MRI for Understanding Glioblastoma Biology

This study is looking at how Magnetic Resonance Imaging (MRI) can help us better understand glioblastoma, a type of brain tumor that can be removed by surgery. Researchers want to see if specific measurements from MRI scans can tell us more about the tumor's biology, specifically about certain proteins (like Decorin, or DCN) and genetic material (DNA and RNA) within the tumor. This could lead to better ways to understand and treat glioblastoma. You might be able to join if you are over 18 and have newly diagnosed or recurrent glioblastoma that can be surgically removed. The study aims to enroll 50 participants, but its current recruitment status is unclear.

Study design
This is an interventional study with a planned enrollment of 50 participants. It is not specified if it is randomized or blinded.
What's involved
You would undergo one MRI scan before surgery, and researchers would collect tissue samples from your tumor during surgery. Your medical chart would also be reviewed.
Compensation
Not stated in the trial record.
Follow-up
Researchers will look at certain measurements for up to 5 years after you join the study.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT06090903

Magnetic Resonance Imaging for Improving Knowledge of Brain Tumor Biology in Patients With Resectable Glioblastoma

Recruiting
NAAges 18+InterventionalScreening
Jonsson Comprehensive Cancer Center
~50 participants
Updated 2025-11-10 on ClinicalTrials.gov
What's tested:Biospecimen CollectionMagnetic Resonance ImagingMedical Chart Review

At a glance

Recruiting sites
1 of 1 listed site is recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Decorin (DCN) expression
Measured over Up to 5 years
+3 more outcomes measured
Glioblastoma
Recurrent Glioblastoma
Resectable Glioblastoma
1 sites across 1 states
California1
  • Benjamin M Ellingson · PRINCIPAL_INVESTIGATOR · UCLA / Jonsson Comprehensive Cancer Center

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Eligibility criteria

Inclusion

Patients \> 18 years of age
Patients with newly diagnosed, suspected or recurrent glioblastoma (GBM) patients with enhancing tumors greater than 1.5 mL clinically indicated for surgical resection. Recurrent GBM must have occurred more than 3 months after the end of radiation therapy per Response Assessment in Neuro-Oncology Criteria (RANO) guidelines

Exclusion

Counterindication to magnetic resonance imaging (MRI) (Patient has a pacemaker or metal in the body)
Patients \< 18 years of age
  • Decorin (DCN) expressionUp to 5 years

    Will use a two-sided t-test to compare DCN immunohistochemistry (IHC), in-situ hybridization (ISH), and ribonucleic acid (RNA) sequencing positivity between low apparent diffusion coefficient (ADCL) \< 1.24 um\^2/ms and ADCL \> 1.24 um2/ms groups.

  • DCN expression correlated to ADCLUp to 5 years

    Will assess whether DCN IHC, ISH, and RNA expression within the tumor is linearly correlated with continuous values of ADCL. To test this, will examine Pearson's correlation coefficient (R\^2) and test whether the slope of the linear regression line is significantly different from zero. After purification, will also quantify the particular genotype or cell states represented by tumor cells for each ADCL phenotype.

  • Incidence of tumors with high diffusion measurements among MES-like cellsUp to 5 years

    Will assess whether MES-like cells have higher frequency of incidence of ADCL \> 1.24 um\^2/ms compared to other genotypes. To test this, will use a chi-squared goodness of fit test to assess the frequency of observations and an analysis of variance (ANOVA) to look at DCN protein, deoxyribonucleic acid (DNA), and RNA expression between genotypes.

  • DCN expression among Mesenchymal-Like (MES-like) cellsUp to 5 years

    Will assess whether MES-like cells have higher overall DCN expression levels compared to other genotypes. To test this, will use a chi-squared goodness of fit test to assess the frequency of observations and an ANOVA to look at DCN protein, DNA, and RNA expression between genotypes.