Motion artifact reduction in ultrasound based thermal strain imaging of atherosclerotic plaques using time-series analysis

Abstract

Large lipid pools in vulnerable plaques, in principle, can be detected using US based thermal strain imaging (US-TSI). One practical challenge for in vivo cardiovascular application of US-TSI is that the thermal strain is masked by the mechanical strain caused by cardiac pulsation. ECG gating is a widely adopted method for cardiac motion compensation, but it is often susceptible to electrical and physiological noise. In this paper, we present an alternative time series analysis approach to separate thermal strain from the mechanical strain without using ECG. The performance and feasibility of the time-series analysis technique was tested via numerical simulation as well as in vitro water tank experiments using a vessel mimicking phantom and an excised human atherosclerotic artery where the cardiac pulsation is simulated by a pulsatile pump.

An adaptive displacement estimation algorithm for improved reconstruction of thermal strain

“…Assuming a typical clinical imaging depth of 50 mm and an ultrasound array transducer with 128 beams, this corresponds to an imaging time of 265 ms. Furthermore, when displacement is estimated for clinical use, it is often necessary to design motion compensation algorithms to account for transducer motion and physiologic motion [37], [38]. Oftentimes, these algorithms rely on the acquisition of number of reference frames to track and subsequently remove confounding motion [39]–[41].…”

“…Using the adaptive algorithm, the appropriate estimator would naturally be chosen in systole and diastole on the basis of the observed displacement. Furthermore, an improved estimate of vascular mechanical strain might also be helpful for TSI when a time series analysis approach is used to estimate the thermal strain [38]. In addition to extending this adaptive algorithm, future work should also include a comparison of the adaptive algorithm and other higher order displacement estimation techniques including Bayesian speckle tracking, dynamic programming approaches, and estimation techniques based on the monogenic signal [17], [20], [45].…”

Multi-Focus Beamforming for Thermal Strain Imaging Using a Single Ultrasound Linear Array Transducer

“…These developments involve correction of undesirable displacements due to in vivo tissue motion and improved strain estimates (Kim et al 2007; Mahmoud et al 2014; Dutta 2013; Mahmoud et al 2013; Ding et al 2016). Other improvements in instrumentation involve development of an ultrasound transducer array for efficient local energy delivery (Kim et al 2008; Huang et al 2006; Huang et al 2007).…”

Uncertainty estimation for temperature measurement with diagnostic ultrasound

“…Progress was made i.a. in the fields of two-dimensional [26], three-dimensional [27], and compound imaging [28], improved algorithms [29–33], and the estimation of limitations [34]. Furthermore, the applicability of the method in different media was described: homogeneous [35, 36] and multilayer [30] phantoms, and in tissue in vitro [37–40] and in vivo [41].…”