Clinical trial · Observational
Radiomics for Prediction of Survival in GBM
Radiomics for the Prediction of Survival in GBM After Radiotherapy With/Without Temozolomide
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Radiomics, the extraction of large amounts of quantitative image features to convert medical images into minable data, is an in-development field that intends to provide accurate risk stratification of oncologic patients. Published prognostic scores only take clinical variables into account. The investigators hypothesize that a combination of CT/MRI features, molecular biology and clinical data can provide an accurate prediction of medical outcome. The long term objective is to build a Decision Support System based on the predictive models established in this study.
Conditions
Conditions (3)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Astrocytoma | Astrocytoma | CURATED_BROADER | 0.80 |
| Glioblastoma | Glioblastoma | CURATED_BROADER | 0.80 |
| Glioma | Glioma | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- Sensitive value of 6 months survival after radiotherapy with radiomics
- timeFrame
- 6 months
Secondary outcomes (3)
- measure
- Sensitive value of 12 months survival after radiotherapy with radiomics
- timeFrame
- 12 months
- measure
- Specificity value of 6 months survival after radiotherapy with radiomics
- timeFrame
- 6 months
- measure
- Specificity value of 12 months survival after radiotherapy with radiomics
- timeFrame
- 12 months
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: * Histologically proven glioblastoma * Diagnosed with a biopsy only * Treated with curative intent * Required data available (clinical/radiological/radiotherapy structure set) Exclusion Criteria: \-
References
Publications (5)
- BACKGROUNDAerts HJ, Velazquez ER, Leijenaar RT, Parmar C, Grossmann P, Carvalho S, Bussink J, Monshouwer R, Haibe-Kains B, Rietveld D, Hoebers F, Rietbergen MM, Leemans CR, Dekker A, Quackenbush J, Gillies RJ, Lambin P. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014 Jun 3;5:4006. doi: 10.1038/ncomms5006. PMID 24892406
- BACKGROUNDLambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RG, Granton P, Zegers CM, Gillies R, Boellard R, Dekker A, Aerts HJ. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012 Mar;48(4):441-6. doi: 10.1016/j.ejca.2011.11.036. Epub 2012 Jan 16. PMID 22257792
- BACKGROUNDCarvalho S, Leijenaar RT, Velazquez ER, Oberije C, Parmar C, van Elmpt W, Reymen B, Troost EG, Oellers M, Dekker A, Gillies R, Aerts HJ, Lambin P. Prognostic value of metabolic metrics extracted from baseline positron emission tomography images in non-small cell lung cancer. Acta Oncol. 2013 Oct;52(7):1398-404. doi: 10.3109/0284186X.2013.812795. Epub 2013 Sep 9. PMID 24047338
- BACKGROUNDLeijenaar RT, Carvalho S, Velazquez ER, van Elmpt WJ, Parmar C, Hoekstra OS, Hoekstra CJ, Boellaard R, Dekker AL, Gillies RJ, Aerts HJ, Lambin P. Stability of FDG-PET Radiomics features: an integrated analysis of test-retest and inter-observer variability. Acta Oncol. 2013 Oct;52(7):1391-7. doi: 10.3109/0284186X.2013.812798. Epub 2013 Sep 9. PMID 24047337
- BACKGROUNDPanth KM, Leijenaar RT, Carvalho S, Lieuwes NG, Yaromina A, Dubois L, Lambin P. Is there a causal relationship between genetic changes and radiomics-based image features? An in vivo preclinical experiment with doxycycline inducible GADD34 tumor cells. Radiother Oncol. 2015 Sep;116(3):462-6. doi: 10.1016/j.radonc.2015.06.013. Epub 2015 Jul 7. PMID 26163091