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

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. © RSNA, 2020 Online supplemental material is available for this article.

Figures

Graphical abstract

Figure 1:

Eastern Cooperative Oncology Group and American College of Radiology Imaging Network Cancer Research Group A6702 trial participant flowchart. BI-RADS = Breast Imaging Reporting and Data System, DWI = diffusion-weighted imaging.

Figure 2:

Malignant breast lesion in 41-year-old woman who underwent axial contrast material–enhanced MRI for evaluation of disease extent for new cancer diagnosis. Dynamic contrast-enhanced MRI demonstrated additional 19-mm irregular mass at 12 o’clock position in right breast, assessed as Breast Imaging Reporting and Data System category 5. At diffusion-weighted MRI, lesion mean apparent diffusion coefficient (ADC) was 1.10 × 10−3 mm2/sec, and ipsilateral normal tissue mean ADC was 1.43 × 10−3 mm2/sec. Representative T1-weighted postcontrast image (DCE), diffusion-weighted image (DWI) (b = 800 sec/mm2), ADC map created using all b values (0, 100, 600, and 800 sec/mm2), and ADC histogram for lesion region of interest (shown in red on diffusion-weighted MRI scan and ADC images) are shown (top row, left to right). ADC maps were further generated for a variety of b-value combinations, as shown for lesion region (bottom row), including for nonzero minimum b values. Core-needle biopsy revealed invasive ductal carcinoma.

Figure 3:

Benign breast lesion in 44-year-old woman who underwent axial contrast material–enhanced MRI for evaluation of disease extent for new cancer diagnosis. Dynamic contrast-enhanced MRI demonstrated additional 12-mm oval mass at 6 o’clock position in right breast, assessed as Breast Imaging Reporting and Data System category 4. At diffusion-weighted MRI, lesion mean apparent diffusion coefficient (ADC) was 1.49 × 10−3 mm2/sec, and ipsilateral normal tissue mean ADC was 1.44 × 10−3 mm2/sec. Representative T1-weighted postcontrast image (DCE), diffusion-weighted image (DWI) (b = 800 sec/mm2), ADC map created using all b values (0, 100, 600, and 800 sec/mm2), and ADC histogram for lesion region of interest (shown in red on DWI scan and ADC images) are shown (top row, left to right). ADC maps were generated for a variety of b-value combinations, as shown for the lesion region (bottom row), including for nonzero minimum b values. Core-needle biopsy and excisional biopsy revealed benign atypical ductal hyperplasia.

Figure 4:

Scatterplots for apparent diffusion coefficient (ADC) metrics in malignant and benign lesions with associated thresholds. Standard mean ADC calculated from all b values, reported in Eastern Cooperative Oncology Group and American College of Radiology Imaging Network Cancer Research Group A6702 primary analysis, is shown in upper-left panel. All metrics were calculated in 81 evaluable lesions except normalized ADC, which was calculated for 73 lesions with measurable normal tissue. Measures for Breast Imaging Reporting and Data System (BI-RADS) category 4 and 5 lesions are shown in black, and measures for BI-RADS category 3 lesions are shown in red. Optimal threshold values (maintaining 100% sensitivity) for each metric are illustrated by blue dashed line. For all metrics except standard deviation, maximum malignant value was chosen as threshold value, where lesions above threshold could potentially avoid biopsy. For standard deviation with reverse association with malignancy, minimum malignant value was selected as threshold, and lesions with lower standard deviation could potentially avoid biopsy.

Figure 5a:

Receiver operating characteristic curves for all apparent diffusion coefficient (ADC) metrics. (a) Graph shows histogram-based ADC metrics from whole-lesion regions of interest (ROI) (n = 81 lesions). (b) Graph shows hotspot ADC (n = 81 lesions). (c) Graph shows normalized ADC (n = 73 lesions, normal tissue was not measurable in eight women). (d) Graph shows mean ADCs calculated with varying b-value combinations (n = 81 lesions). Reference mean ADC calculated using all b values (0, 100, 600, and 800 sec/mm2) is shown on each plot for comparison (red line). AUC = area under the receiver operating characteristic curve, SD = standard deviation.

Figure 5b:

Receiver operating characteristic curves for all apparent diffusion coefficient (ADC) metrics. (a) Graph shows histogram-based ADC metrics from whole-lesion regions of interest (ROI) (n = 81 lesions). (b) Graph shows hotspot ADC (n = 81 lesions). (c) Graph shows normalized ADC (n = 73 lesions, normal tissue was not measurable in eight women). (d) Graph shows mean ADCs calculated with varying b-value combinations (n = 81 lesions). Reference mean ADC calculated using all b values (0, 100, 600, and 800 sec/mm2) is shown on each plot for comparison (red line). AUC = area under the receiver operating characteristic curve, SD = standard deviation.

Figure 5c:

Receiver operating characteristic curves for all apparent diffusion coefficient (ADC) metrics. (a) Graph shows histogram-based ADC metrics from whole-lesion regions of interest (ROI) (n = 81 lesions). (b) Graph shows hotspot ADC (n = 81 lesions). (c) Graph shows normalized ADC (n = 73 lesions, normal tissue was not measurable in eight women). (d) Graph shows mean ADCs calculated with varying b-value combinations (n = 81 lesions). Reference mean ADC calculated using all b values (0, 100, 600, and 800 sec/mm2) is shown on each plot for comparison (red line). AUC = area under the receiver operating characteristic curve, SD = standard deviation.

Figure 5d:

Receiver operating characteristic curves for all apparent diffusion coefficient (ADC) metrics. (a) Graph shows histogram-based ADC metrics from whole-lesion regions of interest (ROI) (n = 81 lesions). (b) Graph shows hotspot ADC (n = 81 lesions). (c) Graph shows normalized ADC (n = 73 lesions, normal tissue was not measurable in eight women). (d) Graph shows mean ADCs calculated with varying b-value combinations (n = 81 lesions). Reference mean ADC calculated using all b values (0, 100, 600, and 800 sec/mm2) is shown on each plot for comparison (red line). AUC = area under the receiver operating characteristic curve, SD = standard deviation.