Three-step one-way model in terahertz biomedical detection

Yan Peng; Jieli Huang; Jie Luo; Zhangfan Yang; Liping Wang; Xu Wu; Xiaofei Zang; Chen Yu; Min Gu; Qing Hu; Xicheng Zhang; Yiming Zhu; Songlin Zhuang

doi:10.1186/s43074-021-00034-0

Three-step one-way model in terahertz biomedical detection

doi: 10.1186/s43074-021-00034-0

基金项目:

This work is financially supported by NSFC (61922059, 81961138014, 61805140, 81873609, 61771314) and the Terahertz Science and Technology Frontier Project (6198802).

计量
- 文章访问数: 324
- HTML全文浏览量: 2
- PDF下载量: 21
- 被引次数: 0
出版历程
- 收稿日期: 2021-04-19
- 录用日期: 2021-06-11
- 网络出版日期: 2021-07-23

Three-step one-way model in terahertz biomedical detection

1.
Shanghai Key Lab of Modern Optical System, Terahertz Technology Innovation Research Institute, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai, 200093, China
2.
Department of Nephrology, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
3.
Laboratory of Artificial-Intelligence Nanophotonics, University of Shanghai for Science and Technology, Shanghai, 200093, P
4.
Department of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
5.
The Institute of Optics, University of Rochester, Rochester, New York, 14627, USA

Funds:

This work is financially supported by NSFC (61922059, 81961138014, 61805140, 81873609, 61771314) and the Terahertz Science and Technology Frontier Project (6198802).

摘要

摘要: Terahertz technology has broad application prospects in biomedical detection. However, the mixed characteristics of actual samples make the terahertz spectrum complex and difficult to distinguish, and there is no practical terahertz detection method for clinical medicine. Here, we propose a three-step one-way terahertz model, presenting a detailed flow analysis of terahertz technology in the biomedical detection of renal fibrosis as an example:1) biomarker determination:screening disease biomarkers and establishing the terahertz spectrum and concentration gradient; 2) mixture interference removal:clearing the interfering signals in the mixture for the biomarker in the animal model and evaluating and retaining the effective characteristic peaks; and 3) individual difference removal:excluding individual interference differences and confirming the final effective terahertz parameters in the human sample. The root mean square error of our model is three orders of magnitude lower than that of the gold standard, with profound implications for the rapid, accurate and early detection of diseases.
- /
- /
- /
- /
- /
Abstract: Terahertz technology has broad application prospects in biomedical detection. However, the mixed characteristics of actual samples make the terahertz spectrum complex and difficult to distinguish, and there is no practical terahertz detection method for clinical medicine. Here, we propose a three-step one-way terahertz model, presenting a detailed flow analysis of terahertz technology in the biomedical detection of renal fibrosis as an example: 1) biomarker determination: screening disease biomarkers and establishing the terahertz spectrum and concentration gradient; 2) mixture interference removal: clearing the interfering signals in the mixture for the biomarker in the animal model and evaluating and retaining the effective characteristic peaks; and 3) individual difference removal: excluding individual interference differences and confirming the final effective terahertz parameters in the human sample. The root mean square error of our model is three orders of magnitude lower than that of the gold standard, with profound implications for the rapid, accurate and early detection of diseases.
- Terahertz spectroscopy /
- Renal fibrosis /
- Biomedical detection /
- Biomarker /
- Mixture interference /
- Individual difference

HTML全文

下载: 全尺寸图片幻灯片

参考文献(43)

[1]	Lucchinetti CF, Popescu BF, Bunyan RF, Moll NM, Roemer SF, Lassmann H, et al. Inflammatory cortical demyelination in early multiple sclerosis. N Engl J Med. 2011;365(23):2188-2197. https://doi.org/10.1056/NEJMoa1100648.
[2]	Longerich T, Endris V, Neumann O, Rempel E, Kirchner M, Abadi Z, et al. RSPO2 gene rearrangement: a powerful driver of β-catenin activation in liver tumours. Gut. 2019;68(7):1287-96. https://doi.org/10.1136/gutjnl-2018-317632.
[3]	Balázs M, Koroknai V, Szász I, Ecsedi S. Detection of CCND1 Locus Amplification by Fluorescence In Situ Hybridization. Methods Mol Biol. 2018;1726:85-100. https://doi.org/10.1007/978-1-4939-7565-5_9.
[4]	Worlikar T, Mendiratta-Lala M, Vlaisavljevich E, Hubbard R, Shi J, Hall TL, et al. Effects of histotripsy on local tumor progression in vivo Orthotopic rodent liver tumor model. BME Frontiers. 2020;1-14. https://doi.org/10.34133/2020/9830304.
[5]	Stephens PJ, McBride DJ, Lin ML, Varela I, Pleasance ED, Simpson JT, et al. Complex landscapes of somatic rearrangement in human breast cancer genomes. Nature. 2009;462(7276):1005-10. https://doi.org/10.1038/nature08645.
[6]	Potts PJ, Ellis AT, Kregsamer P, Streli C. X-ray fluorescence spectrometry. J Anal At Spectrom. 1999;14(11):1773-99.
[7]	Höhne J, Hohenberger C, Proescholdt M, Riemenschneider MJ, Wendl C, Brawanski A, et al. Fluorescein sodium-guided resection of cerebral metastases-an update. Acta Neurochir (Wien). 2017;159(2):363-7. https://doi.org/10.1007/s00701-016-3054-3.
[8]	Stummer W, Tonn JC, Goetz C, Ullrich W, Stepp H, Bink A,et al. 5-Aminolevulinic acid-derived tumor fluorescence: the diagnostic accuracy of visible fluorescence qualities as corroborated by spectrometry and histology and postoperative imaging. Neurosurgery. 2014;74(3):310-9. discussion 319-320. https://doi.org/10.1227/NEU.0000000000000267.
[9]	Ishizawa T, Fukushima N, Shibahara J, Masuda K, Tamura S, Aoki T, et al. Real-time identification of liver cancers by using indocyanine green fluorescent imaging. Cancer. 2009;115(11):2491-504. https://doi.org/10.1002/cncr.24291.
[10]	Zhu Y, Zheng W, Wang W, et al. Raman tensor of layered black phosphorus. PhotoniX. 2020;1:17.
[11]	11.You AYF, Bergholt MS, St-Pierre JP, Kit-Anan W, Pence IJ, Chester AH, et al. Raman spectroscopy imaging reveals interplay between atherosclerosis and medial calcification in the human aorta. Sci Adv. 2017;3(12):e1701156. https://doi.org/10.1126/sciadv.1701156.
[12]	Peng Y, Shi C, Wu X, Zhu Y, Zhuang S. Terahertz Imaging and Spectroscopy in Cancer Diagnostics: A Technical Review. BME Frontiers. 2020;2547609.
[13]	Peng Y, Shi C, Zhu Y, Gu M, Zhuang S. Terahertz spectroscopy in biomedical field: a review on signal-to-noise ratio improvement. PhotoniX. 2020;1(1). https://doi.org/10.1186/s43074-020-00011-z.
[14]	Ge H, Jiang Y, Lian F, Zhang Y, Xia S. Quantitative determination of aflatoxin B1 concentration in acetonitrile by chemometric methods using terahertz spectroscopy. Food Chem. 2016;209:286–92. https://doi.org/10.1016/j.foodchem.2016.04.070.
[15]	Wang Z, Wu J, Yang W, Bera AK, Kamenskyi D, Islam ATMN, et al. Experimental observation of Bethe strings. Nature. 2018;554(7691):219–23. https://doi.org/10.1038/nature25466.
[16]	Chanana A, Liu X, Zhang C, Vardeny ZV, Nahata A. Ultrafast frequency-agile terahertz devices using methylammonium lead halide perovskites. Sci Adv. 2018;4(5):eaar7353. https://doi.org/10.1126/sciadv.aar7353.
[17]	Lu S, Zhang X, Zhang Z, Yang Y, Xiang Y. Quantitative measurements of binary amino acids mixtures in yellow foxtail millet by terahertz time domain spectroscopy. Food Chem. 2016;211:494–501. https://doi.org/10.1016/j.foodchem.2016.05.079.
[18]	Peng Y, Shi C, Xu M, Kou T, Wu X, Song B, et al. Qualitative and quantitative identification of components in mixture by terahertz spectroscopy. IEEE Trans Terahertz Sci Technol. 2018;8(6):696–701. https://doi.org/10.1109/TTHZ.2018.2867816.
[19]	Wu X, Dai Y, Wang L, Peng Y, Lu L, Zhu Y, et al. Diagnosis of methylglyoxal in blood by using far-infrared spectroscopy and o-phenylenediamine derivation. Biomed. Opt. Express. 2020;11(2):963–70. https://doi.org/10.1364/BOE.381542.
[20]	Stantchev RI, Sun B, Hornett SM, Hobson PA, Gibson GM, Padgett MJ, et al. Noninvasive, near-field terahertz imaging of hidden objects using a single-pixel detector. Sci Adv. 2016;2(6):e1600190. https://doi.org/10.1126/sciadv.1600190.
[21]	Lee SH, Lee D, Choi MH, Son JH, Seo M. Highly sensitive and selective detection of steroid hormones using terahertz molecule-specific sensors. Anal Chem. 2019;91(10):6844–9. https://doi.org/10.1021/acs.analchem.9b01066.
[22]	Elgabarty H, Kampfrath T, Bonthuis DJ, Balos V, Kaliannan NK, Loche P, et al. Energy transfer within the hydrogen bonding network of water following resonant terahertz excitation. Sci Adv. 2020;6(17):eaay7074. https://doi.org/10.1126/sciadv.aay7074.
[23]	El Haddad J, de Miollis F, Bou Sleiman J, Canioni L, Mounaix P, Bousquet B. Chemometrics applied to quantitative analysis of ternary mixtures by terahertz spectroscopy. Anal Chem. 2014;86(10):4927–33. https://doi.org/10.1021/ac500253b.
[24]	Wu X, Wang L, Peng Y, Wu F, Cao J, Chen X, et al. Quantitative analysis of direct oral anticoagulant rivaroxaban by terahertz spectroscopy. Analyst. 2020;145(11):3909–15. https://doi.org/10.1039/D0AN00268B.
[25]	Du SQ, Li H, Xie L, Chen L, Peng Y, Zhu YM, et al. Vibrational frequencies of anti-diabetic drug studied by terahertz time-domain spectroscopy. Appl Phys Lett. 2012;100:143702.
[26]	Sommer S, Koch M, Adams A. Terahertz time-domain spectroscopy of plasticized poly(vinyl chloride). Anal Chem. 2018;90(4):2409–13. https://doi.org/10.1021/acs.analchem.7b04548.
[27]	Gu H, Shi C, Wu X, Peng Y. Molecular methylation detection based on terahertz metamaterial technology. Analyst. 2020;145(20):6705–12. https://doi.org/10.1039/D0AN01062F.
[28]	Peng Y, Yuan X, Zou X, Chen W, Huang H, Zhao H, et al. Terahertz identification and quantification of neurotransmitter and neurotrophy mixture. Biomed Opt Express. 2016;7(11):4472-9. https://doi.org/10.1364/BOE.7.004472.
[29]	Li T, Ma H, Peng Y, Chen X, Zhu Z, Wu X, et al. Gaussian numerical analysis and terahertz spectroscopic measurement of homocysteine. Biomed Opt Express. 2018;9(11):5467–76. https://doi.org/10.1364/BOE.9.005467.
[30]	Ajito K, Ueno Y, Kim JY, Sumikama T. Capturing the freeze-drying dynamics of NaCl nanoparticles using THz spectroscopy. J Am Chem Soc. 2018;140(42):13793–7. https://doi.org/10.1021/jacs.8b07828.
[31]	Zhou D, Liu Y. Renal fibrosis in 2015: Understanding the mechanisms of kidney fibrosis. Nat Rev Nephrol. 2016;12(2):68-70. https://doi.org/10.1038/nrneph.2015.215
[32]	Malvar A, Pirruccio P, Alberton V, Lococo B, Recalde C, Fazini B, et al. Histologic versus clinical remission in proliferative lupus nephritis. Nephrol Dial Transplant. 2017;32(8):1338-44. https://doi.org/10.1093/ndt/gfv296.
[33]	Mengel M, Chapman JR, Cosio FG, Cavaille-Coll MW, Haller H, Halloran PF, et al. Protocol biopsies in renal transplantation: insights into patient management and pathogenesis. Am J Transplant. 2007;7(3):512–7. https://doi.org/10.1111/j.1600-6143.2006.01677.x.
[34]	Zhuo L, Wang H, Chen D, Lu H, Zou G, Li W. Alternative renal biopsies: past and present. Int Urol Nephrol. 2018;50(3):475–9. https://doi.org/10.1007/s11255-017-1668-x.
[35]	Torres HR, Queirós S, Morais P, Oliveira B, Fonseca JC, Vilaça JL. Kidney segmentation in ultrasound, magnetic resonance and computed tomography images: a systematic review. Comput Meth Prog Bio. 2018;157:49–67. https://doi.org/10.1016/j.cmpb.2018.01.014.
[36]	Zhang XQ, Li X, Zhou WQ, Liu X, Huang JL, Zhang YY, et al. Serum Lysyl oxidase is a potential diagnostic biomarker for kidney fibrosis. Am J Nephrol. 2020;51(11):907–18. https://doi.org/10.1159/000509381.
[37]	Nakhjavani M, Etemadi J, Pourlak T, Mirhosaini Z, Zununi Vahed S, Abediazar S. Plasma levels of miR-21, miR-150, miR-423 in patients with lupus nephritis. Iran J Kidney Dis. 2019;13(3):198–206.
[38]	Hewitson TD, Smith ER, Samuel CS. Qualitative and quantitative analysis of fibrosis in the kidney. Nephrology (Carlton). 2014;19(11):721-6. https://doi.org/10.1111/nep.12321.
[39]	Samuel CS. Determination of collagen content, concentration, and sub-types in kidney tissue. Methods Mol Biol. 2009;466:223-35. https://doi.org/10.1007/978-1-59745-352-3_16.
[40]	Skibba M, Hye Khan MA, Kolb LL, Yeboah MM, Falck JR, Amaradhi R, et al. Epoxyeicosatrienoic acid analog decreases renal fibrosis by reducing epithelial-to-mesenchymal transition. Front Pharmacol. 2017;8:406. https://doi.org/10.3389/fphar.2017.00406.
[41]	Frisch MJ, Trucks G, Schlegel HB, Scuseria GE, Robb MA, Cheeseman J, et al. Gaussian 09 Revision A.1: Gaussian Inc; 2009.
[42]	Joseph J, Jemmis ED. Red-, blue-, or no-shift in hydrogen bonds: a unified explanation. J Am Chem Soc. 2007;129(15):4620–32. https://doi.org/10.1021/ja067545z.
[43]	Shen YC, Upadhya PC, Linfield EH, Davies AG. Temperature-dependent low-frequency vibrational spectra of purine and adenine. Appl Phys Lett. 2003;82(14):2350–2. https://doi.org/10.1063/1.1565680.