DWI in Assessing Treatment Response in Patients With Breast Cancer Receiving Neoadjuvant Chemotherapy (ACRIN6698)

Diffusion Weighted MR Imaging Biomarkers for Assessment of Breast Cancer Response to Neoadjuvant Treatment: A Sub-study of the I-SPY 2 TRIAL (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging And MoLecular Analysis)

RATIONALE: Imaging procedures, such as diffusion-weighted magnetic resonance imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), may help in evaluating how well patients with breast cancer respond to treatment.

PURPOSE: This research trial studies DWI and DCE-MRI in assessing treatment response in patients with breast cancer undergoing neoadjuvant chemotherapy.

Study Overview

• Status: Completed
• Conditions: Breast Cancer
• Intervention / Treatment: Procedure: diffusion-weighted magnetic resonance imaging

Detailed Description

OBJECTIVES:

Primary

• To determine if the change in tumor apparent diffusion coefficient (ADC) value measured from each treatment timepoint to baseline is predictive of pathologic complete response (pCR).

Secondary

• To determine if the combined measurement of change in tumor ADC value, change in tumor volume, and change in peak signal-enhancement ratio (SER) is predictive of pCR.
• To investigate the relative effectiveness of the individual measurements, change in tumor ADC value, change in tumor volume, and change in peak SER for predicting pCR in experimental treatment arms.
• To assess the test-retest reproducibility of ADC metrics applied to breast tumors.

OUTLINE: This is a multicenter study.

Patients undergo diffusion-weighted magnetic resonance imaging (DWI) at baseline, after week 3 of neoadjuvant paclitaxel regimen, and prior to and after completion of 4 courses of neoadjuvant chemotherapy. Patients then undergo surgery. Patients undergo DWI prior to contrast administration for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

After completion of treatment procedure, patients are followed up for 5 years on the I-SPY 2 TRIAL.

• Study Type: Interventional
• Enrollment (Actual): 406
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Alabama
    • Birmingham, Alabama, United States, 35294
      • University of Alabama at Birmingham
  • California
    • San Francisco, California, United States, 94143
      • University of California, San Francisco
  • Minnesota
    • Minneapolis, Minnesota, United States, 55455
      • University of Minnesota
  • Oregon
    • Portland, Oregon, United States, 97239
      • Oregon Health and Science University
  • Pennsylvania
    • Philadelphia, Pennsylvania, United States, 19104
      • University of Pennsylvania
  • Texas
    • Houston, Texas, United States, 77030
      • University of Texas M.D. Anderson Cancer Center
  • Washington
    • Seattle, Washington, United States, 98195
      • University of Washington/SCCA

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

DISEASE CHARACTERISTICS:

• Meets I-SPY 2 TRIAL inclusion criteria

  • High-risk for recurrent disease

PATIENT CHARACTERISTICS:

• Able to tolerate imaging required by protocol

PRIOR CONCURRENT THERAPY:

• Not specified

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Diffusion Weighted-MRI; Participants on all arms of the I-SPY II trial will undergo diffusion-weighted magnetic resonance imaging as described in the ACRIN 6698 protocol. The experimental component/intervention is whether DW-MRI can predict therapeutic response in neoadjuvant treatment for breast cancer.	Procedure: diffusion-weighted magnetic resonance imaging; diffusion-weighted magnetic resonance imaging examination and subsequent radiologist interpretation; Other Names: diffusion-weighted MRI; DWI; DW-MRI; functional MRI

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Pathologic Complete Response (pCR)	Pathologic complete response (pCR) is defined as the lack of all signs of cancer in tissue samples removed during surgery after Neoadjuvant treatment for Breast cancer. ie., no residual invasive disease in either breast or axillary lymph nodes after neoadjuvant therapy (ypT0/is, ypN0) Histopathologic analysis was performed using the Residual Cancer Burden system	Surgery

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Functional Tumor Volume (FTV) as a Predictor of Pathologic Complete Response (pCR)	Pathologic complete response (pCR) is defined as the lack of all signs of cancer in tissue samples removed during surgery after Neoadjuvant treatment for Breast cancer. ie., no residual invasive disease in either breast or axillary lymph nodes after neoadjuvant therapy (ypT0/is, ypN0) Histopathologic analysis was performed using the Residual Cancer Burden system Functional tumor volume (FTV) (units cm3) was computed by summing all tumor voxels meeting specific enhancement criteria, with customized thresholds for each site to account for variability in MR imaging systems	Surgery
Determine the Accuracy of Predictive Models Including Covariates for Combined Measurement of Change in Tumor ADC Value, Change in Tumor Volume, and Other Variables	Accuracy will be measured as the Area under the Receiver Operating Characteristic Curve (AUC) Predictive logistic regression modeling was performed in 207 patients with complete mid-treatment ΔADC and ΔFTV data. To build prediction models with ADC and other variables, a data-splitting approach was used where a randomly selected 60% of participants (124 patients), stratified according to pCR status and tumor subtype, were selected as the training data set and the rest (86 patients) as the test set. Logistic regression with backward variable selection was used to construct the prediction models, which were then applied to the remaining 40% of the data to obtain predictive scores for each participant.	baseline and mid-treatment
Repeatability Coefficient (RC)Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors	within-subject standard deviation (wSD) Repeatability coefficient (RC): [RC = 2.77*wSD] (units: 10E-3 mm/sec^2) Smaller values of RC, bounded [0, ...), represent agreement	baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)
Within-subject Coefficient of Variation (wCV) Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors	within-subject standard deviation (wSD) Within-subject coefficient of variation (wCV): [wCV = 100%*wSD/mean] Smaller values of wCV bounded for [0,...) represent better agreement	baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)
ICC Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors	Test and retest DWI measurements for a given patient were performed on the same day in a single imaging session. Intraclass correlation coefficient (ICC) is derived from the analysis of variance (ANOVA) model estimates (Barnhart,Haber, Lin 2007), Larger values of ICC (bounded [-1,1]) represent agreement	baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)
Agreement Index (AI) Test-retest Metric for Reproducibility of ADC as Applied to Breast Tumors	Test and retest DWI measurements for a given patient were performed on the same day in a single imaging session. Agreement index (AI): (Zhang, Wang, Duan - 2014) is based on the data's overall ranking. AI confidence intervals were obtained via bootstrap method Larger values AI (bounded [0.5,1]) represent agreement	baseline (pre-treatment) or after 3 weeks of taxane-based treatment (early-treatment)

Collaborators and Investigators

• Sponsor: American College of Radiology Imaging Network
• Collaborators: National Cancer Institute (NCI)
• Investigators: Principal Investigator: Nola M. Hylton, PhD, University of California, San Francisco

Publications and helpful links

General Publications

• DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988 Sep;44(3):837-45.
• Li W, Partridge SC, Newitt DC, Steingrimsson J, Marques HS, Bolan PJ, Hirano M, Bearce BA, Kalpathy-Cramer J, Boss MA, Teng X, Zhang J, Cai J, Kontos D, Cohen EA, Mankowski WC, Liu M, Ha R, Pellicer-Valero OJ, Maier-Hein K, Rabinovici-Cohen S, Tlusty T, Ozery-Flato M, Parekh VS, Jacobs MA, Yan R, Sung K, Kazerouni AS, DiCarlo JC, Yankeelov TE, Chenevert TL, Hylton NM. Breast Multiparametric MRI for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: The BMMR2 Challenge. Radiol Imaging Cancer. 2024 Jan;6(1):e230033. doi: 10.1148/rycan.230033.
• Partridge SC, Zhang Z, Newitt DC, Gibbs JE, Chenevert TL, Rosen MA, Bolan PJ, Marques HS, Romanoff J, Cimino L, Joe BN, Umphrey HR, Ojeda-Fournier H, Dogan B, Oh K, Abe H, Drukteinis JS, Esserman LJ, Hylton NM; ACRIN 6698 Trial Team and I-SPY 2 Trial Investigators. Diffusion-weighted MRI Findings Predict Pathologic Response in Neoadjuvant Treatment of Breast Cancer: The ACRIN 6698 Multicenter Trial. Radiology. 2018 Dec;289(3):618-627. doi: 10.1148/radiol.2018180273. Epub 2018 Sep 4.
• Newitt DC, Amouzandeh G, Partridge SC, Marques HS, Herman BA, Ross BD, Hylton NM, Chenevert TL, Malyarenko DI. Repeatability and Reproducibility of ADC Histogram Metrics from the ACRIN 6698 Breast Cancer Therapy Response Trial. Tomography. 2020 Jun;6(2):177-185. doi: 10.18383/j.tom.2020.00008.
• Newitt DC, Zhang Z, Gibbs JE, Partridge SC, Chenevert TL, Rosen MA, Bolan PJ, Marques HS, Aliu S, Li W, Cimino L, Joe BN, Umphrey H, Ojeda-Fournier H, Dogan B, Oh K, Abe H, Drukteinis J, Esserman LJ, Hylton NM; ACRIN Trial Team and I-SPY 2 TRIAL Investigators. Test-retest repeatability and reproducibility of ADC measures by breast DWI: Results from the ACRIN 6698 trial. J Magn Reson Imaging. 2019 Jun;49(6):1617-1628. doi: 10.1002/jmri.26539. Epub 2018 Oct 22.
• Partridge SC, Steingrimsson J, Newitt DC, Gibbs JE, Marques HS, Bolan PJ, Boss MA, Chenevert TL, Rosen MA, Hylton NM. Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial. Tomography. 2022 Mar 4;8(2):701-717. doi: 10.3390/tomography8020058.
• Newitt DC, Tan ET, Wilmes LJ, Chenevert TL, Kornak J, Marinelli L, Hylton N. Gradient nonlinearity correction to improve apparent diffusion coefficient accuracy and standardization in the american college of radiology imaging network 6698 breast cancer trial. J Magn Reson Imaging. 2015 Oct;42(4):908-19. doi: 10.1002/jmri.24883. Epub 2015 Mar 11.

Helpful Links

• National Cancer Institute's Clinical trial database

Study record dates

Study Major Dates

• Study Start (Actual): August 27, 2012
• Primary Completion (Actual): July 19, 2018
• Study Completion (Actual): January 14, 2020

Study Registration Dates

• First Submitted: March 24, 2012
• First Submitted That Met QC Criteria: March 24, 2012
• First Posted (Estimated): March 27, 2012

Study Record Updates

• Last Update Posted (Estimated): April 15, 2024
• Last Update Submitted That Met QC Criteria: March 18, 2024
• Last Verified: March 1, 2024

More Information

Terms related to this study

• Keywords: stage IV breast cancer; stage IIIA breast cancer; stage IIIB breast cancer; stage II breast cancer; stage IIIC breast cancer; HER2-positive breast cancer; HER2-negative breast cancer
• Additional Relevant MeSH Terms: Skin Diseases; Neoplasms; Neoplasms by Site; Breast Diseases; Breast Neoplasms
• Other Study ID Numbers: CDR0000729174; U01CA080098 (U.S. NIH Grant/Contract); U01CA079778 (U.S. NIH Grant/Contract); ACRIN-6698 (Other Identifier: NCI CIP)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: See ACRIN data sharing Policy https://www.acrin.org/RESEARCHERS/POLICIES/DATAANDIMAGESHARINGPOLICY.aspx
• IPD Sharing Time Frame: 6mo post publication
• IPD Sharing Access Criteria: upon request
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP