Evidence map›Paper›PMID 31256360›Full record

ArticleInternational journal of computer assisted radiology and surgery2019

Video-based computer navigation in knee arthroscopy for patient-specific ACL reconstruction.

Carolina Raposo, João P Barreto, Cristóvão Sousa, Luis Ribeiro, Rui Melo, João Pedro Oliveira, Pedro Marques, Fernando Fonseca, David Barrett

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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
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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

9 authors.

Carolina RaposoInstitute of Systems and Robotics, University of Coimbra, Coimbra, Portugal. carolina.raposo@perceive3d.com.ORCID http://orcid.org/0000-0002-2884-5000
João P BarretoInstitute of Systems and Robotics, University of Coimbra, Coimbra, Portugal.
Cristóvão SousaPerceive3D, Coimbra, Portugal.
Luis RibeiroPerceive3D, Coimbra, Portugal.
Rui MeloPerceive3D, Coimbra, Portugal.
João Pedro OliveiraFaculty of Medicine, Coimbra Hospital and Universitary Centre, Coimbra, Portugal.
Pedro MarquesFaculty of Medicine, Coimbra Hospital and Universitary Centre, Coimbra, Portugal.
Fernando FonsecaFaculty of Medicine, Coimbra Hospital and Universitary Centre, Coimbra, Portugal.
David BarrettBioengineering Science Research Group, School of Engineering Sciences, University of Southampton, Southampton, UK.

Funding

Fundação para a Ciência e a Tecnologi PTDC/EEIAUT/3024/2014Horizon 2020 766850
6 · The paper itself

Abstract

purposeThe anterior cruciate ligament tear is a common medical condition that is treated using arthroscopy by pulling a tissue graft through a tunnel opened with a drill. The correct anatomical position and orientation of this tunnel are crucial for knee stability, and drilling an adequate bone tunnel is the most technically challenging part of the procedure. This paper presents the first guidance system based solely on intra-operative video for guiding the drilling of the tunnel.

methodsOur solution uses small, easily recognizable visual markers that are attached to the bone and tools for estimating their relative pose. A recent registration algorithm is employed for aligning a pre-operative image of the patient's anatomy with a set of contours reconstructed by touching the bone surface with an instrumented tool.

resultsExperimental validation using ex-vivo data shows that the method enables the accurate registration of the pre-operative model with the bone, providing useful information for guiding the surgeon during the medical procedure. Experiments also demonstrate that the guided drilling of the tunnel leads to errors as low as 2.5 mm in the footprint and [Formula: see text] in orientation, which compares favourably to other works in the field.

conclusionThe high accuracy and short time overhead evinced by the experimental validation combined with no additional incisions or capital equipment make this video-based computer-aided arthroscopy solution an appealing alternative to the existing approaches.

Indexed as

Video RecordingAlgorithmsAnterior Cruciate LigamentAnterior Cruciate Ligament InjuriesAnterior Cruciate Ligament ReconstructionArthroscopyCalibrationFemurHumansImaging, Three-DimensionalKneeKnee JointLigamentsSoftwareSurgery, Computer-AssistedTibia3D registrationArthroscopyComputer guidanceVisual tracking

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.