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Cortical Bone Assessment Using Ultrasonic Guided Waves: A Reproducibility Study in a Healthy Population

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Wavelet transform-based photoacoustic time-frequency spectral analysis for bone assessment.

Weiya Xie^1,2, Ting Feng^1,3, Mengjiao Zhang¹

¹Institute of Acoustics, School of Physics Science and Engineering, Tongji University, Shanghai, PR China.

|March 29, 2021

Summary

Photoacoustic time-frequency spectral analysis (PA-TFSA) shows potential for assessing bone health. This method can differentiate between osteoporotic and normal bone by analyzing frequency changes over time.

Keywords:

ARTB, area ratio of trabecular bone BMD, bone mineral density Bone assessment CWT, continuous wavelet transform DEXA, dual energy X-ray absorptiometry EDTA, ethylenediaminetetraacetic acid MTT, mean trabecular thickness PA, photoacoustic PA-TFS, photoacoustic time-frequency spectrum PA-TFSA, photoacoustic time-frequency spectral analysis PWMF, power-weighted mean frequency Photoacoustic measurement QUS, quantitative ultrasound ROI, region of interest Time-frequency spectral analysis US, ultrasound Wavelet transform

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Area of Science:

Biomedical Engineering
Medical Imaging
Orthopedics

Background:

Osteoporosis significantly impacts bone health, necessitating advanced diagnostic tools.
Current methods for assessing bone mineral density (BMD) and structure have limitations.
Photoacoustic imaging offers a non-invasive approach for tissue characterization.

Purpose of the Study:

To evaluate the feasibility of photoacoustic time-frequency spectral analysis (PA-TFSA) for bone mineral density (BMD) and bone structure assessment.
To correlate PA-TFSA parameters with bone properties like BMD and mean trabecular thickness (MTT).
To determine if PA-TFSA can differentiate between osteoporotic and normal bone.

Main Methods:

Simulations and ex vivo experiments were performed on bone samples with varying BMD and MTT.
Photoacoustic signals were analyzed using wavelet transform-based PA-TFSA.
Power-weighted mean frequency (PWMF) over time was quantified, along with y-intercept, midband-fit, and slope of its linear fit.

Main Results:

Osteoporotic bone samples (lower BMD, thinner MTT) exhibited higher frequency components.
These samples showed lower acoustic frequency attenuation over time, resulting in higher y-intercept, midband-fit, and slope.
The midband-fit and slope parameters demonstrated sensitivity to BMD variations.

Conclusions:

PA-TFSA is a feasible technique for evaluating bone mineral density and structure.
The midband-fit and slope derived from PA-TFSA can effectively distinguish between osteoporotic and normal bone.
This method holds promise for improved non-invasive bone assessment.