Design of a Lab-On-Chip for Cancer Cell Detection through Impedance and Photoelectrochemical Response Analysis

Hsiao, Yu‐Ping; Mukundan, Arvind; Chen, Wei‐Chung; Wu, Ming-Tsang; Hsieh, Shang-Chin; Wang, Hsiang‐Chen

doi:10.3390/bios12060405

Cited by 28 publications

(15 citation statements)

References 88 publications

(89 reference statements)

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“…Impedance sensors can also identify cancer cells that are affected by drugs. A biosensor combining impedance and photoelectrochemical analysis of cancer cells was designed, as shown in Figure 1d [33], where monocrystalline silicon was used as a substrate for the biosensor. The serrated interdigitated electrodes not only can focus cells but also sense impedance signals.…”

Section: Silicon-based Impedance Biosensorsmentioning

confidence: 99%

A Review on Microfluidics-Based Impedance Biosensors

et al. 2023

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Electrical impedance biosensors are powerful and continuously being developed for various biological sensing applications. In this line, the sensitivity of impedance biosensors embedded with microfluidic technologies, such as sheath flow focusing, dielectrophoretic focusing, and interdigitated electrode arrays, can still be greatly improved. In particular, reagent consumption reduction and analysis time-shortening features can highly increase the analytical capabilities of such biosensors. Moreover, the reliability and efficiency of analyses are benefited by microfluidics-enabled automation. Through the use of mature microfluidic technology, complicated biological processes can be shrunk and integrated into a single microfluidic system (e.g., lab-on-a-chip or micro-total analysis systems). By incorporating electrical impedance biosensors, hand-held and bench-top microfluidic systems can be easily developed and operated by personnel without professional training. Furthermore, the impedance spectrum provides broad information regarding cell size, membrane capacitance, cytoplasmic conductivity, and cytoplasmic permittivity without the need for fluorescent labeling, magnetic modifications, or other cellular treatments. In this review article, a comprehensive summary of microfluidics-based impedance biosensors is presented. The structure of this article is based on the different substrate material categorizations. Moreover, the development trend of microfluidics-based impedance biosensors is discussed, along with difficulties and challenges that may be encountered in the future.

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Section: Silicon-based Impedance Biosensorsmentioning

confidence: 99%

A Review on Microfluidics-Based Impedance Biosensors

et al. 2023

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“…Electrochemiluminescence (ECL) is another photoemission mechanism that can be exploited for the detection and quantification of the target analyte in LoC-based systems [ 75 , 76 , 77 ]. It is usually observed during the application of a potential (several volts) to the electrodes of an electrochemical cell that contains a solution of luminescent species (polycyclic aromatic hydrocarbons, metal complexes, Quantum Dots or Nanoparticles) in an aprotic organic solvent [ 78 ].…”

Section: Evaluation Of System Performancesmentioning

confidence: 99%

Thin-Film-Based Multifunctional System for Optical Detection and Thermal Treatment of Biological Samples

et al. 2022

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In this work, we present a multifunctional Lab-on-Chip (LoC) platform based on hydrogenated amorphous silicon sensors suitable for a wide range of application in the fields of biochemical and food quality control analysis. The proposed system includes a LoC fabricated on a 5 cm × 5 cm glass substrate and a set of electronic boards for controlling the LoC functionalities. The presented Lab-on-Chip comprises light and temperature sensors, a thin film resistor acting as a heating source, and an optional thin film interferential filter suitable for fluorescence analysis. The developed electronics allows to control the thin film heater, a light source for fluorescence and absorption measurements, and the photosensors to acquire luminescent signals. All these modules are enclosed in a black metal box ensuring the portability of the whole platform. System performances have been evaluated in terms of sensor optical performances and thermal control achievements. For optical sensors, we have found a minimum number of detectable photons of 8 × 104 s−1·cm−2: at room temperature, 1.6 × 106 s−1·cm−2: in presence of fluorescence excitation source, and 2.4 × 106 s−1·cm−2· at 90 °C. From a thermal management point of view, we have obtained heating and cooling rates both equal to 2.2 °C/s, and a temperature sensor sensitivity of about 3 mV/°C even in presence of light. The achieved performances demonstrate the possibility to simultaneously use all integrated sensors and actuators, making promising the presented platform for a wide range of application fields.

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“…Barbeiro et al (2019) used NBI to study gastrointestinal endoscopy and found that NBI can be used as an important auxiliary image for WLI, which can improve the detection of gastrointestinal lesions. Apart from CAD, many biosensors have been recently researched to detect different cancer types [ 35 , 36 , 37 ]. However, most of these biosensors have a high limit of detection, thereby leading to poor sensitivity in early-stage cancer detection.…”

Section: Introductionmentioning

confidence: 99%

Identification of Early Esophageal Cancer by Semantic Segmentation

Fang

Mukundan

Tsao

et al. 2022

JPM

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Early detection of esophageal cancer has always been difficult, thereby reducing the overall five-year survival rate of patients. In this study, semantic segmentation was used to predict and label esophageal cancer in its early stages. U-Net was used as the basic artificial neural network along with Resnet to extract feature maps that will classify and predict the location of esophageal cancer. A total of 75 white-light images (WLI) and 90 narrow-band images (NBI) were used. These images were classified into three categories: normal, dysplasia, and squamous cell carcinoma. After labeling, the data were divided into a training set, verification set, and test set. The training set was approved by the encoder–decoder model to train the prediction model. Research results show that the average time of 111 ms is used to predict each image in the test set, and the evaluation method is calculated in pixel units. Sensitivity is measured based on the severity of the cancer. In addition, NBI has higher accuracy of 84.724% when compared with the 82.377% accuracy rate of WLI, thereby making it a suitable method to detect esophageal cancer using the algorithm developed in this study.

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Design of a Lab-On-Chip for Cancer Cell Detection through Impedance and Photoelectrochemical Response Analysis

Cited by 28 publications

References 88 publications

A Review on Microfluidics-Based Impedance Biosensors

A Review on Microfluidics-Based Impedance Biosensors

Thin-Film-Based Multifunctional System for Optical Detection and Thermal Treatment of Biological Samples

Identification of Early Esophageal Cancer by Semantic Segmentation

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