IEEE Trans Biomed Eng. 2024 Jan;71(1):367-374. doi: 10.1109/TBME.2023.3305986. Epub 2023 Dec 22.
Ultrasound elasticity imaging is a class of ultrasound techniques with applications that include the detection of malignancy in breast lesions. Although elasticity imaging traditionally assumes linear elasticity, the large strain elastic response of soft tissue is known to be nonlinear. This study evaluates the nonlinear response of breast lesions for the characterization of malignancy using force measurement and force-controlled compression during ultrasound imaging.
54 patients were recruited for this study. A custom force-instrumented compression device was used to apply a controlled force during ultrasound imaging. Motion tracking derived strain was averaged over lesion or background ROIs and matched with compression force. The resulting force-matched strain was used for subsequent analysis and curve fitting.
Greater median differences between malignant and benign lesions were observed at higher compressional forces (p-value < 0.05 for compressional forces of 2-6N). Of three candidate functions, a power law function produced the best fit to the force-matched strain. A statistically significant difference in the scaling parameter of the power function between malignant and benign lesions was observed (p-value = 0.025).
We observed a greater separation in average lesion strain between malignant and benign lesions at large compression forces and demonstrated the characterization of this nonlinear effect using a power law model. Using this model, we were able to differentiate between malignant and benign breast lesions.
With further development, the proposed method to utilize the nonlinear elastic response of breast tissue has the potential for improving non-invasive lesion characterization for potential malignancy.
超声弹性成像是一类超声技术,其应用包括检测乳腺病变中的恶性肿瘤。尽管弹性成象传统上假设为线性弹性,但众所周知,软组织的大应变弹性响应为非线性。本研究使用力测量和超声成像过程中的力控制压缩来评估乳腺病变的非线性响应,以进行恶性肿瘤特征描述。
本研究招募了 54 名患者。使用定制的力仪器压缩设备在超声成像过程中施加受控力。从病变或背景 ROI 中得出的运动跟踪应变进行平均,并与压缩力匹配。将所得的力匹配应变用于后续的分析和曲线拟合。
在较高的压缩力下,恶性和良性病变之间的中位数差异更大(在 2-6N 的压缩力下,p 值<0.05)。在三个候选函数中,幂律函数与力匹配应变的拟合最佳。观察到恶性和良性病变之间幂函数的标度参数存在统计学显著差异(p 值=0.025)。
我们观察到在较大的压缩力下,恶性和良性病变之间的平均病变应变差异更大,并使用幂律模型证明了这种非线性效应的特征描述。使用该模型,我们能够区分恶性和良性乳腺病变。
随着进一步的发展,利用乳腺组织非线性弹性响应的这种方法有可能改善潜在恶性肿瘤的非侵入性病变特征描述。