Evidence map›Paper›PMID 35071009›Full record

ArticleFrontiers in oncology2021

Augmented Reality to Assist Skin Paddle Harvesting in Osteomyocutaneous Fibular Flap Reconstructive Surgery: A Pilot Evaluation on a 3D-Printed Leg Phantom.

Laura Cercenelli, Federico Babini, Giovanni Badiali, Salvatore Battaglia, Achille Tarsitano, Claudio Marchetti, Emanuela Marcelli

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PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
–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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Accuracy of augmented reality-assisted pedicle screw placement: a systematic review.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2024
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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

7 authors.

Laura CercenellieDIMES Lab - Laboratory of Bioengineering, Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
Federico BabinieDIMES Lab - Laboratory of Bioengineering, Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
Giovanni BadialiMaxillofacial Surgery Unit, Head and Neck Department, IRCCS Azienda Ospedaliera Universitaria di Bologna, Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Salvatore BattagliaMaxillofacial Surgery Unit, Policlinico San Marco University Hospital, University of Catania, Catania, Italy.
Achille TarsitanoMaxillofacial Surgery Unit, Head and Neck Department, IRCCS Azienda Ospedaliera Universitaria di Bologna, Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Claudio MarchettiMaxillofacial Surgery Unit, Head and Neck Department, IRCCS Azienda Ospedaliera Universitaria di Bologna, Department of Biomedical and Neuromotor Sciences, Alma Mater Studiorum University of Bologna, Bologna, Italy.
Emanuela MarcellieDIMES Lab - Laboratory of Bioengineering, Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAugmented Reality (AR) represents an evolution of navigation-assisted surgery, providing surgeons with a virtual aid contextually merged with the real surgical field. We recently reported a case series of AR-assisted fibular flap harvesting for mandibular reconstruction. However, the registration accuracy between the real and the virtual content needs to be systematically evaluated before widely promoting this tool in clinical practice. In this paper, after description of the AR based protocol implemented for both tablet and HoloLens 2 smart glasses, we evaluated in a first test session the achievable registration accuracy with the two display solutions, and in a second test session the success rate in executing the AR-guided skin paddle incision task on a 3D printed leg phantom.

methodsFrom a real computed tomography dataset, 3D virtual models of a human leg, including fibula, arteries and skin with planned paddle profile for harvesting, were obtained. All virtual models were imported into Unity software to develop a marker-less AR application suitable to be used both

resultsOn average, the marker-less AR protocol showed comparable registration errors (ranging within 1-5 mm) for tablet-based and HoloLens-based solution. Registration accuracy seems to be quite sensitive to ambient light conditions. We found a good success rate in completing the AR-guided task within an error margin of 4 mm (97% and 100% for tablet and HoloLens, respectively). All subjects reported greater usability and ergonomics for HoloLens 2 solution.

conclusionsResults revealed that the proposed marker-less AR based protocol may guarantee a registration error within 1-5 mm for assisting skin paddle harvesting in the clinical setting. Optimal lightening conditions and further improvement of marker-less tracking technologies have the potential to increase the efficiency and precision of this AR-assisted reconstructive surgery.

Indexed as

3D modeling3D printingaugmented realityHead and Neck CancerMicrosoft HoloLensreconstructive surgeryregistrationvirtual planning

Identifiers

PMID35071009
PMCPMC8770836

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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.