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时域信号平均提高微流控阻抗细胞仪中小粒子检测和计数的准确性。

Time-domain signal averaging to improve microparticles detection and enumeration accuracy in a microfluidic impedance cytometer.

机构信息

Department of Biomedical Engineering, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA.

Department of Electrical and Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA.

出版信息

Biotechnol Bioeng. 2021 Nov;118(11):4428-4440. doi: 10.1002/bit.27910. Epub 2021 Aug 16.

Abstract

Microfluidic impedance cytometry is a powerful system to measure micro and nano-sized particles and is routinely used in point-of-care disease diagnostics and other biomedical applications. However, small objects near a sensor's detection limit are plagued with relatively significant background noise and are difficult to identify for every case. While many data processing techniques can be utilized to reduce noise and improve signal quality, frequently they are still inadequate to push sensor detection limits. Here, we report the first demonstration of a novel signal averaging algorithm effective in noise reduction of microfluidic impedance cytometry data, improving enumeration accuracy, and reducing detection limits. Our device uses a 22 µm tall × 100 µm wide (with 30 µm wide focused aperture) microchannel and gold coplanar microelectrodes that generate an electric field, recording bipolar pulses from polystyrene microparticles flowing through the channel. In addition to outlining a modified moving signal averaging technique theoretically and with a model data set, we also performed a compendium of characterization experiments including variations in flow rate, input voltage, and particle size. Multivariate metrics from each experiment are compared including signal amplitude, pulse width, background noise, and signal-to-noise ratio (SNR). Incorporating our technique resulted in improved SNR and counting accuracy across all experiments conducted, and the limit of detection improved from 5 to 1 µm particles without modifying microchannel dimensions. Succeeding this, we envision implementing our modified moving average technique to develop next-generation microfluidic impedance cytometry devices with an expanded dynamic range and improved enumeration accuracy. This can be exceedingly useful for many biomedical applications, such as infectious disease diagnostics where devices may enumerate larger-scale immune cells alongside sub-micron bacterium in the same sample.

摘要

微流控阻抗细胞术是一种强大的测量微纳米颗粒的系统,常用于即时疾病诊断和其他生物医学应用。然而,接近传感器检测极限的微小物体受到相对较大的背景噪声的困扰,并且对于每种情况都难以识别。虽然可以利用许多数据处理技术来降低噪声并提高信号质量,但它们通常仍然不足以推动传感器检测极限。在这里,我们首次展示了一种新颖的信号平均算法,该算法可有效降低微流控阻抗细胞术数据的噪声,提高计数精度,并降低检测极限。我们的设备使用 22μm 高×100μm 宽(带有 30μm 宽聚焦孔径)的微通道和金共面微电极,产生电场,记录流过通道的聚苯乙烯微球的双极脉冲。除了从理论上和模型数据集概述修改后的移动信号平均技术外,我们还进行了一系列特征描述实验,包括流速、输入电压和颗粒大小的变化。比较了每个实验的多变量指标,包括信号幅度、脉冲宽度、背景噪声和信噪比 (SNR)。在所有进行的实验中,采用我们的技术都可以提高 SNR 和计数精度,而无需修改微通道尺寸即可将检测极限从 5μm 提高到 1μm 颗粒。在此之后,我们设想实施我们的修改后的移动平均技术,以开发具有扩展动态范围和提高计数精度的下一代微流控阻抗细胞术设备。这对于许多生物医学应用非常有用,例如传染病诊断,其中设备可以在同一样本中对较大规模的免疫细胞与亚微米细菌进行计数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c430/8589102/32342fb1e1f2/nihms-1731806-f0001.jpg

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