Photoacoustic-based approach to surgical guidance performed with and without a da Vinci robot
Photoacoustic-based approach to surgical guidance performed with and without a da Vinci robot
复制标题
有或没有DA Vinci机器人执行的基于光声指导的基于光声指导的方法
DOI：
10.1117/1.jbo.22.12.121606
复制
发表时间：
2017-08-24
影响因子：
3.5
通讯作者：
Lediju Bell MA
中科院分区：
文献类型：
--
作者：
Gandhi N;Allard M;Kim S;Kazanzides P;Lediju Bell MA
死亡和瘫痪是现代外科手术的重大风险，由骨骼和其他组织隐藏的血管和神经损伤引起。我们提出了一种手术指导方法，该方法依赖于光声（PA）成像来确定这些关键解剖特征之间的分离，并评估手术过程中安全区的范围。图像是在使用研究型达芬奇手术系统进行远程操作的情况下，在光纤扫过血管模拟目标时获得的。直接从PA图像测量血管间隔距离。基于对应于观察到的PA信号的纤维位置（根据da芬奇机器人运动学计算）额外记录血管位置，并且这些记录用于间接测量血管分离距离。使用基于幅度和相干性的波束形成来估计血管间隔，与通过da芬奇机器人运动学获得的纤维位置测量相比，平均绝对误差为0.52至0.56 mm，均方根误差为0.66至0.71 mm，准确度提高了65%至68%。在存在高达4.5 mm厚的离体组织的情况下实现了类似的准确性。结果表明，PA图像为基础的测量解剖标志之间的分离可能是一种可行的方法，在多个介入PA应用程序的实时路径规划。
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.