A novel stress sensor enables accurate estimation of micro-scale tissue mechanics in quantitative micro-elastography

Quantitative micro-elastography (QME) is a compression-based optical coherence elastography technique enabling the estimation of tissue mechanical properties on the micro-scale. QME utilizes a compliant layer as an optical stress sensor, placed between an imaging window and tissue, providing quantitative estimation of elasticity. However, the implementation of the layer is challenging and introduces unpredictable friction conditions at the contact boundaries, deteriorating the accuracy and reliability of elasticity estimation. This has largely limited the use of QME to <i>ex vivo</i> studies and is a barrier to clinical translation. In this work, we present a novel implementation by affixing the stress sensing layer to the imaging window and optimizing the layer thickness, enhancing the practical use of QME for <i>in vivo</i> applications by eliminating the requirement for manual placement of the layer, and significantly reducing variations in the friction conditions, leading to substantial improvement in the accuracy and repeatability of elasticity estimation. We performed a systematic validation of the integrated layer, demonstrating >30% improvement in sensitivity and the ability to provide mechanical contrast in a mechanically heterogeneous phantom. In addition, we demonstrate the ability to obtain accurate estimation of elasticity (<6% error compared to <14% achieved using existing QME) in homogeneous phantoms with mechanical properties ranging from 40 to 130 kPa. Furthermore, we show the integrated layer to be more robust, exhibiting increased temporal stability, as well as improved conformity to variations in sample surface topography, allowing for accurate estimation of elasticity over acquisition times 3× longer than current methods. Finally, when applied to <i>ex vivo</i> human breast tissue, we demonstrate the ability to distinguish between healthy and diseased tissue features, such as stroma and cancer, confirmed by co-registered histology, showcasing the potential for routine use in biomedical applications.

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Publication Details

Journal
APL Bioengineering
Published
2024-09-01
DOI
https://doi.org/10.1063/5.0220309
Citations
1
Primary Topic
Ultrasound Imaging and Elastography
Type
article
Field-Weighted Citation Impact
0.40

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article

A novel stress sensor enables accurate estimation of micro-scale tissue mechanics in quantitative micro-elastography

Yen Yeow, K. Metzner, Juliana Hamzah, C. Green et al.
1 citations
APL Bioengineering
Ultrasound Imaging and Elastography
0.40
article

A novel stress sensor enables accurate estimation of micro-scale tissue mechanics in quantitative micro-elastography

Yen Yeow, K. Metzner, Juliana Hamzah, C. Green, Alireza Mowla, Brendan F. Kennedy, Q. Fang, Rowan W. Sanderson, Farah Abdul-Aziz
article en
1 citations

Abstract

Quantitative micro-elastography (QME) is a compression-based optical coherence elastography technique enabling the estimation of tissue mechanical properties on the micro-scale. QME utilizes a compliant layer as an optical stress sensor, placed between an imaging window and tissue, providing quantitative estimation of elasticity. However, the implementation of the layer is challenging and introduces unpredictable friction conditions at the contact boundaries, deteriorating the accuracy and reliability of elasticity estimation. This has largely limited the use of QME to <i>ex vivo</i> studies and is a barrier to clinical translation. In this work, we present a novel implementation by affixing the stress sensing layer to the imaging window and optimizing the layer thickness, enhancing the practical use of QME for <i>in vivo</i> applications by eliminating the requirement for manual placement of the layer, and significantly reducing variations in the friction conditions, leading to substantial improvement in the accuracy and repeatability of elasticity estimation. We performed a systematic validation of the integrated layer, demonstrating >30% improvement in sensitivity and the ability to provide mechanical contrast in a mechanically heterogeneous phantom. In addition, we demonstrate the ability to obtain accurate estimation of elasticity (<6% error compared to <14% achieved using existing QME) in homogeneous phantoms with mechanical properties ranging from 40 to 130 kPa. Furthermore, we show the integrated layer to be more robust, exhibiting increased temporal stability, as well as improved conformity to variations in sample surface topography, allowing for accurate estimation of elasticity over acquisition times 3× longer than current methods. Finally, when applied to <i>ex vivo</i> human breast tissue, we demonstrate the ability to distinguish between healthy and diseased tissue features, such as stroma and cancer, confirmed by co-registered histology, showcasing the potential for routine use in biomedical applications.

APL BioengineeringVol. 8(3)
Australian Research Council (AU), The University of Western Australia (AU), Harry Perkins Institute of Medical Research (AU), Hollywood Private Hospital (AU), Nicolaus Copernicus University (PL), Institute of Physics (PL), Queen Elizabeth II Medical Centre (AU), Pathwest Laboratory Medicine (AU)
Australian Government, Narodowym Centrum Nauki, Department of Health, Government of Western Australia, Narodowa Agencja Wymiany Akademickiej, Australian Research Council
Openalex Percentile: Top 35%
Ultrasound Imaging and Elastography
0.40
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