Autonomous robotic laparoscopic surgery for intestinal anastomosis.

Autonomous robotic surgery has the potential to provide efficacy, safety, and consistency independent of individual surgeon's skill and experience. Autonomous anastomosis is a challenging soft-tissue surgery task because it requires intricate imaging, tissue tracking, and surgical planning techniques, as well as a precise execution via highly adaptable control strategies often in unstructured and deformable environments. In the laparoscopic setting, such surgeries are even more challenging because of the need for high maneuverability and repeatability under motion and vision constraints. Here we describe an enhanced autonomous strategy for laparoscopic soft tissue surgery and demonstrate robotic laparoscopic small bowel anastomosis in phantom and in vivo intestinal tissues. This enhanced autonomous strategy allows the operator to select among autonomously generated surgical plans and the robot executes a wide range of tasks independently. We then use our enhanced autonomous strategy to perform in vivo autonomous robotic laparoscopic surgery for intestinal anastomosis on porcine models over a 1-week survival period. We compared the anastomosis quality criteria-including needle placement corrections, suture spacing, suture bite size, completion time, lumen patency, and leak pressure-of the developed autonomous system, manual laparoscopic surgery, and robot-assisted surgery (RAS). Data from a phantom model indicate that our system outperforms expert surgeons' manual technique and RAS technique in terms of consistency and accuracy. This was also replicated in the in vivo model. These results demonstrate that surgical robots exhibiting high levels of autonomy have the potential to improve consistency, patient outcomes, and access to a standard surgical technique.

A Novel Wax Based Piezo Actuator for Autonomous Deep Anterior Lamellar Keratoplasty (Piezo-DALK).

This paper reports the design and evaluation of a novel piezo based actuator for needle drive in autonomous Deep Anterior Lamellar Keratoplasty (piezo-DALK). The actuator weighs less than 8g and is 20mm × 20mm × 10.5mm in size, making it ideal for eye-mounted applications. Mean open loop positional deviation was 1.17 ± 3.15um, and system repeatability and accuracy were 17.16um and 18.33um, respectively. Stall force was found to vary linearly with the cooling cycle and the actuator achieved a maximum drive force of 3.98N. When simulating the DALK procedure in synthetic corneal tissue, the piezo-DALK achieved a penetration depth of 643.56um which was equivalent to 92.1% of the total corneal thickness. This correlated closely with our desired depth of 90% ± 5% and took 2.5 hours to achieve. This work represents the first eye mountable actuator capable of "Big Bubble" needle drive for autonomous DALK procedures.

Supervised Autonomous Electrosurgery via Biocompatible Near-Infrared Tissue Tracking Techniques.

Autonomous robotic surgery systems aim to improve patient outcomes by leveraging the repeatability and consistency of automation and also reducing human induced errors. However, intraoperative autonomous soft tissue tracking and robot control still remains a challenge due to the lack of structure, and high deformability of such tissues. In this paper, we take advantage of biocompatible Near-Infrared (NIR) marking methods and develop a supervised autonomous 3D path planning, filtering, and control strategy for our Smart Tissue Autonomous Robot (STAR) to enable precise and consistent incisions on complex 3D soft tissues. Our experimental results on cadaver porcine tongue samples indicate that the proposed strategy reduces surface incision error and depth incision error by 40.03% and 51.5%, respectively, compared to a teleoperation strategy via da Vinci. Furthermore, compared to an autonomous path planning method with linear interpolation between the NIR markers, the proposed strategy reduces the incision depth error by 48.58% by taking advantage of 3D tissue surface information.

Semi-autonomous Robotic Anastomoses of Vaginal Cuffs Using Marker Enhanced 3D Imaging and Path Planning.

Autonomous robotic anastomosis has the potential to improve surgical outcomes by performing more consistent suture spacing and bite size compared to manual anastomosis. However, due to soft tissue's irregular shape and unpredictable deformation, performing autonomous robotic anastomosis without continuous tissue detection and three-dimensional path planning strategies remains a challenging task. In this paper, we present a novel three-dimensional path planning algorithm for Smart Tissue Autonomous Robot (STAR) to enable semi-autonomous robotic anastomosis on deformable tissue. The algorithm incorporates (i) continuous detection of 3D near infrared (NIR) markers manually placed on deformable tissue before the procedure, (ii) generating a uniform and consistent suture placement plan using 3D path planning methods based on the locations of the NIR markers, and (iii) updating the remaining suture plan after each completed stitch using a non-rigid registration technique to account for tissue deformation during anastomosis. We evaluate the path planning algorithm for accuracy and consistency by comparing the anastomosis of synthetic vaginal cuff tissue completed by STAR and a surgeon. Our test results indicate that STAR using the proposed method achieves 2.6 times better consistency in suture spacing and 2.4 times better consistency in suture bite sizes than the manual anastomosis.

Autonomous Laparoscopic Robotic Suturing with a Novel Actuated Suturing Tool and 3D Endoscope.

Compared to open surgical techniques, laparoscopic surgical methods aim to reduce the collateral tissue damage and hence decrease the patient recovery time. However, constraints imposed by the laparoscopic surgery, i.e. the operation of surgical tools in limited spaces, turn simple surgical tasks such as suturing into time-consuming and inconsistent tasks for surgeons. In this paper, we develop an autonomous laparoscopic robotic suturing system. More specific, we expand our smart tissue anastomosis robot (STAR) by developing i) a new 3D imaging endoscope, ii) a novel actuated laparoscopic suturing tool, and iii) a suture planning strategy for the autonomous suturing. We experimentally test the accuracy and consistency of our developed system and compare it to sutures performed manually by surgeons. Our test results on suture pads indicate that STAR can reach 2.9 times better consistency in suture spacing compared to manual method and also eliminate suture repositioning and adjustments. Moreover, the consistency of suture bite sizes obtained by STAR matches with those obtained by manual suturing.