Precise DCE-MRI in Diagnosing Participants With Recurrent High Grade Glioma or Melanoma Brain Metastases

NCT03698162 | Terminated DMC

• 4 other identifiers: 6B-17-2NCI-2018-01890P30CA014089R33CA225400
• Study Type: interventional
• Target: 15
• Locations: 1 country
• Sites: 1

Brief Summary

Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) is a potentially powerful diagnostic tool for the management of brain cancer and other conditions in which the blood-brain barrier is compromised. This trial studies how well precise DCE MRI works in diagnosing participants with high grade glioma that has come back or melanoma that has spread to the brain. The specially-tailored acquisition and reconstruction (STAR) DCE MRI could provide improved assessment of brain tumor status and response to therapy.

Conditions

Brain Metastases; Glioma of Brain; Brain Tumor; Metastatic Melanoma

Outcome Measures

Primary Outcomes (4)

• Volume transfer constant (Ktrans)

  The raw data will be acquired at the voxel level. Then the analytic parameters will be extracted from voxel-wise data such as the mean, median, interquartile range, skewness and kurtosis. Receiver-operating characteristic curves (ROC) will be used to illustrate the univariate prediction accuracy for each parameter in predicting the clinically determined outcome. The pattern of change with different clinical response status will be visually illustrated using spaghetti plots or other graphical approaches. Classification and Regression Tree (CART) with 10-fold cross validation will be used for building the final prediction model and determine the diagnostic cut point(s). CART analysis will also include demographics, comorbidity information, and relevant biological variables including sex. The final model accuracy will be assessed using area under the curve (AUC) when fitting a ROC curve using predicted outcome against the actual outcome.

  Up to 3 years

• Fractional plasma volume (vp)

  The raw data will be acquired at the voxel level. Then the analytic parameters will be extracted from voxel-wise data such as the mean, median, interquartile range, skewness and kurtosis. ROC will be used to illustrate the univariate prediction accuracy for each parameter in predicting the clinically determined outcome. The pattern of change with different clinical response status will be visually illustrated using spaghetti plots or other graphical approaches. CART with 10-fold cross validation will be used for building the final prediction model and determine the diagnostic cut point(s). CART analysis will also include demographics, comorbidity information, and relevant biological variables including sex. The final model accuracy will be assessed using AUC when fitting a ROC curve using predicted outcome against the actual outcome.

  Up to 3 years

• Fractional extravascular-extracellular space volume (ve)

  The raw data will be acquired at the voxel level. Then the analytic parameters will be extracted from voxel-wise data such as the mean, median, interquartile range, skewness and kurtosis. ROC will be used to illustrate the univariate prediction accuracy for each parameter in predicting the clinically determined outcome. The pattern of change with different clinical response status will be visually illustrated using spaghetti plots or other graphical approaches. CART with 10-fold cross validation will be used for building the final prediction model and determine the diagnostic cut point(s). CART analysis will also include demographics, comorbidity information, and relevant biological variables including sex. The final model accuracy will be assessed using AUC when fitting a ROC curve using predicted outcome against the actual outcome.

  Up to 3 years

• Model-free initial area under the contrast agent concentration curve (iAUC)

  The raw data will be acquired at the voxel level. Then the analytic parameters will be extracted from voxel-wise data such as the mean, median, interquartile range, skewness and kurtosis. ROC will be used to illustrate the univariate prediction accuracy for each parameter in predicting the clinically determined outcome. The pattern of change with different clinical response status will be visually illustrated using spaghetti plots or other graphical approaches. CART with 10-fold cross validation will be used for building the final prediction model and determine the diagnostic cut point(s). CART analysis will also include demographics, comorbidity information, and relevant biological variables including sex. The final model accuracy will be assessed using AUC when fitting a ROC curve using predicted outcome against the actual outcome.

  Up to 3 years

Study Arms (2)

Cohort I (STAR DCE-MRI)

EXPERIMENTAL

Participants with recurrent high-grade glioma undergo STAR DCE-MRI every 2 months, and just prior to and 4-6 weeks after starting bevacizumab treatment. Participants may undergo more frequent MRI if there is concern for tumor progression.

Other: Dynamic Contrast-Enhanced Magnetic Resonance Imaging; Other: Bevacizumab Injection

Cohort II (STAR DCE-MRI)

EXPERIMENTAL

Participants with melanoma brain metastases undergo STAR DCE-MRI at baseline and 4-6 weeks after therapy. Participants may undergo more frequent MRI if there is concern for tumor progression.

Other: Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Interventions

Dynamic Contrast-Enhanced Magnetic Resonance Imaging OTHER

Undergo STAR DCE-MRI

Also known as: DCE MRI, DCE-MRI, DYNAMIC CONTRAST ENHANCED MRI

Cohort I (STAR DCE-MRI); Cohort II (STAR DCE-MRI)

Bevacizumab Injection OTHER

Bevacizumab will be give to participants who have recurrent high-grade glioma as part of standard of care.

Also known as: Avastin

Cohort I (STAR DCE-MRI)

Eligibility Criteria

• Age: 21 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• COHORT I: Recurrent high-grade glioma (often with thin areas of enhancement) treated with bevacizumab.
• COHORT I: We will include adult patients with histopathologically confirmed high-grade glioma with evidence of tumor progression at baseline MRI who will undergo treatment with an anti-angiogenic agent (bevacizumab) with or without concomitant chemotherapy, and Karnofsky Performance Score \> 60%.
• COHORT I: At least 30 days should have elapsed since prior therapy including surgery and temozolomide chemoradiation.
• COHORT I: Satisfactory renal, hepatic, and hematologic function is required.
• COHORT II: Melanoma brain metastases (often small and spread throughout the brain) treated with immunotherapy.
• COHORT II: We will include adult patients with a tissue-proven history of melanoma who have contrast enhancing brain masses who will undergo treatment with immunotherapy with an anti-CTLA-4 or anti-PD-1 approach (e.g. ipilimumab, pembrolizumab, or nivolumab), and Karnofsky Performance Score \> 60%.
• COHORT II: At least 30 days should have elapsed since prior therapy including surgery, stereotactic brain irradiation, and corticosteroid use.

You may not qualify if:

• COHORT I: Pregnant women, prisoners, and institutionalized individuals will be excluded.
• COHORT II: Non-cutaneous melanomas will be excluded.
• COHORT II: Pregnant women, prisoners, and institutionalized individuals will be excluded.

Sponsors & Collaborators

• University of Southern California: lead
• National Cancer Institute (NCI): collaborator

Study Sites (1)

USC / Norris Comprehensive Cancer Center

Los Angeles, California, 90033, United States

Location

MeSH Terms

Conditions

Brain Neoplasms; Melanoma

Interventions

Bevacizumab

Condition Hierarchy (Ancestors)

Central Nervous System Neoplasms; Nervous System Neoplasms; Neoplasms by Site; Neoplasms; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Neuroendocrine Tumors; Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms by Histologic Type; Neoplasms, Nerve Tissue; Nevi and Melanomas; Skin Neoplasms; Skin Diseases; Skin and Connective Tissue Diseases

Intervention Hierarchy (Ancestors)

Antibodies, Monoclonal, Humanized; Antibodies, Monoclonal; Antibodies; Immunoglobulins; Immunoproteins; Blood Proteins; Proteins; Amino Acids, Peptides, and Proteins; Serum Globulins; Globulins

Study Officials

• Krishna Nayak, PhD

  University of Southern California

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: October 1, 2018
• First Posted: October 5, 2018
• Study Start: April 13, 2021
• Primary Completion: November 22, 2023
• Study Completion: March 1, 2025
• Last Updated: August 5, 2025

Record last verified: 2025-06

Locations

US (1)