Akkus Zeynettin, Bayat Mahdi, Cheong Mathew, Viksit Kumar, Erickson Bradley J, Alizad Azra, Fatemi Mostafa
Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, Minnesota, USA; Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
Ultrasound Med Biol. 2016 Oct;42(10):2504-12. doi: 10.1016/j.ultrasmedbio.2016.06.002. Epub 2016 Jul 15.
Tissue stiffness is often linked to underlying pathology and can be quantified by measuring the mechanical transient transverse wave speed (TWS) within the medium. Time-of-flight methods based on correlation of the transient signals or tracking of peaks have been used to quantify the TWS from displacement maps obtained with ultrasound pulse-echo techniques. However, it is challenging to apply these methods to in vivo data because of tissue inhomogeneity, noise and artifacts that produce outliers. In this study, we introduce a robust and fully automated method based on dynamic programming to estimate TWS in tissues with known geometries. The method is validated using ultrasound bladder vibrometry data from an in vivo study. We compared the results of our method with those of time-of-flight techniques. Our method performs better than time-of-flight techniques. In conclusion, we present a robust and accurate TWS detection method that overcomes the difficulties of time-of-flight methods.
组织硬度通常与潜在病理状况相关联,并且可以通过测量介质内的机械瞬态横向波速度(TWS)来进行量化。基于瞬态信号相关性或峰值跟踪的飞行时间方法已被用于从超声脉冲回波技术获得的位移图中量化TWS。然而,由于组织不均匀性、噪声和产生异常值的伪像,将这些方法应用于体内数据具有挑战性。在本研究中,我们引入了一种基于动态规划的稳健且完全自动化的方法,用于估计具有已知几何形状的组织中的TWS。该方法通过一项体内研究的超声膀胱振动测量数据进行了验证。我们将我们方法的结果与飞行时间技术的结果进行了比较。我们的方法比飞行时间技术表现更好。总之,我们提出了一种稳健且准确的TWS检测方法,该方法克服了飞行时间方法的困难。