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Optically-Validated Microvascular Phantom for Super-Resolution Ultrasound Imaging

Medical Physics 2024-10-22 v1

Abstract

Super-resolution ultrasound (SRUS) visualises microvasculature beyond the ultrasound diffraction limit (wavelength(λ\lambda)/2) by localising and tracking spatially isolated microbubble contrast agents. SRUS phantoms typically consist of simple tube structures, where diameter channels below 100 μ\mum are not available. Furthermore, these phantoms are generally fragile and unstable, have limited ground truth validation, and their simple structure limits the evaluation of SRUS algorithms. To aid SRUS development, robust and durable phantoms with known and physiologically relevant microvasculature are needed for repeatable SRUS testing. This work proposes a method to fabricate durable microvascular phantoms that allow optical gauging for SRUS validation. The methodology used a microvasculature negative print embedded in a Polydimethylsiloxane to fabricate a microvascular phantom. Branching microvascular phantoms with variable microvascular density were demonstrated with optically validated vessel diameters down to \sim 60 μ\mum (λ\lambda/5.8; λ\lambda =\sim 350 μ\mum). SRUS imaging was performed and validated with optical measurements. The average SRUS error was 15.61 μ\mum (λ\lambda/22) with a standard deviation error of 11.44 μ\mum. The average error decreased to 7.93 μ\mum (λ\lambda/44) once the number of localised microbubbles surpassed 1000 per estimated diameter. In addition, the less than 10%\% variance of acoustic and optical properties and the mechanical toughness of the phantoms measured a year after fabrication demonstrated their long-term durability. This work presents a method to fabricate durable and optically validated complex microvascular phantoms which can be used to quantify SRUS performance and facilitate its further development.

Keywords

Cite

@article{arxiv.2409.09031,
  title  = {Optically-Validated Microvascular Phantom for Super-Resolution Ultrasound Imaging},
  author = {Jaime Parra Raad and Daniel Lock and Yi-Yi Liu and Mark Solomon and Laura Peralta and Kirsten Christensen-Jeffries},
  journal= {arXiv preprint arXiv:2409.09031},
  year   = {2024}
}

Comments

This work has been submitted to the IEEE for possible publication

R2 v1 2026-06-28T18:44:03.695Z