Autofluorescence lifetime augmented reality as a means for real-time robotic surgery guidance in human patients.

Due to loss of tactile feedback the assessment of tumor margins during robotic surgery is based only on visual inspection, which is neither significantly sensitive nor specific. Here we demonstrate time-resolved fluorescence spectroscopy (TRFS) as a novel technique to complement the visual inspection of oral cancers during transoral robotic surgery (TORS) in real-time and without the need for exogenous contrast agents. TRFS enables identification of cancerous tissue by its distinct autofluorescence signature that is associated with the alteration of tissue structure and biochemical profile. A prototype TRFS instrument was integrated synergistically with the da Vinci Surgical robot and the combined system was validated in swine and human patients. Label-free and real-time assessment and visualization of tissue biochemical features during robotic surgery procedure, as demonstrated here, not only has the potential to improve the intraoperative decision making during TORS but also other robotic procedures without modification of conventional clinical protocols.

Recognition of tumor cells by immuno-SERS-markers in a microfluidic chip at continuous flow.

SERS active nanoparticles were labeled with a reporter molecule and conjugated with anti-EpCAM antibodies. These immuno SERS markers were mixed with leukocytes, MCF-7 breast cancer cells and polystyrene beads, and the mixture was injected into a microfluidic quartz chip. Raman spectra were acquired at 785 nm excitation with 25 milliseconds exposure time in a continuous flow regime. Spectral unmixing by N-FINDR identified spectral signatures of SERS-labelled cells and polystyrene beads. This approach demonstrated rapid and reproducible SERS-assisted cell detection. Strategies are discussed to further increase the throughput for cell sorting.