Computers in Biology and Medicine 127 (2020) 104078 Available online 23 October 2020 0010-4825/© 2020 Elsevier Ltd. All rights reserved. A digital viscoelastic liver phantom for investigation of elastographic measurements Pezhman Pasyar a, *, 1 , Sadegh Masjoodi b , Zahra Montazeriani a, 1 , Bahador Makkiabadi a, 1 a Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran b Institute for Cognitive and Brain Science, Shahid Beheshti University, Tehran, Iran A R T I C L E INFO Keywords: Acoustic radiation force Computed tomography Digital liver phantom Elastography Finite element analysis Transient mechanical vibration ABSTRACT 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 ge- ometry as well as composition, biomechanical parameters, and details of applying stress cannot be modifed 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 fnite 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. 1. Introduction Many and various studies employing various imaging methods esti- mate the healthy human liver tissue at low shear stiffness values (less than 7 kPa for the ultrasound and less than 4 kPa for magnetic resonance-based methods) [1–6]. Yet, in response to the chronic injury and infammation, liver cells are replaced by collagenous fbrils, particularly around the branches of liver blood vessels and bile ducts. As fbrosis progresses and involves more pathways, a more rigid structure with a higher stiffness is created, such that a cirrhotic liver is collabo- ratively stiffer than a healthy one. If the infammation or injury is diagnosed at the early stages, the chance of liver to recover will increase. Acute fbrosis (cirrhosis), which is almost irreversible, hence, leads to liver failure [7]. Additionally, cirrhosis closely correlates with liver cancer. In other words, after cirrhosis, the risk of liver cancer will experience a rise of 5% per year [7,8]. If these patients are monitored periodically, it is highly likely that we can prevent the risk of developing liver cancer and transplantation. As a result, a simple and non-invasive monitoring method, accordingly, seems to be a critical component not only for liver cancer screening but also for diagnosis, treatment, and following-up the patients with the disease. In this regard, non-invasive elastography technologies, in contrast to the other invasive methods such as tissue biopsy [1], seek to address these challenges. Elastography is a medical imaging technique that helps to determine the stiffness of the organs and other structures in the body using an induced distortion in the tissue to observe and process the related response. From early research stages to extensive clinical ap- plications, numerous elastographic techniques exist, each of which can be characterized by the details of applying stress and imaging modal- ities. Among these, magnetic resonance [5,6] and ultrasound elastog- raphy [9–31] are the most prominent imaging techniques to determine the response of tissues. Beyond these methods, optical coherence tomography-based elastography technology (optical coherence elas- tography) is also applied to study tissue biomechanical properties [28, * Corresponding author. Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Keshavarz Blvd, Tehran, Iran. E-mail address: pasyar_p@alumnus.tums.ac.ir (P. Pasyar). 1 Also at: Research Center of Biomedical Technology and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, Iran. Contents lists available at ScienceDirect Computers in Biology and Medicine journal homepage: http://www.elsevier.com/locate/compbiomed https://doi.org/10.1016/j.compbiomed.2020.104078 Received 26 May 2020; Received in revised form 12 October 2020; Accepted 20 October 2020