Precise DCE-MRI in Diagnosing Participants With Recurrent High Grade Glioma or Melanoma Brain Metastases
Primary Purpose
Brain Metastases, Glioma of Brain, Brain Tumor
Status
Recruiting
Phase
Not Applicable
Locations
United States
Study Type
Interventional
Intervention
Dynamic Contrast-Enhanced Magnetic Resonance Imaging
Bevacizumab Injection
Sponsored by
About this trial
This is an interventional diagnostic trial for Brain Metastases
Eligibility Criteria
Inclusion Criteria:
- 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.
Exclusion Criteria:
- COHORT I: Exclusion criteria include treatment with any other anti-cancer treatment, enzyme-inducing antiepileptic agents, anticoagulant treatment, pregnancy, other anti-angiogenesis therapy and prior thrombo-embolic disorders.
- COHORT I: Exclusion criteria will include the standard contraindications for MRI: 1) prior work as a machinist or metal worker, or history of metal being removed from the eyes, 2) cardiac pacemaker or internal pacing wires, 3) non-MRI compatible vena cava filter, vascular aneurysm clip, heart valve, spinal or ventricular shunt, optic implant, neuro-stimulator unit, ocular implant, or intrauterine device, or 4) claustrophobia, or uncontrollable motion disorder.
- COHORT I: Pregnant women, prisoners, and institutionalized individuals will be excluded.
- COHORT II: Exclusion criteria include treatment with any other anti-cancer treatment, and other immunotherapy exclusion criteria.
- COHORT II: Non-cutaneous melanomas will be excluded.
- COHORT II: Exclusion criteria will include the standard contraindications for MRI: 1) prior work as a machinist or metal worker, or history of metal being removed from the eyes, 2) cardiac pacemaker or internal pacing wires, 3) non-MRI compatible vena cava filter, vascular aneurysm clip, heart valve, spinal or ventricular shunt, optic implant, neuro-stimulator unit, ocular implant, or intrauterine device, or 4) claustrophobia, or uncontrollable motion disorder.
- COHORT II: Pregnant women, prisoners, and institutionalized individuals will be excluded.
Sites / Locations
- USC / Norris Comprehensive Cancer CenterRecruiting
Arms of the Study
Arm 1
Arm 2
Arm Type
Experimental
Experimental
Arm Label
Cohort I (STAR DCE-MRI)
Cohort II (STAR DCE-MRI)
Arm Description
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.
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.
Outcomes
Primary Outcome Measures
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.
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.
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.
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.
Secondary Outcome Measures
Full Information
NCT ID
NCT03698162
First Posted
October 1, 2018
Last Updated
June 6, 2023
Sponsor
University of Southern California
Collaborators
National Cancer Institute (NCI)
1. Study Identification
Unique Protocol Identification Number
NCT03698162
Brief Title
Precise DCE-MRI in Diagnosing Participants With Recurrent High Grade Glioma or Melanoma Brain Metastases
Official Title
Area B: Precise DCE-MRI Assessment of Brain Tumors
Study Type
Interventional
2. Study Status
Record Verification Date
June 2023
Overall Recruitment Status
Recruiting
Study Start Date
April 13, 2021 (Actual)
Primary Completion Date
April 13, 2024 (Anticipated)
Study Completion Date
April 13, 2025 (Anticipated)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor
Name of the Sponsor
University of Southern California
Collaborators
National Cancer Institute (NCI)
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
Yes
Product Manufactured in and Exported from the U.S.
No
Data Monitoring Committee
Yes
5. Study Description
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.
Detailed Description
PRIMARY OBJECTIVES:
I. To optimize and technically validate specially-tailored acquisition and reconstruction (STAR) DCE-MRI based on the accuracy and reproducibility of whole-brain tracer-kinetic (TK) parameter maps.
SECONDARY OBJECTIVES:
I. To develop a robust clinical implementation of STAR DCE-MRI. II. To clinically evaluate STAR DCE-MRI in patients with brain tumors.
OUTLINE: Participants are assigned to 1 of 2 cohorts.
COHORT I: 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. If there is concern for tumor progression (i.e. increased contrast enhancement), more frequent MRI scans will be scheduled.
COHORT II: 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.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Brain Metastases, Glioma of Brain, Brain Tumor, Metastatic Melanoma
7. Study Design
Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
None (Open Label)
Allocation
Non-Randomized
Enrollment
150 (Anticipated)
8. Arms, Groups, and Interventions
Arm Title
Cohort I (STAR DCE-MRI)
Arm Type
Experimental
Arm Description
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.
Arm Title
Cohort II (STAR DCE-MRI)
Arm Type
Experimental
Arm Description
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.
Intervention Type
Device
Intervention Name(s)
Dynamic Contrast-Enhanced Magnetic Resonance Imaging
Other Intervention Name(s)
DCE MRI, DCE-MRI, DYNAMIC CONTRAST ENHANCED MRI
Intervention Description
Undergo STAR DCE-MRI
Intervention Type
Drug
Intervention Name(s)
Bevacizumab Injection
Other Intervention Name(s)
Avastin
Intervention Description
Bevacizumab will be give to participants who have recurrent high-grade glioma as part of standard of care.
Primary Outcome Measure Information:
Title
Volume transfer constant (Ktrans)
Description
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.
Time Frame
Up to 3 years
Title
Fractional plasma volume (vp)
Description
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.
Time Frame
Up to 3 years
Title
Fractional extravascular-extracellular space volume (ve)
Description
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.
Time Frame
Up to 3 years
Title
Model-free initial area under the contrast agent concentration curve (iAUC)
Description
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.
Time Frame
Up to 3 years
10. Eligibility
Sex
All
Minimum Age & Unit of Time
21 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
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.
Exclusion Criteria:
COHORT I: Exclusion criteria include treatment with any other anti-cancer treatment, enzyme-inducing antiepileptic agents, anticoagulant treatment, pregnancy, other anti-angiogenesis therapy and prior thrombo-embolic disorders.
COHORT I: Exclusion criteria will include the standard contraindications for MRI: 1) prior work as a machinist or metal worker, or history of metal being removed from the eyes, 2) cardiac pacemaker or internal pacing wires, 3) non-MRI compatible vena cava filter, vascular aneurysm clip, heart valve, spinal or ventricular shunt, optic implant, neuro-stimulator unit, ocular implant, or intrauterine device, or 4) claustrophobia, or uncontrollable motion disorder.
COHORT I: Pregnant women, prisoners, and institutionalized individuals will be excluded.
COHORT II: Exclusion criteria include treatment with any other anti-cancer treatment, and other immunotherapy exclusion criteria.
COHORT II: Non-cutaneous melanomas will be excluded.
COHORT II: Exclusion criteria will include the standard contraindications for MRI: 1) prior work as a machinist or metal worker, or history of metal being removed from the eyes, 2) cardiac pacemaker or internal pacing wires, 3) non-MRI compatible vena cava filter, vascular aneurysm clip, heart valve, spinal or ventricular shunt, optic implant, neuro-stimulator unit, ocular implant, or intrauterine device, or 4) claustrophobia, or uncontrollable motion disorder.
COHORT II: Pregnant women, prisoners, and institutionalized individuals will be excluded.
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Steven Carrasco
Phone
323-442-7469
Email
Steven.Carrasco@med.usc.edu
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Krishna Nayak, PhD
Organizational Affiliation
University of Southern California
Official's Role
Principal Investigator
Facility Information:
Facility Name
USC / Norris Comprehensive Cancer Center
City
Los Angeles
State/Province
California
ZIP/Postal Code
90033
Country
United States
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Krishna Nayak, PhD
Phone
213-740-3494
Email
knayak@usc.edu
First Name & Middle Initial & Last Name & Degree
Krishna Nayak, PhD
12. IPD Sharing Statement
Learn more about this trial
Precise DCE-MRI in Diagnosing Participants With Recurrent High Grade Glioma or Melanoma Brain Metastases
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