Evidence map›Paper›PMID 37058232›Full record

ArticleInternational journal of computer assisted radiology and surgery2023

A semi-automated robotic system for percutaneous interventions.

Marius Siegfarth, Raffael Lutz, Nils-Christian Iseke, Javier Moviglia, Fabian Sadi, Jan Stallkamp

Abstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2023. 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
–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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Marius SiegfarthMannheim Institute for Intelligent Systems in Medicine, Heidelberg University, Mannheim, Germany. marius.siegfarth@medma.uni-heidelberg.de.ORCID http://orcid.org/0000-0002-2736-3683
Raffael LutzMannheim Institute for Intelligent Systems in Medicine, Heidelberg University, Mannheim, Germany.ORCID http://orcid.org/0000-0002-6477-8941
Nils-Christian IsekeMannheim Institute for Intelligent Systems in Medicine, Heidelberg University, Mannheim, Germany.ORCID http://orcid.org/0000-0002-6242-5122
Javier MovigliaMannheim Institute for Intelligent Systems in Medicine, Heidelberg University, Mannheim, Germany.ORCID http://orcid.org/0000-0002-3939-5893
Fabian SadiMannheim Institute for Intelligent Systems in Medicine, Heidelberg University, Mannheim, Germany.ORCID http://orcid.org/0000-0001-7052-844X
Jan StallkampMannheim Institute for Intelligent Systems in Medicine, Heidelberg University, Mannheim, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeA robotic assistive device is developed for needle-based percutaneous interventions. The aim is a hybrid system using both manual and actuated robotic operation in order to obtain a device that has a large workspace but can still fit in the gantry opening of a CT scanner. This will enable physicians to perform precise and time-efficient CT-guided percutaneous interventions. The concept of the mechanics and software of the device is presented in this work.

methodsThe approach is a semi-automated robotic assistive device, which combines manual and robotic positioning to reduce the number and size of necessary motors. The system consists of a manual rough positioning unit, a robotic fine positioning unit and an optical needle tracking unit. The resulting system has eight degrees of freedom, of which four are manual, which comprise encoders to monitor the position of each axis. The remaining four axes are actuated axes for fine positioning of the needle. Cameras are attached to the mechanical structure for 3D tracking of the needle pose. The software is based on open-source software, mainly ROS2 as robotic middleware, Moveit2 for trajectory calculation and 3D Slicer for needle path planning.

resultsThe communication between the components was successfully tested with a clinical CT scanner. In a first experiment, four needle insertions were planned and the deviation of the actual needle path from the planned path was measured. The mean deviation from the needle path to the target point was 21.9 mm, which is mainly caused both by translational deviation (15.4 mm) and angular deviation (6.8°) of the needle holder. The optical tracking system was able to detect the needle position with a mean deviation of 3.9 mm.

conclusionThe first validation of the system was successful which proves that the proposed concept for both the hardware and software is feasible. In a next step, an automatic position correction based on the optical tracking system will be integrated, which is expected to significantly improve the system accuracy.

Indexed as

RoboticsRobotic Surgical ProceduresHumansNeedlesPhantoms, ImagingSoftwareTomography, X-Ray ComputedCT robotInterventional radiologyMedical roboticsPercutaneous intervention

Identifiers

PMID37058232
PMCPMC10491544

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LicenceCC BY
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Registered trials

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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.