Optimizing light delivery through fiber bundle in photoacoustic imaging with clinical ultrasound system: Monte Carlo simulation and experimental validation
Translating photoacoustic (PA) imaging into clinical setup is a challenge. We report an integrated PA and ultrasound imaging system by combining the light delivery to the tissue with the ultrasound probe. First, Monte Carlo simulations were run to study the variation in absorbance within tissue for...
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sg-ntu-dr.10356-839512023-12-29T06:50:06Z Optimizing light delivery through fiber bundle in photoacoustic imaging with clinical ultrasound system: Monte Carlo simulation and experimental validation Sivasubramanian, Kathyayini Periyasamy, Vijitha Wen, Kew Kok Pramanik, Manojit School of Chemical and Biomedical Engineering Photoacoustic imaging Monte Carlo simulation with embedded object Translating photoacoustic (PA) imaging into clinical setup is a challenge. We report an integrated PA and ultrasound imaging system by combining the light delivery to the tissue with the ultrasound probe. First, Monte Carlo simulations were run to study the variation in absorbance within tissue for different angles of illumination, fiber-to-probe distance (FPD), and fiber-to-tissue distance (FTD). This is followed by simulation for different depths of the embedded sphere (object of interest). Several probe holders were designed for different light launching angles. Phantoms were developed to mimic a sentinel lymph node imaging scenario. It was observed that, for shallower imaging depths, the variation in signal-to-noise ratio (SNR) values could be as high as 100% depending on the angle of illumination at a fixed FPD and FTD. Results confirm that different light illumination angles are required for different imaging depths to get the highest SNR PA images. The results also validate that one can use Monte Carlo simulation as a tool to optimize the probe holder design depending on the imaging needs. This eliminates a trial-and-error approach generally used for designing a probe holder. MOE (Min. of Education, S’pore) Published version 2017-07-18T04:31:08Z 2019-12-06T15:35:13Z 2017-07-18T04:31:08Z 2019-12-06T15:35:13Z 2016 Journal Article Sivasubramanian, K., Periyasamy, V., Wen, K. K., & Pramanik, M. (2017). Optimizing light delivery through fiber bundle in photoacoustic imaging with clinical ultrasound system: Monte Carlo simulation and experimental validation. Journal of Biomedical Optics, 22(4), 041008-. 1083-3668 https://hdl.handle.net/10356/83951 http://hdl.handle.net/10220/42898 10.1117/1.JBO.22.4.041008 en Journal of Biomedical Optics © 2016 Society of Photo-optical Instrumentation Engineers (SPIE). This paper was published in Journal of Biomedical Optics and is made available as an electronic reprint (preprint) with permission of Society of Photo-optical Instrumentation Engineers (SPIE). The published version is available at: [http://dx.doi.org/10.1117/1.JBO.22.4.041008]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 10 p. application/pdf |
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Photoacoustic imaging Monte Carlo simulation with embedded object Sivasubramanian, Kathyayini Periyasamy, Vijitha Wen, Kew Kok Pramanik, Manojit Optimizing light delivery through fiber bundle in photoacoustic imaging with clinical ultrasound system: Monte Carlo simulation and experimental validation |
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Translating photoacoustic (PA) imaging into clinical setup is a challenge. We report an integrated PA and ultrasound imaging system by combining the light delivery to the tissue with the ultrasound probe. First, Monte Carlo simulations were run to study the variation in absorbance within tissue for different angles of illumination, fiber-to-probe distance (FPD), and fiber-to-tissue distance (FTD). This is followed by simulation for different depths of the embedded sphere (object of interest). Several probe holders were designed for different light launching angles. Phantoms were developed to mimic a sentinel lymph node imaging scenario. It was observed that, for shallower imaging depths, the variation in signal-to-noise ratio (SNR) values could be as high as 100% depending on the angle of illumination at a fixed FPD and FTD. Results confirm that different light illumination angles are required for different imaging depths to get the highest SNR PA images. The results also validate that one can use Monte Carlo simulation as a tool to optimize the probe holder design depending on the imaging needs. This eliminates a trial-and-error approach generally used for designing a probe holder. |
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School of Chemical and Biomedical Engineering |
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School of Chemical and Biomedical Engineering Sivasubramanian, Kathyayini Periyasamy, Vijitha Wen, Kew Kok Pramanik, Manojit |
format |
Article |
author |
Sivasubramanian, Kathyayini Periyasamy, Vijitha Wen, Kew Kok Pramanik, Manojit |
author_sort |
Sivasubramanian, Kathyayini |
title |
Optimizing light delivery through fiber bundle in photoacoustic imaging with clinical ultrasound system: Monte Carlo simulation and experimental validation |
title_short |
Optimizing light delivery through fiber bundle in photoacoustic imaging with clinical ultrasound system: Monte Carlo simulation and experimental validation |
title_full |
Optimizing light delivery through fiber bundle in photoacoustic imaging with clinical ultrasound system: Monte Carlo simulation and experimental validation |
title_fullStr |
Optimizing light delivery through fiber bundle in photoacoustic imaging with clinical ultrasound system: Monte Carlo simulation and experimental validation |
title_full_unstemmed |
Optimizing light delivery through fiber bundle in photoacoustic imaging with clinical ultrasound system: Monte Carlo simulation and experimental validation |
title_sort |
optimizing light delivery through fiber bundle in photoacoustic imaging with clinical ultrasound system: monte carlo simulation and experimental validation |
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2017 |
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https://hdl.handle.net/10356/83951 http://hdl.handle.net/10220/42898 |
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1787136662538551296 |