Evidence map›Paper›PMID 33521798›Full record

ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2019

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

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

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. A Confidence-Based Supervised-Autonomous Control Strategy for Robotic Vaginal Cuff Closure.IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

M KamDepartment of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA.
H SaeidiDepartment of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA.
S WeiElectrical and Computer Science Engineering Department, Johns Hopkins University, Baltimore, MD 21211, USA.
J D OpfermannSheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, 111 Michigan Avenue N.W., Washington, DC 20010, USA.
S LeonardElectrical and Computer Science Engineering Department, Johns Hopkins University, Baltimore, MD 21211, USA.
M H HsiehSheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, 111 Michigan Avenue N.W., Washington, DC 20010, USA.
J U KangElectrical and Computer Science Engineering Department, Johns Hopkins University, Baltimore, MD 21211, USA.
A KriegerDepartment of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA.
Johns Hopkins University · USUniversity of Maryland, College Park · 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 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.

Indexed as

3D path planningImage-guided surgeryMedical robotics

Identifiers

PMID33521798
PMCPMC7841647
OpenAlexW2979775562

What OpenQuestion holds

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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.