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Highly sensitive and specific molecular detection is essential for advancing early cancer diagnosis. In this paper, we present an imaging system that combines swept source Raman spectroscopy with surface-enhanced Raman scattering (SERS) nanoparticles to enhance cancer detection capability. By incorporating a high-efficiency superconducting nanowire single-photon detector (SNSPD), the system achieves remarkable detection sensitivity to the femtomolar concentrations. This performance was demonstrated under practical conditions using only 30 mW excitation power and 40 ms wavelength point exposure time, enabling ultra-sensitive acquisition. Imaging experiments on both cell and tissue samples confirm the system’s compatibility with various biological applications. Combining high sensitivity, speed, and specificity, this platform offers a promising approach for molecular imaging and early stage cancer detection using SERS-based probes. 

Imaging of surface-enhanced Raman scattering (SERS) nanoparticles (NPs) has been intensively studied for cancer detection due to its high sensitivity, unconstrained low signal-to-noise ratios, and multiplexing detection capability. Furthermore, conjugating SERS NPs with various biomarkers is straightforward, resulting in numerous successful studies on cancer detection and diagnosis. However, Raman spectroscopy only provides spectral data from an imaging area without co-registered anatomic context. This is not practical and suitable for clinical applications. Here, we propose a custom-made Raman spectrometer with computer-vision-based positional tracking and monocular depth estimation using deep learning (DL) for the visualization of 2D and 3D SERS NPs imaging, respectively. In addition, the SERS NPs used in this study (hyaluronic acid-conjugated SERS NPs) showed clear tumor targeting capabilities (target CD44 typically overexpressed in tumors) by anex vivoexperiment and immunohistochemistry. The combination of Raman spectroscopy, image processing, and SERS molecular imaging, therefore, offers a robust and feasible potential for clinical applications.