@article {93, title = {The posterior cerebellum, a new organ at risk?}, journal = {Clinical and Translational Radiation Oncology}, volume = {8}, year = {2018}, month = {Jan-01-2018}, pages = {22 - 26}, abstract = {

Eekers et al. have recently proposed a neuro-oncology atlas [doi:10.17195/candat.2017.08.1, Ed.], which was co-authored by most centers associated in the European Proton Therapy Network (EPTN). With the introduction of new treatment techniques, such as integrated magnetic resonance imaging and linear accelerators (MR-linac) or particle therapy, the prediction of clinical efficacy of these more costly treatment modalities becomes more relevant. One of the side-effects of brain irradiation, being cognitive decline, is one of the toxicities most difficult to measure and predict. In order to validly compare different treatment modalities, 1) a uniform nomenclature of the organs at risk (OARs), 2) uniform atlas-based delineation [e.g., Eekers et al.], 3) long-term follow-up data with standardized cognitive tests, 4) a large patient population, and 5) (thus derived) validated normal tissue complication probability (NTCP) models are mandatory.

Apart from the Gondi model, in which the role of the dose to 40\% of both hippocampi (HC) proves to be significantly related to cognition in 18 patients, no similar models are available. So there is a strong need for more NTCP models, on HC, brain tissue and possible other relevant brain structures.

In this review we summarize the available evidence on the role of the posterior cerebellum as a possible new organ at risk for cognition, which is deemed relevant for irradiation of brain and head and neck tumors.

}, keywords = {Cognition, Delineation atlas, Neuro-oncology, Organ at risk, Posterior cerebellum, Radiotherapy}, issn = {24056308}, doi = {10.1016/j.ctro.2017.11.010}, url = {http://linkinghub.elsevier.com/retrieve/pii/S2405630817300769}, author = {Eekers, Dani{\"e}lle B.P. and Lieke in {\textquoteright}t Ven and Deprez, Sabine and Jacobi, Linda and Erik Roelofs and Ann Hoeben and Lambin, Philippe and Dirk De Ruysscher and Troost, Esther G.C.} } @article {79, title = {Data from: Developing and validating a survival prediction model for NSCLC patients through distributed learning across three countries}, year = {2017}, publisher = {CancerData}, abstract = {

Purpose

Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with (chemo)radiotherapy are of limited quality. In this work, we develop a predictive model of survival at two years based on a large volume of historical patient data, as a proof of concept, using a distributed learning approach.

Patients and methods

Clinical data from 698 lung cancer patients, treated with curative intent with chemoradiation (CRT) or radiotherapy (RT) alone were collected and stored in 2 different cancer institutes (559 patients at Maastro clinic (Netherlands), 139 at University of Manchester (UK). The model was further validated on 196 patients originating from the University of Michigan (USA).

A Bayesian network model is adapted for distributed learning (watch the animation). Two-year post-treatment survival was chosen as endpoint.\ The Institute 1 cohort data is publicly available\ and the developed models can be found at\ PredictCancer.org)

Results

Variables included in the final model were T and N stage, age, performance status, and total tumor dose. The model has an AUC of 0.66 on the external validation set and an AUC of 0.62 on a 5-fold cross-validation. A model based on T and N stage performed with an AUC of 0.47 on the validation set, significantly worse than our model (P\<0.001). A high- and low-risk chance of survival group can be identified using the model presented in this study, these groups have significantly different overall survival (P\<0.01).

Conclusion

Distributed learning from federated databases allows learning of predictive models on data originating from multiple institutions while avoiding many of the data sharing barriers.\ We believe that Distributed learning is the future of sharing data in health care.

}, keywords = {Bayesian network, lung cancer, NSCLC, prediction model}, doi = {10.17195/candat.2017.02.2}, author = {Arthur Jochems and Timo M. Deist and Issam El Naqa and Marc Kessler and Chuck Mayo and Jackson Reeves and Shruti Jolly and Martha Matuszak and Randall Ten Haken and Johan van Soest and Cary Oberije and Corinne Faivre-Finn and Gareth Price and Dirk De Ruysscher and Philippe Lambin and Andr{\'e} Dekker} } @article {72, title = {Data from: Nitroglycerin in non-small cell lung cancer: does it impact tumor hypoxia and tumor perfusion? A window-of-opportunity clinical trial.}, year = {2016}, abstract = {

Despite preclinical evidence that nitric oxide (NO) donors influence both tumor perfusion and hypoxia, in clinical trials nitroglycerin has not been shown to improve the treatment results of all patients with non-small cell lung cancer (NSCLC). Biomarkers are therefore needed to select patients for treatment with NO donors. In this window-of-opportunity study we demonstrate the effect of nitroglycerin on hypoxia in patients using repeated hypoxia PET-imaging: we observed a reduction of hypoxia - quantified by uptake of PET tracer HX4- of varying magnitude upon application of a nitroglycerin patch in approximately two thirds of patients with hypoxic loco-regional disease.

In a quarter of patients with baseline hypoxia, the tumor and nodes become normoxic after treatment with nitroglycerin. Furthermore, through dynamic contrast enhanced CT-scans (DCE-CT) we demonstrated that this effect on hypoxic tracer uptake is negatively correlated with tumor perfusion in hypoxic tumors.

Using in vitro experiments we show that the metabolism of 2-nitroimidazoles is not influenced by nitroglycerin itself and furthermore that nitroglycerin does not inhibit mitochondrial respiration at human achievable concentrations. Therefore, 2-nitroimidazole based imaging biomarkers can be used to evaluate the nitroglycerin treatment efficacy in an individual patient.\ 

The current results do support the hypothesis that hypoxia scans and/or DCE-CT scans could form a tool to select patients for a nitroglycerin patch adjuvant to anti-cancer treatment (radiotherapy, chemotherapy, targeted agents or immunotherapy) to increase drug uptake and/or to decrease hypoxia.

An animation summarizing our results is available at https://youtu.be/udJSBYaRv9w.

Figure 1. Uptake of HX4 before and after nitoglycerin administration

A. Images of a HX4 PET/CT scan before and after nitroglycerin administration of the same patient.
B. Evolution of high-uptake fraction (HF) of HX4 after application of nitroglycerin patch in baseline hypoxic lesions. Blue = decline \> CR of HX4 (17\%), grey = stable: change \< CR.

Note: dataset was updated 2017-11-24
}, doi = {10.17195/candat.2016.07.2}, author = {Bart Reymen and Marike W. van Gisbergen and Aniek J.G. Even and Catharina M.L. Zegers and Cary Oberije and Felix Mottaghy and Marco Das and Ala Yaromina and Wouter van Elmpt and Dirk De Ruysscher and Ludwig Dubois and Philippe Lambin} } @article {34, title = {Cardiac comorbidity is an independent risk factor for radiation-induced lung toxicity in lung cancer patients}, journal = {Radiotherapy and Oncology}, volume = {109}, year = {2013}, month = {Jan-10-2013}, pages = {100 - 106}, issn = {01678140}, doi = {10.1016/j.radonc.2013.08.035}, url = {http://linkinghub.elsevier.com/retrieve/pii/S0167814013004350}, author = {Nalbantov, Georgi and Kietselaer, Bas and Vandecasteele, Katrien and Cary Oberije and Maaike Berbee and Esther G C Troost and Anne-Marie C. Dingemans and Baardwijk, Angela van and Smits, Kim and Andr{\'e} Dekker and Johan Bussink and Dirk De Ruysscher and Lievens, Yolande and P. Lambin} } @article {37, title = {PET imaging of hypoxia using [18F]HX4: a phase I trial}, journal = {European Journal of Nuclear Medicine and Molecular Imaging}, volume = {37}, year = {2010}, month = {Jan-08-2010}, pages = {1663 - 1668}, abstract = {

Download the images using\ these instructions\ and this DOI :\ 10.1007/s00259-010-1437-x

Background and purpose
Non-invasive PET imaging of tumour hypoxia could help in the selection of those patients who could benefit from chemotherapy or radiation with specific antihypoxic treatments such as bioreductive drugs or hypoxic radiosensitizers. In this phase I trial, we aimed to determine the toxicity of [18F]HX4, a member of the 2-nitroimidazole family, at different dose levels. The secondary aim was to analyse image quality related to the HX4 dose and the timing of imaging.

Methods
Patients with a histologically proven solid cancer without curative treatment options were eligible for this study. A study design with two dose steps was used in which a single dose of a maximum of 222MBq (step 1) or 444 MBq (step 2) [18F]HX4 was injected. Toxicity was scored on day 0 and on days 3 and 7 after injection, according to the CTCAE 3.0 scoring system. PET/CT images of the largest tumour site were acquired 30, 60 and 120 min after injection.

Results
Six patients with stage IV carcinoma were included, four with non-small-cell lung carcinoma, one with thymus carcinoma, and one with colon carcinoma. No toxicity was observed in any of the patients at either dose level. The median tumour to muscle ratio 120 min after injection was 1.40 (range 0.63{\textendash}1.98).

Conclusion\ 
The findings of this study showed that [18F] HX4 PET imaging for the detection of hypoxia is not associated with any toxicity. Imaging was successful; however, future trials are needed to determine the optimal image parameters.

}, keywords = {2-Nitroimidazoles, HX4, Hypoxia, PET}, issn = {1619-7070}, doi = {10.1007/s00259-010-1437-x}, url = {http://link.springer.com/10.1007/s00259-010-1437-x}, author = {Loon, Judith and Marco H. M. Janssen and M. C. Oellers and Hugo J. W. L. Aerts and L. J. Dubois and Hochstenbag, Monique and Anne-Marie C. Dingemans and Lalisang, Roy and Brans, Boudewijn and Windhorst, Bert and Dongen, Guus A. and H. C. Kolb and Zhang, James and Dirk De Ruysscher and P. Lambin} } Error | CancerData.org

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