Open Access
8 November 2019 Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction
Nima Akhlaghi, T. Joshua Pfefer, Keith A. Wear, Brian S. Garra, William C. Vogt
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Abstract

As photoacoustic imaging (PAI) technology matures, computational modeling will increasingly represent a critical tool for facilitating clinical translation through predictive simulation of real-world performance under a wide range of device and biological conditions. While modeling currently offers a rapid, inexpensive tool for device development and prediction of fundamental image quality metrics (e.g., spatial resolution and contrast ratio), rigorous verification and validation will be required of models used to provide regulatory-grade data that effectively complements and/or replaces in vivo testing. To address methods for establishing model credibility, we developed an integrated computational model of PAI by coupling a previously developed three-dimensional Monte Carlo model of tissue light transport with a two-dimensional (2D) acoustic wave propagation model implemented in the well-known k-Wave toolbox. We then evaluated ability of the model to predict basic image quality metrics by applying standardized verification and validation principles for computational models. The model was verified against published simulation data and validated against phantom experiments using a custom PAI system. Furthermore, we used the model to conduct a parametric study of optical and acoustic design parameters. Results suggest that computationally economical 2D acoustic models can adequately predict spatial resolution, but metrics such as signal-to-noise ratio and penetration depth were difficult to replicate due to challenges in modeling strong clutter observed in experimental images. Parametric studies provided quantitative insight into complex relationships between transducer characteristics and image quality as well as optimal selection of optical beam geometry to ensure adequate image uniformity. Multidomain PAI simulation tools provide high-quality tools to aid device development and prediction of real-world performance, but further work is needed to improve model fidelity, especially in reproducing image noise and clutter.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Nima Akhlaghi, T. Joshua Pfefer, Keith A. Wear, Brian S. Garra, and William C. Vogt "Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction," Journal of Biomedical Optics 24(12), 121910 (8 November 2019). https://doi.org/10.1117/1.JBO.24.12.121910
Received: 31 May 2019; Accepted: 14 October 2019; Published: 8 November 2019
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CITATIONS
Cited by 10 scholarly publications.
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KEYWORDS
3D modeling

Image quality

Acoustics

Data modeling

Computer simulations

Monte Carlo methods

Tissue optics

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