Multi-parameter Sub-Hertz Analysis of Viscoelasticity With a Quality Metric for Differentiation of Breast Masses

Abstract

We applied sub-Hertz analysis of viscoelasticity (SAVE) to differentiate breast masses in pre-biopsy patients. Tissue response during external ramp-and-hold stress was ultrasonically detected. Displacements were used to acquire tissue viscoelastic parameters. The fast instantaneous response and slow creep-like deformations were modeled as the response of a linear standard solid from which viscoelastic parameters were estimated. These parameters were used in a multi-variable classification framework to differentiate malignant from benign masses identified by pathology. When employing all viscoelasticity parameters, SAVE resulted in 71.43% accuracy in differentiating lesions. When combined with ultrasound features and lesion size, accuracy was 82.24%. Adding a quality metric based on uniaxial motion increased the accuracy to 81.25%. When all three were combined with SAVE, accuracy was 91.3%. These results confirm the utility of SAVE as a robust ultrasound-based diagnostic tool for non-invasive differentiation of breast masses when used as stand-alone biomarkers or in conjunction with ultrasonic features.

Keywords: Breast lesion; Creep; Retardation time; Ultrasound; Viscoelasticity.

Figure 1:

Schematic diagram showing steps for calculating the quality metric (QM). The red closed trajectory represents the hypothetic lesion margin in the pre-compressed state. Blue closed trajectory shows the lesion margin during compression. Slight boundary mismatch represents displacement tracking and interpolation errors associated with motion compensation. The dashed line represents a threshold to determine reliable tracking based on the QM.

Figure 2:

B-mode image and viscoelasticity parameters obtained by SAVE from three representative cases that were revealed as benign by pathology. Each column represents a separate case, and each row represents a specific viscoelastic parameter or B-mode image. The specific subtypes of these cases were: Case 1: benign sclerosing adenosis with the apocrine change, Case 2: fibroadenoma and Case 3: benign clustered apocrine cysts. The minimum QM values for case 1,2 and 3 were 0.05, 0.15 and 0.12, respectively.

Figure 3:

B-mode image and viscoelasticity parameters obtained by SAVE from three representative cases that were revealed as malignant by pathology. Each column represents a separate case, and each row represents a specific viscoelastic parameter or B-mode image. The specific subtypes of these cases were: invasive mammary carcinoma with mixed ductal and lobular features, grade II, calcifications present in invasive carcinoma, Case 2: invasive mammary carcinoma with abundant tumor-infiltrating lymphocytes, grade III and Case 3: Invasive Lobular Carcinoma (ILC) Grade II. The minimum QM values for case 1,2 and 3 were 0.48, 0.05 and 0.07, respectively.

Figure 4:

(a,c,e) Error-bar plot of different viscoelasticity parameters obtained by SAVE for lesion (red) and non-lesion (blue) tissue in benign and malignant lesions; (b,d,f) error-bar plot of corresponding contrast values in benign and malignant lesions. In each plot, middle horizontal bar represents mean and extended error bars represent 95% confidence interval for the corresponding parameter. p-values for paired parameters are shown with asterisk indicating significant, i.e. p<0.05.

Figure 5:

2-D normalized fitting error maps in three repeated acquisitions from a single lesion and corresponding QM curves as a function of frame number. Only the third acquisition exceeded the predefined threshold (Thr = 0.1) for QM with visible reduced fitting errors compared to the first two acquisitions. The mean $\overline{\text{χ}}$ for Acquisition 1, 2 and 3 were 4.12%, 4.16% and 2.82% respectively.

Figure 6:

Receiver operator curves when using the (a) mean value of different viscoelastic parameters on the lesion area for classification, (b) when considering contrast values based on different viscoelastic parameters for classification, and (c) when using the standard deviation of different viscoelastic parameters on the lesion area for classification.

Figure 7:

Receiver operator curves when using (a) the mean value of different viscoelastic parameters on the lesion area for classification of cases that exceeded the quality metric (QM) requirement, (b) when considering contrast values based on different viscoelastic parameters for classification of cases that exceeded the QM requirement, (c) when using the standard deviation of different viscoelastic parameters on the lesion area for classification of cases that exceeded the QM requirement.