Image-derived Prediction of Response to Chemo-radiation in Glioblastoma
- Registration Number
- NCT02329795
- Lead Sponsor
- Rigshospitalet, Denmark
- Brief Summary
This study seeks to investigate if advanced image-analysis of diagnostic scans, can be used to predict how aggressive brain tumors (glioblastoma) respond to standard chemo- and radiation treatment.
- Detailed Description
Generally, response prediction models seeks to predict time to an event, e.g. time-to-progression and/or overall survival. The aim of this study is to explore the feasibility of establishing an individualized response model, that, based on several morphologic, physiologic and metabolic parameters extracted from computed tomography (CT), positron emission tomography (PET) and magnetic resonance imaging (MRI), is able to predict the tumor response at the level of an imaging voxel, using machine learning techniques.
Imaging modalities include MRI, PET/CT with 18F-fluroethyltyrosine (18F-FET), and PET/MRI with 64Cu-diacetyl-bis(N4-methylthiosemicarbazone) (64Cu-ATSM).
Recruitment & Eligibility
- Status
- TERMINATED
- Sex
- All
- Target Recruitment
- 16
- Histologically confirmed, primary supratentorial glioblastoma (WHO grade IV).
- No informed consent can be obtained
- Inability to undergo MRI examination, due to metal implants, pacemaker etc.
- Not eligible for Stupp-regimen
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Standard chemoradiotherapy Radiotherapy Group to receive 60 Gy radiotherapy in 30 fractions with concomitant and adjuvant temozolomide. Standard chemoradiotherapy Temozolomide Group to receive 60 Gy radiotherapy in 30 fractions with concomitant and adjuvant temozolomide.
- Primary Outcome Measures
Name Time Method Sensitivity and specificity of predicted response 3 months post radiotherapy Tumor response is measured as contrast-enhancing tumor on T1-weighted MRI and by metabolic active tumor using 18F-fluroethyl-tyrosine (FET)-PET. Pre-treatment risk map is constructed using machine learning methods and compared to post-treatment scans.
- Secondary Outcome Measures
Name Time Method DICE-similarity coefficient and percentage overlap of 64Cu-ATSM and contrast-enhanced T1-weighted MRI 3 months post radiotherapy Pre-chemoradiotherapy 64Cu-ATSM-PET is used as a surrogate marker for hypoxia and compared to treatment response, measured as contrast-enhancing tumor on T1-weighted MRI
Correlation (volume and maximum values) between lactate and hypoxia 1 week before start of chemoradiotherapy Lactate measured by MR spectroscopy is compared to metabolic uptake of 64Cu-ATSM-PET
Trial Locations
- Locations (1)
Department of Oncology, Section for Radiotherapy, Rigshospitalet
🇩🇰Copenhagen, Denmark