Label-Free Cancer Cells Detection Using Optical Sensors

Ahmad, Mahmoud Al; Najar, Adel; Moutaouakil, Amine El; Nasir, Nida; Hussein, Minas; Raji, Shaima; Hilal‐Alnaqbi, Ali

doi:10.1109/access.2018.2872768

Cited by 20 publications

(14 citation statements)

References 29 publications

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“…A higher order (higher p values) will result in redundancy and require further processing resources. The responses were collected using the experimental setup reported in [25]. It is recommended to apply the same order to both the 293T and HeLa cell suspensions for fair comparison.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, the FOM for lung and liver normal and cancerous suspensions were extracted per the introduced procedure and are depicted in The figure of merit (FOM) which we are introducing for the first time relates the location of the poles (L(p)) and the coefficient of poles C(p)). Scientifically: significant differences in cell composition for normal and cancer cells have been reported [25]. Their interaction with light will cause a change in the optical absorption and transmission response.…”

Section: Resultsmentioning

confidence: 99%

“…Mini-Spectrometers C11708MA from Hamamatsu/Japan, the optical sensor used in this work, convert the variable attenuation or reflectance into signals. The details of the integrated MEMS sensor and the light source used in this work are reported in [25].…”

Section: Sensor and Light Sourcementioning

confidence: 99%

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Label-Free Normal and Cancer Cells Classification Combining Prony’s Method and Optical Techniques

Abdulgani

Ahmad

2020

IEEE Access

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Label-free methods neither cause cell damage nor contribute to any change in cell composition and intrinsic characteristics. Indeed, there is much interest in the scientific community to learn more from existing methods and to develop new label-free based methods for detection and classification of cells. Cell classification using optical measurements has been frequently utilized. When cells interact with light, due to differences in the composition of different types of cells, changes in the optical absorption and transmission response result. This work combined the advancement in optical measurements and Prony techniques to enhance the classification of cells based on their measured optical profiles. In this work, six types of cells, HeLa, 293T, lung-cancer and normal, and liver-cancer and normal, were suspended in their corresponding medium and their transmission characteristics were assessed. After media de-embedding, the transmission profiles were fitted with a sum of exponentially decaying signals using the Prony algorithm. After that, the optical response of each cell was modeled with a set of extracted parameters: amplitude, frequency, phase, and damping factor. The four parameters extracted via the Prony method are related to the coefficients and locations of the poles for each fitted model. A figure of merit (FOM) has been introduced, whose distribution in the complex z-plane plays a major role in the classification of cell type. The changes in the values of FOM are due to the changes in cell composition and intrinsic characteristics of different cells.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Label-Free Normal and Cancer Cells Classification Combining Prony’s Method and Optical Techniques

Abdulgani

Ahmad

2020

IEEE Access

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“…Figure 2(c) illustrates the incident, reflected, and transmitted light intensities. The light intensities were linked through the Kirchhoff’s Law of Radiation 37 , which correlates the optical absorbance, transmittance, and reflection along with the incident wave.…”

Section: Resultsmentioning

confidence: 99%

Development of an Optical Assay to Detect SARS-CoV-2 Spike Protein Binding Interactions with ACE2 and Disruption of these Interactions Using Electric Current

Ahmad

Mustafa

Panicker³

et al. 2020

Preprint

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This study proposes a novel optical method of detecting and reducing SARS-CoV-2 transmission, the virus responsible for the COVID-19 pandemic that is sweeping the world today. SARS-CoV-2 belongs to the β-coronaviruses characterized by the crown-shaped spike protein that protrudes out of the virus particles, giving the virus a “corona” shape; hence the name coronavirus. This virus is similar to the viruses that caused SARS (severe acute respiratory syndrome) and MERS (Middle East respiratory syndrome), the other two coronavirus epidemics that were recently contained within the last ten years. The technique being proposed uses a light source from a smart phone and a mobile spectrophotometer to enable detection of viral proteins in solution or paper as well as protein-protein interactions. The proof-of-concept is shown by detecting soluble preparations of spike protein subunits from SARS-CoV-2, followed by detection of the actual binding potential of the spike protein with its host receptor, the angiotensin-converting enzyme 2 (ACE2). The results are validated by showing that this method can detect antigen-antibody binding using two independent viral protein-antibody pairs. The binding could be detected optically both in solution and on a solid support such as nitrocellulose membrane. Finally, this technique is combined with DC bias to show that introduction of a current into the system can be used to disrupt the antigen-antibody reaction, suggesting that the proposed extended technique can be a potential means of not only detecting the virus, but also reducing virus transmission by disrupting virus-receptor interactions electrically.SignificanceThe measured intensity of light can reveal information about different cellular parameters under study. When light passes through a bio-composition, the intensity is associated with its content. The nuclei size, cell shape and the refractive index variation of cells contributes to light intensity. In this work, an optical label-free real time detection method incorporating the smartphone light source and a portable mini spectrometer for SARS-CoV-2 detection was developed based on the ability of its spike protein to interact with the ACE2 receptor. The light interactions with control and viral protein solutions were capable of providing a quick decision regarding whether the sample under test was positive or negative, thus enabling SARS-CoV-2 detection in a rapid manner.

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“…Implemented gives more accuracy than before used method and takes less computation time, this procedure is very helpful for earlier detection of lung cancer. [6] It makes use of non-invasive screening system to differentiate normal cell to cancer cell and it uses label free discrimination techniques. Optical absorption and transmission response can cause a change in their interaction with light.…”

Section: IImentioning

confidence: 99%

Lung Cancer Detection using Matlab based on Image Processing

Pradeepa¹

2019

IJRASET

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Lung cancer is one of the world's most frequent causes of death. It is also known as carcinoma of the lung. Malignant lung tumor known as pathology tends to cause death. It can be classified by tissue abundance in the lung. Lung cancer can be classified into two classes of non-small cell lung cancer and cancer of the small cells. It forms alongside the genetic problem and the transformation of epigenetics. Most lung tumor cells grow larger and spread widely throughout the parts. CT image provides more data on the issue of detection of lung cancer by chest X-ray, but the small tumors cannot be found. One of the important techniques is the processing of images mostly used for lung cancer detection. In our proposed work we are using graphcut by use of DCE function for segmentation of foreground and background and for classification we are using image based on computer aided detection (CADe) by use of regions with CNN(Convolutional Neural Network) features.

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Label-Free Cancer Cells Detection Using Optical Sensors

Cited by 20 publications

References 29 publications

Label-Free Normal and Cancer Cells Classification Combining Prony’s Method and Optical Techniques

Label-Free Normal and Cancer Cells Classification Combining Prony’s Method and Optical Techniques

Development of an Optical Assay to Detect SARS-CoV-2 Spike Protein Binding Interactions with ACE2 and Disruption of these Interactions Using Electric Current

Lung Cancer Detection using Matlab based on Image Processing

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