Editorial Feature

What Are Biophotonic Sensors for Medical Diagnostics?

Biophotonics generally refers to using photonics concepts for biomedical applications like studying tissues, cells, and other biological processes. This article discusses biophotonic sensors in medical diagnostics, how they are used, their functionality and recent advancements in this regard.

Image Credit: PopTika/Shutterstock.com

Biophotonic Sensors in Medical Diagnostics

In the modern medical industry, different types of equipment and machinery are used to help diagnose diseases, inspect cells and tissues, view hidden organs, and treat specific diseases. These equipment work on a variety of technologies and principles and have specific use cases accordingly. For instance, X-ray technology is used to view beyond the external skin layer into the bone structures, and endoscope technology can be used to inspect the inside of the stomach, etc. Similarly, biophotonic sensors also utilize various technologies like fluorescence-based imaging, optical coherence tomography (OCT), surface plasmon resonance (SPR ), Raman spectroscopy, etc, depending on the specific use case.

How are these Biophotonic Sensors Used?

Biophotonic sensors utilizing OCT are used in ophthalmology for retinal imaging due to OCT’s high resolution and depth penetration, which enables detailed visualization of tissue structures, aiding in the early detection of abnormalities. SPR-based biophotonic sensors can detect changes in refractive index near the sensor surface, making them suitable for studying and real-time monitoring of binding events between biological molecules, like protein-protein interactions and drug development processes. Similarly, Raman spectroscopy can help characterize biomolecules, which can be crucial for cancer detection by analyzing the chemical composition of tissues to distinguish between healthy and diseased states.

Recent Advancements in Biophotonic Sensors for Medical Diagnostics

Advancements in biophotonic sensors allow medical experts to diagnose early and efficiently since these sensors provide high accuracy, precision, repeatability, fast and real-time results and non-invasive procedures. Some of the recent research on the advancements of biophotonic sensors are discussed below.

Low-Cost Point-of-Care Biophotonic Sensors

In a 2021 study, researchers addressed the need for early and efficient disease diagnosis using low-cost point-of-care devices in the field of personalized medicine and public health protection. The researchers demonstrated optical biosensors that integrate silicon nitride (Si3N4) waveguide-based sensor circuits with on-chip organic lasers, forming Si3N4-organic hybrid (SiNOH) lasers. These lasers utilize dye-doped cladding materials deposited on passive waveguides and are optically pumped by external light sources.

The fabrication process involves a single lithography step for Si3N4 waveguides and subsequent application of organic gain medium through dispensing, spin-coating, or ink-jet printing. The proof-of-concept experiment successfully detected different concentrations of fibrinogen, demonstrating the feasibility of this integrated sensor system driven by a low-cost organic light source.

Defected Photonic Crystals in Dengue Detection

In another 2022 study, researchers explored the biosensing capabilities of one-dimensional defected photonic crystals (1D PC) for medical diagnostics. The proposed biophotonic sensor, designed with a defect layer of air in the middle of 1D PC, demonstrated the ability to distinguish between infected and normal blood samples containing hemoglobin, plasma, and platelet components. The sensitivity of the biosensor reached a maximum of 428.6 nm/RIU when loaded with an infected blood sample containing plasma only.

The study focused on the detection of the dengue virus in blood, relying on the change in the position of the defect mode inside the photonic band gap due to variations in the refractive index of blood components. The biosensor exhibited high sensitivity, figure of merit, and quality factor values, making it a unique tool for rapid and accurate medical diagnostics in diverse applications.

Natural Material-Based Biosensor

A 2021 study emphasizes the need for photonic structures interfacing with biological systems for sensitive detection of biological signals and precise imaging of cellular structures. Unlike conventional photonic structures based on artificial materials, the study focuses on designing biophotonic probes using natural materials, particularly biological entities like viruses, cells, and tissues.

The study discusses three representative biophotonic probes: bio-microlenses, cell-based biophotonic waveguides, and biological lasers. Biological lasers, utilizing naturally derived biomaterials, are highlighted for their potential in bio-detection and imaging, especially those based on viruses. Additionally, the study discusses the application of cell-based biophotonic waveguides for guiding light in biological systems, offering an alternative to traditional materials with higher biocompatibility. The study also explores cell-based bio-microlenses usage for label-free imaging of living cells and blood diagnostics.

Future Prospects

Recently, every scientific field has turned its attention towards integrating machine learning  (ML) and artificial intelligence (AI). Similarly, the integration of biophotonic sensors with artificial intelligence and machine learning algorithms in the near future is anticipated to enhance the interpretation of complex data generated by these sensors, which will further improve diagnostic accuracy.

Conclusion

In conclusion, biophotonic sensors are very useful for medical diagnostics, offering a non-invasive, real-time, and highly sensitive approach to understanding biological processes. Recent advancements in biophotonic sensors, such as low-cost point-of-care sensors, Si3N4-organic hybrid lasers and natural material-based probes, provide accurate medical diagnostics. Finally, AI and Ml integration with biophotonic sensors are expected to enhance their capabilities even further.

More from AZoOptics: What to Know About Integrated Photonics in Data Centers

References and Further Reading

Khetrapal, Afsaneh. (2023, July 20). Biophotonic Instruments. News-Medical. Retrieved on February 17, 2024 from https://www.news-medical.net/life-sciences/Biophotonic-Instruments.aspx

Kohler, D., Schindler, G., Hahn, L., Milvich, J., Hofmann, A., Länge, K., ... & Koos, C. (2021). Biophotonic sensors with integrated Si3N4-organic hybrid (SiNOH) lasers for point-of-care diagnostics. Light: Science & Applications. https://doi.org/10.1038/s41377-021-00486-w

Marcu, L., Boppart, S. A., Hutchinson, M. R., Popp, J., & Wilson, B. C. (2018). Biophotonics: the big picture. Journal of biomedical optics. https://doi.org/10.1117/1.JBO.23.2.021103

Matar, Z. S., Al-Dossari, M., Awasthi, S. K., Mohamed, D., Abd El-Gawaad, N. S., & Aly, A. H. (2022). Conventional biophotonic sensing approach for sensing and detection of normal and infected samples containing different blood components. Crystals. https://doi.org/10.3390/cryst12050650

Nouman, W. M., Abd El-Ghany, S. S., Sallam, S. M., Dawood, A. F. B., & Aly, A. H. (2020). Biophotonic sensor for rapid detection of brain lesions using 1D photonic crystal. Optical and Quantum Electronics. https://doi.org/10.1007/s11082-020-02409-2

Pan, T., Lu, D., Xin, H., & Li, B. (2021). Biophotonic probes for bio-detection and imaging. Light: Science & Applications. https://doi.org/10.1038/s41377-021-00561-2

Pradhan, P., Guo, S., Ryabchykov, O., Popp, J., & Bocklitz, T. W. (2020). Deep learning a boon for biophotonics?. Journal of Biophotonics. https://doi.org/10.1002/jbio.201960186

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Taha Khan

Written by

Taha Khan

Taha graduated from HITEC University Taxila with a Bachelors in Mechanical Engineering. During his studies, he worked on several research projects related to Mechanics of Materials, Machine Design, Heat and Mass Transfer, and Robotics. After graduating, Taha worked as a Research Executive for 2 years at an IT company (Immentia). He has also worked as a freelance content creator at Lancerhop. In the meantime, Taha did his NEBOSH IGC certification and expanded his career opportunities.  

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Khan, Taha. (2024, February 19). What Are Biophotonic Sensors for Medical Diagnostics?. AZoOptics. Retrieved on April 17, 2024 from https://www.azooptics.com/Article.aspx?ArticleID=2546.

  • MLA

    Khan, Taha. "What Are Biophotonic Sensors for Medical Diagnostics?". AZoOptics. 17 April 2024. <https://www.azooptics.com/Article.aspx?ArticleID=2546>.

  • Chicago

    Khan, Taha. "What Are Biophotonic Sensors for Medical Diagnostics?". AZoOptics. https://www.azooptics.com/Article.aspx?ArticleID=2546. (accessed April 17, 2024).

  • Harvard

    Khan, Taha. 2024. What Are Biophotonic Sensors for Medical Diagnostics?. AZoOptics, viewed 17 April 2024, https://www.azooptics.com/Article.aspx?ArticleID=2546.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this article?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.