In Vivo Confocal Imaging of Fluorescently Labeled Microbubbles: Implications for Ultrasound Localization Microscopy

Matthew R. Lowerison; Chengwu Huang; Yohan Kim; Fabrice Lucien; Shigao Chen; Pengfei Song

doi:10.1109/TUFFC.2020.2988159

In Vivo Confocal Imaging of Fluorescently Labeled Microbubbles: Implications for Ultrasound Localization Microscopy

Matthew R. Lowerison, Chengwu Huang, Yohan Kim, Fabrice Lucien, Shigao Chen, Pengfei Song

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

We report the time kinetics of fluorescently labeled microbubbles (MBs) in capillary-level microvasculature as measured via confocal microscopy and compare these results to ultrasound localization microscopy (ULM). The observed 19.4 ± 4.2 MBs per confocal field-of-view (212μ m× 212 μ m) are in excellent agreement with the expected count of 19.1 MBs per frame. The estimated time to fully perfuse this capillary network was 193 s, which corroborates the values reported in the literature. We then modeled the capillary network as an empirically determined discrete-time Markov chain with adjustable MB transition probabilities though individual capillaries. The Monte Carlo random walk simulations found perfusion times ranging from 24.5 s for unbiased Markov chains up to 182 s for heterogeneous flow distributions. This pilot study confirms a probability-derived explanation for the long acquisition times required for super-resolution ULM.

Original language	English (US)
Article number	9068283
Pages (from-to)	1811-1819
Number of pages	9
Journal	IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Volume	67
Issue number	9
DOIs	https://doi.org/10.1109/TUFFC.2020.2988159
State	Published - Sep 2020

Keywords

Microbubble (MB) tracking
microvasculature
super-resolution
ultrasound microvessel imaging

ASJC Scopus subject areas

Instrumentation
Acoustics and Ultrasonics
Electrical and Electronic Engineering

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10.1109/TUFFC.2020.2988159

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@article{ad479ace987d47da855e265a1a9ec2a2,

title = "In Vivo Confocal Imaging of Fluorescently Labeled Microbubbles: Implications for Ultrasound Localization Microscopy",

abstract = "We report the time kinetics of fluorescently labeled microbubbles (MBs) in capillary-level microvasculature as measured via confocal microscopy and compare these results to ultrasound localization microscopy (ULM). The observed 19.4 ± 4.2 MBs per confocal field-of-view (212μ m× 212 μ m) are in excellent agreement with the expected count of 19.1 MBs per frame. The estimated time to fully perfuse this capillary network was 193 s, which corroborates the values reported in the literature. We then modeled the capillary network as an empirically determined discrete-time Markov chain with adjustable MB transition probabilities though individual capillaries. The Monte Carlo random walk simulations found perfusion times ranging from 24.5 s for unbiased Markov chains up to 182 s for heterogeneous flow distributions. This pilot study confirms a probability-derived explanation for the long acquisition times required for super-resolution ULM. ",

keywords = "Microbubble (MB) tracking, microvasculature, super-resolution, ultrasound microvessel imaging",

author = "Lowerison, {Matthew R.} and Chengwu Huang and Yohan Kim and Fabrice Lucien and Shigao Chen and Pengfei Song",

note = "Funding Information: Manuscript received March 13, 2020; accepted April 12, 2020. Date of publication April 15, 2020; date of current version August 27, 2020. This work was supported in part by the National Institutes of Health (NIH) under Grant R00CA214523 and Grant R01DK120559. (Corresponding author: Pengfei Song.) Matthew R. Lowerison and Pengfei Song are with the Beckman Institute, University of Illinois at Urbana–Champaign, Urbana, IL 61801 USA, also with the Department of Electrical and Computer Engineering, University of Illinois at Urbana–Champaign, Urbana, IL 61801 USA, and also with the Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA (e-mail: songp. . .edu). Publisher Copyright: {\textcopyright} 1986-2012 IEEE.",

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AU - Lucien, Fabrice

AU - Chen, Shigao

AU - Song, Pengfei

N1 - Funding Information: Manuscript received March 13, 2020; accepted April 12, 2020. Date of publication April 15, 2020; date of current version August 27, 2020. This work was supported in part by the National Institutes of Health (NIH) under Grant R00CA214523 and Grant R01DK120559. (Corresponding author: Pengfei Song.) Matthew R. Lowerison and Pengfei Song are with the Beckman Institute, University of Illinois at Urbana–Champaign, Urbana, IL 61801 USA, also with the Department of Electrical and Computer Engineering, University of Illinois at Urbana–Champaign, Urbana, IL 61801 USA, and also with the Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA (e-mail: songp. . .edu). Publisher Copyright: © 1986-2012 IEEE.

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N2 - We report the time kinetics of fluorescently labeled microbubbles (MBs) in capillary-level microvasculature as measured via confocal microscopy and compare these results to ultrasound localization microscopy (ULM). The observed 19.4 ± 4.2 MBs per confocal field-of-view (212μ m× 212 μ m) are in excellent agreement with the expected count of 19.1 MBs per frame. The estimated time to fully perfuse this capillary network was 193 s, which corroborates the values reported in the literature. We then modeled the capillary network as an empirically determined discrete-time Markov chain with adjustable MB transition probabilities though individual capillaries. The Monte Carlo random walk simulations found perfusion times ranging from 24.5 s for unbiased Markov chains up to 182 s for heterogeneous flow distributions. This pilot study confirms a probability-derived explanation for the long acquisition times required for super-resolution ULM.

AB - We report the time kinetics of fluorescently labeled microbubbles (MBs) in capillary-level microvasculature as measured via confocal microscopy and compare these results to ultrasound localization microscopy (ULM). The observed 19.4 ± 4.2 MBs per confocal field-of-view (212μ m× 212 μ m) are in excellent agreement with the expected count of 19.1 MBs per frame. The estimated time to fully perfuse this capillary network was 193 s, which corroborates the values reported in the literature. We then modeled the capillary network as an empirically determined discrete-time Markov chain with adjustable MB transition probabilities though individual capillaries. The Monte Carlo random walk simulations found perfusion times ranging from 24.5 s for unbiased Markov chains up to 182 s for heterogeneous flow distributions. This pilot study confirms a probability-derived explanation for the long acquisition times required for super-resolution ULM.

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In Vivo Confocal Imaging of Fluorescently Labeled Microbubbles: Implications for Ultrasound Localization Microscopy

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Keywords

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