Sharing data for cancer research
Biblio
] The posterior cerebellum, a new organ at risk?. Clinical and Translational Radiation Oncology. 2018;8:22 - 26. doi:10.1016/j.ctro.2017.11.010.
Data from: 4DCT imaging to assess radiomics feature stability: an investigation for thoracic cancers. 2017. doi:10.17195/candat.2017.05.1.
Data from: 4DCT imaging to assess radiomics feature stability: an investigation for thoracic cancers. 2017. doi:10.17195/candat.2017.05.1.
Data from: 4DCT imaging to assess radiomics feature stability: an investigation for thoracic cancers. 2017. doi:10.17195/candat.2017.05.1.
Data from: Developing and validating a survival prediction model for NSCLC patients through distributed learning across three countries. 2017. doi:10.17195/candat.2017.02.2.
Jochems-2017-MaastroDataUnbinned.csv (62.76 KB)
Jochems-2017-MaastroDataUnbinned.csv (62.76 KB) Data from: Survival prediction of non-small cell lung cancer patients using radiomics analyses of cone-beam CT images. 2017. doi:10.17195/candat.2017.02.1.
Van-Timmeren_2017_cases-001-020.zip (750.99 MB) Van-Timmeren_2017_cases-021-040.zip (726.98 MB) Van-Timmeren_2017_cases-041-060.zip (777.6 MB) Van-Timmeren_2017_cases-061-080.zip (795.72 MB) Van-Timmeren_2017_cases-081-102.zip (827.01 MB)
Van-Timmeren_2017_cases-001-020.zip (750.99 MB) Van-Timmeren_2017_cases-021-040.zip (726.98 MB) Van-Timmeren_2017_cases-041-060.zip (777.6 MB) Van-Timmeren_2017_cases-061-080.zip (795.72 MB) Van-Timmeren_2017_cases-081-102.zip (827.01 MB) Data from: Survival prediction of non-small cell lung cancer patients using radiomics analyses of cone-beam CT images. 2017. doi:10.17195/candat.2017.02.1. Van-Timmeren_2017_cases-001-020.zip (750.99 MB) Van-Timmeren_2017_cases-021-040.zip (726.98 MB) Van-Timmeren_2017_cases-041-060.zip (777.6 MB) Van-Timmeren_2017_cases-061-080.zip (795.72 MB) Van-Timmeren_2017_cases-081-102.zip (827.01 MB)
Van-Timmeren_2017_cases-001-020.zip (750.99 MB) Van-Timmeren_2017_cases-021-040.zip (726.98 MB) Van-Timmeren_2017_cases-041-060.zip (777.6 MB) Van-Timmeren_2017_cases-061-080.zip (795.72 MB) Van-Timmeren_2017_cases-081-102.zip (827.01 MB) Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries. International Journal of Radiation Oncology*Biology*Physics. 2017;99(2):344 - 352. doi:10.1016/j.ijrobp.2017.04.021.
Data from: Nitroglycerin in non-small cell lung cancer: does it impact tumor hypoxia and tumor perfusion? A window-of-opportunity clinical trial. 2016. doi:10.17195/candat.2016.07.2. 2017-08-28 Reymen - Nitro database HX-4 DCECT clean.zip (20.3 KB)
2017-08-28 Reymen - Nitro database HX-4 DCECT clean.zip (20.3 KB) Data from: Nitroglycerin in non-small cell lung cancer: does it impact tumor hypoxia and tumor perfusion? A window-of-opportunity clinical trial. 2016. doi:10.17195/candat.2016.07.2. 2017-08-28 Reymen - Nitro database HX-4 DCECT clean.zip (20.3 KB)
2017-08-28 Reymen - Nitro database HX-4 DCECT clean.zip (20.3 KB) Data from: Quantitative assessment of Zirconium-89 labeled cetuximab using PETCT imaging in patients with advanced head and neck cancer - a theragnostic approach. 2016. doi:10.17195/candat.2016.11.1. Even_P0037C0006I4475579.ZIP (97.26 MB) Even_P0037C0006I5879176.ZIP (131.21 MB) Even_P0037C0006I6042760.ZIP (115.71 MB) Even_P0037C0006I8991415.ZIP (101.03 MB)
Even_P0037C0006I4475579.ZIP (97.26 MB) Even_P0037C0006I5879176.ZIP (131.21 MB) Even_P0037C0006I6042760.ZIP (115.71 MB) Even_P0037C0006I8991415.ZIP (101.03 MB) Data from: Quantitative assessment of Zirconium-89 labeled cetuximab using PETCT imaging in patients with advanced head and neck cancer - a theragnostic approach. 2016. doi:10.17195/candat.2016.11.1. Even_P0037C0006I4475579.ZIP (97.26 MB) Even_P0037C0006I5879176.ZIP (131.21 MB) Even_P0037C0006I6042760.ZIP (115.71 MB) Even_P0037C0006I8991415.ZIP (101.03 MB)
Even_P0037C0006I4475579.ZIP (97.26 MB) Even_P0037C0006I5879176.ZIP (131.21 MB) Even_P0037C0006I6042760.ZIP (115.71 MB) Even_P0037C0006I8991415.ZIP (101.03 MB) Data from: Quantitative assessment of Zirconium-89 labeled cetuximab using PETCT imaging in patients with advanced head and neck cancer - a theragnostic approach. 2016. doi:10.17195/candat.2016.11.1. Even_P0037C0006I4475579.ZIP (97.26 MB) Even_P0037C0006I5879176.ZIP (131.21 MB) Even_P0037C0006I6042760.ZIP (115.71 MB) Even_P0037C0006I8991415.ZIP (101.03 MB)
Even_P0037C0006I4475579.ZIP (97.26 MB) Even_P0037C0006I5879176.ZIP (131.21 MB) Even_P0037C0006I6042760.ZIP (115.71 MB) Even_P0037C0006I8991415.ZIP (101.03 MB) Data from: Quantitative assessment of Zirconium-89 labeled cetuximab using PETCT imaging in patients with advanced head and neck cancer - a theragnostic approach. 2016. doi:10.17195/candat.2016.11.1. Even_P0037C0006I4475579.ZIP (97.26 MB) Even_P0037C0006I5879176.ZIP (131.21 MB) Even_P0037C0006I6042760.ZIP (115.71 MB) Even_P0037C0006I8991415.ZIP (101.03 MB)
Even_P0037C0006I4475579.ZIP (97.26 MB) Even_P0037C0006I5879176.ZIP (131.21 MB) Even_P0037C0006I6042760.ZIP (115.71 MB) Even_P0037C0006I8991415.ZIP (101.03 MB) Data from: A validated Tumor Control Probability model based on a meta-analysis of low, intermediate, and high-risk prostate cancer patients treated by photon, proton, or carbon-ion radiotherapy. 2015. doi:10.17195/candat.2015.10.8. Walsh - TCP meta-analysis of patients treated with photon, proton and c-ion radiotherapy (CSV) (15.82 KB)
Walsh - TCP meta-analysis of patients treated with photon, proton and c-ion radiotherapy (XLS) (13.85 KB)
Walsh - TCP meta-analysis of patients treated with photon, proton and c-ion radiotherapy (CSV) (15.82 KB) Walsh - TCP meta-analysis of patients treated with photon, proton and c-ion radiotherapy (XLS) (13.85 KB) Data from: Development and Evaluation of an Online Three-Level Proton vs Photon Decision Support Prototype for Head and Neck Cancer - Comparison of Dose, Toxicity and Cost-Effectiveness. 2015. doi:10.17195/candat.2015.10.5. PRODECIS-HNC-results.xlsx (43.25 KB)
PRODECIS-HNC-Figure-2.png (47.07 KB)
PRODECIS-HNC-results.xlsx (43.25 KB) PRODECIS-HNC-Figure-2.png (47.07 KB)
Data from: Development and Evaluation of an Online Three-Level Proton vs Photon Decision Support Prototype for Head and Neck Cancer - Comparison of Dose, Toxicity and Cost-Effectiveness. 2015. doi:10.17195/candat.2015.10.5. PRODECIS-HNC-results.xlsx (43.25 KB) PRODECIS-HNC-Figure-2.png (47.07 KB)
PRODECIS-HNC-results.xlsx (43.25 KB) PRODECIS-HNC-Figure-2.png (47.07 KB) Data from: MMP2 small immuno protein antibody uptake in xenograft tumors is associated with MMP2 activity. 2015. doi:10.17195/candat.2015.10.6. Panth_MMP2-activity-vs-uptake.csv (2.03 KB) Panth_MMP2-analysis.csv (6.1 KB)
Panth_MMP2-representative-images.rar (570.44 KB)
Panth_MMP2-activity-vs-uptake.csv (2.03 KB) Panth_MMP2-analysis.csv (6.1 KB) Panth_MMP2-representative-images.rar (570.44 KB) PET-based dose painting in non-small cell lung cancer: Comparing uniform dose escalation with boosting hypoxic and metabolically active sub-volumes. Radiother Oncol. 2015;116(2):281-6. doi:10.1016/j.radonc.2015.07.013.
PET-based dose painting in non-small cell lung cancer: Comparing uniform dose escalation with boosting hypoxic and metabolically active sub-volumes. Radiother Oncol. 2015;116(2):281-6. doi:10.1016/j.radonc.2015.07.013.
A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients. Int J Radiat Oncol Biol Phys. 2015;92(4):935-44. doi:10.1016/j.ijrobp.2015.02.048.
Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014;5:4006. doi:10.1038/ncomms5006.
Externally validated HPV-based prognostic nomogram for oropharyngeal carcinoma patients yields more accurate predictions than TNM staging. Radiother Oncol. 2014;113(3):324-30. doi:10.1016/j.radonc.2014.09.005.
. International data-sharing for radiotherapy research: an open-source based infrastructure for multicentric clinical data mining. Radiother Oncol. 2014;110(2):370-374. doi:10.1016/j.radonc.2013.11.001.
. International data-sharing for radiotherapy research: an open-source based infrastructure for multicentric clinical data mining. Radiother Oncol. 2014;110(2):370-374. doi:10.1016/j.radonc.2013.11.001.