Image quality evaluation of a new high-performance ring-gantry cone-beam computed tomography imager.

Objective. Newer cone-beam computed tomography (CBCT) imaging systems offer reconstruction algorithms including metal artifact reduction (MAR) and extended field-of-view (eFoV) techniques to improve image quality. In this study a new CBCT imager, the new Varian HyperSight CBCT, is compared to fan-beam CT and two CBCT imagers installed in a ring-gantry and C-arm linear accelerator, respectively.Approach. The image quality was assessed for HyperSight CBCT which uses new hardware, including a large-size flat panel detector, and improved image reconstruction algorithms. The decrease of metal artifacts was quantified (structural similarity index measure (SSIM) and root-mean-squared error (RMSE)) when applying MAR reconstruction and iterative reconstruction for a dental and spine region using a head-and-neck phantom. The geometry and CT number accuracy of the eFoV reconstruction was evaluated outside the standard field-of-view (sFoV) on a large 3D-printed chest phantom. Phantom size dependency of CT numbers was evaluated on three cylindrical phantoms of increasing diameter. Signal-to-noise and contrast-to-noise were quantified on an abdominal phantom.Main results. In phantoms with streak artifacts, MAR showed comparable results for HyperSight CBCT and CT, with MAR increasing the SSIM (0.97-0.99) and decreasing the RMSE (62-55 HU) compared to iterative reconstruction without MAR. In addition, HyperSight CBCT showed better geometrical accuracy in the eFoV than CT (Jaccard Conformity Index increase of 0.02-0.03). However, the CT number accuracy outside the sFoV was lower than for CT. The maximum CT number variation between different phantom sizes was lower for the HyperSight CBCT imager (∼100 HU) compared to the two other CBCT imagers (∼200 HU), but not fully comparable to CT (∼50 HU).Significance. This study demonstrated the imaging performance of the new HyperSight CBCT imager and the potential of applying this CBCT system in more advanced scenarios by comparing the quality against fan-beam CT.

Relating pre-treatment non-Gaussian intravoxel incoherent motion diffusion-weighted imaging to human papillomavirus status and response in oropharyngeal carcinoma.

Background and purpose: Diffusion-weighted imaging (DWI) is a promising technique for response assessment in head-and-neck cancer. Recently, we optimized Non-Gaussian Intravoxel Incoherent Motion Imaging (NG-IVIM), an extension of the conventional apparent diffusion coefficient (ADC) model, for the head and neck. In the current study, we describe the first application in a group of patients with human papillomavirus (HPV)-positive and HPV-negative oropharyngeal squamous cell carcinoma. The aim of this study was to relate ADC and NG-IVIM DWI parameters to HPV status and clinical treatment response. Materials and methods: Thirty-six patients (18 HPV-positive, 18 HPV-negative) were prospectively included. Presence of progressive disease was scored within one year. The mean pre-treatment ADC and NG-IVIM parameters in the gross tumor volume were compared between HPV-positive and HPV-negative patients. In HPV-negative patients, ADC and NG-IVIM parameters were compared between patients with and without progressive disease. Results: ADC, the NG-IVIM diffusion coefficient D, and perfusion fraction f were significantly higher, while pseudo-diffusion coefficient D* and kurtosis K were significantly lower in the HPV-negative compared to HPV-positive patients. In the HPV-negative group, a significantly lower D was found for patients with progressive disease compared to complete responders. No relation with ADC was observed. Conclusion: The results of our single-center study suggest that ADC is related to HPV status, but not an independent response predictor. The NG-IVIM parameter D, however, was independently associated to response in the HPV-negative group. Noteworthy in the opposite direction as previously thought based on ADC.

Personalizing dental screening and prevention protocols in dentulous patients with oropharyngeal cancer undergoing radiotherapy: A retrospective cohort study.

Objectives: Patients with head and neck cancer are routinely screened for dental foci prior to radiotherapy (RT) to prevent post- RT tooth extractions associated with an increased risk of osteoradionecrosis. We evaluated the risk factors for post-RT tooth extraction to personalise dental screening and prevention protocols prior to RT. Materials and methods: This retrospective cohort study included dentulous patients diagnosed with oropharyngeal cancer who had undergone radiation therapy at doses 60-70 Gy and achieved a disease-free survival of ≥ 1 year (N = 174). Risk factors were assessed using Cox regression models. Results: The cumulative incidence of post-RT tooth extraction was 30.7 % at 5 years. Main indications for extraction (n = 62) were radiation caries (n = 20) and periodontal disease (n = 27). Risk factors associated (p < 0.05) with radiation caries-related extractions included active smoking, alcohol abuse, poor oral hygiene, parotid gland irradiation, and mandibular irradiation. A high-dose volume in the mandible was associated with periodontal disease events. Conclusion: Post-RT extractions due to radiation caries were influenced by lifestyle factors and RT dose in the mandible and parotid glands. Periodontal disease-related extractions were primarily associated with the mandibular dose. During dental screening these post-RT risk factors should be taken into account to prevent osteoradionecrosis.

Professional development through mentoring: Final evaluation of the pilot mentoring programme of the European society of radiotherapy and oncology.

The European SocieTy for Radiotherapy and Oncology (ESTRO) organized a one-year pilot mentoring programme. At evaluation after one year, both mentors and mentees scored the programme with a median score of 9 on a scale of 10. All of the mentors indicated that they wanted to participate again as mentors.

Evaluating AI-generated CBCT-based synthetic CT images for target delineation in palliative treatments of pelvic bone metastasis at conventional C-arm linacs.

PURPOSE: One-table treatments with treatment imaging, preparation and delivery occurring at one treatment couch, could increase patients' comfort and throughput for palliative treatments. On regular C-arm linacs, however, cone-beam CT (CBCT) imaging quality is currently insufficient. Therefore, our goal was to assess the suitability of AI-generated CBCT based synthetic CT (sCT) images for target delineation and treatment planning for palliative radiotherapy. MATERIALS AND METHODS: CBCTs and planning CT-scans of 22 female patients with pelvic bone metastasis were included. For each CBCT, a corresponding sCT image was generated by a deep learning model in ADMIRE 3.38.0. Radiation oncologists delineated 23 target volumes (TV) on the sCTs (TVsCT) and scored their delineation confidence. The delineations were transferred to planning CTs and manually adjusted if needed to yield gold standard target volumes (TVclin). TVsCT were geometrically compared to TVclin using Dice coefficient (DC) and Hausdorff Distance (HD). The dosimetric impact of TVsCT inaccuracies was evaluated for VMAT plans with different PTV margins. RESULTS: Radiation oncologists scored the sCT quality as sufficient for 13/23 TVsCT (median: DC = 0.9, HD = 11 mm) and insufficient for 10/23 TVsCT (median: DC = 0.7, HD = 34 mm). For the sufficient category, remaining inaccuracies could be compensated by +1 to +4 mm additional margin to achieve coverage of V95% > 95% and V95% > 98%, respectively in 12/13 TVsCT. CONCLUSION: The evaluated sCT quality allowed for accurate delineation for most targets. sCTs with insufficient quality could be identified accurately upfront. A moderate PTV margin expansion could address remaining delineation inaccuracies. Therefore, these findings support further exploration of CBCT based one-table treatments on C-arm linacs.

Robust optimization of a radiotherapy pretreatment preparation workflow.

Objective. Increasing cancer incidence, staff shortage and high burnout rate among radiation oncologists, medical physicists and radiation technicians are putting many departments under strain. Operations research (OR) tools could optimize radiotherapy processes, however, clinical implementation of OR-tools in radiotherapy is scarce since most investigated optimization methods lack robustness against patient-to-patient variation in duration of tasks. By combining OR-tools, a method was developed that optimized deployment of radiotherapy resources by generating robust pretreatment preparation schedules that balance the expected average patient preparation time (Fmean) with the risk of working overtime (RoO). The method was evaluated for various settings of an one-stop shop (OSS) outpatient clinic for palliative radiotherapy.Approach. The OSS at our institute sees, scans and treats 3-5 patients within one day. The OSS pretreatment preparation workflow consists of a fixed sequence of tasks, which was manually optimized for radiation oncologist and CT availability. To find more optimal sequences, with shorterFmeanand lowerRoO, a genetic algorithm was developed which regards these sequences as DNA-strands. The genetic algorithm applied natural selection principles to produce new sequences. A decoder translated sequences to schedules to find the conflicting fitness parametersFmeanandRoO. For every generation, fitness of sequences was determined by the distance to the estimated Pareto front ofFmeanandRoO. Experiments were run in various OSS-settings.Main results. According to our approach, the expectedFmeanof the current clinical schedule could be reduced with 37%, without increasingRoO. Additional experiments provided insights in trade-offs betweenFmean,RoO, working shift length, number of patients treated on a single day and staff composition.Significance. Our approach demonstrated that OR-tools could optimize radiotherapy resources by robust pretreatment workflow scheduling. The results strongly support further exploration of scheduling optimization for treatment preparation also outside a one-stop shop or radiotherapy setting.

Accounting for fractionation and heterogeneous dose distributions in the modelling of osteoradionecrosis in oropharyngeal carcinoma treatment.

BACKGROUND AND PURPOSE: Osteoradionecrosis (ORN) of the mandible is a severe complication following radiotherapy (RT). With a renewed interest in hypofractionation for head and neck radiotherapy, more information concerning ORN development after high fraction doses is important. The aim of this explorative study was to develop a model for ORN risk prediction applicable across different fractionation schemes using Equivalent Uniform Doses (EUD). MATERIAL AND METHODS: We performed a retrospective cohort study in 334 oropharyngeal squamous cell carcinoma (OPSCC) patients treated with either a hypofractionated Stereotactic Body Radiation Therapy (HF-SBRT) boost or conventional Intensity Modulated Radiation Therapy (IMRT). ORN was scored with the CTCAE v5.0. HF-SBRT and IMRT dose distributions were converted into equivalent dose in 2 Gy fractions (α/ß = 0.85 Gy) and analyzed using EUD. The parameter a that led to an EUD that best discriminated patients with and without grade ≥ 2 ORN was selected. Patient and treatment-related risk factors of ORN were analyzed with uni- and multivariable regression analysis. RESULTS: A total of 32 patients (9.6%) developed ORN grade ≥ 2. An EUD(a = 8) best discriminated between ORN and non-ORN (AUC = 0.71). In multivariable regression, pre-RT extractions (SHR = 2.34; p = 0.012), mandibular volume (SHR = 1.04; p = 0.003), and the EUD(a = 8) (SHR = 1.14; p < 0.001) were significantly associated with ORN. CONCLUSION: Risk models for ORN based on conventional DVH parameters cannot be directly applied to HF-SBRT fractionation schemes and dose distributions. However, after correcting for fractionation and non-uniform dose distributions using EUD, a single model can distinguish between ORN and non-ORN after conventionally fractionated radiotherapy and hypofractionated boost treatments.

Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network.

Objective. In MR-only clinical workflow, replacing CT with MR image is of advantage for workflow efficiency and reduces radiation to the patient. An important step required to eliminate CT scan from the workflow is to generate the information provided by CT via an MR image. In this work, we aim to demonstrate a method to generate accurate synthetic CT (sCT) from an MR image to suit the radiation therapy (RT) treatment planning workflow. We show the feasibility of the method and make way for a broader clinical evaluation.Approach. We present a machine learning method for sCT generation from zero-echo-time (ZTE) MRI aimed at structural and quantitative accuracies of the image, with a particular focus on the accurate bone density value prediction. The misestimation of bone density in the radiation path could lead to unintended dose delivery to the target volume and results in suboptimal treatment outcome. We propose a loss function that favors a spatially sparse bone region in the image. We harness the ability of the multi-task network to produce correlated outputs as a framework to enable localization of region of interest (RoI) via segmentation, emphasize regression of values within RoI and still retain the overall accuracy via global regression. The network is optimized by a composite loss function that combines a dedicated loss from each task.Main results. We have included 54 brain patient images in this study and tested the sCT images against reference CT on a subset of 20 cases. A pilot dose evaluation was performed on 9 of the 20 test cases to demonstrate the viability of the generated sCT in RT planning. The average quantitative metrics produced by the proposed method over the test set were-(a) mean absolute error (MAE) of 70 ± 8.6 HU; (b) peak signal-to-noise ratio (PSNR) of 29.4 ± 2.8 dB; structural similarity metric (SSIM) of 0.95 ± 0.02; and (d) Dice coefficient of the body region of 0.984 ± 0.Significance. We demonstrate that the proposed method generates sCT images that resemble visual characteristics of a real CT image and has a quantitative accuracy that suits RT dose planning application. We compare the dose calculation from the proposed sCT and the real CT in a radiation therapy treatment planning setup and show that sCT based planning falls within 0.5% target dose error. The method presented here with an initial dose evaluation makes an encouraging precursor to a broader clinical evaluation of sCT based RT planning on different anatomical regions.

Development of a local dose-response relationship for osteoradionecrosis within the mandible.

PURPOSE: Osteoradionecrosis (ORN) of the mandible is a severe complication following radiotherapy of the head and neck, but not all regions of the mandible may be equally at risk. Therefore our goal was to explore a local dose response relationship for subregions of the mandible. MATERIALS AND METHODS: All oropharyngeal cancer patients treated at our hospital between 2009 and 2016 were reviewed. Follow-up was cut-off at 3 years. For patients that developed ORN, the ORN volume was delineated on the planning CT. Each mandible was divided into 16 volumes of interest (VOIs) based on the location of the dental elements and the presence of ORN in each was scored. Generalized estimating equations were used to build a model for the probability of developing ORN in an element VOI. RESULTS: Of the 219 included patients, 22 developed ORN in 89 element VOIs. Mean dose to the element VOI (odds ratio (OR) = 1.05 per Gy, 95% confidence interval (CI): (1.04,1.07)), pre-radiotherapy extractions of an element ipsilateral to element of interest (OR = 2.81, 95% CI: (1.12,7.05)), and smoking at start of radiotherapy (OR = 3.37, 95% CI: (1.29,8.78)) were significantly associated with an increased probability of ORN in the VOI. CONCLUSION: The developed dose-response model indicates that the probability of ORN varies within the mandible and strongly depends on the local dose, the location of extractions, and smoking.

Comprehensive dose evaluation of a Deep Learning based synthetic Computed Tomography algorithm for pelvic Magnetic Resonance-only radiotherapy.

BACKGROUND AND PURPOSE: Magnetic Resonance (MR)-only radiotherapy enables the use of MR without the uncertainty of MR-Computed Tomography (CT) registration. This requires a synthetic CT (sCT) for dose calculations, which can be facilitated by a novel Zero Echo Time (ZTE) sequence where bones are visible and images are acquired in 65 seconds. This study evaluated the dose calculation accuracy for pelvic sites of a ZTE-based Deep Learning sCT algorithm developed by GE Healthcare. MATERIALS AND METHODS: ZTE and CT images were acquired in 56 pelvic radiotherapy patients in the radiotherapy position. A 2D U-net convolutional neural network was trained using pairs of deformably registered CT and ZTE images from 36 patients. In the remaining 20 patients the dosimetric accuracy of the sCT was assessed using cylindrical dummy Planning Target Volumes (PTVs) positioned at four different central axial locations, as well as the clinical treatment plans (for prostate (n = 10), rectum (n = 4) and anus (n = 6) cancers). The sCT was rigidly and deformably registered, the plan recalculated and the doses compared using mean differences and gamma analysis. RESULTS: Mean dose differences to the PTV D98% were ≤ 0.5% for all dummy PTVs and clinical plans (rigid registration). Mean gamma pass rates at 1%/1 mm were 98.0 ± 0.4% (rigid) and 100.0 ± 0.0% (deformable), 96.5 ± 0.8% and 99.8 ± 0.1%, and 95.4 ± 0.6% and 99.4 ± 0.4% for the clinical prostate, rectum and anus plans respectively. CONCLUSIONS: A ZTE-based sCT algorithm with high dose accuracy throughout the pelvis has been developed. This suggests the algorithm is sufficiently accurate for MR-only radiotherapy for all pelvic sites.

Qualitative Study on Diversity, Equity, and Inclusion Within Radiation Oncology in Europe.

PURPOSE: Organizational culture plays a major role in prioritizing diversity, equity, and inclusion (DEI) objectives by aligning individual values of employees with organizational values. However, effective strategies to create an inclusive organizational culture, in which these values are aligned, remain unclear. The European Society for Radiotherapy and Oncology (ESTRO) launched a qualitative study, as a follow-up of the previous project on DEI that highlighted low levels of inclusion and work engagement among radiation oncology (RO) professionals in Europe. The aim of the present study was to gain an understanding of how DEI could be improved within RO departments by creating a more inclusive organizational culture. METHODS AND MATERIALS: A qualitative research study was conducted by enrolling RO professionals from 4 selected European countries through an open call on the ESTRO platform. Respondents who completed an online survey and met the inclusion criteria, such as experiencing low DEI levels at work, were invited for an online semistructured interview. Interview transcripts were analyzed thematically with an abductive approach via concepts in relation to "DEI," "work engagement," "organizational culture," and "professional values." RESULTS: Twenty-six eligible respondents from Great Britain, Italy, Poland, and Switzerland were interviewed. The thematic analysis identified cases in which limited engagement at work emerged when the personal values of RO professionals conflicted with dominant organizational values, hampering DEI. Three conflicts were found between the following personal versus organizational values: (1) self-development versus efficiency, (2) togetherness versus competition, and (3) people-oriented versus task-oriented cultures. CONCLUSIONS: Awareness of how organizational values can conflict with professionals' values should be raised to improve inclusion and engagement in the workplace. Additionally, efforts should be focused on tackling existing power imbalances that hamper effective deliberation on organizational- versus personal-value conflicts.

Magnetic Resonance Imaging-Based Delineation of Organs at Risk in the Head and Neck Region.

Purpose: The aim of this article is to establish a comprehensive contouring guideline for treatment planning using only magnetic resonance images through an up-to-date set of organs at risk (OARs), recommended organ boundaries, and relevant suggestions for the magnetic resonance imaging (MRI)-based delineation of OARs in the head and neck (H&N) region. Methods and Materials: After a detailed review of the literature, MRI data were collected from the H&N region of healthy volunteers. OARs were delineated in the axial, coronal, and sagittal planes on T2-weighted sequences. Every contour defined was revised by 4 radiation oncologists and subsequently by 2 independent senior experts (H&N radiation oncologist and radiologist). After revision, the final structures were presented to the consortium partners. Results: A definitive consensus was reached after multi-institutional review. On that basis, we provided a detailed anatomic and functional description and specific MRI characteristics of the OARs. Conclusions: In the era of precision radiation therapy, the need for well-built, straightforward contouring guidelines is on the rise. Precise, uniform, delineation-based, automated OAR segmentation on MRI may lead to increased accuracy in terms of organ boundaries and analysis of dose-dependent sequelae for an adequate definition of normal tissue complication probability.

Multidelay pseudocontinuous arterial spin labeling to measure blood flow in the head and neck.

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.

Ex Vivo Functional Assay for Evaluating Treatment Response in Tumor Tissue of Head and Neck Squamous Cell Carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) displays a large heterogeneity in treatment response, and consequently in patient prognosis. Despite extensive efforts, no clinically validated model is available to predict tumor response. Here we describe a functional test for predicting tumor response to radiation and chemotherapy on the level of the individual patient. METHODS: Resection material of 17 primary HNSCC patients was cultured ex vivo, irradiated or cisplatin-treated, after which the effect on tumor cell vitality was analyzed several days after treatment. RESULTS: Ionizing radiation (IR) affected tumor cell growth and viability with a clear dose-response relationship, and marked heterogeneity between tumors was observed. After a single dose of 5Gy, proliferation in IR-sensitive tumors dropped below 30% of the untreated level, while IR-resistant tumors maintained at least 60% of proliferation. IR-sensitive tumors showed on average a twofold increase in apoptosis, as well as an increased number and size of DNA damage foci after treatment. No differences in the homologous recombination (HR) proficiency between IR-sensitive and -resistant tumors were detected. Cisplatin caused a decrease in proliferation, as well as induction of apoptosis, again with marked variation between the samples. CONCLUSIONS: Our functional ex vivo assay discriminated between IR-sensitive and IR-resistant HNSCC tumors, and may also be suitable for predicting response to cisplatin. Its predictive value is currently under investigation in a prospective clinical study.

Post radiation mucosal ulcer risk after a hypofractionated stereotactic boost and conventional fractionated radiotherapy for oropharyngeal carcinoma.

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.

An impact model to understand and improve work-life balance in early-career researchers in radiation oncology.

Purpose: The COVID-19 pandemic had a substantial effect on mental health and work productivity of early-career researchers working in Radiation Oncology (RO). However, the underlying mechanisms of these effects are unclear. The aim of the current qualitative study was therefore to achieve a better understanding of how these effects arose and could be managed in the future. Methods: This study was conducted jointly by RO and qualitative health researchers. Data was collected in four online Focus Groups with 6-11 RO researchers (total N = 31) working in Europe. The transcripts were analysed through a qualitative cross-impact analysis. Results: Causal relations were identified between seventeen variables that depict the impact of disrupted working conditions. Mental health and work productivity were indeed the most important affected variables, but relations between variables towards these impacts were complex. Relations could either be positive or negative and direct or indirect, leading to a cascade of interrelated events which are highly personal and could change over time. We developed the model 'impact of disrupted working conditions' depicting the identified variables and their relations, to allow more individual assessment and personalised solutions. Conclusion: The impacts of disrupted working conditions on RO researchers varied due to the complexity of interrelated variables. Consequently, collective actions are not sufficient, and a more personal approach is needed. Our impact model is recommended to help guide conversations and reflections with the aim of improving work/life balance. The participants showed high levels of personal responsibility towards their own mental health and work productivity. Although being an individual issue, a collective responsibility in developing such approaches is key due to the dependency on organizational variables.

An online adaptive plan library approach for intensity modulated proton therapy for head and neck cancer.

BACKGROUND AND PURPOSE: In intensity modulated proton therapy (IMPT), the impact of setup errors and anatomical changes is commonly mitigated by robust optimization with population-based setup robustness (SR) settings and offline replanning. In this study we propose and evaluate an alternative approach based on daily plan selection from patient-specific pre-treatment established plan libraries (PLs). Clinical implementation of the PL strategy would be rather straightforward compared to daily online re-planning. MATERIALS AND METHODS: For 15 head-and-neck cancer patients, the planning CT was used to generate a PL with 5 plans, robustly optimized for increasing SR: 0, 1, 2, 3, 5 mm, and 3% range robustness. Repeat CTs (rCTs) and realistic setup and range uncertainty distributions were used for simulation of treatment courses for the PL approach, treatments with fixed SR (fSR3) and a trigger-based offline adaptive schedule for 3 mm SR (fSR3OfA). Daily plan selection in the PL approach was based only on recomputed dose to the CTV on the rCT. RESULTS: Compared to using fSR3 and fSR3OfA, the risk of xerostomia grade ≥ II & III and dysphagia ≥ grade III were significantly reduced with the PL. For 6/15 patients the risk of xerostomia and/or dysphagia ≥ grade II could be reduced by > 2% by using PL. For the other patients, adherence to target coverage constraints was often improved. fSR3OfA resulted in significantly improved coverage compared to PL for selected patients. CONCLUSION: The proposed PL approach resulted in overall reduced NTCPs compared to fSR3 and fSR3OfA at limited cost in target coverage.