Biblio

Author [ Title(Asc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
R
Lambin P. Radiomics Digital Phantom. 2016. doi:10.17195/candat.2016.08.1.Package icon PHANTOM_DICOM.zip (7.73 MB)Package icon GTV_B_DICOM.zip (281.74 KB)Package icon GTV_M_DICOM.zip (175.39 KB)Package icon GTV_O_DICOM.zip (421.42 KB)
P
Starmans MHW, Chu KC, Haider S, et al. The prognostic value of temporal in vitro and in vivo derived hypoxia gene-expression signatures in breast cancer. Radiotherapy and Oncology. 2012;102(3):436 - 443. doi:10.1016/j.radonc.2012.02.002.
Carvalho S, Leijenaar RTH, Velazquez ERios, et al. Prognostic value of metabolic metrics extracted from baseline positron emission tomography images in non-small cell lung cancer. Acta Oncol. 2013;52(7):1398-404. doi:10.3109/0284186X.2013.812795.
Dubois LJ, Lieuwes NG, Janssen MHM, et al. Preclinical evaluation and validation of [18F]HX4, a promising hypoxia marker for PET imaging. Proceedings of the National Academy of Sciences. 2011;108(35):14620 - 14625. doi:10.1073/pnas.1102526108.
Eekers DBP, Ven Lin 't, Deprez S, et al. 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.
Even AJG, van der Stoep J, Zegers CML, et al. 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.
Loon J, Janssen MHM, Oellers MC, et al. PET imaging of hypoxia using [18F]HX4: a phase I trial. European Journal of Nuclear Medicine and Molecular Imaging. 2010;37(9):1663 - 1668. doi:10.1007/s00259-010-1437-x.
O
Eekers DBP. Optimization of Brain and Head & Neck Radiotherapy. GROW - School for Oncology and Developmental Biology. 2018;Ph.D.:201. doi:10.17195/candat.2018.12.7.PDF icon 2018-Eekers-Thesis.pdf (5.47 MB)PDF icon 2018-Eekers-Propositions.pdf (381.59 KB)PDF icon 2018-Eekers-Thesis-Summary.pdf (318.74 KB)
F
Roelofs E. From Data to Decision - A Knowledge Engineering approach to individualise cancer therapy. GROW - School for Oncology and Developmental Biology. 2016;Ph.D.:175. doi:10.17195/candat.2016.07.01.PDF icon Dissertation - full (6.52 MB)PDF icon Propositions (51.51 KB)
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Aerts HJWL, Velazquez ERios, Leijenaar RTH, et al. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014;5:4006. doi:10.1038/ncomms5006.
van Timmeren J, Leijenaar RTH, van Elmpt W, et al. 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.Package icon Van-Timmeren_2017_cases-001-020.zip (750.99 MB)Package icon Van-Timmeren_2017_cases-021-040.zip (726.98 MB)Package icon Van-Timmeren_2017_cases-041-060.zip (777.6 MB)Package icon Van-Timmeren_2017_cases-061-080.zip (795.72 MB)Package icon Van-Timmeren_2017_cases-081-102.zip (827.01 MB)
Even A, Hamming-Vrieze O, van Elmpt W, et al. 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.Package icon Even_P0037C0006I4475579.ZIP (97.26 MB)Package icon Even_P0037C0006I5879176.ZIP (131.21 MB)Package icon Even_P0037C0006I6042760.ZIP (115.71 MB)Package icon Even_P0037C0006I8991415.ZIP (101.03 MB)
Carvalho S, Troost EGC, Bons J, Menheere P, Lambin P, Oberije C. Data from: 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. 2016. doi:10.17195/candat.2016.04.1.File carvalho-prognostic-biomarkers-NSCLC.xlsx (69.51 KB)
Reymen B, van Gisbergen MW, Even AJG, et al. 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.Package icon 2017-08-28 Reymen - Nitro database HX-4 DCECT clean.zip (20.3 KB)
Panth K, van den Beucken T, Biemans R, et al. Data from: MMP2 small immuno protein antibody uptake in xenograft tumors is associated with MMP2 activity. 2015. doi:10.17195/candat.2015.10.6.File Panth_MMP2-activity-vs-uptake.csv (2.03 KB)File Panth_MMP2-analysis.csv (6.1 KB)File Panth_MMP2-representative-images.rar (570.44 KB)
Eekers D, Roelofs E, Cubillos-Mesias M, et al. Data from: Intensity-modulated proton therapy decreases dose to organs at risk in low-grade glioma patients: results of a multicentric in silico ROCOCO trial. 2018. doi:10.17195/candat.2018.05.1.File CanDat - 2018 Eekers - Data LGG .ods (157.14 KB)File CanDat - 2018 Eekers - Data LGG .xlsx (183.07 KB)
Cheng Q, Roelofs E, Ramaekers B, et al. 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.File PRODECIS-HNC-results.xlsx (43.25 KB)Image icon PRODECIS-HNC-Figure-2.png (47.07 KB)
Jochems A, Deist TM, Naqa IEl, et al. 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.File Jochems-2017-MaastroDataUnbinned.csv (62.76 KB)
Eekers D, Roelofs E, Jelen U, et al. Data from: Benefit of particle therapy in re-irradiation of head and neck patients. Results of a multicenter in silico ROCOCO trial. 2016. doi:10.17195/candat.2016.04.2.
Walsh S, Roelofs E, Kuess P, et al. 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.File Walsh - TCP meta-analysis of patients treated with photon, proton and c-ion radiotherapy (CSV) (15.82 KB)File Walsh - TCP meta-analysis of patients treated with photon, proton and c-ion radiotherapy (XLS) (13.85 KB)
Larue RTHM, Van De Voorde L, van Timmeren JE, et al. Data from: 4DCT imaging to assess radiomics feature stability: an investigation for thoracic cancers. 2017. doi:10.17195/candat.2017.05.1.
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