Ultrasound poroelastography is a cost-effective and noninvasive imaging technique, which can be used to reconstruct mechanical parameters of tissues such as Young’s modulus, Poisson’s ratio, interstitial permeability, and vascular permeability. To estimate interstitial permeability and vascular permeability using poroelastography, accurate estimation of the strain time constant (TC) is required. This can be a challenging task due to the nonlinearity of the exponential strain curve and noise affecting the experimental data. Due to motion artifacts caused by the sonographer, animal/patient, and/or the environment, noise affecting some strain frames can be significantly higher than the strain signal. If these frames are used for the computation of the strain TC, the resulting TC estimate can be highly inaccurate, which, in turn, can cause high errors in the reconstructed mechanical parameters. In this paper, we introduce a cubic spline–based interpolation method, which allows to use only good quality strain frames (i.e., frames with sufficiently high signal-to-noise ratio [SNR]) to estimate the strain TC. Using finite element simulations, we demonstrate that the proposed interpolation method can improve the estimation accuracy of the strain TC by 46% with respect to the case where no interpolation and filtering are used and by 37% with respect to the case where the strain frames are Kalman filtered before TC estimation (at an SNR of 30 dB). We also prove the technical feasibility of the proposed technique using in vivo experimental data. While detecting the bad frames in both simulations and experiments, we assumed the lower limit SNR to be below 10 dB. Based on our results, the proposed technique may be of great help in applications relying on the accurate assessment of the temporal behavior of strain data.

中文翻译：

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一种基于样条插值的数据重建技术，用于估计超声多孔弹性成像中的应变时间常数

超声多孔弹性成像是一种经济高效且无创的成像技术，可用于重建组织的力学参数，如杨氏模量、泊松比、间质通透性和血管通透性。为了使用多孔弹性成像估计间质渗透性和血管渗透性，需要准确估计应变时间常数 (TC)。由于指数应变曲线的非线性和影响实验数据的噪声，这可能是一项具有挑战性的任务。由于超声医师、动物/患者和/或环境引起的运动伪影，影响某些应变帧的噪声可能明显高于应变信号。如果这些帧用于计算应变 TC，则由此产生的 TC 估计可能非常不准确，反过来，可能导致重建的机械参数的高误差。在本文中，我们介绍了一种基于三次样条的插值方法，该方法允许仅使用质量好的应变帧（即具有足够高信噪比 [SNR] 的帧）来估计应变 TC。使用有限元模拟，我们证明所提出的插值方法可以将应变 TC 的估计精度提高 46% 相对于不使用插值和滤波的情况，以及 37% 相对于应变框架的情况在 TC 估计之前进行卡尔曼滤波（SNR 为 30 dB）。我们还使用体内实验数据证明了所提出技术的技术可行性。在模拟和实验中检测坏帧时，我们假设下限 SNR 低于 10 dB。