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Radiomics of lung cancer (RAIL): non-invasive stratification of tumour heterogeneity for personalised cancer therapy

Total Cost €


EC-Contrib. €






Project "RAIL" data sheet

The following table provides information about the project.


Organization address
postcode: 6229 EV
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Netherlands [NL]
 Project website
 Total cost 2˙427˙593 €
 EC max contribution 2˙427˙593 € (100%)
 Programme 1. H2020-EU.3.1.3. (Treating and managing disease)
 Code Call H2020-SMEINST-2-2014
 Funding Scheme SME-2
 Starting year 2015
 Duration (year-month-day) from 2015-06-01   to  2020-03-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    PT THERAGNOSTIC BV NL (MAASTRICHT) coordinator 2˙427˙593.00


 Project objective

Lung cancer is the most common cause of death from cancer worldwide with 1.59 million deaths annually. It also places the highest economic burden of all cancers on the EU with EUR 18.8 billion. Non-small cell lung cancer (NSCLC) comprises 85% of all lung cancer cases. The current clinical routine to guide treatment for NSCLC patients is primarily based on the TNM staging system founded in 1958, mainly to look at surgical operability. However, TNM-based evaluation, nor doctors prediction do not provide an accurate prognosis. The heterogeneity between patients (inter-patient), tumours (inter-tumour) and even within one tumour (intra-tumour) underlies these highly variable prognosis and presents a major clinical challenge. There is a lack of easy to perform, ‘actionable’ biomarkers to stratify NSCLC patients which results in i) under-treatment in 20% of NSCLC patients leading to disease progression and ultimately death, ii) over-treatment in 30% of NSCLC patients which reduces the quality of life of patients and places an economic burden on the healthcare system and iii) ineffective clinical trial design, due to lack of optimal stratification, which requires very large, costly clinical trials to be performed in order to bring new therapeutic strategies to the market. ptTheragnostic has developed breakthrough technology, called “Radiomics”, which was recently published in Nature Communications, which enables patient stratification through the use of imaging biomarkers acquired from routine CT & PET imaging (see animation on In Radiomics for lung cancer (RAIL) we will validate and qualify a multi-site level I imaging biomarker together with a ready-to-use application to deliver more accurate prognostic information, personalise treatment for NSCLC patients, reduce healthcare costs by EUR 500 million and enable efficient clinical trial design.


List of deliverables.
CE approval Demonstrators, pilots, prototypes 2019-07-22 16:50:22
Annual update communication and dissemination plan M48 Documents, reports 2019-07-22 16:50:20
Completion of patient accrual Demonstrators, pilots, prototypes 2019-07-22 16:50:23
Annual update communication and dissemination plan M36 Documents, reports 2019-07-22 16:50:21
Medical ethical approval of the phase II protocol in all centres Documents, reports 2019-07-22 16:50:21
Dissemination material and updates Documents, reports 2019-05-30 12:53:05
Online version of public web site Websites, patent fillings, videos etc. 2019-05-30 12:53:10
Detailed communication and dissemination plan Documents, reports 2019-05-30 12:53:11
Annual update communication and dissemination plan Documents, reports 2019-05-30 12:53:13
Research protocol written and distributed to all participating centres Documents, reports 2019-05-20 13:05:27
Design History File Documents, reports 2019-05-20 13:05:26
Exploitation plan and annual updates Documents, reports 2019-05-20 13:05:27

Take a look to the deliverables list in detail:  detailed list of RAIL deliverables.


year authors and title journal last update
List of publications.
2016 Weimiao Wu, Chintan Parmar, Patrick Grossmann, John Quackenbush, Philippe Lambin, Johan Bussink, Raymond Mak, Hugo J. W. L. Aerts
Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology
published pages: , ISSN: 2234-943X, DOI: 10.3389/fonc.2016.00071
Frontiers in Oncology 6 2019-07-08
2016 Sara Carvalho, Esther G.C. Troost, Judith Bons, Paul Menheere, Philippe Lambin, Cary Oberije
Prognostic value of blood-biomarkers related to hypoxia, inflammation, immune response and tumour load in non-small cell lung cancer – A survival model with external validation
published pages: 487-494, ISSN: 0167-8140, DOI: 10.1016/j.radonc.2016.04.024
Radiotherapy and Oncology 119/3 2019-07-08
2015 Chintan Parmar, Patrick Grossmann, Derek Rietveld, Michelle M. Rietbergen, Philippe Lambin, Hugo J. W. L. Aerts
Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer
published pages: , ISSN: 2234-943X, DOI: 10.3389/fonc.2015.00272
Frontiers in Oncology 5 2019-07-08
2016 Philippe Lambin, Jaap Zindler, Ben G.L. Vanneste, Lien Van De Voorde, Daniëlle Eekers, Inge Compter, Kranthi Marella Panth, Jurgen Peerlings, Ruben T.H.M. Larue, Timo M. Deist, Arthur Jochems, Tim Lustberg, Johan van Soest, Evelyn E.C. de Jong, Aniek J.G. Even, Bart Reymen, Nicolle Rekers, Marike van Gisbergen, Erik Roelofs, Sara Carvalho, Ralph T.H. Leijenaar, Catharina M.L. Zegers, Maria Jacobs
Decision support systems for personalized and participative radiation oncology
published pages: , ISSN: 0169-409X, DOI: 10.1016/j.addr.2016.01.006
Advanced Drug Delivery Reviews 2019-07-08
2015 Ralph T.H. Leijenaar, Georgi Nalbantov, Sara Carvalho, Wouter J.C. van Elmpt, Esther G.C. Troost, Ronald Boellaard, Hugo J.W.L Aerts, Robert J. Gillies, Philippe Lambin
The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis
published pages: 11075, ISSN: 2045-2322, DOI: 10.1038/srep11075
Scientific Reports 5 2019-07-08

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