We present a multimodal deep learning model for segmenting 25 organs defined in the European Particle Therapy Network (EPTN) international neurological contouring atlas. Multiple input configurations were evaluated on 74 patients using 5-fold cross-validation (59 training, 14–15 per fold for evaluation), with each patient assessed once on unseen data. The dual-input model combining contrast-enhanced T1-weighted magnetic resonance (MR) and computed tomography (CT) achieved the best overall results (median Dice of 0.80, median surface Dice of 0.84), with no added benefit from T2 FLAIR.

Modern radiotherapy workflows depend heavily on software, yet proprietary solutions limit adaptability and transparency. Many institutions create in-house tools, resulting in duplicated efforts and sustainability challenges. Free and open-source software (FOSS) offers transparency, customization, and collaborative development opportunities, but faces barriers including fragmented efforts, regulatory complexity, and clinical adoption hurdles. This vision paper, inspired by the 2024 ESTRO Physics Workshop on “Resource sharing: open-source software & development in radiotherapy” explores these challenges and proposes strategies to promote sustainable and discoverable open-source ecosystems in radiation oncology. Key recommendations include improving interoperability, clear licensing, risk management, validation frameworks, and creating a centralised registry for resource visibility. Embracing open-source practices can accelerate innovation, reduce redundancy, and enhance patient care.

Magnetic resonance imaging (MRI) is essential for post-treatment surveillance of patients with intracranial central nervous system (CNS) tumours. However, interpretation is often complicated due to post radiotherapy MRI abnormalities. Current literature demonstrates substantial heterogeneity in terminology and definitions used to describe these MRI abnormalities, limiting clinical decision-making and comparability across studies. To address this, an international multidisciplinary Delphi consensus was conducted within the Radiation Imaging and Neuro-Oncology Group (RING). Questionnaires were developed by the steering committee and distributed to experts in radiation oncology, neuroradiology, neuro-oncology, medical oncology, and neurosurgery. A three-round Delphi method was employed, with consensus defined as ≥ 75% agreement. Consensus was reached on the applicability and definitions with adoption of the term Treatment-Related Imaging Abnormality (TRIA). Clear definitions for potential and confirmed TRIA were established. Subcategorization based on imaging features all demonstrated high agreement. For consistent application of the framework minimal essential elements for MRI request forms were identified. The final consensus was endorsed by ESTRO, ESNR and EORTC. This Delphi consensus provides a standardized framework for MRI abnormalities following radiotherapy for intracranial CNS tumours. The framework aims to harmonize reporting, support clinical decision-making, and improve comparability in future neuro-oncology research. Central nervous system neoplasms - Radiotherapy - Magnetic resonance imaging - Delphi Technique - Treatment-Related Imaging Abnormality (TRIA).

We present an expert-trained deep learning model for automated delineation of 25 organs-at-risk defined in the EPTN atlas for neuro-oncological radiotherapy. Multiple input configurations were evaluated. The dual-input channel model combining contrast-enhanced T1-weighted MRI and CT achieved the best overall results (median surface Dice Similarity Coefficient = 0.84). It demonstrated robust performance across a wide range of organs-at-risk, supporting its use as a segmentation-support tool under human supervision and for fully automated retrospective dose–response analyses. We release the model publicly to the international community, while explicitly acknowledging that clinical use remains the responsibility of each institution within its regulatory context.

Background and Purpose: To investigate the impact of organ motion on hypoxia-guided proton therapy treatments for non-small cell lung cancer (NSCLC) patients. Materials and Methods: Hypoxia PET and 4D imaging data of six NSCLC patients were used to simulate hypoxia-guided proton therapy with different motion mitigation strategies including rescanning, breath-hold, respiratory gating and tumour tracking. Motion-induced dose degradation was estimated for treatment plans with dose painting of hypoxic tumour sub-volumes at escalated dose levels. Tumour control probability (TCP) and dosimetry indices were assessed to weigh the clinical benefit of dose escalation and motion mitigation. In addition, the difference in normal tissue complication proba-bility (NTCP) between escalated proton and photon VMAT treatments has been assessed. Results: Motion-induced dose degradation was found for target coverage (CTV V95% up to-4%) and qual-ity of the dose-escalation-by-contour (QRMS up to 6%) as a function of motion amplitude and amount of dose escalation. The TCP benefit coming from dose escalation (+4-13%) outweighs the motion-induced losses (< 2%). Significant average NTCP reductions of dose-escalated proton plans were found for lungs (-14%), oesophagus (-10%) and heart (-16%) compared to conventional VMAT plans. The best plan dosimetry was obtained with breath hold and respiratory gating with rescanning. Conclusion: NSCLC affected by hypoxia appears to be a prime target for proton therapy which, by dose -escalation, allows to mitigate hypoxia-induced radio-resistance despite the sensitivity to organ motion. Furthermore, substantial reduction in normal tissue toxicity can be expected compared to conventional VMAT. Accessibility and standardization of hypoxia imaging and clinical trials are necessary to confirm these findings in a clinical setting. (C) 2022 The Author(s). Published by Elsevier B.V.

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.

Mobile health data capture applications (mHDA's) may improve communication between healthcare providers and patients. However, there is limited literature about the use of mHDA's facilitating clinical trials. In this study, the effectiveness of an application, supporting follow-up visits of cancer trial participants was investigated. Twenty participants were provided with an e-questionnaire via the mHDA. Participants rated the usability of the application as high performing (mean Systems Usability Scale 87 points). The research team rated the mHDA as highly applicable and efficient in preparing visits. Anamnesis, physical examination and agreement on further policy were performed within an average of 31 min.

Background and purposeProton therapy is expected to outperform photon-based treatment regarding organs at risk (OAR) sparing but to date there is no method to practically measure clinical benefit. Here, we introduce the novel ROCOCO Performance Scoring System (RPSS) translating dose differences into clinically relevant endpoints and apply this to a treatment plan comparison of volumetric modulated arc therapy (VMAT) and intensity modulated proton therapy (IMPT) in 20 pilocytic astrocytoma patients.Material and methodsThe RPSS was developed on the basis of expert-based weighting factors and toxicity scores per OAR. The imaging datasets of 20 pilocytic astrocytoma patients having undergone radiotherapy were included in this in silico dosimetric comparison trial as proof of principle. For each of these patients, treatment plans to a total dose of 54 Gy (RBE) were generated for VMAT and IMPT and these were compared regarding radiation dose to the clinical target volume (CTV) and OARs. The RPSS was calculated for each treatment plan comparing VMAT and IMPT.ResultsIn 40 analysed treatment plans, the average and low dose volumes to various OARs were significantly reduced when using IMPT compared to VMAT (p < 0.05). Using the RPSS, a significant difference between both treatment modalities was found, with 85% of the patients having a lower RPSS in favour of the IMPT plan.ConclusionThere are dosimetric differences between IMPT and VMAT in pilocytic astrocytoma patients. In absence of clinically validated NTCP models we introduce the RPSS model in order to objectively compare treatment modalities by translating dosimetric differences in potential clinical differences.

PURPOSE:Dose escalation yields higher complete response to rectal tumors, which may enable the omission of surgery. Dose escalation using 50 kVp contact x-ray brachytherapy (CXB) allow the treatment of a selective volume, resulting in low toxicity and organs-at-risk preservation. However, the use of CXB devices is limited because of its high cost and lack of treatment planning tools. Hence, the MAASTRO applicator (for HDR 192Ir sources) was developed and characterized by measurements and Monte Carlo simulations to be a cost-effective alternative to CXB devices. METHODS AND MATERIALS:A cylindrical applicator with lateral shielding was designed to be used with a rectoscope using its tip as treatment surface. Both the applicator and the rectoscope have a slanted edge to potentially allow easier placement against tumors. The applicator design was achieved by Monte Carlo modeling and validated experimentally with film dosimetry, using the Papillon 50 (P50) device as reference. RESULTS:The applicator delivers CXB doses in less than 9 min using a 20375 U source for a treatment area of approximately 20 × 20 mm2 at 2 mm depth. Normalized at 2 mm, the dose falloff for depths of 0 mm, 5 mm, and 10 mm are 130%, 70%, and 43% for the P50 and 140%, 67%, and 38% for the MAASTRO applicator, respectively. CONCLUSIONS:The MAASTRO applicator was designed to use HDR 192Ir sources to deliver a dose distribution similar to those of CXB devices. The applicator may provide a cost-effective solution for endoluminal boosting with clinical treatment planning system integration.

Objective: Locally recurrent disease is of increasing concern in (non-)small cell lung cancer [(N)SCLC] patients. Local reirradiation with photons or particles may be of benefit to these patients. In this multicentre in silico trial performed within the Radiation Oncology Collaborative Comparison (ROCOCO) consortium, the doses to the target volumes and organs at risk (OARs) were compared when using several photon and proton techniques in patients with recurrent localised lung cancer scheduled to undergo reirradiation. Methods: 24 consecutive patients with a second primary (N)SCLC or recurrent disease after curative-intent, standard fractionated radio(chemo) therapy were included in this study. The target volumes and OARs were centrally contoured and distributed to the participating ROCOCO sites. Remaining doses to the OARs were calculated on an individual patient's basis. Treatment planning was performed by the participating site using the clinical treatment planning system and associated beam characteristics. Results: Treatment plans for all modalities (five photon and two proton plans per patient) were available for 22 patients (N = 154 plans). 3D-conformal photon therapy and double-scattered proton therapy delivered significantly lower doses to the target volumes. The highly conformal techniques, i.e., intensity modulated radiation therapy (IMRT), volumetric modulated arc therapy (VMAT), CyberKnife, TomoTherapy and intensity-modulated proton therapy (IMPT), reached the highest doses in the target volumes. Of these, IMPT was able to statistically significantly decrease the radiation doses to the OARs. Conclusion: Highly conformal photon and proton beam techniques enable high-dose reirradiation of the target volume. They, however, significantly differ in the dose deposited in the OARs. The therapeutic options, i.e., reirradiation or systemic therapy, need to be carefully weighed and discussed with the patients. Advances in knowledge: Highly conformal photon and proton beam techniques enable high-dose reirradiation of the target volume. In light of the abilities of the various highly conformal techniques to spare specific OARs, the therapeutic options need to be carefully weighed and patients included in the decision-making process.

Background and purpose: Patients with low-grade glioma (LGG) have a prolonged survival expectancy due to better discriminative tumor classification and multimodal treatment. Consequently, long-term treatment toxicity gains importance. Contemporary radiotherapy techniques such as intensity-modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT), tomotherapy (TOMO) and intensity-modulated proton therapy (IMPT) enable high-dose irradiation of the target but they differ regarding delivered dose to organs at risk (OARs). The aim of this comparative in silico study was to determine these dosimetric differences in delivered doses.Material and methods: Imaging datasets of 25 LGG patients having undergone postoperative radiotherapy were included. For each of these patients, in silico treatment plans to a total dose of 50.4Gy to the target volume were generated for the four treatment modalities investigated (i.e., IMRT, VMAT, TOMO, IMPT). Resulting treatment plans were analyzed regarding dose to target and surrounding OARs comparing IMRT, TOMO and IMPT to VMAT.Results: In total, 100 treatment plans (four per patient) were analyzed. Compared to VMAT, the IMPT mean dose (D-mean) for nine out of 10 (90%) OARs was statistically significantly (p<.02) reduced, for TOMO this was true in 3/10 (30%) patients and for 1/10 (10%) patients for IMRT. IMPT was the prime modality reducing dose to the OARs followed by TOMO.Discussion: The low dose volume to the majority of OARs was significantly reduced when using IMPT compared to VMAT. Whether this will lead to a significant reduction in neurocognitive decline and improved quality of life is to be determined in carefully designed future clinical trials.

Purpose: To create a digital, online atlas for organs at risk (OAR) delineation in neuro-oncology based on high-quality computed tomography (CT) and magnetic resonance (MR) imaging. Methods: CT and 3 Tesla (3T) MR images (slice thickness 1 mm with intravenous contrast agent) were obtained from the same patient and subsequently fused. In addition, a 7T MR without intravenous contrast agent was obtained from a healthy volunteer. Based on discussion between experienced radiation oncologists, the clinically relevant organs at risk (OARs) to be included in the atlas for neuro-oncology were determined, excluding typical head and neck OARs previously published. The draft atlas was delineated by a senior radiation oncologist, 2 residents in radiation oncology, and a senior neuro-radiologist incorporating relevant available literature. The proposed atlas was then critically reviewed and discussed by European radiation oncologists until consensus was reached. Results: The online atlas includes one CT-scan at two different window settings and one MR scan (3T) showing the OARs in axial, coronal and sagittal view. This manuscript presents the three-dimensional descriptions of the fifteen consensus OARs for neuro-oncology. Among these is a new OAR relevant for neuro-cognition, the posterior cerebellum (illustrated on 7T MR images). Conclusion: In order to decrease interand intra-observer variability in delineating OARs relevant for neuro-oncology and thus derive consistent dosimetric data, we propose this atlas to be used in photon and particle therapy. The atlas is available online at www.cancerdata.org and will be updated whenever

PURPOSE:To compare dose to organs at risk (OARs) and dose-escalation possibility for 24 stage I non-small cell lung cancer (NSCLC) patients in a ROCOCO (Radiation Oncology Collaborative Comparison) trial.METHODS:For each patient, 3 photon plans [Intensity-modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT) and CyberKnife], a double scattered proton (DSP) and an intensity-modulated carbon-ion (IMIT) therapy plan were created. Dose prescription was 60 Gy (equivalent) in 8 fractions.RESULTS:The mean dose and dose to 2% of the clinical target volume (CTV) were lower for protons and ions compared with IMRT (p < 0.01). Doses to the lungs, heart, and mediastinal structures were lowest with IMIT (p < 0.01), doses to the spinal cord were lowest with DSP (p < 0.01). VMAT and CyberKnife allowed for reduced doses to most OARs compared with IMRT. Dose escalation was possible for 8 patients. Generally, the mediastinum was the primary dose-limiting organ.CONCLUSION:On average, the doses to the OARs were lowest using particles, with more homogenous CTV doses. Given the ability of VMAT and CyberKnife to limit doses to OARs compared with IMRT, the additional benefit of particles may only be clinically relevant in selected patients and thus should be carefully weighed for every individual patient.

In the last decade, major advances have been made in the field of radiation oncology, bringing new diagnostic techniques and expanding the number of treatment modalities. Traditional evidence-based medicine uses randomised trials that are designed to represent homogenous populations of patients, and are not based upon patient, disease and treatment parameters. The human cognitive capacity is limited, however, making predictive modelling and big data in radiation oncology an increasingly essential tool in decision-making. This chapter discusses the process of gathering data, training models and developing DSS using rapid learning health care (RLHC). This is especially important when considering treatments such as hadron therapy. Modern technologies such as intensity-modulated radiotherapy (IMRT), brachytherapy (BT), volumetric arc radiotherapy (VMAT) or particle-beam therapy, such as hadron therapy, allow for localised dose delivery around the target volume with maximum sparing of the organs at risk with very high dosimetric accuracy.