Integration of cellular-resolution optical coherence tomography and Raman spectroscopy for discrimination of skin cancer cells with machine learning.

Significance: An integrated cellular-resolution optical coherence tomography (OCT) module with near-infrared Raman spectroscopy was developed on the discrimination of various skin cancer cells and normal cells. Micron-level three-dimensional (3D) spatial resolution and the spectroscopic capability on chemical component determination can be obtained simultaneously. Aim: We experimentally verified the effectiveness of morphology, intensity, and spectroscopy features for discriminating skin cells. Approach: Both spatial and spectroscopic features were employed for the discrimination of five types of skin cells, including keratinocytes (HaCaT), the cell line of squamous cell carcinoma (A431), the cell line of basal cell carcinoma (BCC-1/KMC), primary melanocytes, and the cell line of melanoma (A375). The cell volume, compactness, surface roughness, average intensity, and internal intensity standard deviation were extracted from the 3D OCT images. After removing the fluorescence components from the acquired Raman spectra, the entire spectra (600 to 2100 cm-1) were used. Results: An accuracy of 85% in classifying five types of skin cells was achieved. The cellular-resolution OCT images effectively differentiate cancer and normal cells, whereas Raman spectroscopy can distinguish the cancer cells with nearly 100% accuracy. Conclusions: Among the OCT image features, cell surface roughness, internal average intensity, and standard deviation of internal intensity distribution effectively differentiate the cancerous and normal cells. The three features also worked well in sorting the keratinocyte and melanocyte. Using the full Raman spectra, the melanoma and keratinocyte-based cell carcinoma cancer cells can be discriminated effectively.

On-Chip Monolithically Integrated Ultraviolet Low-Threshold Plasmonic Metal-Semiconductor Heterojunction Nanolasers.

The metal-semiconductor heterojunction is imperative for the realization of electrically driven nanolasers for chip-level platforms. Progress in developing such nanolasers has hitherto rarely been realized, however, because of their complexity in heterojunction fabrication and the need to use noble metals that are incompatible with microelectronic manufacturing. Most plasmonic nanolasers lase either above a high threshold (101 -103 MW cm-2 ) or at a cryogenic temperature, and lasing is possible only after they are removed from the substrate to avoid the large ohmic loss and the low modal reflectivity, making monolithic fabrication impossible. Here, for the first time, record-low-threshold, room-temperature ultraviolet (UV) lasing of plasmon-coupled core-shell nanowires that are directly grown on silicon is demonstrated. The naturally formed core-shell metal-semiconductor heterostructure of the nanowires leads to a 100-fold improvement in growth density over previous results. This unprecedentedly high nanowire density creates intense plasmonic resonance, which is outcoupled to the resonant Fabry-Pérot microcavity. By boosting the emission strength by a factor of 100, the hybrid photonic-plasmonic system successfully facilitates a record-low laser threshold of 12 kW cm-2 with a spontaneous emission coupling factor as high as ≈0.32 in the 340-360 nm range. Such architecture is simple and cost-competitive for future UV sources in silicon integration.