Harmonic motion imaging of human breast masses: an in vivo clinical feasibility

Abstract

Non-invasive diagnosis of breast cancer is still challenging due to the low specificity of the imaging modalities that calls for unnecessary biopsies. The diagnostic accuracy can be improved by assessing the breast tissue mechanical properties associated with pathological changes. Harmonic motion imaging (HMI) is an elasticity imaging technique that uses acoustic radiation force to evaluate the localized mechanical properties of the underlying tissue. Herein, we studied the in vivo feasibility of a clinical HMI system to differentiate breast tumors based on their relative HMI displacements, in human subjects. We performed HMI scans in 10 female subjects with breast masses: five benign and five malignant masses. Results revealed that both benign and malignant masses were stiffer than the surrounding tissues. However, malignant tumors underwent lower mean HMI displacement (1.1 ± 0.5 µm) compared to benign tumors (3.6 ± 1.5 µm) and the adjacent non-cancerous tissue (6.4 ± 2.5 µm), which allowed to differentiate between tumor types. Additionally, the excised breast specimens of the same patients (n = 5) were imaged post-surgically, where there was an excellent agreement between the in vivo and ex vivo findings, confirmed with histology. Higher displacement contrast between cancerous and non-cancerous tissue was found ex vivo, potentially due to the lower nonlinearity in the elastic properties of ex vivo tissue. This preliminary study lays the foundation for the potential complementary application of HMI in clinical practice in conjunction with the B-mode to classify suspicious breast masses.

Figure 1

(a) Clinical B-mode image of a patient with a 0.9-cm invasive ductal carcinoma (IDC). (b) B-mode image of the mass acquired with the HMI imaging transducer (2.5 MHz). (c) HMI displacement map overlaid on the B-mode image (tumor contour is shown with white-dashed lines). (d–f) H&E staining of the mass. The red arrows show invasive carcinoma, the yellow arrows show fibrous normal breast tissue, and the blue arrow shows mature adipose tissue.

Figure 2

(a) Clinical B-mode image of a hypoechoic 1.4 cm solid breast mass. (b) B-mode image of the mass acquired with the HMI imaging transducer (2.5 MHz). (c) HMI displacement map overlaid on the B-mode image (tumor contour is shown with white-dashed lines). (d–f) H&E staining of the mass diagnosed as fibrotic stroma with adenosis. The yellow arrows show adenosis, and the blue arrow shows fibrous normal breast tissue and mature adipose tissue.

Figure 3

(a) US image of a 2.2-cm microlobulated solid hypoechoic invasive ductal carcinoma. (b–c) HMI B-mode image and displacement map of the in vivo tumor acquired before surgery (tumor contour is shown with white-dashed lines). (d–e) HMI B-mode image and displacement map of the tumor lumpectomy specimen scanned immediately after surgery. The contrast difference between the ex vivo displacement map and the corresponding in vivo map shown in (c) might be due to the change in the boundary conditions and lack of physical constraints in the ex vivo specimen. (f–g) HMI B-mode image and displacement map of the specimen at an imaging plane distant from the tumor. (h–j) H&E-stained sections. The red arrows show invasive carcinoma, the yellow arrows show fibrous normal breast tissue, and the blue arrow shows mature adipose tissue.

Figure 4

(a) A 4-cm invasive ductal carcinoma US image acquired using a clinical scanner (b–c) B-mode image and overlaid HMI displacement map of the in vivo tumor respectively before surgical resection (tumor contour is shown with white-dashed lines). (d–e) B-mode image and overlaid HMI displacement map of the ex vivo tumor respectively after surgical resection. (f–h) H&E-stained sections. The red arrows show invasive carcinoma, the yellow arrows show fibrous normal breast tissue, and the blue arrow shows mature adipose tissue.

Figure 5

Harmonic motion imaging (HMI) displacement estimated in (a) non-cancerous tissue and tumor in five patients with malignant lesions, (b) surrounding tissue and tumor in five patients with benign lesions, (c) malignant (n = 5) and benign (n = 5) tumors in vivo, (d) non-cancerous tissue and tumor in patients with malignant (n = 4) and benign (n = 1) masses, in vivo and ex vivo. *p < 0.05, **p < 0.01 and ***p < 0.001.

Figure 6

Estimated HMI displacement in different size tumors. No correlation was found between the displacement and tumor size (Pearson r = −0.1588, P = 0.66).

Figure 7

Schematic of the clinical harmonic motion imaging (HMI) setup. (a) Positioning of the patient and HMI transducers. (b) Block diagram of HMI data acquisition.

Figure 8

Flowchart of HMI data acquisition, processing, motion correction, and attenuation correction. (a) HMI transducers were moved mechanically in a 1-D point-by-point raster scan regimen. (b) RF data were acquired at each point. (c) RF data were processed offline according to the processing pipeline. (d) Large-scale motion artifacts were corrected by applying 2-D cross-correlation on the RF data in the lateral and axial directions (e) HMI displacement values were co-registered based on the motion artifact correction. A 2-D displacement map was reconstructed accordingly. (f, g) Displacement values along the axial direction (red dashed line) were fitted into two exponential curves to correct for acoustic force attenuation above and below the FUS transducer focus. The blue and red lines show the displacement values along the axial direction before and after attenuation correction, respectively. (h) Overlaid HMI displacement map on the B-mode image before attenuation correction. (i) Overlaid HMI displacement map on the B-mode image after attenuation correction.