Building a virtual simulation platform for quasistatic breast ultrasound elastography using open source software: A preliminary investigation. Issue 9 (21st August 2015)

• Record Type: Journal Article
• Authors: Wang, Yu; Helminen, Emily; Jiang, Jingfeng
• Is Part Of: Medical physics. Volume 42:Issue 9(2015)
• Page Start: 5453
• Page End: 5466
• Publication Date: 2015-08-21
• Subjects: biological tissues -- biomedical ultrasonics -- finite element analysis -- mammography -- medical diagnostic computing -- phantoms -- physiological models -- public domain software; Ultrasonography -- Computer‐aided diagnosis -- Finite element calculations; Diagnosis using ultrasonic, sonic or infrasonic waves -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications; ultrasound simulation -- numerical phantom -- elastography -- finite element modeling; Ultrasonography -- Cancer -- Shear deformation -- Computer software -- Finite element methods -- Acoustic modeling -- Relaxation times -- Magnetic resonance imaging -- Medical image contrast; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4928707
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: Quasistatic ultrasound elastography (QUE) is being used to augment in vivo characterization of breast lesions. Results from early clinical trials indicated that there was a lack of confidence in image interpretation. Such confidence can only be gained through rigorous imaging tests using complex, heterogeneous but known media. The objective of this study is to build a virtual breast QUE simulation platform in the public domain that can be used not only for innovative QUE research but also for rigorous imaging tests. Methods: The main thrust of this work is to streamline biomedical ultrasound simulations by leveraging existing open source software packages including Field II (ultrasound simulator), VTK (geometrical visualization and processing), FEBio [finite element (FE) analysis], and Tetgen (mesh generator). However, integration of these open source packages is nontrivial and requires interdisciplinary knowledge. In the first step, a virtual breast model containing complex anatomical geometries was created through a novel combination of image‐based landmark structures and randomly distributed (small) structures. Image‐based landmark structures were based on data from the NIH Visible Human Project. Subsequently, an unstructured FE‐mesh was created by Tetgen. In the second step, randomly positioned point scatterers were placed within the meshed breast model through an octree‐based algorithm to make a virtual breast ultrasound phantom. In the third step, an ultrasound simulator (Field II) was used to interrogate the virtual breast phantom to obtain simulated ultrasound echo data. Of note, tissue deformation generated using a FE‐simulator (FEBio) was the basis of deforming the original virtual breast phantom in order to obtain the postdeformation breast phantom for subsequent ultrasound simulations. Using the procedures described above, a full cycle of QUE simulations involving complex and highly heterogeneous virtual breast phantoms can be accomplished for the first time. Results: Representative examples were used to demonstrate capabilities of this virtual simulation platform. In the first set of three ultrasound simulation examples, three heterogeneous volumes of interest were selected from a virtual breast ultrasound phantom to perform sophisticated ultrasound simulations. These resultant B‐mode images realistically represented the underlying complex but known media. In the second set of three QUE examples, advanced applications in QUE were simulated. The first QUE example was to show breast tumors with complex shapes and/or compositions. The resultant strain images showed complex patterns that were normally seen in freehand clinical ultrasound data. The second and third QUE examples demonstrated (deformation‐dependent) nonlinear strain imaging and time‐dependent strain imaging, respectively. Conclusions: The proposed virtual QUE platform was implemented and successfully tested in this study. Through show‐case examples, the proposed work has demonstrated its capabilities of creating sophisticated QUE data in a way that cannot be done through the manufacture of physical tissue‐mimicking phantoms and other software. This open software architecture will soon be made available in the public domain and can be readily adapted to meet specific needs of different research groups to drive innovations in QUE.