NCT Number: NCT05704062
The goal of this observational study is to investigate and validate multi-parametric magnetic resonance imaging (MRI) modalities for assessment of breast cancer response to neoadjuvant chemotherapy in a multi-site and multi-MRI scanner platform setting. This study is conducted at Oregon Health & Science University (OHSU), University of Washington (UW), and University of Iowa (UI) using Siemens, Philips, and General Electric MRI scanners, respectively. MRI is a type of scan that uses a very strong magnet and no radiation to take very detailed pictures of parts of the body. MRI is often used as standard of care to take pictures of breast tumor(s) before and after chemotherapy treatment in order to measure the tumor size changes in response to treatment, and in order to plan for surgery. MRI is used because the images it takes are very clear and the borders of the tumor can be measured very accurately. However the tumor size alone is often not a good early indicator of whether or not the tumor responds to treatment. Tumor size change usually happens late during the period of treatment, and tumor size measured with MRI after treatment can overestimate or underestimate the residual cancer. This makes it difficult to do the right surgical planning. In addition to measuring tumor size, the MRI scans in this research study will also measure changes in tumor blood vessels and the number of cancer cells per unit of tumor volume. The purpose of this study is to see whether MRI measurements of these functional tumor properties provide better early prediction and evaluation of breast cancer response to neoadjuvant chemotherapy than tumor size measurement. This is an observational study because the MRI procedures are not expected to have an effect on health outcomes. Eligible participants on this study are receiving standard of care neoadjuvant treatment for their cancer.
Interested in participating?
Request Info18 year and older
All sexes
Observational
University of Iowa, Iowa City, Iowa, United States
PRIMARY OBJECTIVE:
I. To investigate, compared to tumor size measurement, if functional MRI biomarkers or combination of a set of functional biomarkers provide earlier prediction of responders vs. non-responders with pathological analyses of surgical specimens as the endpoints.
SECONDARY OBJECTIVES:
I. To investigate, compared to tumor size measurement, which MRI functional biomarker or combination of a set of biomarkers provides:
Ia. A more accurate assessment of residual cancer burden with pathological analyses of surgical specimens as the endpoints.
Ib. A more accurate prognosis of five-year recurrence-free survival.
II. To validate that the Shutter-Speed dynamic contrast-enhanced (DCE) MRI method, which measures tumor blood flow and vessel wall leakiness, as well as tumor metabolic activity, and was developed by OHSU investigators on the Siemens scanner platform, is a robust method for prediction and evaluation of breast cancer response to neoadjuvant chemotherapy across major MRI scanner platforms (Siemens, Philips, and General Electric).
OUTLINE:
Patients undergo dynamic contrast-enhanced (DCE)-MRI (for measuring tumor blood vessel changes) and diffusion-weighted (DW)-MRI (for measuring tumor cell density changes) together with some standard anatomic MRI scans for about 45 minutes at baseline, after first treatment cycle, at mid-point of treatment course, and after completion of neoadjuvant chemotherapy.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Undergo DW-MRI
Other names: Diffusion Weighted MRI, Diffusion-Weighted Magnetic Resonance Imaging, Diffusion-Weighted MR Imaging, Diffusion-Weighted MRI, DW-MRI, DWI, DWI MRI, DWI-MRI, MR Diffusion-Weighted Imaging
Undergo DCE-MRI
Other names: DCE, DCE MRI, DCE-MRI, DYNAMIC CONTRAST ENHANCED MRI
Time frame: Through study completion, up to 5 years
Functional MRI biomarkers, Kᵗʳᵃⁿˢ (transfer rate constant in min-¹), vₑ (extravascular and extracellular space volume fraction), kₑₚ (efflux rate constant in min-¹), and τᵢ (mean intracellular water lifetime in sec) along with ADC (apparent diffusion coefficient in mm²/sec) will be obtained from DCE- and DW-MRI. Tumor longest diameter (LD) will be measured (in mm). Early changes (%) in each MRI parameter will be derived and correlated with pathologic response status, pathologic complete response (pCR) or non-pCR, obtained from the resected tumor. Predictive accuracy for pCR vs. non-pCR is determined by area under the receiver operating characteristic curve (ROC AUC) for each parameter change (%). Comparison of AUC will determine if change (%) of a functional MRI biomarker is more accurate than LD in prediction of pCR vs. non-pCR. Also, changes (%) of all functional biomarkers will be combined using multivariate logistic regression and compared with that of LD for predictive accuracy.
Time frame: Through study completion, up to 5 years
MRI parameters Kᵗʳᵃⁿˢ, vₑ, kₑₚ, τᵢ, ADC, and LD derived from the MRI data obtained after completion of neoadjuvant chemotherapy but before surgery will be correlated with residual cancer burden (RCB) ranks (RCB I, II, and III) determined by standard of care pathologist review of surgical specimens. Correlation coefficients will be compared to determine if a functional MRI biomarker is more accurate than LD in assessing RCB ranks. In addition, all functional MRI biomarkers will be combined using a multivariate logistic regression model and compared with LD in assessing RCB ranks.
Time frame: Up to 5 years after study completion
MRI parameters Kᵗʳᵃⁿˢ, vₑ, kₑₚ, τᵢ, ADC, and LD derived from the MRI data obtained after completion of neoadjuvant chemotherapy but before surgery will be correlated with recurrence-free survival (in the unit of month) to determine if a functional MRI biomarker provides more accurate prognosis of five-year recurrence-free survival than LD. In addition, all functional MRI biomarkers will be combined using a multivariate logistic regression model and compared with LD in prognosis of recurrence-free survival.
Time frame: Through study completion, up to 5 years
DCE-MRI data will be collected from participants using a Siemens scanner at OHSU, a Philips scanner at University of Washington, and a General Electric (GE) scanner at University of Iowa. The Shutter-Speed pharmacokinetic model will be used to analyze DCE-MRI data from each site to derive Kᵗʳᵃⁿˢ, vₑ, kₑₚ, and τᵢ parameters. As described above, ROC AUC value for prediction of response to neoadjuvant chemotherapy and correlation coefficient with RCB ranks will be calculated for each functional DCE-MRI biomarker. The ROC AUC value and correlation coefficient for each functional DCE-MRI biomarker will be compared across the three scanners (or three sites), respectively, to determine if the functional DCE-MRI biomarkers derived with the Shutter-Speed pharmacokinetic model provide similar predictive performances regardless of the MRI scanner vendor.
Contact information is provided by the study sponsor or research team.
Kristen Grant, RN
CONTACT
Wei Huang, Chief, MR Rad Imaging Physics, PhD
CONTACT
Corewell Health East
Other
Functional Magnetic Resonance Imaging Assessment of Breast Cancer Response to Neoadjuvant Chemotherapy
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