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d data over a wide range of dose-fractionation schemes. The same model, with only a few fitted parameters of clear mechanistic meaning, thus synthesizes both photon radiotherapy and CIRT clinical experience with early stage lung tumors.<br /><br /> To enable accurate magnetic resonance imaging (MRI)-based dose calculations, synthetic computed tomography (sCT) images need to be generated. We aim at assessing the feasibility of dose calculations from MRI acquired with a heterogeneous set of imaging protocol for paediatric patients affected by brain tumours.<br /><br /> Sixty paediatric patients undergoing brain radiotherapy were included. MR imaging protocols varied among patients, and data heterogeneity was maintained in train/validation/test sets. Three 2D conditional generative adversarial networks (cGANs) were trained to generate sCT from T1-weighted MRI, considering the three orthogonal planes and its combination (multi-plane sCT). For each patient, median and standard deviation (σ) of the three views were calculated, obtaining a combined sCT and a proxy for uncertainty map, respectively. The sCTs were evaluated against the planning CT in terms of image similarity and accuracy for photon and proton dose calculations.<br /><br /> A mean absolute error of 61±14 HU (mean±1σ) was obtained in the intersection of the body contours between CT and sCT. The combined multi-plane sCTs performed better than sCTs from any single plane. Uncertainty maps highlighted that multi-plane sCTs differed at the body contours and air cavities. A dose difference of -0.1±0.3% and 0.1±0.4% was obtained on the D&gt;90% of the prescribed dose and mean γ<br /><br /> pass-rate of 99.5±0.8% and 99.2±1.1% for photon and proton planning, respectively.<br /><br /> Accurate MR-based dose calculation using a combination of three orthogonal planes for sCT generation is feasible for paediatric brain cancer patients, even when training on a heterogeneous dataset.<br /><br />Accurate MR-based dose calculation using a combination of three orthogonal planes for sCT generation is feasible for paediatric brain cancer patients, even when training on a heterogeneous dataset.RR secondary to ICI (nivolumab in all patients) were observed in the lung (n = 1) or skin (n = 3). All patients had a long-term response to ICI and are currently alive with no active disease (Median FU from ICI discontinuation 30 months). RR could reflect a beneficial immune activation and constitute a predictive clinical biomarker of ICI long-term efficacy.<br /><br /> Daily online adaptation of the clinical target volume (CTV) using MR-guided radiotherapy enables margin reduction of the planning target volume (PTV). This study describes the implementation and initial experience of MR-guided radiotherapy on the 1.5T MR-linac and evaluates treatment time, patient compliance, and target coverage, including an initial assessment of margin reduction.<br /><br /> Patients were treated on a 1.5T MR-linac (7MV, FFF). At each fraction a 3D T2 weighted (T2w) MR-sequence was acquired on which the CTV was adapted after a deformable registration of the contours from the pre-planning CT scan. Based on the new contours a full online replanning was done after which a new 3D T2w MR-sequence was acquired for position verification. A 5 field Intensity Modulated Radiotherapy (IMRT) plan was delivered.<br /><br /> Forty-three patients with rectal cancer were treated with 25Gy in 5 fractions of which 18 with reduced margins. In total, 204 of 215 fractions were delivered on the MR-linac all of which obtained a clinically acceptable treatment plan. Median in-room time per fraction was 48min (interquartile range 8). No fractions were canceled or interrupted because of patient intolerance. CTV coverage after margin reduction was good on all post-treatment scans but one due to passing gas.<br /><br /> MR-guided radiotherapy using daily full online recontouring and replanning on a 1.5T MR-linac for rectal cancer is feasible and currently takes about 48min per fraction.<br /><br />MR-guided radiotherapy using daily full online recontouring and replanning on a 1.5T MR-linac for rectal cancer is feasible and currently takes about 48 min per fraction.<br /><br /> We aimed to develop a radiomics model for the prediction of survival and chemotherapeutic benefits using pretreatment multiparameter MR images and clinicopathological features in patients with locally advanced rectal cancer (LARC).<br /><br /> 186 consecutive patients with LARC underwent feature extraction from the whole tumor on T2-weighted, contrast enhanced T1-weighted, and ADC images. Feature selection was based on feature stability and the Boruta algorithm. [https://www.selleckchem.com/products/milademetan.html DS-3032b mw] Radiomics signatures for predicting DFS (disease-free survival) were then generated using the selected features. Combining clinical risk factors, a radiomics nomogram was constructed using Cox proportional hazards regression model. The predictive performance was evaluated by Harrell's concordance indices (C-index) and time-independent receiver operating characteristic (ROC) analysis.<br /><br /> Four features were selected to construct the radiomics signature, significantly associated with DFS (P&lt;0.001). The radiomics nomogram, incorporating radiomics signature and ARC.Radiotherapy treatment planning studies contribute significantly to advances and improvements in radiation treatment of cancer patients. They are a pivotal step to support and facilitate the introduction of novel techniques into clinical practice, or as a first step before clinical trials can be carried out. There have been numerous examples published in the literature that demonstrated the feasibility of such techniques as IMRT, VMAT, IMPT, or that compared different treatment methods (e.g. non-coplanar vs coplanar treatment), or investigated planning approaches (e.g. automated planning). However, for a planning study to generate trustworthy new knowledge and give confidence in applying its findings, then its design, execution and reporting all need to meet high scientific standards. This paper provides a 'quality framework' of recommendations and guidelines that can contribute to the quality of planning studies and resulting publications. Throughout the text, questions are posed and, if applicable to a specific study and if met, they can be answered positively in the provided 'RATING' score sheet.