Mean apparent diffusion coefficient is a sufficient conventional diffusion-weighted MRI metric to improve breast MRI diagnostic performance: Results from the ECOG-ACRIN cancer research group A6702 diffusion imaging trial

Elizabeth S. McDonald, Justin Romanoff, Habib Rahbar, Averi E. Kitsch, Sara M. Harvey, Jennifer G. Whisenant, Thomas E. Yankeelov, Linda Moy, Wendy B. DeMartini, Basak E. Dogan, Wei T. Yang, Lilian C. Wang, Bonnie N. Joe, Lisa J. Wilmes, Nola M. Hylton, Karen Y. Oh, Luminita A. Tudorica, Colleen H. Neal, Dariya I. Malyarenko, Christopher E. ComstockMitchell D. Schnall, Thomas L. Chenevert, Savannah C. Partridge*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background: The Eastern Cooperative Oncology Group and American College of Radiology Imaging Network Cancer Research Group A6702 multicenter trial helped confirm the potential of diffusion-weighted MRI for improving differential diagnosis of suspicious breast abnormalities and reducing unnecessary biopsies. A prespecified secondary objective was to explore the relative value of different approaches for quantitative assessment of lesions at diffusion-weighted MRI. Purpose: To determine whether alternate calculations of apparent diffusion coefficient (ADC) can help further improve diagnostic performance versus mean ADC values alone for analysis of suspicious breast lesions at MRI. Materials and Methods: This prospective trial (ClinicalTrials.gov identifier: NCT02022579) enrolled consecutive women (from March 2014 to April 2015) with a Breast Imaging Reporting and Data System category of 3, 4, or 5 at breast MRI. All study participants underwent standardized diffusion-weighted MRI (b = 0, 100, 600, and 800 sec/mm2). Centralized ADC measures were performed, including manually drawn whole-lesion and hotspot regions of interest, histogram metrics, normalized ADC, and variable b-value combinations. Diagnostic performance was estimated by using the area under the receiver operating characteristic curve (AUC). Reduction in biopsy rate (maintaining 100% sensitivity) was estimated according to thresholds for each ADC metric. Results: Among 107 enrolled women, 81 lesions with outcomes (28 malignant and 53 benign) in 67 women (median age, 49 years; interquartile range, 41–60 years) were analyzed. Among ADC metrics tested, none improved diagnostic performance versus standard mean ADC (AUC, 0.59–0.79 vs AUC, 0.75; P = .02–.84), and maximum ADC had worse performance (AUC, 0.52; P , .001). The 25th-percentile ADC metric provided the best performance (AUC, 0.79; 95% CI: 0.70, 0.88), and a threshold using median ADC provided the greatest reduction in biopsy rate of 23.9% (95% CI: 14.8, 32.9; 16 of 67 BI-RADS category 4 and 5 lesions). Nonzero minimum b value (100, 600, and 800 sec/mm2) did not improve the AUC (0.74; P = .28), and several combinations of two b values (0 and 600, 100 and 600, 0 and 800, and 100 and 800 sec/mm2; AUC, 0.73–0.76) provided results similar to those seen with calculations of four b values (AUC, 0.75; P = .17–.87). Conclusion: Mean apparent diffusion coefficient calculated with a two–b-value acquisition is a simple and sufficient diffusion-weighted MRI metric to augment diagnostic performance of breast MRI compared with more complex approaches to apparent diffusion coefficient measurement.

Original languageEnglish (US)
Pages (from-to)60-70
Number of pages11
JournalRadiology
Volume298
Issue number1
DOIs
StatePublished - 2021

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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