Ultrasound elastography using shear wave interference patterns: a finite element study of affecting factors.

Elastography as one of the non-invasive medical imaging techniques which can help determine the stiffness of organs and other structures is currently attracting more attention. An interesting imaging rate-independent technique which has been discussed in literature uses shear wave interference patterns (SWIP). In this method, two external continuous harmonic vibration sources were used to induced SWIP and the resulting tissue displacements are mapped using ultrasonic imaging called sonoelastography. In this paper, a finite element model (FEM) of viscoelastic soft tissue with circular stiffer lesion inside, is simulated for testing the effect of stimulation characteristics on the propagation of SWIPs and shear speed map reconstruction. Also, we proposed an elastography probe, including miniature vibration sources and ultrasound transducer, which can be appropriate for experimental tests. The elastographic average speed ratio (ASR) and some scores like Dice coefficient, related to the binary image of shear speed map, are calculated for quantitatively measuring the effect of different contributing harmonic vibration parameters. Results show that the potential of providing useful diagnostic information can be improved if the preferable parameters are considered for implementation. According to these results the ASR, Dice and Jaccard scores would diverge from the ground truth of FEA if the parameter level is not selected correctly. Particularly, the Dice and Jaccard coefficients are obtained about 0.9 and 0.8, respectively, for the best vibration parameters level choice.

A digital viscoelastic liver phantom for investigation of elastographic measurements.

To develop elastography imaging technologies and implement image reconstruction algorithms, testing is done with phantoms. Although the validation step is usually taken using real data and physical phantoms, their geometry as well as composition, biomechanical parameters, and details of applying stress cannot be modified readily. Such considerations have gained increasing importance with the growth of elastography techniques as one of the non-invasive medical imaging modalities, which can map the elastic properties and stiffness of soft tissues. In this article, we develop a digital viscoelastic phantom using computed tomography (CT) imaging data and several application software tools based on illustrations of normal liver anatomy so as to investigate the biomechanics of elastography via finite element modeling (FEM). Here we discuss how to create this phantom step by step, demonstrate typical shear wave elastography (SWE) experiments of applying transient stress to the liver model, and calculate quantitative measurements. In particular, shear wave velocities are investigated through a parametric study designed based on tissue stiffness and distance from the applied stress. According to the results of FEM analysis, low errors were obtained for shear wave velocity estimation for both mechanical stress (~2-5%) and acoustic radiation force (~3-7%). Results show that our model is a powerful framework and benchmark for simulating and implementing different algorithms in shear wave elastography, which can serve as a guide for upcoming researches and assist scientists to optimize their subsequent experiments in terms of design.

Semi-automatic measurement of rigid gas-permeable contact lens movement in keratoconus patients using blinking images.

PURPOSE: To introduce a method for estimation of the rigid gas-permeable contact lens (RGP) movement. MATERIALS AND METHODS: Videos captured from normal blinking of keratoconus patients while wearing RGP lenses were used for this study. The videos are recorded using the CCD camera of a smart phone attached to the eyepiece of the slit lamp. The algorithm starts with extracting two frames of the video related to the highest and lowest positions of the lens during blinking, followed by an appropriate edge detection method. In the next step circular Hough transform is used to find the center of lens and to segment it in each image. Finally the lens movement is estimated by measuring vertical displacement of the lens center between these two frames. RESULTS: Mean and standard deviation of the difference between real movement and results of the algorithm for 20 cases are -8.66% and 10.71% respectively. The results are highly correlated with Pearson coefficient 0.986 P < 0.001. Bland-Altman plot with 95% levels of agreement (LoA) shows an agreement between exact manual measurement method and the proposed algorithm. CONCLUSION: The proposed algorithm shows a relatively high accuracy as the first attempt and compared to the routine qualitative visual estimation. Considering the importance of the lens movement, although this system was not tested on a series of RGP fitting patients yet, semi-automatic measurement may potentially help practitioners decide the appropriate RGP lens fit and reduce the fitting time.