IEEE Trans Biomed Eng. 2020 Apr;67(4):1083-1096. doi: 10.1109/TBME.2019.2929134. Epub 2019 Jul 17.
Vascular permeability (VP) is a mechanical parameter which plays an important role in cancer initiation, metastasis, and progression. To date, there are only a few non-invasive methods that can be used to image VP in solid tumors. Most of these methods require the use of contrast agents and are expensive, limiting widespread use.
In this paper, we propose a new method to image VP in tumors, which is based on the use of ultrasound poroelastography. Estimation of VP by poroelastography requires knowledge of the Young's modulus (YM), Poisson's ratio (PR), and strain time constant (TC) in the tumors. In our method, we find the ellipse which best fits the tumor (regardless of its shape) using an eigen-system-based fitting technique and estimate the YM and PR using Eshelby's elliptic inclusion formulation. A Fourier method is used to estimate the axial strain TC, which does not require any initial guess and is highly robust to noise.
It is demonstrated that the proposed method can estimate VP in irregularly shaped tumors with an accuracy of above [Formula: see text] using ultrasound simulation data with signal-to-noise ratio of 20 dB or higher. In vivo feasibility of the proposed technique is demonstrated in an orthotopic mouse model of breast cancer.
The proposed imaging method can provide accurate and localized estimation of VP in cancers non-invasively and cost-effectively.
Accurate and non-invasive assessment of VP can have a significant impact on diagnosis, prognosis, and treatment of cancers.
血管通透性（VP）是一个机械参数，在癌症的发生、转移和进展中起着重要作用。迄今为止，只有少数几种非侵入性方法可用于对实体瘤中的 VP 进行成像。这些方法大多需要使用对比剂，且价格昂贵，限制了其广泛应用。
本文提出了一种新的肿瘤 VP 成像方法，该方法基于超声多孔弹性成像。通过多孔弹性成像估计 VP 需要了解肿瘤中的杨氏模量（YM）、泊松比（PR）和应变时间常数（TC）。在我们的方法中，使用基于特征系统的拟合技术找到最适合肿瘤的椭圆（无论其形状如何），并使用 Eshelby 的椭圆包含公式估计 YM 和 PR。傅里叶方法用于估计轴向应变 TC，该方法不需要任何初始猜测，对噪声具有高度鲁棒性。
研究表明，该方法可以使用具有 20 dB 或更高信噪比的超声模拟数据，对具有不规则形状的肿瘤进行精确的 VP 估计，精度高于[公式：见文本]。在乳腺癌的原位小鼠模型中证明了该技术的体内可行性。
该成像方法可以非侵入性、经济有效地提供癌症中 VP 的准确和局部估计。
准确和非侵入性的 VP 评估可以对癌症的诊断、预后和治疗产生重大影响。
