Evidence map›Paper›PMID 35080901›Full record

ArticleScience robotics2022

Autonomous robotic laparoscopic surgery for intestinal anastomosis.

H Saeidi, J D Opfermann, M Kam, S Wei, S Leonard, M H Hsieh, J U Kang, A Krieger

Open access · greenAbstract readComparative StudyEvaluation Study
In one paragraph

Article in Science robotics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 111 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
111citing papers in PubMed, 4 pooled it
64.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

111 citing papers in PubMed, 4 syntheses or guidelines pooled it, 328 citations in OpenAlex.

  1. Pooled it
  2. [Artificial intelligence in urological surgery].Urologie (Heidelberg, Germany) · 2026
    Pooled it
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  7. Article
  8. An Expertise Transfer Framework For Autonomous Surgical Assistance.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
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  14. Bioinspired Photodetectors: From Nature to Advanced Applications.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
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51 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

H SaeidiDepartment of Computer Science, University of North Carolina Wilmington, Wilmington, NC 28403, USA.ORCID 0000-0001-6170-9310
J D OpfermannDepartment of Mechanical Engineering, Johns Hopkins University; Baltimore, MD 21211, USA.
M KamDepartment of Mechanical Engineering, Johns Hopkins University; Baltimore, MD 21211, USA.ORCID 0000-0002-7687-0980
S WeiLaboratory for Computational Sensing and Robotics, Johns Hopkins University; Baltimore, MD 21211, USA.ORCID 0000-0001-8679-9615
S LeonardLaboratory for Computational Sensing and Robotics, Johns Hopkins University; Baltimore, MD 21211, USA.ORCID 0000-0001-6429-4755
M H HsiehDepartment of Urology, Children's National Hospital, 111 Michigan Ave. N.W., Washington, DC 20010, USA.
J U KangLaboratory for Computational Sensing and Robotics, Johns Hopkins University; Baltimore, MD 21211, USA.
A KriegerDepartment of Mechanical Engineering, Johns Hopkins University; Baltimore, MD 21211, USA.ORCID 0000-0001-8169-075X
Johns Hopkins University · USChildren's National · US

Funding

Next Generation of Surgical Imaging and Robotics for Supervised Autonomous Soft Tissue SurgeryR01EB020610 · NIBIB · UNIV OF MARYLAND, COLLEGE PARK · PI HSIEH, MICHAEL HARRISON, KANG, JIN U · 2016 to 2019
$1.5M
Development and Pre-Clinical Evaluation of a Robotic System for Supervised Autonomous Tumor SurgeryR21EB024707 · NIBIB · UNIV OF MARYLAND, COLLEGE PARK · PI KRIEGER, AXEL · 2017 to 2018
$446k
NIBIB NIH HHS R01 EB020610NIBIB NIH HHS R21 EB024707
6 · The paper itself

Abstract

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.

Indexed as

AlgorithmsAnastomosis, SurgicalAnimalsDigestive System Surgical ProceduresHumansIntestine, SmallLaparoscopyMachine LearningMotionPhantoms, ImagingRobotic Surgical ProceduresSuture TechniquesSwine

Identifiers

PMID35080901
PMCPMC8992572
OpenAlexW4210656949

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.