Evidence map›Paper›PMID 41152350›Full record

ArticleScientific reports2025

Feasibility of automatic screw planning via transformer-based shape completion from RGB-D imaging.

Aidana Massalimova, David Bauer, Nicola Cavalcanti, Fabio Carrillo, Farshad Mazda, Philipp Fuernstahl

Abstract read
In one paragraph

Article in Scientific reports, 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.

Aidana MassalimovaResearch in Orthopedic Computer Science (ROCS), University Hospital Balgrist, University of Zurich, 8008, Zurich, Switzerland. aidana.massalimova@balgrist.ch.
David BauerDepartment of Orthopedics, University Hospital Balgrist, 8008, Zurich, Switzerland.
Nicola CavalcantiResearch in Orthopedic Computer Science (ROCS), University Hospital Balgrist, University of Zurich, 8008, Zurich, Switzerland.
Fabio CarrilloResearch in Orthopedic Computer Science (ROCS), University Hospital Balgrist, University of Zurich, 8008, Zurich, Switzerland.
Farshad MazdaDepartment of Orthopedics, University Hospital Balgrist, 8008, Zurich, Switzerland.
Philipp FuernstahlResearch in Orthopedic Computer Science (ROCS), University Hospital Balgrist, University of Zurich, 8008, Zurich, Switzerland.

Funding

Horizon 2020 Framework Programme 101016985
6 · The paper itself

Abstract

Accurate pedicle screw placement (PSP) is essential in spinal fusion surgery. Conventional navigation relies on computed tomography (CT) or fluoroscopy, which involves ionizing radiation and requires an error-prone registration procedure. We propose a pipeline that enables PSP planning directly on vertebral point clouds reconstructed from intraoperative RGB-D scans, using the SurgPointTransformer network. The system detects screw entry and pedicle regions, estimates initial trajectories, and refines them via anatomically constrained optimization. We evaluated our method on nine ex-vivo cadaveric specimens, comparing RGB-D-based planning to a CT-based baseline using both RGB-D reconstructions and ground-truth CT meshes. No significant differences were found in entry-point offset (3.53 ± 1.30 mm vs. 3.90 ± 1.29 mm), pedicle-center offset (1.58 ± 0.58 mm vs. 1.68 ± 0.59 mm), trajectory-angle error (7.31 ± 3.34[Formula: see text] vs. 7.67 ± 3.59[Formula: see text]); all [Formula: see text]. Safety analysis using the Gertzbein-Robbins classification showed 100% radiologically optimal screw placement (grade A) with both methods. PSP planned from RGB-D reconstructions of the exposed dorsal surface alone achieved planning-level accuracy comparable to CT-based planning on the entire vertebral body. Prospective intraoperative validation is required to establish execution accuracy and clinical outcomes.

Indexed as

Imaging, Three-DimensionalPedicle ScrewsSpinal FusionSurgery, Computer-AssistedCadaverFeasibility StudiesFluoroscopyHumansTomography, X-Ray Computed

Identifiers

PMID41152350
PMCPMC12569008

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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.