Evidence map›Paper›PMID 40331235›Full record

ArticleIEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society2025

Safe Start Regions for Medical Steerable Needle Automation.

Janine Hoelscher, Inbar Fried, Spiros Tsalikis, Jason Akulian, Robert J Webster, Ron Alterovitz

Abstract read
In one paragraph

Article in IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Janine HoelscherDepartment of Bioengineering, Clemson University, Clemson, SC 29681, USA.
Inbar FriedDepartment of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Spiros TsalikisDepartment of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Jason AkulianDivision of Pulmonary Diseases and Critical Care Medicine at the University of North Carolina at Chapel Hill, NC 27599, USA.
Robert J WebsterDepartment of Mechanical Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Ron AlterovitzDepartment of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

Funding

Bronchoscopic Steerable Needles for Transparenchymal Access to Lung NodulesR01EB024864 · NIBIB · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ALTEROVITZ, RON · 2017 to 2021
$2.5M
Real-Time Bronchoscope Localization Using Machine Learning To Improve Lung Cancer DiagnosisF30CA265234 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI FRIED, INBAR · 2021 to 2025
$223k
NCI NIH HHS F30 CA265234NIBIB NIH HHS R01 EB024864
6 · The paper itself

Abstract

Steerable needles are minimally invasive devices that enable novel medical procedures by following curved paths to avoid critical anatomical obstacles. We introduce a new start pose robustness metric for steerable needle motion plans. A steerable needle deployment typically consists of a physician manually placing a steerable needle at a precomputed start pose on the surface of tissue and handing off control to a robot, which then autonomously steers the needle through the tissue to the target. The handoff between humans and robots is critical for procedure success, as even small deviations from a planned start pose change the steerable needle's reachable workspace. Our metric is based on a novel geometric method to efficiently compute how far the physician can deviate from the planned start pose in both position and orientation such that the steerable needle can still reach the target. We evaluate our metric through simulation in liver and lung scenarios. Our evaluation shows that our metric can be applied to plans computed by different steerable needle motion planners and that it can be used to efficiently select plans with large safe start regions.

Indexed as

Motion and Path PlanningNon-holonomic Motion PlanningSurgical Robotics: PlanningSurgical Robotics: Steerable Catheters/Needles

Identifiers

PMID40331235
PMCPMC12052366

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.