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The randomized clinical trial ESO-SPARE investigates if oesophagus-sparing radiotherapy (RT) can reduce dysphagia in patients with metastatic spinal cord compression (MSCC). Patient-reported outcome (PRO) is the only follow-up measure. Due to the fragile patient population, low respondent compliance was anticipated. We performed a planned interim analysis of dosimetry and respondent compliance, to ensure that the protocol requirements were met. Patients >18 years referred for cervical/thoracic MSCC radiotherapy in 1-10 fractions were included from two centres. Patients were randomized (1:1) to standard RT or oesophagus-sparing RT, where predefined oesophageal dose constraints were prioritized over target coverage. Patients completed a trial diary with daily reports of dysphagia for 5 weeks (PRO-CTC-AE) and weekly quality of life reports for 9 weeks (QLQ-C30, EQ-5D-5L). According to power calculation, 124 patients are needed for primary endpoint analysis. The sample size was inflated to 200 patients to account for the fragile patient population. The co-primary endpoints, peak patient-reported dysphagia, and preserved ability to walk (EQ-5D-5L), are analysed at 5 and 9 weeks, respectively. The interim analysis was conducted 90 days after the inclusion of patient no 100. Respondent compliance was assessed at 5 and 9 weeks. In all RT plans, oesophagus and target doses were evaluated regarding adherence to protocol constraints. From May 2021 to November 2022, 100 patients were included. Fifty-two were randomized to oesophagus-sparing RT. In 23% of these plans, oesophagus constraints were violated. Overall, the dose to both target and oesophagus was significantly lower in the oesophagus-sparing plans. Only 51% and 41% of the patients were evaluable for co-primary endpoint analysis at five and nine weeks, respectively. Mortality and hospitalization rates were significantly larger in patients who completed <4 days PRO questionnaires. Compliance was lower than anticipated and interventions to maintain study power are needed. [ABSTRACT FROM AUTHOR]

Purpose: Current radiation therapy planning uses a set of defined dose–volume constraints to ensure a specified level of tumor coverage while constraining the dose distribution in the organs at risk. Such constraints are aggregated, population‐based quantities that do not adequately consider patient‐specific risk factors. Furthermore, these constraints are calculated for each organ independently and it is therefore not guaranteed that the optimal trade‐off between organs is achieved. We introduce a novel radiotherapy planning approach where a patient‐specific all‐cause mortality risk is minimized using inverse plan optimization. As illustration of concept, our outcome risk model incorporates patient age, sex, cardiac risk factor (CRF), and smoking. Methods and materials: We retrospectively analyzed a left‐sided breast cancer case and a Hodgkin's lymphoma case, both clinically treated with three‐dimensional conformal radiotherapy (3D‐CRT). Our objective function for inverse plan optimization was an equally weighted summation of risk models for cancer recurrence and mortality from radiation‐induced coronary heart disease and secondary lung and breast cancers incorporating patient age, sex, CRF, and smoking. We allowed the optimization algorithm to choose from a large set of gantry angles. The optimization task was to choose beams and optimize monitor units (MUs) so that overall survival was maximized (and the total risk of cancer recurrence and mortality from radiation‐induced causes were minimized). The sensitivity analysis was performed in the lymphoma case by changing the tumor control probability model from using mean dose (Model 1) to using generalized equivalent uniform dose (Model 2). Results: For the breast case in this study, the 3D‐CRT clinical plan used eight beams while the proposed 3D‐CRT outcome‐optimized plan used five beams, reducing the total risk — summation of the risks of recurrence and secondary disease mortality — from 3% to 2%. The mean doses to clinical target volume (CTV) and internal mammary nodes (IMN) were increased in the outcome‐optimized plan by 1.9 and 1.8 Gy, respectively. For the Hodgkin's lymphoma case, the clinical 3D‐CRT plan used two beams, while the proposed 3D‐CRT outcome‐optimized plan used three beams, reducing the total risk by 6% (from 16% to 10%). Using either of the two tumor control models for the lymphoma case resulted in outcome‐optimized plans where tumor control was compensated at the cost of saving organs at risk. However, the impact of sensitivity to models was comparatively large. Using Model 1 resulted in a reduction in mean target dose by 15.2 vs 7.1 Gy for Model 2. In all cases, the chosen beams in outcome‐optimized plans were different from clinically used beams. Conclusions: The proposed optimization strategy, supplanting dosimetric objectives with comprehensive individual risk estimates, has the potential to yield improved outcomes in terms of reduced mortality risk in cancer patients treated with radiotherapy. The approach is, however, currently limited by gaps in knowledge about the effect of compromising dose to part of the target, for example, in order to spare cardiac structures. [ABSTRACT FROM AUTHOR]

Abstract: Monte Carlo simulations are increasingly used for dose calculations in proton therapy due to its inherent accuracy. However, dosimetric deviations have been found using Monte Carlo code when high density materials are present in the proton beamline. The purpose of this work was to quantify the magnitude of dose perturbation caused by metal objects. We did this by comparing measurements and Monte Carlo predictions of dose perturbations caused by the presence of small metal spheres in several clinical proton therapy beams as functions of proton beam range and drift space. Monte Carlo codes MCNPX, GEANT4 and Fast Dose Calculator (FDC) were used. Generally good agreement was found between measurements and Monte Carlo predictions, with the average difference within 5% and maximum difference within 17%. The modification of multiple Coulomb scattering model in MCNPX code yielded improvement in accuracy and provided the best overall agreement with measurements. Our results confirmed that Monte Carlo codes are well suited for predicting multiple Coulomb scattering in proton therapy beams when short drift spaces are involved. [Copyright &y& Elsevier]

Prostate cancer patients who undergo radiotherapy are at an increased risk to develop a radiogenic second cancer. Proton therapy has been shown to reduce the predicted risk of second cancer when compared to intensity modulated radiotherapy. However, it is unknown if this is also true for the rotational therapies proton arc therapy and volumetric modulated arc therapy (VMAT). The objective of this studywas to compare the predicted risk of cancer following proton arc therapy andVMATfor prostate cancer. Proton arc therapy andVMAT plans were created for three patients. Various risk models were combined with the dosimetric data (therapeutic and stray dose) to predict the excess relative risk (ERR) of cancer in the bladder and rectum. Ratios of ERR values (RRR) from proton arc therapy and VMAT were calculated. RRR values ranged from 0.74 to 0.99, and all RRR values were shown to be statistically less than 1, except for the value calculated with the linear-non-threshold risk model. We conclude that the predicted risk of cancer in the bladder or rectum following proton arc therapy for prostate cancer is either less than or approximately equal to the risk following VMAT, depending on which risk model is applied. [ABSTRACT FROM AUTHOR]