Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction.
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| Title: | Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction. |
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| Authors: | Akhlaghi, Nima1 nima.akhlaghi@fda.hhs.gov, Pfefer, T. Joshua1, Wear, Keith A.1, Garra, Brian S.1, Vogt, William C.1 |
| Source: | Journal of Biomedical Optics. Dec2019, Vol. 24 Issue 12, p1-12. 12p. |
| Subjects: | Monte Carlo method, Acoustic imaging, Acoustic wave propagation, Clutter (Noise), Light propagation, Acoustic models, Photoacoustic spectroscopy, Sound design, Two-dimensional models |
| 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Biomedical Optics is the property of SPIE - International Society of Optical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 140991145 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Akhlaghi%2C+Nima%22">Akhlaghi, Nima</searchLink><relatesTo>1</relatesTo><i> nima.akhlaghi@fda.hhs.gov</i><br /><searchLink fieldCode="AR" term="%22Pfefer%2C+T%2E+Joshua%22">Pfefer, T. Joshua</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Wear%2C+Keith+A%2E%22">Wear, Keith A.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Garra%2C+Brian+S%2E%22">Garra, Brian S.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Vogt%2C+William+C%2E%22">Vogt, William C.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Biomedical+Optics%22">Journal of Biomedical Optics</searchLink>. Dec2019, Vol. 24 Issue 12, p1-12. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Monte+Carlo+method%22">Monte Carlo method</searchLink><br /><searchLink fieldCode="DE" term="%22Acoustic+imaging%22">Acoustic imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Acoustic+wave+propagation%22">Acoustic wave propagation</searchLink><br /><searchLink fieldCode="DE" term="%22Clutter+%28Noise%29%22">Clutter (Noise)</searchLink><br /><searchLink fieldCode="DE" term="%22Light+propagation%22">Light propagation</searchLink><br /><searchLink fieldCode="DE" term="%22Acoustic+models%22">Acoustic models</searchLink><br /><searchLink fieldCode="DE" term="%22Photoacoustic+spectroscopy%22">Photoacoustic spectroscopy</searchLink><br /><searchLink fieldCode="DE" term="%22Sound+design%22">Sound design</searchLink><br /><searchLink fieldCode="DE" term="%22Two-dimensional+models%22">Two-dimensional models</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Biomedical Optics is the property of SPIE - International Society of Optical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1117/1.JBO.24.12.121910 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 1 Subjects: – SubjectFull: Monte Carlo method Type: general – SubjectFull: Acoustic imaging Type: general – SubjectFull: Acoustic wave propagation Type: general – SubjectFull: Clutter (Noise) Type: general – SubjectFull: Light propagation Type: general – SubjectFull: Acoustic models Type: general – SubjectFull: Photoacoustic spectroscopy Type: general – SubjectFull: Sound design Type: general – SubjectFull: Two-dimensional models Type: general Titles: – TitleFull: Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Akhlaghi, Nima – PersonEntity: Name: NameFull: Pfefer, T. Joshua – PersonEntity: Name: NameFull: Wear, Keith A. – PersonEntity: Name: NameFull: Garra, Brian S. – PersonEntity: Name: NameFull: Vogt, William C. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2019 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 10833668 Numbering: – Type: volume Value: 24 – Type: issue Value: 12 Titles: – TitleFull: Journal of Biomedical Optics Type: main |
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