Evidence map›Paper›PMID 38533465›Full record

ArticleProceedings. IEEE International Symposium on Bioinformatics and Bioengineering2021

Supervised Autonomous Electrosurgery for Soft Tissue Resection.

Jiawei Ge, Hamed Saeidi, Michael Kam, Justin Opfermann, Axel Krieger

Open access · greenAbstract read
In one paragraph

Article in Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 11 citations in OpenAlex.

  1. 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

5 authors at 2 institutions in 1 country.

Jiawei GeDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0001-8336-1837
Hamed SaeidiDepartment of Computer Science, University of North Carolina Wilmington, Wilmington, NC, USA.
Michael KamDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Justin OpfermannDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Axel KriegerDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Johns Hopkins University · USUniversity of North Carolina Wilmington · 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

Surgical resection is the current clinical standard of care for treating squamous cell carcinoma. Maintaining an adequate tumor resection margin is the key to a good surgical outcome, but tumor edge delineation errors are inevitable with manual surgery due to difficulty in visualization and hand-eye coordination. Surgical automation is a growing field of robotics to relieve surgeon burdens and to achieve a consistent and potentially better surgical outcome. This paper reports a novel robotic supervised autonomous electrosurgery technique for soft tissue resection achieving millimeter accuracy. The tumor resection procedure is decomposed to the subtask level for a more direct understanding and automation. A 4-DOF suction system is developed, and integrated with a 6-DOF electrocautery robot to perform resection experiments. A novel near-infrared fluorescent marker is manually dispensed on cadaver samples to define a pseudotumor, and intraoperatively tracked using a dual-camera system. The autonomous dual-robot resection cooperation workflow is proposed and evaluated in this study. The integrated system achieves autonomous localization of the pseudotumor by tracking the near-infrared marker, and performs supervised autonomous resection in cadaver porcine tongues (N=3). The three pseudotumors were successfully removed from porcine samples. The evaluated average surface and depth resection errors are 1.19 and 1.83mm, respectively. This work is an essential step towards autonomous tumor resections.

Indexed as

autonomous surgeryelectrosurgeryimage-guided surgerysurgical roboticstumor resection

Identifiers

PMID38533465
PMCPMC10965307
OpenAlexW4200467713

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.