Evidence map›Paper›PMID 42731106›Full record

ArticleThe international journal of medical robotics + computer assisted surgery : MRCAS2026

An Optical Tracking-Based Robot-Assisted System for Spinal Fixation Rod Bending.

Weijun Zhang, Yaohui Huang, Xingye Li, Changsheng Li, Xingguang Duan

Abstract read
In one paragraph

Article in The international journal of medical robotics + computer assisted surgery : MRCAS, 2026. 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

5 authors.

Weijun ZhangBeijing Institute of Technology, School of Medical Science and Engineering, Zhuhai, China.
Yaohui HuangBeijing Institute of Technology, Zhuhai, China.
Xingye LiBeijing Jishuitan Hospital, Capital Medical University, Zhuhai, China.ORCID https://orcid.org/0009-0001-2953-6330
Changsheng LiBeijing Institute of Technology, School of Medical Science and Engineering, Zhuhai, China.ORCID https://orcid.org/0000-0003-2469-4222
Xingguang DuanBeijing Institute of Technology, School of Medical Science and Engineering, Zhuhai, China.ORCID https://orcid.org/0000-0002-9640-4928

Funding

the Beijing Nova Program H020821500190
6 · The paper itself

Abstract

backgroundIn spinal pedicle screw-rod fixation, rod contouring quality influences insertion ease, construct stability, and corrective effect. Conventional bending relies on surgeon experience and is limited by insufficient support, repeated adjustment, and inefficient workflow.

methodsThis study developed a tracking-based robot-assisted system for rod bending comprising an acquisition unit, software, and actuator. The system acquires screw-head coordinates, generates target rod shape, and discretises the curve into bending positions, axial rotations, and angles.

resultsIn five in vitro experiments, five assisted-versus-manual comparisons, and twenty paired cases, planned rods showed high consistency with target curves, with mean angle, rotation, and length errors within acceptable ranges. Assisted bending improved efficiency and reduced placement errors versus manual bending; clinically, the assisted side had a shorter operation time.

conclusionsThe system achieves a workflow from acquisition to rod formation, improving quantifiability, consistency, efficiency, and conformity, thus providing a pathway towards automated spinal rod shaping.

Indexed as

Robotic Surgical ProceduresSpinal FusionSpineEquipment DesignHumansPedicle ScrewsRotationSoftwareSurgery, Computer-Assisteddigital planningoptical trackingpedicle screwrobot‐assisted spine surgeryrod bendingspinal fixation rod

Identifiers

PMID42731106
PMCPMC13570714

What OpenQuestion holds

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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.