Multifunctional nanophotonic photoacoustic biosensors: a new era in molecular imaging–guided deep-tissue cancer monitoring
1
Issued Date
2025-10-01
Resource Type
ISSN
10462023
eISSN
10959130
Scopus ID
2-s2.0-105008092119
Journal Title
Methods
Volume
242
Start Page
1
End Page
23
Rights Holder(s)
SCOPUS
Bibliographic Citation
Methods Vol.242 (2025) , 1-23
Suggested Citation
Taha B.A., Sulaiman G.M., Addie A.J., Khalil K.A.A., Ahmed E.M., Chaudhary V., Arsad N. Multifunctional nanophotonic photoacoustic biosensors: a new era in molecular imaging–guided deep-tissue cancer monitoring. Methods Vol.242 (2025) , 1-23. 23. doi:10.1016/j.ymeth.2025.06.005 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/110826
Title
Multifunctional nanophotonic photoacoustic biosensors: a new era in molecular imaging–guided deep-tissue cancer monitoring
Corresponding Author(s)
Other Contributor(s)
Abstract
Monitoring cancer therapy is difficult because of restricted imaging depth, inadequate molecular specificity, and delayed response evaluation. Moreover, conventional imaging techniques fail to provide high-resolution, real-time views of the dynamic tumor microenvironment during therapy. Among emerging technologies, nanophotonic photoacoustic biosensors have gained prominence as multifunctional platforms that enable real-time, non-invasive imaging and dynamic monitoring of cancer therapy. This review discusses advances in nanophotonic engineering, including plasmonic nanostructures, NIR-II fluorophore-integrated systems, SERS-active materials, fiber-optic probes, and hybrid nanosystems, all tailored to enhance molecular targeting and signal specificity. In addition, biomimetic and biologically inspired nanosystems with enhanced tissue penetration and reduced autofluorescence in the NIR-II spectrum can be specifically highlighted. The key aspects of clinical translation are examined including biosafety, molecular specificity, and scalability. Furthermore, further explore the convergence of these biosensors with artificial intelligence and Internet of Things (IoT) frameworks to support adaptive, patient-specific decision-making in oncology. As a result of these multifunctional systems that combine nanophotonics, machine learning, and molecular diagnostics, oncology could shift towards precision-guided treatment. Finally, it proposes strategic avenues for clinical adoption, placing PAS at the vanguard of the next generation of cancer diagnostics.