Journal of Innovative Optical Health Sciences, 2017, 10 (3): 1750008, Published Online: Dec. 27, 2018  

Cell counting for in vivo flow cytometry signals with baseline drift

Author Affiliations
1 Med-X Research Institute and School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, P. R. China
2 School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, P. R. China
Abstract
In biomedical research fields, the in vivo flow cytometry (IVFC) is a widely used technology which is able to monitor target cells dynamically in living animals. Although the setup of IVFC system has been well established, baseline drift is still a challenge in the process of quantifying circulating cells. Previous methods, i.e., the dynamic peak picking method, counted cells by setting a static threshold without considering the baseline drift, leading to an inaccurate cell quantification. Here, we developed a method of cell counting for IVFC data with baseline drift by interpolation fitting, automatic segmentation and wavelet-based denoising. We demonstrated its performance for IVFC signals with three types of representative baseline drift. Compared with non-baseline-correction methods, this method showed a higher sensitivity and specificity, as well as a better result in the Pearson's correlation coe±cient and the mean-squared error (MSE).
References

[1] E. I. Galanzha, M. G. Viegas, T. I. Malinsky, A. V. Melerzanov, M. A. Juratli, M. Sarimollaoglu, D. A. Nedosekin, V. P. Zharov, “ In vivo acoustic and photoacoustic focusing of circulating cells,” Sci. Rep. 6, 21531 (2016).

[2] E. I. Galanzha, E. V. Shashkov, P. M. Spring, J. Y. Suen, V. P. Zharov, “In vivo, noninvasive, label-free detection and eradication of circulating metastatic melanoma cells using two-color photoacoustic flow cytometry with a diode laser, ” Cancer Res. 69, 7926–7934 (2009).

[3] Z. Fan, X. Wei, “ In vivo flow cytometry: A powerful optical technology to detect circulating tumor cells and diagnose cancer metastasis in vivo/In-vivo-Durchflusszytometrie: Ein leistungsstarkes optisches Verfahren zur Detektion zirkulierender Tumorzellen und zur In-vivo-Diagnose von Metastasen,” Photonics Lasers Med. 2, 27–35 (2013).

[4] J. Novak, I. Georgakoudi, X. Wei, A. Prossin, C. Lin, “In vivo flow cytometer for real-time detection and quantification of circulating cells, ” Opt. Lett. 29, 77–79 (2004).

[5] V. P. Zharov, E. I. Galanzha, V. V. Tuchin, “Photothermal image flow cytometry in vivo, ” Optics Lett. 30, 628–630 (2005).

[6] V. P. Zharov, E. I. Galanzha, E. V. Shashkov, N. G. Khlebtsov, V. V. Tuchin, “ In vivo photoacoustic flow cytometry for monitoring of circulating single cancer cells and contrast agents,” Opt. Lett. 31, 3623–3625 (2006).

[7] Y. Li, Z. Fan, J. Guo, G. Liu, X. Tan, C. Wang, Z. Gu, X. Wei, “ Circulation times of hepatocellular carcinoma cells by in vivo flow cytometry,” Chin. Opt. Lett. 8, 953–956 (2010).

[8] J. Yan, Z. Fan, X. Wu, M. Xu, J. Jiang, C. Tan, W. Wu, X. Wei, J. Zhou, “ Circulating tumor cells are correlated with disease progression and treatment response in an orthotopic hepatocellular carcinoma model,” Cytometry A 87, 1020–1028 (2015).

[9] I. Georgakoudi, N. Solban, J. Novak, W. L. Rice, X. Wei, T. Hasan, C. P. Lin, “In vivo flow cytometry a new method for enumerating circulating cancer cells, ” Cancer Res. 64, 5044–5047 (2004).

[10] D. A. Sipkins, X. Wei, J. W. Wu, J. M. Runnels, D. Coté, T. K. Means, A. D. Luster, D. T. Scadden, C. P. Lin, “ In vivo imaging of specialized bone marrow endothelial microdomains for tumor engraftment,” Nature 435, 969–973 (2005).

[11] Z.-C. Fan, J. Yan, G.-D. Liu, X.-Y. Tan, X.-F. Weng, W.-Z. Wu, J. Zhou, X.-B. Wei, “ Real-time monitoring of rare circulating hepatocellular carcinoma cells in an orthotopic model by in vivo flow cytometry assesses resection on metastasis,” Cancer Res. 72, 2683–2691 (2012).

[12] X. Wei, D. A. Sipkins, C. M. Pitsillides, J. Novak, I. Georgakoudi, C. P. Lin, “ Real-time detection of circulating apoptotic cells by in vivo flow cytometry,” Mol. Imaging 4, 415 (2005).

[13] Z. Fan, J. A. Spencer, Y. Lu, C. M. Pitsillides, G. Singh, P. Kim, S. H. Yun, V. Toxavidis, T. B. Strom, C. P. Lin, “In vivo tracking of ‘color-coded’ effector, natural and induced regulatory T cells in the allograft response, ” Nat. Med. 16, 718–722 (2010).

[14] J. Guo, Z. Fan, Z. Gu, X. Wei, “Studying the role of macrophages in circulating prostate cancer cells by in vivo flow cytometry, ” J. Innov. Opt. Health Sci. 5, 1250027 (2012). Link, ISI,

[15] Y. A. Menyaev, D. A. Nedosekin, M. Sarimollaoglu, M. A. Juratli, E. I. Galanzha, V. V. Tuchin, V. P. Zharov, “Optical clearing in photoacoustic flow cytometry, ” Biomed. Opt. Exp. 4, 3030–3041 (2013).

[16] S. Lee, C. Vinegoni, P. F. Feruglio, L. Fexon, R. Gorbatov, M. Pivoravov, A. Sbarbati, M. Nahrendorf, R. Weissleder, “Real-time in vivo imaging of the beating mouse heart at microscopic resolution, ” Nat. Commun. 3, 1054 (2012).

[17] M.-C. Zhong, X.-B. Wei, J.-H. Zhou, Z.-Q. Wang, Y.-M. Li, “Trapping red blood cells in living animals using optical tweezers, ” Nat. Commun. 4, 1768 (2013).

[18] Z. A. Nima, M. Mahmood, Y. Xu, T. Mustafa, F. Watanabe, D. A. Nedosekin, M. A. Juratli, T. Fahmi, E. I. Galanzha, J. P. Nolan, “Circulating tumor cell identification by functionalized silver–gold nanorods with multicolor, super-enhanced SERS and photothermal resonances, ” Sci. Rep. 4, 4752 (2014).

[19] M. V. Khodakovskaya, K. de Silva, D. A. Nedosekin, E. Dervishi, A. S. Biris, E. V. Shashkov, E. I. Galanzha, V. P. Zharov, “Complex genetic, photothermal, and photoacoustic analysis of nanoparticle–plant interactions, ” Proc. Natl. Acad. Sci. 108, 1028–1033 (2011).

[20] J.-W. Kim, E. I. Galanzha, E. V. Shashkov, H.-M. Moon, V. P. Zharov, “Golden carbon nanotubes as multimodal photoacoustic and photothermal high-contrast molecular agents, ” Nat. Nanotechnol. 4, 688–694 (2009).

[21] J. Shao, R. J. Griffin, E. I. Galanzha, J.-W. Kim, N. Koonce, J. Webber, T. Mustafa, A. S. Biris, D. A. Nedosekin, V. P. Zharov, “Photothermal nanodrugs: Potential of TNF-gold nanospheres for cancer theranostics, ” Sci. Rep. 3, 1293 (2013).

[22] E. I. Galanzha, E. V. Shashkov, T. Kelly, J.-W. Kim, L. Yang, V. P. Zharov, “ In vivo magnetic enrichment and multiplex photoacoustic detection of circulating tumor cells,” Nat. Nanotechnol. 4, 855–860 (2009).

[23] D. Damm, C. Wang, X. Wei, A. Mosig, “Cell counting for in vivo flow cytometer signals using wavelet-based dynamic peak picking, ” IEEE 2009 2nd Int. Conf. on Biomedical Engineering and Informatics, pp. 1–4, IEEE, Washington, D.C. (2009).

[24] Y. Suo, T. Liu, C. Xie, D. Wei, X. Tan, L. Wu, X. Wang, H. He, G. Shi, X. Wei, “ Near infrared in vivo flow cytometry for tracking fluorescent circulating cells,” Cytometry A 87, 878–884 (2015).

[25] Y. Ding, J. Wang, Z. Fan, D. Wei, R. Shi, Q. Luo, D. Zhu, X. Wei, “ Signal and depth enhancement for in vivo flow cytometer measurement of ear skin by optical clearing agents,” Biomed. Opt. Exp. 4, 2518–2526 (2013).

[26] Y. Li, J. Guo, C. Wang, Z. Fan, G. Liu, C. Wang, Z. Gu, D. Damm, A. Mosig, X. Wei, “ Circulation times of prostate cancer and hepatocellular carcinoma cells by in vivo flow cytometry,” Cytometry A 79, 848–854 (2011).

[27] C. D. McManus, U. Teppner, D. Neubert, S. M. Lobodzinski, “ Estimation and removal of baseline drift in the electrocardiogram,” Comput. Biomed. Res. 18, 1–9 (1985). Crossref,

[28] D. Ruan, J. Fessler, J. Balter, P. Keall, “ Real-time profiling of respiratory motion: Baseline drift, frequency variation and fundamental pattern change,” Phys. Med. Biol. 54, 4777 (2009).

[29] V. S. Chouhan, S. S. Mehta, “Total removal of baseline drift from ECG signal, ” Computing: Theory and Applications, 2007. ICCTA’07. Int. Conf., pp. 512–515, IEEE, USA (2007).

[30] R. F. Von Borries, J. H. Pierluissi, H. Nazeran, “Wavelet transform-based ECG baseline drift removal for body surface potential mapping, ” 2005 IEEE Engineering in Medicine and Biology. 27th Ann. Conf., pp. 3891–3894, IEEE, USA (2006).

[31] L. Xu, D. D. Zhang, K. Wang, “ Wavelet-based cascaded adaptive filter for removing baseline drift in pulse waveforms,” IEEE Trans. Biomed. Eng. 52, 1973–1975 (2005).

[32] D. L. Donoho, “ De-noising by soft-thresholding,” IEEE Trans. Inf. Theory 41, 613–627 (1995).

Xiaoling Wang, Yuanzhen Suo, Dan Wei, Hao He, Fan Wu, Xunbin We. Cell counting for in vivo flow cytometry signals with baseline drift[J]. Journal of Innovative Optical Health Sciences, 2017, 10(3): 1750008.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!