Image-derived Prediction of Response to Chemo-radiation in Glioblastoma

Rigshospitalet, Denmark16 enrolled

Overview

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.

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).

Study Type

OBSERVATIONAL

Enrollment

Conditions

Glioblastoma

Interventions

RadiotherapyRADIATION

60 Gy in 30 fractions, 5 days a week, modulated arc therapy.

TemozolomideDRUG

Concomitant: 75 mg/m2 5 days a week from start of radiotherapy. Adjuvant: 150/200 mg/m2 in 5 days per 28 days in 6 months.

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Histologically confirmed, primary supratentorial glioblastoma (WHO grade IV). Exclusion Criteria: * No informed consent can be obtained * Inability to undergo MRI examination, due to metal implants, pacemaker etc. * Not eligible for Stupp-regimen

Locations (1)

Department of Oncology, Section for Radiotherapy, Rigshospitalet

Copenhagen, Denmark

Outcomes

Primary Outcomes

Sensitivity and specificity of predicted response

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.

Time frame: 3 months post radiotherapy

Secondary Outcomes

DICE-similarity coefficient and percentage overlap of 64Cu-ATSM and contrast-enhanced T1-weighted MRI

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

Time frame: 3 months post radiotherapy

Correlation (volume and maximum values) between lactate and hypoxia

Lactate measured by MR spectroscopy is compared to metabolic uptake of 64Cu-ATSM-PET

Time frame: 1 week before start of chemoradiotherapy

Data from ClinicalTrials.gov

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