Photoacoustic-based approach to surgical guidance performed with and without a da Vinci robot

Death and paralysis are significant risks of modern surgeries, caused by injury to blood vessels and nerves hidden by bone and other tissue. We propose an approach to surgical guidance that relies on photoacoustic (PA) imaging to determine the separation between these critical anatomical features and to assess the extent of safety zones during surgical procedures. Images were acquired as an optical fiber was swept across vessel-mimicking targets, in the absence and presence of teleoperation with a research da Vinci Surgical System. Vessel separation distances were measured directly from PA images. Vessel positions were additionally recorded based on the fiber position (calculated from the da Vinci robot kinematics) that corresponded to an observed PA signal, and these recordings were used to indirectly measure vessel separation distances. Amplitude- and coherence-based beamforming were used to estimate vessel separations, resulting in 0.52- to 0.56-mm mean absolute errors, 0.66- to 0.71-mm root-mean-square errors, and 65% to 68% more accuracy compared to fiber position measurements obtained through the da Vinci robot kinematics. Similar accuracy was achieved in the presence of up to 4.5-mm-thick ex vivo tissue. Results indicate that PA image-based measurements of the separation among anatomical landmarks could be a viable method for real-time path planning in multiple interventional PA applications.