Quantification of number density of random microstructure from a photoacoustic signal by using Nakagami statistics

Nakagami statistics-based photoacoustic spectroscopy used for label-free assessment of bone tissue

Quick identification of abnormal molecular metabolism of bone tissues is challenging. Photoacoustic (PA) spectroscopy techniques have great potential in molecular imaging. However, most of them are amplitude-dependent and easily affected by the light deposition, especially for bone tissues with high optical scattering. In this Letter, we propose a Nakagami statistics-based PA spectroscopy (NSPS) method for characterizing molecules in bone tissues. We indicate that the NSPS curve can intelligently identify changes in the content of molecules in bone tissues, with a high disturbance-resisting ability. The NSPS has remarkable potential for use in the early and rapid detection of bone diseases.

Characterization of multi-biomarkers for bone health assessment based on photoacoustic physicochemical analysis method

Photoacoustic (PA) techniques are potential alternatives to histopathology. The physicochemical spectrogram (PCS) generated by the PA measurement at multiple wavelengths can presents the morphology and chemical composition target at multi-biomarkers simultaneously. In this work, via multi-wavelength PA measurements performed on rabbit bone models, we investigated the feasibility of using PCSs for bone health assessment. A comprehensive analysis of the PCSs, termed PA physicochemical analysis (PAPCA), was conducted. The "slope" and "relative content" were used as the PAPCA-quantified parameters to characterize the changes in the physical and chemical properties of bone tissue, respectively. The findings are consistent well with the gold-standard imaging results. It demonstrated that the PAPCA can be used to characterize both the microstructure and content of multi-biomarkers which highly related with bone health. Considering the PA technique is noninvasive and radiation-free, it has great potential in the implementation and monitoring of bone diseases progression.

Multiple information extracted from photoacoustic radio-frequency signal and the application on tissue classification

Photoacoustic imaging is a hybrid biomedical imaging technique, combining rich optical contrasts and good acoustic resolution in deep tissues. As a noninvasive and nonionized imaging method, photoacoustic imaging has shown great potentials in biomedicine in the past decade. In this review, we give a brief introduction of the physical principle and three major implementations of photoacoustic imaging. Then, we present pictures of some recent progress about the extraction of new imaging parameters from photoacoustic radio-frequency signals. These parameters are highly associated with the tissue microstructure characteristics, including characteristic size, number density, and elasticity. This information could give us insight into various properties of tissue in-depth and be applied to tissue classification for basic research and clinical settings.