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Applications of Spectrum Analysis Technology Based on Time-Domain Photoacoustic Signalin Biomedical Field |
Zheng Jiaxin1, Tian Rui1, Liu Mingqing1, Zan Kehua1, Wang Yihan1,2*, Zhu Shouping1,2 |
1(School of Life Science and Technology, Xidian University, Xi′an 710126, China) 2(Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, Xidian University, Xi′an 710126, China) |
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Abstract Time-domain photoacoustic (PA) signal measurement and spectral analysis technique is a non-invasive detection method that can provide the structural and functional information of biological tissue. Combining with the high contrast of optical modality and the high resolution of ultrasonic modality in deep tissue, PA signal data sets of target tissues under different wavelengths of light excitation are processed and analyzed. Compared with the conventional spectral detection, this technique is less susceptible to the limitations of the shape and morphology of the object to be measured and is not affected by the light scattering, therefore has a high sensitivity for the detection of deep tissues. In contrast to photoacoustic imaging, this technique does not require image reconstruction and focuses on achieving quantitative analysis. This article summarized the applications of time-domain PA signal spectral analysis technique in the detection of biological tissue, biological fluid, and biological exhaled gas, and reviewed the research progress and development directions of this technique around the improved experimental systems or different signal processing methods used in various studies.
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Received: 09 June 2021
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Corresponding Authors:
*E-mail: wangyihan@xidian.edu.cn
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[1] Alexander GB. Upon the production and reproduction of sound by light[J]. Journal of the Society of Telegraph Engineers, 1880, 9(34): 404-426. [2] Li Jingsong, Chen Weidong, Yu Benli. Recent Progress on Infrared Photoacoustic Spectroscopy Techniques[J]. Applied Spectroscopy Reviews, 2011, 46(6): 440-471. [3] 封婷. 光声分析方法在骨质定性和定量评估中的研究[D]. 南京:南京大学,2016. [4] 李佳瑞,王继芬. 光声光谱在法庭科学生物物证分析的研究进展[J/OL].http://kns.cnki.net/kcms/detail/31.1690.TN.20210301.1544.066.html,2021-03-02/2021-05-29. [5] 吕小虎,赵贵文. 光声光谱法及其应用[J]. 分析仪器, 1993(2): 37-41. [6] 王少华. 光声信号频谱分析[D]. 南京: 南京大学,2014. [7] Sinha S, Rao NA, Chinni BK, et al. Evaluation of frequency domain analysis of a multiwavelength photoacoustic signal for differentiating malignant from benign and normal prostates: Ex vivo study with human prostates[J]. Journal of Ultrasound in Medicine, 2016. 35(10): 2165-2177. [8] Ma Xiang, Cao Meng, Shen Qinghong, et al. Adipocyte size evaluation based on photoacoustic spectral analysis combined with deep learning method[J]. Applied Sciences, 2018, 8(11): 2178. [9] 文龙. 皮肤鳞状细胞癌的光声物理化学谱分析研究[D]. 合肥: 安徽医科大学,2019. [10] 丁宇. 基于光声技术的血糖无损检测与成像研究[D]. 南昌: 江西科技师范大学,2019. [11] Wang Yihan, He Jie, Li Jiao, et al. Toward whole-body quantitative photoacoustic tomography of small-animals with multi-angle light-sheet illuminations[J]. Biomedical optics express, 2017, 8(8): 3778-3795. [12] Wang Yihan, Xu Menglu, Gao Feng, et al. Nonlinear iterative perturbation scheme with simplified spherical harmonics (SP3) light propagation model for quantitative photoacoustic tomography[J]. Journal of Biophotonics, 2021: e202000446. [13] 梁丽荣. 呼出氨气光声光谱检测及医学应用研究[D]. 大连: 大连理工大学,2012. [14] 吕鹏飞,陆志谦,何巧芝,等. 基于光声谱法的无创血糖在体检测[J]. 光学精密工程, 2019, 27(6): 1301-1308. [15] Feng Ting, Joseph EP, Kenneth MK, et al. Characterization of bone microstructure using photoacoustic spectrum analysis[J]. Optics express, 2015. 23(19): 25217-25224. [16] 王维江,朱延彬. 光声光谱技术在生物医学领域的发展与应用[J]. 激光生物学报, 1997 (1): 65-70. [17] 刘洋. 模拟生物组织频域光声成像检测试验研究[D]. 黑龙江:哈尔滨工业大学,2015. [18] 孔庆霖. 频率域光声断层成像高性能重建算法研究[D]. 西安:西安电子科技大学,2019. [19] Rosencwaig A. Photoacoustic spectroscopy[J]. Annual Review of Biophysics and Bioengineering, 1980, 9(1): 31-54. [20] Fernandes J, Kang S, Mannoor M. Numerical comparative study on the performance of open photoacoustic cells[J]. Journal of Mechanical Science and Technology, 2021. 35(4): 1473-1485. [21] 李莉,谢文明,李晖. 光声光谱技术在现代生物医学领域的应用[J]. 激光与光电子学进展, 2012, 49(10): 69-76. [22] Mallidi S, Luke GP, Emelianov S. Photoacoustic imaging in cancer detection, diagnosis, and treatment guidance[J]. Trends in biotechnology, 2011, 29(5): 213-221. [23] 周篪声,郭周义,吴宏岳. 癌变组织的光声光谱研究[J]. 光谱学与光谱分析, 1995 (4): 35-38,57. [24] 李江华. 光学技术用于龋牙早期诊断的研究[D]. 广州: 华南师范大学,2010. [25] Xu Guan, Fowlkes JB, Tao Chao, et al. Photoacoustic spectrum analysis for microstructure characterization in biological tissue: analytical model[J]. Ultrasound in Medicine & Biology, 2015, 41(5): 1473-1480. [26] Xu Guan, Meng Zhuoxian, Lin Jiandie, et al. Functional pitch of a liver: fatty liver disease diagnosis with photoacoustic spectrum analysis[J]. Photonics West - Biomedical Optics, 2014. 9843: 89431G. [27] Xu Guan, Meng Zhuoxian, Lin Jiandie, et al. High resolution physio-chemical tissue analysis: Towards non-invasive in vivo biopsy[J]. Scientific Reports, 2016. 6(1): 16937. [28] Xu Guan, Meng Zhuoxian, Lin Jiandie, et al. The functional pitch of an organ: Quantification of tissue texture with photoacoustic spectrum analysis[J]. Radiology, 2014. 271(1): 248-254. [29] Chen Yingna, Xu Chengdang, Zhang Zhaoyu, et al. Prostate cancer identification via photoacoustic spectroscopy and machine learning[J]. Photoacoustics, 2021. 23: 100280. [30] Zhang Haonan, Chao Wanyu, Cheng Qian, et al. Interstitial photoacoustic spectral analysis: instrumentation and validation[J]. Biomedical Optics Express, 2017, 8(3): 1689-1697. [31] Ma Xiang, Cao Meng, Shen Qinghong, et al. Adipocyte size evaluation based on photoacoustic spectral analysis combined with deep learning method[J]. Applied Sciences, 2018. 8(11): 2178. [32] Zhou Xue, Jin Zhibin, Feng Ting, et al. Bone mineral density value evaluation based on photoacoustic spectral analysis combined with deep learning method[J]. Chinese Optics Letters, 2020, 18(4): 041701. [33] Feng Ting, Xie Yejing, Xie Weiya, et al. Bone chemical composition analysis using photoacoustic technique[J]. Frontiers in Physics, 2020. 8: 594. [34] Yuan Zhen, Sun Yao, Eric S, et al. Image-guided photoacoustic spectroscopy in diagnosis of osteoarthritis in hands: an initial study[C]//Photonic Therapeutics and Diagnostics VII. San Francisco: SPIE, 2011: 78834N. [35] Feng Ting, Li Qiaochu, Zhang Cheng, et al. Characterizing cellular morphology by photoacoustic spectrum analysis with an ultra-broadband optical ultrasonic detector[J]. Optics Express, 2016. 24(17): 19853-19862. [36] Zhang Cheng, Chen Sungliang, Ling Tao, et al. Review of imprinted polymer microrings as ultrasound detectors: Design, fabrication, and characterization[J]. IEEE Sensors Journal, 2015. 15(6): 3241-3248. [37] 郭萍,刘礼恩,刘琴. 白血病人血液的光声光谱[J]. 光谱学与光谱分析, 2000 (3): 457-458. [38] Tang Liu, Chang Shwu-Jen, Chen Ching-Jung, et al. Non-invasive blood glucose monitoring technology: A review[J]. Sensors, 2020, 20(23): 6925. [39] MacKenzie HA, Christison GB, Hodgson P, et al. A laser photoacoustic sensor for analyte detection in aqueous systems[J]. Elsevier, 1993. 11(1-3): 213-220. [40] Lilienfeld-Toal HV, Weidenmüller M, Xhelaj A, et al. A novel approach to non-invasive glucose measurement by mid-infrared spectroscopy: The combination of quantum cascade lasers (QCL) and photoacoustic detection[J]. Vibrational Spectroscopy, 2005. 38(1-2): 209-215. [41] Bauer A, Hertzberg O, Küderle A, et al. IR-spectroscopy of skin in vivo: Optimal skin sites and properties for non-invasive glucose measurement by photoacoustic and photothermal spectroscopy[J]. Journal of Biophotonics, 2018, 11(1): e201600261. [42] Lepowsky E, Ghaderinezhad F, Knowlton S, et al. Paper-based assays for urine analysis[J]. Biomicrofluidics, 2017. 11(5): 051501. [43] 滕洪明,逄越,李庆伟. 尿液糖蛋白组在泌尿系统癌症诊断中的研究进展[J]. 临床泌尿外科杂志, 2021, 36(4): 314-319, 324. [44] 孙洪伟,黄孟才. 光声光谱技术对人体体液的检测研究[J]. 数据采集与处理, 1989 (S1): 69-70. [45] Huang Mengcai, Sun Hongwei. Study of normal and cancerous urine using photoacoustic spectroscopy[J]. Journal of Biomedical Engineering, 1990, 12(5): 425-428. [46] Wu Shiying, Chen Yingna, Huang Shengsong, et al. Photoacoustic spectrum analysis for quick identification and grading of prostate cancer[C]//2020 IEEE International Ultrasonics Symposium (IUS). Las Vegas: IEEE, 2020: 1-4. [47] Vasilescu A, Hrinczenko B, Swain GM, et al. Exhaled breath biomarker sensing[J]. Biosensors and Bioelectronics, 2021. 182: 113193. [48] Ricci PP, Gregory OJ. Sensors for the detection of ammonia as a potential biomarker for health screening[J]. Scientific Reports, 2021, 11(1): 1-7. [49] Popa C, Bratu AM, Matei C, et al. Qualitative and quantitative determination of human biomarkers by laser photoacoustic spectroscopy methods[J]. Laser Physics, 2011. 21(7): 1336-1342. [50] Peng Qin, Weng Kegui, Li Shitian, et al. A Perspective of Epigenetic Regulation in Radiotherapy[J]. Frontiers in Cell and Developmental Biology, 2021. 9: 261. [51] Anas EMA, Kang Jin, Emad Boctor, et al. Enabling fast and high quality LED photoacoustic imaging: A recurrent neural networks based approach[J]. Biomedical Optics Express, 2018, 9(8): 3852-3866. |
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