Artificial intelligence-assisted spatial correction of augmented reality projections; implementing radiation mapping during radioguided robotic surgery.

Translation of the drop-in gamma probe transformed radioguided robot-assisted prostate cancer (PCa) surgery. This study evaluated whether digitization of radiometric signals could allow conversion into more easier to interpret Augmented Reality radiation mapping (AR^RM) displays. 20 PCa patients were included who underwent robot-assisted sentinel node (SN)- and prostate-specific membrane antigen (PSMA) radioguided resections (24 SNs, 16 PSMA-avid nodes and 1 PSMA-avid primary tumor). Radiometric probe counts/s (dimensionless) synchronized with positional probe data allowed the retrospective creation of dynamic AR^RM overlays in two dimensions. Artificial intelligence was used to segment out, and automatically track, surgical instruments and dynamically de-occlude the AR^RM displays accordingly. Retrospective scoring by end-users indicated a 72.5% preference for the AR^RM displays compared to the currently available radiometric display (bipolar scale; median ≥2; p < 0.001). Thus, indicating that video-feed embedded AR^RM visualizations provide a digital means to further advance the surgeon's perception of intraoperative molecular imaging.