A minimal PKPD interaction model for evaluating synergy effects of combined NSCLC therapies

This paper introduces a mathematical compartmental formulation of dose-effect synergy modelling for multiple therapies in non small cell lung cancer (NSCLC): antiangiogenic, immuno- and radiotherapy. The model formulates the dose-effect relationship in a unified context, with tumor proliferating rates and necrotic tissue volume progression as a function of therapy management profiles. The model accounts for inter- and intra-response variability by using surface model response terms. Slow acting peripheral compartments such as fat and muscle for drug distribution are not modelled. This minimal pharmacokinetic-pharmacodynamic (PKPD) model is evaluated with reported data in mice from literature. A systematic analysis is performed by varying only radiotherapy profiles, while antiangiogenesis and immunotherapy are fixed to their initial profiles. Three radiotherapy protocols are selected from literature: (1) a single dose 5 Gy once weekly; (2) a dose of 5 Gy x 3 days followed by a 2 Gy x 3 days after two weeks and (3) a dose of 5 Gy + 2 x 0.075 Gy followed after two weeks by a 2 Gy + 2 x 0.075 Gy dose. A reduction of 28% in tumor end-volume after 30 days was observed in Protocol 2 when compared to Protocol 1. No changes in end-volume were observed between Protocol 2 and Protocol 3, this in agreement with other literature studies. Additional analysis on drug interaction suggested that higher synergy among drugs affects up to three-fold the tumor volume (increased synergy leads to significantly lower growth ratio and lower total tumor volume). Similarly, changes in patient response indicated that increased drug resistance leads to lower reduction rates of tumor volumes, with end-volume increased up to 25-30%. In conclusion, the proposed minimal PKPD model has physiological value and can be used to study therapy management protocols and is an aiding tool in the clinical decision making process. Although developed with data from mice studies, the model is scalable to NSCLC patients

A comparative evaluation of 3 different free-form deformable image registration and contour propagation methods for head and neck MRI : the case of parotid changes radiotherapy

Purpose: To validate and compare the deformable image registration and parotid contour propagation process for head and neck magnetic resonance imaging in patients treated with radiotherapy using 3 different approachesthe commercial MIM, the open-source Elastix software, and an optimized version of it. Materials and Methods: Twelve patients with head and neck cancer previously treated with radiotherapy were considered. Deformable image registration and parotid contour propagation were evaluated by considering the magnetic resonance images acquired before and after the end of the treatment. Deformable image registration, based on free-form deformation method, and contour propagation available on MIM were compared to Elastix. Two different contour propagation approaches were implemented for Elastix software, a conventional one (DIR_Trx) and an optimized homemade version, based on mesh deformation (DIR_Mesh). The accuracy of these 3 approaches was estimated by comparing propagated to manual contours in terms of average symmetric distance, maximum symmetric distance, Dice similarity coefficient, sensitivity, and inclusiveness. Results: A good agreement was generally found between the manual contours and the propagated ones, without differences among the 3 methods; in few critical cases with complex deformations, DIR_Mesh proved to be more accurate, having the lowest values of average symmetric distance and maximum symmetric distance and the highest value of Dice similarity coefficient, although nonsignificant. The average propagation errors with respect to the reference contours are lower than the voxel diagonal (2 mm), and Dice similarity coefficient is around 0.8 for all 3 methods. Conclusion: The 3 free-form deformation approaches were not significantly different in terms of deformable image registration accuracy and can be safely adopted for the registration and parotid contour propagation during radiotherapy on magnetic resonance imaging. More optimized approaches (as DIR_Mesh) could be preferable for critical deformations

A phase III randomized-controlled, single-blind trial to improve quality of life with stereotactic body radiotherapy for patients with painful bone metastases (ROBOMET)

Background Bone metastases represent an important source of morbidity in cancer patients, mostly due to severe pain. Radiotherapy is an established symptomatic treatment for painful bone metastases, however, when conventional techniques are used, the effectiveness is moderate. Stereotactic body radiotherapy (SBRT), delivering very high doses in a limited number of fractions in a highly conformal manner, could potentially be more effective and less toxic. Methods This is a phase III, randomized-controlled, single-blind, multicenter study evaluating the response rate of antalgic radiotherapy for painful bone metastases and the acute toxicity associated with this treatment. A total of 126 patients will be randomly assigned to receive either the standard schedule of a single fraction of 8.0 Gy delivered through three-dimensional conformal radiotherapy or a single fraction of 20.0 Gy delivered through SBRT. Primary endpoint is pain response at the treated site at 1 month after radiotherapy. Secondary endpoints are pain flare at 24-48-72 h after radiotherapy, duration of pain response, re-irradiation need, acute toxicity, late toxicity, quality of life and subsequent serious skeletal events. In a supplementary analysis, patient-compliance for a paper-and-pencil questionnaire will be compared with an electronic mode. Discussion If a dose-escalated approach within the context of single fraction stereotactic body radiotherapy could improve the pain response to radiotherapy and minimize acute toxicity, this would have an immediate impact on the quality of life for a large number of patients with advanced cancer. Potential disadvantages of this technique include increased pain flare or a higher incidence of radiation-induced fractures. Trial registration: The Ethics committee of the GZA Hospitals (B099201732915) approved this study on September 4th 2018. Trial registered on Clinicaltrials. gov (NCT03831243) on February 5th 2019

Improvement of European translational cancer research. Collaboration between comprehensive cancer centers

Even though the increasing incidence of cancer is mainly a consequence of a population with a longer life span, part of this augmentation is related to the increasing prevalence of patients living with a chronic cancer disease. To fight the problem, improved preventive strategies are mandatory in combination with an innovative health care provision that is driven by research. To overcome the weakness of translational research the OECI is proposing a practical approach as part of a strategy foreseen by the EUROCAN+PLUS feasibility study, which was launched by the EC in order to identify mechanisms for the coordination of cancer research in Europe

Machine learning-based detection of aberrant deep learning segmentations of target and organs at risk for prostate radiotherapy using a secondary segmentation algorithm

Objective. The output of a deep learning (DL) auto-segmentation application should be reviewed, corrected if needed and approved before being used clinically. This verification procedure is labour-intensive, time-consuming and user-dependent, which potentially leads to significant errors with impact on the overall treatment quality. Additionally, when the time needed to correct auto-segmentations approaches the time to delineate target and organs at risk from scratch, the usability of the DL model can be questioned. Therefore, an automated quality assurance framework was developed with the aim to detect in advance aberrant auto-segmentations. Approach. Five organs (prostate, bladder, anorectum, femoral head left and right) were auto-delineated on CT acquisitions for 48 prostate patients by an in-house trained primary DL model. An experienced radiation oncologist assessed the correctness of the model output and categorised the auto-segmentations into two classes whether minor or major adaptations were needed. Subsequently, an independent, secondary DL model was implemented to delineate the same structures as the primary model. Quantitative comparison metrics were calculated using both models' segmentations and used as input features for a machine learning classification model to predict the output quality of the primary model. Main results. For every organ, the approach of independent validation by the secondary model was able to detect primary auto-segmentations that needed major adaptation with high sensitivity (recall = 1) based on the calculated quantitative metrics. The surface DSC and APL were found to be the most indicated parameters in comparison to standard quantitative metrics for the time needed to adapt auto-segmentations. Significance. This proposed method includes a proof of concept for the use of an independent DL segmentation model in combination with a ML classifier to improve time saving during QA of auto-segmentations. The integration of such system into current automatic segmentation pipelines can increase the efficiency of the radiotherapy contouring workflow

Characterisation and classification of oligometastatic disease : a European Society for Radiotherapy and Oncology and European Organisation for Research and Treatment of Cancer consensus recommendation

Oligometastatic disease has been proposed as an intermediate state between localised and systemically metastasised disease. In the absence of randomised phase 3 trials, early clinical studies show improved survival when radical local therapy is added to standard systemic therapy for oligometastatic disease. However, since no biomarker for the identification of patients with true oligometastatic disease is clinically available, the diagnosis of oligometastatic disease is based solely on imaging findings. A small number of metastases on imaging could represent different clinical scenarios, which are associated with different prognoses and might require different treatment strategies. 20 international experts including 19 members of the European Society for Radiotherapy and Oncology and European Organisation for Research and Treatment of Cancer OligoCare project developed a comprehensive system for characterisation and classification of oligometastatic disease. We first did a systematic review of the literature to identify inclusion and exclusion criteria of prospective interventional oligometastatic disease clinical trials. Next, we used a Delphi consensus process to select a total of 17 oligometastatic disease characterisation factors that should be assessed in all patients treated with radical local therapy for oligometastatic disease, both within and outside of clinical trials. Using a second round of the Delphi method, we established a decision tree for oligometastatic disease classification together with a nomenclature. We agreed oligometastatic disease as the overall umbrella term. A history of polymetastatic disease before diagnosis of oligometastatic disease was used as the criterion to differentiate between induced oligometastatic disease (previous history of polymetastatic disease) and genuine oligometastatic disease (no history of polymetastatic disease). We further subclassified genuine oligometastatic disease into repeat oligometastatic disease (previous history of oligometastatic disease) and de-novo oligometastatic disease (first time diagnosis of oligometastatic disease). In de-novo oligometastatic disease, we differentiated between synchronous and metachronous oligometastatic disease. We did a final subclassification into oligorecurrence, oligoprogression, and oligopersistence, considering whether oligometastatic disease is diagnosed during a treatment-free interval or during active systemic therapy and whether or not an oligometastatic lesion is progressing on current imaging. This oligometastatic disease classification and nomenclature needs to be prospectively evaluated by the OligoCare study

Development of an ultra-thin parallel plate ionization chamber for dosimetry in FLASH radiotherapy

Conventional air ionization chambers (ICs) exhibit ion recombination correction factors that deviate substantially from unity when irradiated with dose per pulse magnitudes higher than those used in conventional radiotherapy. This fact makes these devices unsuitable for the dosimetric characterization of beams in ultra-high dose per pulse as used for FLASH radiotherapyParticipating States; Horizon 2020; European Metrology Programme for Innovation and Research, Grant/Award Number: 18HLT04UHD PulseS

Professional practice changes in radiotherapy physics during the COVID-19 pandemic.

Background and purpose The COVID-19 pandemic has imposed changes in radiotherapy (RT) departments worldwide. Medical physicists (MPs) are key healthcare professionals in maintaining safe and effective RT. This study reports on MPs experience during the first pandemic peak and explores the consequences on their work. Methods A 39-question survey on changes in departmental and clinical practice and on the impact for the future was sent to the global MP community. A total of 433 responses were analysed by professional role and by country clustered on the daily infection numbers. Results The impact of COVID-19 was bigger in countries with high daily infection rate. The majority of MPs worked in alternation at home/on-site. Among practice changes, implementation and/or increased use of hypofractionation was the most common (47% of the respondents). Sixteen percent of respondents modified patient-specific quality assurance (QA), 21% reduced machine QA, and 25% moved machine QA to weekends/evenings. The perception of trust in leadership and team unity was reversed between management MPs (towards increased trust and unity) and clinical MPs (towards a decrease). Changes such as home-working and increased use of hypofractionation were welcomed. However, some MPs were concerned about pressure to keep negative changes (e.g. weekend work). Conclusion COVID-19 affected MPs through changes in practice and QA procedures but also in terms of trust in leadership and team unity. Some changes were welcomed but others caused worries for the future. This report forms the basis, from a medical physics perspective, to evaluate long-lasting changes within a multi-disciplinary setting

Asymétrie d’information et marchés financiers : une synthèse de la littérature récente

Cet article est une synthèse des recherches récentes en matière d’asymétrie d’informations sur les marchés financiers. L’impact de différentes hypothèses sur l’existence et l’efficience informationnelle des équilibres est étudié. Le cas de la concurrence parfaite est d’abord analysé (Grossman et Stiglitz, 1980). Puis la concurrence imparfaite est analysée. On distingue deux cas, selon que le bruit qui empêche le prix d’être parfaitement révélateur provient d’une offre exogène (KyIe, 1985, 1989), ou d’une dotation aléatoire des agents informés (Glosten, 1989; Bhattacharya et Spiegel, 1990; Bossaerts et Hughson, 1991). Dans le premier cas, l’équilibre existe toujours. Dans le second cas, il n’existe que si le bruit est assez élevé ou si le support de sa distribution est borné.The impact of different hypotheses on the existence and informativeness of rational expectations equilibria is analyzed within a simple synthetic model. The case of perfect competition is first analyzed (Grossman and Stiglitz, 1980). Second imperfect competition with exogenous noise trading is studied (KyIe 1985, 1989). Informational efficiency is lower than in the previous case, because of the strategic behaviour of the insider. Third, imperfect competition without noise trader, but with unknown random endowments of the informed agent is analyzed (Glosten, 1989; Bhattacharya and Spiegel, 1990; Bossaerts and Hughson, 1991). In contrast with the previous case, equilibrium exists only if there is enough noise