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The feasibility study of the transmission mode photoacoustic measurement of human calcaneus bone in vivo

The photoacoustic (PA) technique is uniquely positioned for biomedical applications primarily due to its ability to visualize optical absorption contrast in deep tissue at ultrasound resolution. In this work, via both three-dimensional (3D) numerical simulations and in vivo experiments on human subj...

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Detalles Bibliográficos
Autores principales: Feng, Ting, Zhu, Yunhao, Morris, Richard, kozloff, Kenneth M., Wang, Xueding
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552339/
https://www.ncbi.nlm.nih.gov/pubmed/34745881
http://dx.doi.org/10.1016/j.pacs.2021.100273
Descripción
Sumario:The photoacoustic (PA) technique is uniquely positioned for biomedical applications primarily due to its ability to visualize optical absorption contrast in deep tissue at ultrasound resolution. In this work, via both three-dimensional (3D) numerical simulations and in vivo experiments on human subjects, we investigated the possibility of PA measurement of human calcaneus bones in vivo in a non-invasive manner, as well as its feasibility to differentiate osteoporosis patients from normal subjects. The results from the simulations and the experiments both demonstrated that, when one side of the heel is illuminated by laser with light fluence under the ANSI safety limit, the PA signal generated in the human calcaneus bone can be detected by an ultrasonic transducer at the other side of the heel (i.e. transmission mode). Quantitative power spectral analyses of the calcaneus bone PA signals were also conducted, demonstrating that the microarchitectural changes in calcaneus bone due to osteoporosis can be detected, as reflected by enhanced high frequency components in detected PA bone signal. Further statistical analysis of the experimental results from 10 osteoporosis patients and 10 healthy volunteers showed that the weighted frequency as a quantified PA spectral parameter can differentiate the two subject groups with statistical significance.