Differentiation between benign and malignant breast lesions detected by bilateral dynamic contrast-enhanced MRI: a sensitivity and specificity study

Abstract

The purpose of this study was to apply an empirical mathematical model (EMM) to kinetic data acquired under a clinical protocol to determine if the sensitivity and specificity can be improved compared with qualitative BI-RADS descriptors of kinetics. 3D DCE-MRI data from 100 patients with 34 benign and 79 malignant lesions were selected for review under an Institutional Review Board (IRB)-approved protocol. The sensitivity and specificity of the delayed phase classification were 91% and 18%, respectively. The EMM was able to accurately fit these curves. There was a statistically significant difference between benign and malignant lesions for several model parameters: the uptake rate, initial slope, signal enhancement ratio, and curvature at the peak enhancement (at most P=0.04). These results demonstrated that EMM analysis provided at least the diagnostic accuracy of the kinetic classifiers described in the BI-RADS lexicon, and offered a few key advantages. It can be used to standardize data from institutions with different dynamic protocols and can provide a more objective classification with continuous variables so that thresholds can be set to achieve desired sensitivity and specificity. This suggests that the EMM may be useful for analysis of routine clinical data.

FIG. 1

Examples of MRI signal enhancement versus time curves (open circles) are shown for a variety of lesion types and fitted with the modified EMM (solid lines). The top row consists of benign lesions, from left to right: fibrocystic change (FCC), fibroadenoma, and papilloma. The bottom row consists of malignant lesions, from left to right: ductal carcinoma in situ (DCIS), invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC).

FIG. 2

The distributions of the primary EMM parameters are shown according to lesion type. From top to bottom the primary EMM parameters are the amplitude A, the uptake rate α, and the washout rate β. The open circles display the values of the primary EMM parameter for every case in that subtype of benign lesion, and × marks the average value: fibrocystic change (FCC, n = 16), fibroadenoma (n = 4), papilloma (n = 7), and other benign (n = 7). Similarly, the open triangles represent the values of each primary EMM parameter for every case in that subtype of malignant lesion, and × marks the average value: ductal carcinoma in situ (DCIS, n = 30), invasive ductal carcinoma (IDC, n = 36), invasive lobular carcinoma (ILC, n = 7), and other malignant (n = 6).

FIG. 3

The bar graph of the area under the ROC curve (A_z) is shown for each EMM primary and derived parameter. The area under an ROC curve (A_z) gives a measure of how well the diagnostic parameter performs; the larger the area under the curve, the better the performance. The A_z values (and corresponding standard error) were determined from the fitted binormal ROC curves generated by the ROCKIT software. The standard errors are almost the same for all the cases.

FIG. 4

Fitted binormal ROC curves generated by the ROCKIT software are shown for selected parameters α (blue line with solid squares) and SER (red line with solid circles). The A_z values were improved by comparing benign lesions with IDC lesions only, as shown by the ROC curves for α (blue line with open squares) and SER (red line with open circles).