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BI-RADS Density Classification From Areometric and Volumetric Automatic Breast Density Measurements

Rationale and Objectives

The aim of our study was to classify breast density using areometric and volumetric automatic measurements to best match Breast Imaging-Reporting and Data System (BI-RADS) density scores, and determine which technique best agrees with BI-RADS. Second, this study aimed to provide a set of threshold values for areometric and volumetric density to estimate BI-RADS categories.

Materials and Methods

We randomly selected 537 full-field digital mammography examinations from a population-based screening program. Five radiologists assessed breast density using BI-RADS with all views available. A commercial program calculated areometric and volumetric breast density automatically. We compared automatically calculated density to all BI-RADS density thresholds using area under the receiver operating characteristic curve, and used Youden’s index to estimate thresholds in automatic densities, with matching sensitivity and specificity. The 95% confidence intervals were estimated by bootstrapping.

Results

Areometric density correlated well with volumetric density (r 2 = 0.76, excluding outliers, n = 2). For the BI-RADS threshold between II and III, areometric and volumetric assessment showed about equal area under the curve (0.94 vs. 0.93). For the threshold between I and II, areometric assessment was better than volumetric assessment (0.91 vs. 0.86). For the threshold between III and IV, volumetric assessment was better than areometric assessment (0.97 vs. 0.92).

Conclusions

Volumetric assessment is equal to or better than areometric assessment for the most clinically relevant thresholds (ie, between scattered fibroglandular and heterogeneously dense, and between heterogeneously dense and extremely dense breasts). Thresholds found in this study can be applied in daily practice to automatic measurements of density to estimate BI-RADS classification.

Introduction

Dense tissue can mask breast cancer , reducing the effect of mammography screening . Further, women with dense breasts have increased breast cancer risk . Thus, some countries have breast density assessment included in the mammography screening programs. In several US states, women with dense breasts (American College of Radiology Breast Imaging-Reporting and Data System [BI-RADS] density III and IV) will by law be informed about the higher breast cancer risk and the possibility of dense tissue masking a cancer . Austria offers women with dense breasts adjunctive ultrasound in their screening program .

Several methods for breast density classification exist . Radiologist assessment using the semiquantitative BI-RADS density scale is the most common . The BI-RADS system introduced this method mainly to quantify radiologists’ concern of missing cancers because of dense breast tissue . Thus, association between breast density and diagnostic efficacy of mammography is mostly based on this scale. A major disadvantage of BI-RADS assessment is its interobserver variability . Therefore, in a personalized screening setting, a woman’s screening routine would be dependent on the radiologist’s subjective opinion of breast density.

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Materials and Methods

Study Material

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Imaging

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Radiologist Training

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Volumetric Density Measurements

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Quantized Density

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Areometric Density Measurements

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Comparison of Quantra to BI-RADS Using Receiver Operating Characteristic (ROC)

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ROC Software

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Quantra Density Thresholds

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Results

Density Distribution

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Figure 1, (a) Distribution of volumetric density calculated and subgrouped by the radiologists' median Breast Imaging-Reporting and Data System (BI-RADS) density score. (b) The corresponding areometric distribution.

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Areometric-Volumetric Correlation

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Figure 2, Correlation between volumetric and areometric breast density calculated by Quantra. The outliers are marked as crosses.

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Left-Right Breast Comparison

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Figure 3, Comparison of Quantra's density measurements of the left and the right breasts to assess the reliability of the software. ( a and b ) The measurements for volumetric and areometric density, respectively.

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Quantra-BI-RADS Comparison

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Figure 4, Receiver operating characteristic (ROC) curves compare areometric ( light gray ) and volumetric density ( dark gray ) to the radiologists' median Breast Imaging-Reporting and Data System (BI-RADS) density. ( a – c ) ROC curves for the BI-RADS density threshold between I and II, II and III, and III and IV, respectively. Optimal operating points are shown as large filled markers.

Table 1

The Area Under the Curve of the Areometric and Volumetric ROC Curves

BI-RADS Density Threshold AUC A,Emp

(95% CI) AUC A,Fit AUC V,Emp

(95% CI) AUC V,Fit AUC A,Emp –AUC V,Emp

(95% CI) Between I and II 0.91 (0.87–0.94) 0.91 0.86 (0.82–0.90) 0.87 0.04 (0.02–0.07) \* Between II and III 0.94 (0.92–0.96) 0.94 0.93 (0.91–0.95) 0.94 0.01 (−0.01–0.02) Between III and IV 0.92 (0.88–0.96) 0.92 0.97 (0.95–0.99) 0.97 −0.05 (−0.09–−0.02) \*

A, areometric; AUC, area under the curve; CI, confidence intervals; Emp, empirical; Fit,  fitted curve; V, volumetric.

The last column shows the difference in areometric and volumetric area under the curve.

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Quantra Thresholds

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Table 2

Data for the Optimal Operating Point for the ROC Curves in Figure 4a–c

BI-RADS Density Threshold Density Assessment Density Threshold (%) at Optimal Operating Point Sensitivity (%) at Optimal Operating Point Specificity (%) at Optimal Operating Point Between I and II ( Fig 4a ) Areometric 6

(5–7) 83.0

(79.4–86.4) 87.7

(79.6–94.7) Volumetric 7

(6–7) 70.7

(66.5–74.7) 89.0

(81.3–95.8) Quantized density \* 5 93.3

(91.0–95.5) 46.6

(35.3–58.0) Between II and III ( Fig 4b ) Areometric 14

(13–17) 89.3

(85.2–93.0) 84.0

(79.7–88.1) Volumetric 10

(8–10) 80.7

(75.8–85.7) 91.8

(88.5–94.8) Quantized density \* 13 67.6

(61.6–73.4) 94.5

(91.8–97.0) Between III and IV ( Fig 4c ) Areometric 30

(29–33) 87.5

(78.3–95.7) 88.4

(85.5–91.2) Volumetric 16

(13–19) 91.1

(83.0–98.0) 90.0

(87.3–92.7) Quantized density \* 26 55.4

(42.2–68.4) 98.8

(97.7–99.6)

Corresponding data from using quantized density (including Quantra’s default cutoff values) are also shown. Bootstrap estimates of the 95% confidence intervals are shown in parentheses.

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Synthetically Generated BI-RADS Distributions

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Table 3

Distribution of the Synthetically Generated BI-RADS Density Distribution Generated Using the Cutoff Values in Table 2

Density Assessment BI-RADS Density I BI-RADS Density II BI-RADS Density III BI-RADS Density IV Areometric 26.6% 22.2% 31.7% 19.6% Volumetric 37.4% 21.4% 22.7% 18.4% Quantized density 12.1% 54.2% 26.8% 6.9% Radiologists 13.6% 41.0% 33.7% 10.4%

The density distribution using quantized density and the radiologists’ distribution is also shown.

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Thresholds by Imposing Radiologists’ Distribution

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Table 4

Areometric and Volumetric Density Thresholds That Most Closely Yield the Radiologists’ BI-RADS Density Distribution of 13.6%, 41.0%, 33.7%, and 10.4%

BI-RADS Density Threshold Density Assessment Density Threshold (%) Sensitivity (%) Specificity (%) Between I and II Areometric 2 93.8 61.6 Volumetric 5 90.3 54.8 Between II and III Areometric 16 84.0 89.1 Volumetric 9 86.5 86.0 Between III and IV Areometric 38 60.7 95.0 Volumetric 21 67.9 97.1

Sensitivity and specificity for detecting a breast denser than the respective BI-RADS density threshold is shown.

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Discussion

Main Finding

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Areometric Superiority in Fatty Breasts

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Volumetric Superiority in Dense Breasts

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Clinical Implications

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BI-RADS Distribution Generated From Density Data

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Thresholds by Imposing the Radiologist BI-RADS Distribution

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Magnitude of the Threshold Values

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Extension of Thresholds to Other Software

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Outliers

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Study Limitations

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Conclusions

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Acknowledgments

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