Evidence map›Paper›PMID 38816649›Full record

ArticleInternational journal of computer assisted radiology and surgery2024

Beyond the manual touch: situational-aware force control for increased safety in robot-assisted skullbase surgery.

Hisashi Ishida, Deepa Galaiya, Nimesh Nagururu, Francis Creighton, Peter Kazanzides, Russell Taylor, Manish Sahu

Abstract read
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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. ENTRI: Enhanced Navigational Toolkit for Robotic Interventions.IEEE transactions on medical robotics and bionics · 2024
    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

7 authors.

Hisashi IshidaLCSR, Johns Hopkins University, Baltimore, USA.
Deepa GalaiyaLCSR, Johns Hopkins University, Baltimore, USA.
Nimesh NagururuDepartment of Otolaryngology, Johns Hopkins University, Baltimore, USA.
Francis CreightonLCSR, Johns Hopkins University, Baltimore, USA.
Peter KazanzidesLCSR, Johns Hopkins University, Baltimore, USA.
Russell TaylorLCSR, Johns Hopkins University, Baltimore, USA.
Manish SahuLCSR, Johns Hopkins University, Baltimore, USA. manish.sahu@jhu.edu.ORCID http://orcid.org/0000-0003-2158-823X

Funding

NRSA Training CoreTL1TR003100 · NCATS · JOHNS HOPKINS UNIVERSITY · PI SAHA, SOMNATH · 2019 to 2023
$4.5M
Cooperative Control Robotics and Computer Vision: Development of Semi-Autonomous Temporal Bone and Skull Base SurgeryK08DC019708 · NIDCD · JOHNS HOPKINS UNIVERSITY · PI CREIGHTON, FRANCIS XAVIER · 2021 to 2025
$959k
NCATS TL1 TR003100NIDCD NIH HHS DC019708NIDCD NIH HHS K08 DC019708
6 · The paper itself

Abstract

purposeSkullbase surgery demands exceptional precision when removing bone in the lateral skull base. Robotic assistance can alleviate the effect of human sensory-motor limitations. However, the stiffness and inertia of the robot can significantly impact the surgeon's perception and control of the tool-to-tissue interaction forces.

methodsWe present a situational-aware, force control technique aimed at regulating interaction forces during robot-assisted skullbase drilling. The contextual interaction information derived from the digital twin environment is used to enhance sensory perception and suppress undesired high forces.

resultsTo validate our approach, we conducted initial feasibility experiments involving a medical and two engineering students. The experiment focused on further drilling around critical structures following cortical mastoidectomy. The experiment results demonstrate that robotic assistance coupled with our proposed control scheme effectively limited undesired interaction forces when compared to robotic assistance without the proposed force control.

conclusionsThe proposed force control techniques show promise in significantly reducing undesired interaction forces during robot-assisted skullbase surgery. These findings contribute to the ongoing efforts to enhance surgical precision and safety in complex procedures involving the lateral skull base.

Indexed as

Robotic Surgical ProceduresSkull BaseFeasibility StudiesHumansMastoidectomyAdaptive force controlCooperative controlDigital twinForce feedbackSkullbase surgerySurgical roboticsTool–tissue interaction

Identifiers

PMID38816649

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.