Ryan Decker

Supervised autonomous robotic soft tissue surgery

Supervised autonomous in vivo robotic surgery is possible on soft tissues and outperforms standard clinical techniques in a dynamic preclinical environment. Hands-free The operating room may someday be run by robots, with surgeons overseeing their moves. Shademan et al. designed a “Smart Tissue Autonomous Robot,” or STAR, which consists of tools for suturing as well as fluorescent and 3D imaging, force sensing, and submillimeter positioning. With all of these components, the authors were able to use STAR for soft tissue surgery—a difficult task for a robot given tissue deformity and mobility. Surgeons tested STAR against manual surgery, laparoscopy, and robot-assisted surgery for porcine intestinal anastomosis, and found that the supervised autonomous surgery offered by the STAR system was superior. The current paradigm of robot-assisted surgeries (RASs) depends entirely on an individual surgeon’s manual capability. Autonomous robotic surgery—removing the surgeon’s hands—promises enhanced efficacy, safety, and improved access to optimized surgical techniques. Surgeries involving soft tissue have not been performed autonomously because of technological limitations, including lack of vision systems that can distinguish and track the target tissues in dynamic surgical environments and lack of intelligent algorithms that can execute complex surgical tasks. We demonstrate in vivo supervised autonomous soft tissue surgery in an open surgical setting, enabled by a plenoptic three-dimensional and near-infrared fluorescent (NIRF) imaging system and an autonomous suturing algorithm. Inspired by the best human surgical practices, a computer program generates a plan to complete complex surgical tasks on deformable soft tissue, such as suturing and intestinal anastomosis. We compared metrics of anastomosis—including the consistency of suturing informed by the average suture spacing, the pressure at which the anastomosis leaked, the number of mistakes that required removing the needle from the tissue, completion time, and lumen reduction in intestinal anastomoses—between our supervised autonomous system, manual laparoscopic surgery, and clinically used RAS approaches. Despite dynamic scene changes and tissue movement during surgery, we demonstrate that the outcome of supervised autonomous procedures is superior to surgery performed by expert surgeons and RAS techniques in ex vivo porcine tissues and in living pigs. These results demonstrate the potential for autonomous robots to improve the efficacy, consistency, functional outcome, and accessibility of surgical techniques.

Plenoptic cameras in surgical robotics: Calibration, registration, and evaluation

Three-dimensional sensing of changing surgical scenes would improve the function of surgical robots. This paper explores the requirements and utility of a new type of depth sensor, the plenoptic camera, for surgical robots. We present a metric calibration procedure for the plenoptic camera and the registration of its coordinate frame to the robot (hand-eye calibration). We also demonstrate the utility in robotic needle insertion and application of sutures in phantoms. The metric calibration accuracy is reported as 1.14 ± 0.80 mm for the plenoptic camera and 1.57 ± 0.90 mm for hand-eye calibration. The accuracy of needle insertion task is 1.79 ± 0.35 mm for the entire robotic system. Additionally, the accuracy of suture placement with the presented system is reported at 1.80 ± 0.43 mm. Finally, we report consistent suture spacing with only 0.11 mm standard deviation between inter-suture distances. The measured accuracy of less than 2 mm with consistent suture spacing is a promising result to provide repeatable leak-free suturing with a robotic tool and a plenoptic depth imager.

Multispectral tissue characterization for intestinal anastomosis optimization

Abstract. Intestinal anastomosis is a surgical procedure that restores bowel continuity after surgical resection to treat intestinal malignancy, inflammation, or obstruction. Despite the routine nature of intestinal anastomosis procedures, the rate of complications is high. Standard visual inspection cannot distinguish the tissue subsurface and small changes in spectral characteristics of the tissue, so existing tissue anastomosis techniques that rely on human vision to guide suturing could lead to problems such as bleeding and leakage from suturing sites. We present a proof-of-concept study using a portable multispectral imaging (MSI) platform for tissue characterization and preoperative surgical planning in intestinal anastomosis. The platform is composed of a fiber ring light-guided MSI system coupled with polarizers and image analysis software. The system is tested on ex vivo porcine intestine tissue, and we demonstrate the feasibility of identifying optimal regions for suture placement.

Performance evaluation and clinical applications of 3D plenoptic cameras

The observation and 3D quantification of arbitrary scenes using optical imaging systems is challenging, but increasingly necessary in many fields. This paper provides a technical basis for the application of plenoptic cameras in medical and medical robotics applications, and rigorously evaluates camera integration and performance in the clinical setting. It discusses plenoptic camera calibration and setup, assesses plenoptic imaging in a clinically relevant context, and in the context of other quantitative imaging technologies. We report the methods used for camera calibration, precision and accuracy results in an ideal and simulated surgical setting. Afterwards, we report performance during a surgical task. Test results showed the average precision of the plenoptic camera to be 0.90mm, increasing to 1.37mm for tissue across the calibrated FOV. The ideal accuracy was 1.14mm. The camera showed submillimeter error during a simulated surgical task.

In vivo perfusion assessment of an anastomosis surgery on porcine intestinal model(Conference Presentation)

Anastomosis, the connection of two structures, is a critical procedure for reconstructive surgery with over 1 million cases/year for visceral indication alone. However, complication rates such as strictures and leakage affect up to 19% of cases for colorectal anastomoses and up to 30% for visceral transplantation anastomoses. Local ischemia plays a critical role in anastomotic complications, making blood perfusion an important indicator for tissue health and predictor for healing following anastomosis. In this work, we apply a real time multispectral imaging technique to monitor impact on tissue perfusion due to varying interrupted suture spacing and suture tensions. Multispectral tissue images at 470, 540, 560, 580, 670 and 760 nm are analyzed in conjunction with an empirical model based on diffuse reflectance process to quantify the hemoglobin oxygen saturation within the suture site. The investigated tissues for anastomoses include porcine small (jejunum and ileum) and large (transverse colon) intestines. Two experiments using interrupted suturing with suture spacing of 1, 2, and 3 mm and tension levels from 0 N to 2.5 N are conducted. Tissue perfusion at 5, 10, 20 and 30 min after suturing are recorded and compared with the initial normal state. The result indicates the contrast between healthy and ischemic tissue areas and assists the determination of suturing spacing and tension. Therefore, the assessment of tissue perfusion will permit the development and intra-surgical monitoring of an optimal suture protocol during anastomosis with less complications and improved functional outcome.