Dose differences for the various treatment plans, evaluated on the reference (manual) contour, were on average below 1 Gy/1%. For Heart Dmean, higher dose differences were found for overlap with PTV (median 0.2 Gy, 95% 1.7 Gy) vs. no PTV overlap (median 0 Gy, 95% 0.5 Gy). For Dmax-parameters, largest dose difference was found between 0–1 cm distance to PTV (median 1.5 Gy, 95% 4.7 Gy). Conclusion: Dose differences arising from automatic contour variations were of the same magnitude or lower than intra-observer contour variability. For Heart Dmean, we recommend delineation errors to be corrected when the heart overlaps with the PTV. For Dmax-parameters, we recommend checking contours if the distance is close to PTV (

Purpose Hypertensive disorders of pregnancy (HDP) are associated with longer term postpartum cardiovascular sequelae, including double the risk of ischaemic heart disease and cardiovascular mortality (1). Transthoracic echocardiograms (TTE) were performed in women with pregnancies complicated by gestational hypertension and pre-eclampsia, or uncomplicated pregnancy, at six months and two years postpartum. The aim was to longitudinally assess cardiac structure and function in women with HDP and compare this to women who had a normotensive pregnancy. The six-month results have been previously reported, we now present the two-year data. Methods A prospective cohort study was conducted in a pre-specified subgroup of 126 patients within a single, tertiary referral centre as part of the P4 (Post Partum, Physiology, Psychology, and Paediatric Follow Up) study (2). 74 (59%) women had a normotensive pregnancy, and 52 (41%) had a pregnancy complicated by HDP. Women with pre-existing hypertension were excluded from the study. The mean patient age at time of six-month postpartum TTE was 32 years (range 22–47 years). TTEs were performed by blinded experienced sonographers and reported by a single blinded imaging cardiologist. Results Six months postpartum. 126 women underwent TTE at six months postpartum. Although all results fell within normal ranges, compared to women with a normotensive pregnancy, those with HDP had increased left ventricle (LV) wall thickness, higher relative wall thickness, and increased LV mass. E/A ratio was lower, and E/E' ratios higher in the group with pregnancy complicated by HDP, indicating a trend towards poorer diastolic function (2,3). Two years postpartum. 35 women completed a two year postpartum TTE (18 normotensive, 17 HDP). Measurements fell within normal ranges in both groups of women. At two years postpartum, women with HDP had larger BSA (1.9 vs 1.71 m2 p=0.003), larger LV internal diastolic diameter (48.4 vs 45.5mm p=0.017) and increased inter-ventricular septum thickness (8.5 vs 7.7mm p=0.007) compared to those with normotensive pregnancy. LV mass was greater in women with HDP (98.1 vs 81.5g), as was LA volume indexed (25.4 vs 23.4 cm3/m3), however these differences did not reach significance (p=0.053 and 0.196 respectively). Compared to normotensive women, those with HDP had higher septal (8.7 vs 7.3 p=0.014) and lateral (6.6 vs 5.4 p=0.017) E/E' ratios, indicating a trend towards diastolic dysfunction. Conclusion Despite measurements falling within normal ranges, our results indicate that women with HDP have changes in cardiac structure and function that persist out to two years postpartum. Limitations exist due to incomplete follow up, leading to small sample size; this was partially due to restrictions on service provision in the context of the COVID-19 pandemic. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): The St George and Sutherland Research Foundation.Philanthropic donation from Emeritus Professor Richard Henry.

Hybrid perovskites, such as MAPbI3, are very promising materials to fabricate highly efficient and low-cost solar cells and photodetectors. In this work, we propose a new method of deposition of hybrid perovskite thin films through thermal evaporation of MAPbI3 powder from a single source for which was evaluated the effect of evaporation parameters (distance, time, substrate temperature, chamber pressure, and crucible heating rate) on the structural, optical, and morphological properties. It was found that it is necessary to control adequately the chamber partial pressure, substrate temperature, and the crucible heating rate in order to obtain single-phase MAPbI3 perovskite films. Also, it was studied the solvent annealing treatment as a method to increase the grain size of evaporated films. Finally, a study of transient and steady-state photoconductivity allowed verifying that the evaporated MAPbI3 films present fast band to band photogeneration and bimolecular recombination, and also that the grain size growth leads to an increase of the photoconductivity intensity due to the improvement of the diffusion length.

The implementation of high-throughput diagnostic sequencing has led to the generation of large amounts of mutational data, making their interpretation more complex and responsible for long delays. It has been important to prioritize certain analyses, particularly those of “actionable” genes in diagnostic situations, involving specific treatment and/or management. In our project, we carried out an objective assessment of the clinical actionability of genes involved in myopathies, for which only few data obtained methodologically exist to date. Using the ClinGen Actionability criteria, we scored the clinical actionability of all 199 genes implicated in myopathies published by FILNEMUS for the “National French consensus on gene Lists for the diagnosis of myopathies using next generation sequencing”. We objectified that 63 myopathy genes were actionable with currently available data. Among the 36 myopathy genes with highest actionability scores, only 8 had been scored to date by ClinGen. The data obtained through these methodological tools are an important resource for strategic choices in diagnostic approaches and the management of genetic myopathies. The clinical actionability of genes has to be considered as an evolving concept, in relation to progresses in disease knowledge and therapeutic approaches.

Highlights • Professional quality of life is crucial for oncology professionals. • Alexythymia and empathy affect the individual capacity to cope with stress. • Alexythimia has a negative impact on radiation therapists’ professional quality of life. • Higher empatic concern increases the quality of professional well-being. • This data may help targeting professionals at risk to implement preventive strategies., Background and purpose Physical and mental well-being are crucial for oncology professionals as they affect performance at work. Personality traits, as alexithymia and empathy, may influence professional quality of life. Alexithymia involves diminished skills in emotion processing and awareness. Empathy is pertinent to the ability to understand another’s ‘state of mind/emotion’. The PROject on Burn-Out in RadiatioN Oncology (PRO BONO) investigates professional quality of life amongst radiation oncology professionals, exploring the role of alexithymia and empathy. The present study reports on data pertinent to radiation therapists (RTTs). Material and methods An online survey targeted ESTRO members. Participants were asked to fill out 3 questionnaires for alexithymia, empathy and professional quality of life: (a) Toronto Alexithymia Scale (TAS-20); (b) Interpersonal Reactivity Index (IRI); (c) Professional Quality of Life Scale (ProQoL). The present analysis focuses on RTTS to evaluate compassion satisfaction (CS), secondary traumatic stress (STS) and Burnout and their correlation with alexithymia and empathy, using generalized linear modeling. Covariates found significant at univariate linear regression analysis were included in the multivariate linear regression model. Results A total of 399 RTTs completed all questionnaires. The final model for the burnout scale of ProQoL found, as significal predictors, the TAS-20 total score (β = 0.46, p

Highlights • 49% of 543 survey participants worked full-time from home during the COVID-19 pandemic. • Perceived productivity was lower, with associated feelings of guilt. • Anxiety and depressive symptoms were higher than normative values in Europe. • Anxiety symptoms were negatively correlated with the number of years in research. • Mental health symptoms were lower in participants with institutional health support., Introduction With the COVID-19 pandemic, individuals have been forced to follow strict social isolation guidelines. While crucial to control the pandemic, isolation might have a significant impact on productivity and mental health. Especially for researchers working in healthcare, the current situation is complex. We therefore carried out a survey amongst researchers in the field of radiation oncology to gain insights on the impact of social isolation and working from home and to guide future work. Materials and methods An online survey was conducted between March 27th and April 5th, 2020. The first part contained 14 questions intended to capture an overview of the specific aspects related to research while in isolation. The second (optional) part of the questionnaire was the validated Hospital Anxiety and Depression Scale (HADS), a self-reported measure used to assess levels of anxiety and depressive symptoms. Results From 543 survey participants, 48.8% reported to work full-time from home. The impact on perceived productivity, with 71.2% of participants feeling less productive, caused 58% of participants to feel some level of guilt. Compared to normative data, relatively high levels of anxiety and depressive symptoms were recorded for the 335 participants who filled out the HADS questionnaire. Group comparisons found the presence of a supportive institutional program as the sole factor of statistical significance in both anxiety and depressive symptom levels. People having to work full-time on location showed higher depressive symptom levels than those working from home. Anxiety scores were negatively correlated with the number of research years. Conclusion Results of the survey showed there is a non-negligible impact on both productivity and mental health. As the radiation oncology research community was forced to work from home during the COVID-19 pandemic, lessons can be learned to face future adverse situations but also to improve work-life balance in general.

Highlights • Burnout is critical for oncology professionals, affecting quality of life and performance at work. • Alexithymia and empathy are personality traits influencing the capacity to cope with stress. • Alexithymia increases burnout among medical physicists with a negative impact at work. • Higher level of empathy are correlated to a better professional quality of life. • This data may help identifying subjects at risk to implement preventive strategies., Background and purpose The professional quality of life of radiation oncology professionals can be influenced by different contributing factors, including personality traits. Alexithymia involves deficits in emotion processing and awareness. Empathy is the ability to understand another’s ‘state of mind/emotion’. We investigated professional quality of life, including burnout, in radiation oncology, exploring the role of alexithymia and empathy and targeting the population of medical physicists (MPs), since this professional category is usually underrepresented in surveys exploring professional well-being in radiation oncology and MPs may experience professional distress given the increasing complexity of multimodal cancer care. Material and methods An online survey was addressed to ESTRO members. Participants filled out three questionnaires to evaluate alexithymia, empathy and professional quality of life: a) Toronto Alexithymia Scale (TAS-20); b) Interpersonal Reactivity Index (IRI); c) Professional Quality of Life Scale (ProQoL). Professional quality of life as per ProQoL was considered as dependent variable. The three domains of the ProQoL, namely compassion satisfaction (CS), secondary traumatic stress (STS) and burnout were correlated with alexithymia (as per TAS-20) and empathy (as per IRI with three subcategories: empathic concern, perspective taking and personal distress) and demographic/professional characteristics as independent variables. Generalized linear modeling was used. Significant covariates on univariate linear regression analysis were included in the multivariate linear regression model. Results A total of 308 medical physicists completed all questionnaires. Alexithymia as per TAS-20 was correlated to decreased CS (β = −0.25, p

Purpose To demonstrate the feasibility of predicting the patient-specific treatment planning Pareto front (PF) for prostate cancer patients based only on delineations of PTV, rectum and body. Material/methods Our methodology consists of four steps. First, using Erasmus-iCycle, the Pareto fronts of 112 prostate cancer patients were constructed by generating per patient 42 Pareto optimal treatment plans with different priorities. Dose parameters associated to homogeneity, conformity and dose to rectum were extracted. Second, a 3D convex function representing the PF spanned by the 42 plans was fitted for each patient using three patient-specific parameters. Third, ten features were extracted from the, aforementioned, structures to train a linear-regressor prediction algorithm to predict these three patient-specific parameters. Fourth, the quality of the predictions was assessed by calculating the average and maximum distances of the predicted PF to the 42 plans for patients in the validation cohort. Results The prediction model was able to predict the clinically relevant PF within 2 Gy for 90% of the patients with a median average distance of 0.6 Gy. Conclusions We demonstrate the feasibility of fast, accurate predictions of the patient-specific PF for prostate cancer patients based only on delineations of PTV, rectum and body.

The possible uses of artificial intelligence (AI) in radiation oncology are diverse and wide ranging. Herein, the authors discuss the potential applications of AI at each step of the radiation oncology workflow, which might improve the efficiency and overall quality of radiation therapy for patients with cancer. The authors also describe the associated challenges and provide their perspective on how AI platforms might change the roles of radiation oncology medical professionals. Artificial intelligence (AI) has the potential to fundamentally alter the way medicine is practised. AI platforms excel in recognizing complex patterns in medical data and provide a quantitative, rather than purely qualitative, assessment of clinical conditions. Accordingly, AI could have particularly transformative applications in radiation oncology given the multifaceted and highly technical nature of this field of medicine with a heavy reliance on digital data processing and computer software. Indeed, AI has the potential to improve the accuracy, precision, efficiency and overall quality of radiation therapy for patients with cancer. In this Perspective, we first provide a general description of AI methods, followed by a high-level overview of the radiation therapy workflow with discussion of the implications that AI is likely to have on each step of this process. Finally, we describe the challenges associated with the clinical development and implementation of AI platforms in radiation oncology and provide our perspective on how these platforms might change the roles of radiotherapy medical professionals.

Objective: Osteoradionecrosis (ORN) is a severe late complication after radiotherapy but current knowledge on ORN risks in the setting of postoperative radiotherapy (PORT) is limited. We studied the incidence and risk factors of ORN in patients with oral cavity cancers (OCC, treated with PORT.Patients and Methods: A retrospective cohort study was conducted including OCC patients (mainly squamous cell) treated with postoperative intensity modulated radiotherapy between 2010 and 2018 with > 1 year disease-free survival. Cumulative incidences of ORN were computed using the Kaplan Meier method. Clinical and dosimetric risk factors for mandibular ORN were evaluated using Cox regression models.Results: Within our cohort (N = 227, median follow-up 49 months) we observed 46 cases of ORN, mainly in the mandible (n = 41). The cumulative incidence of mandibular ORN was 15.9 % (SE 2.5 %) at three years and 19.8 % (SE 3.0 %) at five years. At univariable analysis, smoking, mandibular mandibulotomy or segment resection, mean dose to the mandible, and mandible volume (%) >= 60 Gy (V60) were significantly associated with increased ORN risks. At multivariable analysis, smoking (HR 2.13, 95 %CI 1.12-4.06) and V60 (HR 1.02 per 1 % increase, 95 %CI 1.01-1.04) remained predictive factors. For active smokers with a high V60 >= 40 % we observed rapid ORN development with a 1-year incidence of 29 % vs 6 % for others (p < 0.01).Conclusion: OCC Patients treated with PORT are at high risk for mandibular ORN. We identified the mandibular volume receiving >= 60 Gy as the dominant risk factor, especially in active smokers. Limiting high-dose volumes at treatment planning may decrease ORN risks.

Background/purpose: To determine the efficacy and toxicity profile of a stereotactic body radiotherapy (SBRT) boost as a first line treatment in patients with oropharyngeal squamous cell carcinoma ...

Purpose: The goal of this study was to generate a large treatment plan database for head and neck (H&N) cancer patients that can be considered as the gold standard to train and validate models for knowledge-based (KB) treatment planning and QA. With this dataset, the intrinsic prediction performance, the effect of interorgan dependency, and the impact of dataset inconsistency was investigated for an existing treatment planning QA model. Methods: The CT scans of 108 previously treated oropharyngeal patients were used to establish the plan database. For each patient, 15 Pareto optimal treatment plans with different planning priorities for the parotid glands were generated with fully automatic multicriterial treatment planning (1620 plans in total). For each of the 15 sets of plans in the database, a KB model was trained with 54 patients and validated on the other 54 by comparing the predictions with the achieved doses. The dose prediction accuracy (predicted—achieved) of the KB models was assessed and compared among the different models to characterize the intrinsic performance and effect of interorgan dependency. In addition, the effect of dataset inconsistency with respect to planning prioritizations was investigated by mixing plans with different prioritizations, for the training, the validation dataset, and for both combined. Results: In the case of a high planning priority, the mean SD of the prediction error for the mean dose of the parotid glands was only 0.2 2.2 Gy, but this increased to 1.0 5.0 Gy in the case that the parotid glands had a low planning priority. Dataset inconsistency (in planning priority) led to a large increase in prediction error for the parotid glands (mean SD) from 0.2 2.2 Gy to 2.8 3.3 Gy, 3.2 5.0 Gy or 0.6 5.4 Gy, depending on the way the datasets were mixed. Conclusions: The generated plan database can be used to validate and characterize KB prediction models for H&N cancer and will be made available upon request. The investigated KB model performed well in case the parotid glands had a high planning priority (little dependence on lower priority OARs), but poorly for organs for which the dose strongly depends on other higher priority OARs. To improve the performance of KB prediction models for H&N cancer, interorgan dependency should be modeled and accounted for. Dataset inconsistency has a large negative impact on the prediction errors of KB models and should be avoided as much as possible.

Coastal marine ecosystems, which play a crucial role in the biogeochemical and ecological functioning of the Earth, are highly sensitive to the combined effects of climate and human activities. Because of their location, coastal ecosystems are directly influenced by human activities, but it remains challenging to assess the spatial and temporal scales at which climate influences coastal ecosystems. We monitored 12 sampling stations, distributed in 8 ecosystems in France, over 2 decades for physico-biogeochemical parameters (temperature, salinity, concentrations of dissolved oxygen, nutrients and particulate material). The study encompasses a large diversity of temperate coastal ecosystems with respect to e.g. geomorphology, trophic status, tidal regime, river influence and turbidity. Time-series analysis coupled with standardised 3-mode principal component analyses, partial triadic analyses and correlations were used to assess bi-decadal variability and ecosystem trajectories, and to identify large-scale, regional and local drivers. Our results highlighted 2 abrupt changes in 2001 and 2005. The bi-decadal changes were related to changes in large-scale and regional climate, detected through proxies of temperature and atmospheric circulation, as well as through river discharge. Ecosystem trajectories tended to move towards an increase in temperature and salinity, and/or a decrease in chlorophyll a, nutrients and particulate matter. However, the magnitude of change, the year-to-year variability and the sensitivity to the 2001 and 2005 changes varied among the ecosystems. This study highlights the need for establishing long-term time series and combining data sets as well as undertaking multi-ecosystem and local studies to better understand the long-term variability of coastal ecosystems and its associated drivers.

Purpose: To optimize the diffusion-weighting b values and postprocessing pipeline for hybrid intravoxel incoherent motion diffusion kurtosis imaging in the head and neck region. Methods: Optimized diffusion-weighting b value sets ranging between 5 and 30 b values were constructed by optimizing the Cramér-Rao lower bound of the hybrid intravoxel incoherent motion diffusion kurtosis imaging model. With this model, the perfusion fraction, pseudodiffusion coefficient, diffusion coefficient, and kurtosis were estimated. Sixteen volunteers were scanned with a reference b value set and 3 repeats of the optimized sets, of which 1 with volunteers swallowing on purpose. The effects of (1) b value optimization and number of b values, (2) registration type (none vs. intervolume vs. intra- and intervolume registration), and (3) manual swallowing artifact rejection on the parameter precision were assessed. Results: The SD was higher in the reference set for perfusion fraction, diffusion coefficient, and kurtosis by a factor of 1.7, 1.5, and 2.3 compared to the optimized set, respectively. A smaller SD (factor 0.7) was seen in pseudodiffusion coefficient. The sets containing 15, 20, and 30 b values had comparable repeatability in all parameters, except pseudodiffusion coefficient, for which set size 30 was worse. Equal repeatability for the registration approaches was seen in all parameters of interest. Swallowing artifact rejection removed the bias when present. Conclusion: To achieve optimal hybrid intravoxel incoherent motion diffusion kurtosis imaging in the head and neck region, b value optimization and swallowing artifact image rejection are beneficial. The optimized set of 15 b values yielded the optimal protocol efficiency, with a precision comparable to larger b value sets and a 50% reduction in scan time.

IntroductionThe locoregional failure (LRF) rate in human papilloma virus (HPV)-negative oropharyngeal squamous cell carcinoma (OPSCC) remains disappointingly high and toxicity is substantial. Response prediction prior to or early during treatment would provide opportunities for personalised treatment. Currently, there are no accurate predictive models available for correct OPSCC patient selection. Apparently, the pivotal driving forces that determine how a OPSCC responds to treatment, have yet to be elucidated. Therefore, the holistiC early respOnse assessMent for oroPharyngeaL cancer paTiEnts study focuses on a holistic approach to gain insight in novel potential prognostic biomarkers, acquired before and early during treatment, to predict response to treatment in HPV-negative patients with OPSCC.Methods and analysisThis single-centre prospective observational study investigates 60 HPV-negative patients with OPSCC scheduled for primary radiotherapy (RT) with cisplatin or cetuximab, according to current clinical practice. A holistic approach will be used that aims to map the macroscopic (with Intra Voxel Incoherent Motion Diffusion Kurtosis Imaging (IVIM-DKI); before, during, and 3 months after RT), microscopic (with biopsies of the primary tumour acquired before treatment and irradiated ex vivo to assess radiosensitivity), and molecular landscape (with circulating tumour DNA (ctDNA) analysed before, during and 3 months after treatment). The main end point is locoregional control (LRC) 2 years after treatment. The primary objective is to determine whether a relative change in the mean of the diffusion coefficient D (an IVIM-DKI parameter) in the primary tumour early during treatment, improves the performance of a predictive model consisting of tumour volume only, for 2 years LRC after treatment. The secondary objectives investigate the potential of other IVIM-DKI parameters, ex vivo sensitivity characteristics, ctDNA, and combinations thereof as potential novel prognostic markers.Ethics and disseminationThe study was approved by the Medical Ethical Committee of Erasmus Medical Center. The main results of the trial will be presented in international meetings and medical journals.Trial registration numberNL8458.

Purpose or Objective A questionnaire among 543 radiation oncology (RO) professionals involved in research demonstrated that approximately half of them were forced to work full-time from home due to the COVID-19 pandemic (Dhont et al, ctRO, 2020). At the same time, those still working on location had to adjust to a new working environment. Both groups and especially early-career researchers experienced a substantial impact on mental health and work productivity. The aim of the current qualitative study was to assess in-depth the specific challenges faced by young researchers in RO and what constitutes helpful support in case of continuing or future adverse situations. Materials and Methods This study was conducted jointly by researchers in the field of RO and experts in qualitative research. Data was collected using online Focus Groups (oFGs) facilitated by qualitative research experts. Three oFGs were held with 7-11 young RO professionals (total N=25), in which data saturation was reached. Invitations to participate in the oFGs were sent out 30 days prior through the ESTRO newsletter, social media and personal networks. Inclusion criteria to participate were (1) working in RO, (2) in a European institution, and (3) with less than 10 years of research experience. Efforts were made to ensure a diverse panel. The design of the oFGs (Figure 1) comprised two main steps: (1) Deepening the understanding of experienced impacts during the COVID-19 pandemic, and (2) formulating solutions that could positively address the identified impacts. The oFGs were recorded and transcribed verbatim. Transcripts were analyzed via the qualitative analysis software Atlas (2019) through inductive coding. The coded segments were then translated into themes. $Φg Results In addition to years of research experience, seven other variables were identified as potentially impacting on the work or personal sphere in a positive and/or negative manner. In total ten main impacts were identified in the personal (2) and work sphere (8), which were either affected directly by the variables or indirectly through other impacts. It was for example found that job title could negatively impact the type of work the researcher had to perform during the pandemic, which in turn negatively impacted his/her mental health. All variables, impacts and how they relate are illustrated in Figure 2. Proposed solutions were mostly technical, illustrating that the most pressing issue was to ensure the possibility to perform one's work. Proposed solutions for social isolation (e.g. virtual social events) were often countered by the presence of “zoom fatigue”. $Φg Conclusion Different variables, their impacts and a complex interplay between them have been identified to determine how early-career RO professionals experienced working during the COVID-19 pandemic. Beyond technical solutions to enable remote working, the distinct personal situations must be considered when proposing solutions to support mental health in these situations.

Pulmonary embolism (PE) is the third leading cause of cardiovascular death in western countries. The enhancement of fibrinolysis constitutes a promising approach to treat thrombotic diseases. In patients, venous thrombosis and thromboembolism risks are associated with increased plasma levels of TAFI (Thrombin Activatable Fibrinolysis Inhibitor) antigen as well as the active form TAFIa. S62798 is a competitive, selective and potent human TAFIa inhibitor (IC50±SD=11.2±0.4nM). It is however less potent on mouse TAFIa (IC50±SD=270±39nM). Here, we tested the ability of S62798 to enhance endogenous fibrinolysis in a mouse model of pulmonary thromboembolism. Human Tissue Factor (TF) was injected in C57Bl6 male mice. Ten minutes later, mice (n=4 to 14 per group) were treated (IV) with S62798 (from 0.01 to 100mg/kg) or vehicle (0.9% NaCl). Ten or twenty minutes (min) later, mice were anesthetized and lungs were collected, homogenized and pulmonary fibrin was quantified by ELISA. Results are expressed as ratio of geometric mean of pulmonary fibrin (μg/mL): tested treatment/ vehicle [95% confidence interval (CI)]. Ten minutes after S62798 treatment, pulmonary fibrin deposition was dose-dependently decreased with a Minimal Effective Dose of 0.04mg/kg [90% prediction interval 0.037 - 0.051] and an ED50 of 0.03mg/kg [95% CI: 0.01; 0.06]. Mice were then treated with 0.1mg/kg S62798 or vehicle (10 min after TF induction) and fibrin deposition in lungs was quantified 10 and 20 minutes post S62798 treatment. The level of pulmonary fibrin deposition was significantly decreased (p In this model, curative S62798 treatment, alone or associated to heparin, accelerated clot degradation by potentiating endogenous fibrinolysis and thus decreased pulmonary fibrin deposition. Due to its capacity to enhance endogenous fibrinolysis, S62798, which has completed phase I studies, is expected to be a therapeutic option for intermediate high risk PE patients on top of anticoagulants. With early recanalization, S62798 should rapidly reduce pulmonary artery pressure and resistance, with concomitant improvement in right ventricular function, preserving cardiac function, and reducing acute PE-related morbidity and mortality in these patients. Funding Acknowledgement Type of funding source: None

Background Thromboembolic diseases, such as venous thromboembolic diseases represent a significant public health burden. S62798, a selective and potent inhibitor of activated thrombin-activatable fibrinolysis inhibitor (TAFIa), is being developed as a fibrinolysis enhancer for the treatment of thromboembolic diseases, including pulmonary embolism. TAFIa inhibits the fibrinolysis by limiting plasmin generation. Objectives This double-blind, randomised, placebo-controlled first-in-man study was conducted to investigate the safety, pharmacokinetics (PK) and pharmacodynamics (PD) of single ascending doses of S62798 in healthy subjects. Methods Young male (18–40 years) subjects were randomised 3:1 to single ascending doses of S62798 ranging from 3.2 mg to 320 mg or placebo, administered as an intravenous bolus followed by a 7 hour 2-step infusion (part 1), or to 30 mg or 40 mg or placebo administered as a 1-min bolus (part 2). Follow-up ranged from 6 to 13 days post S62798 administration depending on cohorts. Exclusion criteria included bleeding disorders, recent bleeding, and abnormal blood coagulation parameters. Anticoagulant/antiplatelet treatments were not allowed for 30 days prior to and during the study. Safety was assessed by recording adverse events (AE), physical examination, vital signs, biochemical, haematological and haemostasis parameters (prothrombin time, activated partial thromboplastin time, thrombin clotting time, D-Dimers and fibrinogen). Plasma and urine samples for PK assessment were collected pre-dose and up to day 13 to assess the full PK profile. In part 1, ex vivo TAFIa inhibition (spiking of purified human TAFIa) and in vitro clot lysis time were assessed at pre-dose, during and after infusion. The study was performed in France in accordance with the declaration of Helsinki revised in Fortaleza. EudraCT number: 2016–002108–25. Results A total of 56 subjects were randomized to part 1 and 16 to part 2. Subjects were (mean ± SD) 29.5 ±- 5.7 years old with a BMI of 23.9±2.6 kg/m2 in part 1 and 31.4±5.2 years old with a BMI of 23.9±2.5 kg/m2 in part 2. All doses of S62798 administered as a bolus and infusion or a single bolus were well tolerated, and no serious adverse events or discontinuations resulting from AEs occurred during the study. No effects of S62798 on haemostasis parameters were observed. Cardiac safety assessed by 12-lead 24h Holter ECG showed no relevant abnormalities. Plasma exposure of S62798 increased proportionally with the dose. S62798 inhibits TAFIa activity and decreases clot lysis time (reflecting TAFIa activity inhibition) rapidly and dose-dependently in all treated groups. Conclusions S62798, a potent TAFIa inhibitor, has a favourable safety profile with a linear PK. PD results on TAFIa inhibition and clot lysis assay suggest that S62798 has relevant properties to pursue clinical development as an enhancer of endogenous fibrinolysis for the treatment of thromboembolic diseases Funding Acknowledgement Type of funding source: Private company. Main funding source(s): IRIS

Artificial intelligence (AI) has the potential to fundamentally alter the way medicine is practised. AI platforms excel in recognizing complex patterns in medical data and provide a quantitative, rather than purely qualitative, assessment of clinical conditions. Accordingly, AI could have particularly transformative applications in radiation oncology given the multifaceted and highly technical nature of this field of medicine with a heavy reliance on digital data processing and computer software. Indeed, AI has the potential to improve the accuracy, precision, efficiency and overall quality of radiation therapy for patients with cancer. In this Perspective, we first provide a general description of AI methods, followed by a high-level overview of the radiation therapy workflow with discussion of the implications that AI is likely to have on each step of this process. Finally, we describe the challenges associated with the clinical development and implementation of AI platforms in radiation oncology and provide our perspective on how these platforms might change the roles of radiotherapy medical professionals.

How animals adapt their behavior according to regular time intervals between events is not well understood, especially when intervals last several seconds. One possibility is that animals use disembodied internal neuronal representations of time to decide when to initiate a given action at the end of an interval. However, animals rarely remain immobile during time intervals but tend to perform stereotyped behaviors, raising the possibility that motor routines improve timing accuracy. To test this possibility, we used a task in which rats, freely moving on a motorized treadmill, could obtain a reward if they approached it after a fixed interval. Most animals took advantage of the treadmill length and its moving direction to develop, by trial-and-error, the same motor routine whose execution resulted in the precise timing of their reward approaches. Noticeably, when proficient animals did not follow this routine, their temporal accuracy decreased. Then, naïve animals were trained in modified versions of the task designed to prevent the development of this routine. Compared to rats trained in the first protocol, these animals didn’t reach a comparable level of timing accuracy. Altogether, our results indicate that timing accuracy in rats is improved when the environment affords cues that animals can incorporate into motor routines.

ObjectivesKnee osteoarthritis (KOA) progression is frequently monitored by calculating the change in knee joint space width (JSW) measurements. Such differences are small and sensitive to measurement error. We aimed to assess the utility of two alternative statistical modelling methods for monitoring KOA.Material and methodsWe used JSW on radiographs from both the control arm of the Strontium Ranelate Efficacy in Knee Osteoarthritis trial (SEKOIA), a 3-year multicentre, double-blind, placebo-controlled phase three trial, and the Osteoarthritis Initiative (OAI), an open-access longitudinal dataset from the USA comprising participants followed over 8 years. Individual estimates of annualised change obtained from frequentist linear mixed effect (LME) and Bayesian hierarchical modelling, were compared with annualised crude change, and the association of these parameters with change in WOMAC pain was examined.ResultsMean annualised JSW changes were comparable for all estimates, a reduction of around 0.14 mm/y in SEKOIA and 0.08 mm/y in OAI. The standard deviation (SD) of change estimates was lower with LME and Bayesian modelling than crude change (SEKOIA SD = 0.12, 0.12 and 0.21 respectively; OAI SD = 0.08, 0.08 and 0.11 respectively). Estimates from LME and Bayesian modelling were statistically significant predictors of change in pain in SEKOIA (LME P-value = 0.04, Bayes P-value = 0.04), while crude change did not predict change in pain (P-value = 0.10).ConclusionsImplementation of LME or Bayesian modelling in clinical trials and epidemiological studies, would reduce sample sizes by enabling all study participants to be included in analysis regardless of incomplete follow up, and precision of change estimates would improve. They provide increased power to detect associations with other measures.

Background and purpose: Different factors may influence the professional quality of life of oncology professionals. Among them, personality traits, as alexithymia and empathy, are underinvestigated. Alexithymia is about deficits in emotion processing and awareness. Empathy is the ability to understand another's 'state of mind'/emotion. The PROject on BurnOut in RadiatioN Oncology (PRO BONO) assesses professional quality of life, including burnout, in the field of radiation oncology and investigates alexithymia and empathy as contributing factors.Material and methods: An online survey was conducted amongst ESTRO members. Participants completed 3 validated questionnaires for alexithymia, empathy and professional quality of life: (a) Toronto Alexithymia Scale; (b) Interpersonal Reactivity Index; (c) Professional Quality of Life Scale. The present analysis, focusing on radiation/clinical oncologists, evaluates Compassion Satisfaction (CS), Secondary Traumatic Stress (STS) and Burnout and correlates them with alexithymia and empathy (empathic concern, perspective taking and personal distress) with generalized linear modeling. Significant covariates on univariate linear regression analysis were included in the multivariate linear regression model.Results: A total of 825 radiation oncologists completed all questionnaires. A higher level of alexithymia was associated to decreased CS (beta:-0.101; SE: 0.018; p Conclusions: Alexithymic personality trait increased burnout risk, with less professional satisfaction. Empathic concern was associated to increased stress, without leading to burnout, resulting in higher professional fulfillment. These results may be used to benchmark preventing strategies, such as work-hour restrictions, peer support, debriefing sessions, and leadership initiatives for professionals at risk. (c) 2020 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 147 (2020) 162-168

espanolLos hundimientos de tension tienen un alto impacto sobre la correcta operacion de equipos y en la continuidad de los procesos en el usuario final de energia electrica. Las perdidas economicas son un problema en crecimiento para las empresas operadoras, para los mismos reguladores y por supuesto para los consumidores finales del servicio de energia electrica; es asi como se hace necesario la formulacion de nuevos metodos matematicos para el diagnostico de los hundimientos de tension. En este sentido, los metodos de estimacion de estado buscan determinar la frecuencia o el numero de hundimientos de tension que experimenta un usuario final. En esta area de investigacion se han formulado problemas de optimizacion basados en tecnicas como la descomposicion en valores singulares, el ajuste de perfiles de tension y la localizacion de las fuentes generadoras de los hundimientos de tension. Los resultados obtenidos usando estas tecnicas son imprecisas cuando se consideran las corrientes pre-falla, las fallas con impedancia diferente de cero y los desbalances. Es asi como en este articulo se evidenciara que, al considerar estas condiciones reales de las fallas, se obtienen resultados imprecisos para el caso del metodo de descomposicion en valores singulares. A su vez, en este trabajo se propone una nueva formulacion matematica del problema de estimacion de estado de hundimientos de tension usando la minimizacion de la norma-l1. Esta propuesta matematica es aplicada y validada en la red de distribucion de prueba de 33 nodos del IEEE. Unicamente los hundimientos de tension causados por fallos en la red de distribucion seran considerados. Los resultados obtenidos validan una notable mejora en comparacion con el metodo de descomposicion en valores singulares y resaltan una innovadora herramienta para la estimacion de estado de los hundimientos de tension en redes radiales de distribucion. EnglishVoltage sags have a high impact on the proper equipment operation and the electric power end-user processes continuity. Economic losses are a growing problem for the electric utilities, regulators and electric energy final customers and therefore, the formulation of new mathematical methods for voltage sags diagnosis are needed. In this sense, the state estimation methods seek the determination of the frequency or the number of voltage sags that an end-user would experience. In this research area, optimization problems based on techniques such as singular value decomposition, voltage profile curve fitting and voltage sag source location have been formulated. The results of these approaches may be inaccurate when the pre-fault currents, non-zero fault impedances and unbalanced conditions are considered. We will evidence that the results from singular value decomposition method are inaccurate considering these real fault conditions. Also, a new mathematical formulation of the voltage sag state estimation problem based on l1-norm minimization is proposed in this work. The proposed method is applied and validated to the IEEE 33-node test distribution network. Voltage sags caused for network faults are only considered. The results validate a remarkable improvement in comparison with the singular value decomposition method and show an innovative tool for voltage sags state estimation in radial electric power distribution systems