Sanabria Sergio J, Rominger Marga B, Goksel Orcun
IEEE Trans Biomed Eng. 2018 Nov 14. doi: 10.1109/TBME.2018.2881302.
Speed-of-sound (SoS) has large potential for tissue and pathology differentiation. We aim to develop a novel Ultrasound Computed Tomography (USCT) technique that can reconstruct local SoS in tissue on conventional ultrasound machines with hand-held linear arrays.
A passive reflector is placed opposite the tissue sample as an echogenic reference to measure the time-of-flight (ToF) of ultrasound wave- fronts. A Dynamic Programming algorithm provides a robust ToF measurements based on global optimization of all transmit- receive echo data. An Anisotropically-Weighted Total Variation (AWTV) algorithm allows sharp delineation of focal lesions based on limited-angle USCT data.
Inclusions, which are not visible in conventional ultrasound, could be delineated in SoS images. AWTV allows to reconstruct focal lesions with a contrast-ratio of 93.7% of their nominal value, compared to that of 31.5% with conventional least-squares based algebraic tomographic reconstruction. In full-wave simulations of realistic heterogeneous breast models, a high CR of 84.3% is observed, with the reconstruction filtering out background heterogeneity. In experiments, our proposed method quantifies SoS in a homogeneous background with an accuracy of 0.93ms, allowing to differentiate several tissue types.
We validate our method using numerical simulations with ray-tracing and full- wave models, and phantom and ex-vivo data. Preliminary in- vivo results show the potential of this new technique to detect and differentiate malignant and benign lesions in the breast.
Breast cancer is the most common cancer in women. Ultrasound B-mode only provides qualitative information about breast lesions, whereas USCT can provide quantitative tissue imaging biomarkers, such as SoS. The proposed method can potentially be implemented as a complementary modality to ultrasound for tissue and disease differentiation.
声速(SoS)在组织和病理鉴别方面具有巨大潜力。我们旨在开发一种新型超声计算机断层扫描(USCT)技术,该技术能够在配备手持线性阵列的传统超声机器上重建组织中的局部声速。
在组织样本对面放置一个无源反射器作为回声参考,以测量超声波束的飞行时间(ToF)。动态规划算法基于对所有发射 - 接收回波数据的全局优化提供稳健的ToF测量。各向异性加权全变差(AWTV)算法允许基于有限角度的USCT数据清晰描绘局灶性病变。
在传统超声中不可见的内含物在声速图像中可以被描绘出来。与基于传统最小二乘法的代数断层重建相比,AWTV能够以其标称值93.7%的对比度重建局灶性病变,而传统方法的对比度为31.5%。在真实异质乳腺模型的全波模拟中,观察到高达84.3%的高对比度,重建过程滤除了背景异质性。在实验中,我们提出的方法在均匀背景中量化声速的精度为0.93ms,能够区分多种组织类型。
我们使用光线追踪和全波模型的数值模拟以及体模和离体数据验证了我们的方法。初步的体内结果显示了这种新技术在检测和区分乳腺恶性和良性病变方面的潜力。
乳腺癌是女性中最常见的癌症。超声B模式仅提供关于乳腺病变的定性信息,而USCT可以提供定量的组织成像生物标志物,如声速。所提出的方法有可能作为超声的补充模态用于组织和疾病鉴别。