Evidence map›Paper›PMID 35877018›Full record

ArticleInternational journal of computer assisted radiology and surgery2022

Organ-based estimation and minimization of clinician's X-ray dose.

Alexandre Krebs, Jean-Paul Mazellier, Juan Verde, Cindy Rolland, Julien Bert, Nicolas Padoy

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Article in International journal of computer assisted radiology and surgery, 2022. 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
0.3field-weighted citation impact, top 45% of its field
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, 2 citations in OpenAlex.

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 at 4 institutions in 1 country.

Alexandre KrebsICube, CNRS, University of Strasbourg, Strasbourg, France. alexandre.krebs@unistra.fr.
Jean-Paul MazellierICube, CNRS, University of Strasbourg, Strasbourg, France.
Juan VerdeIHU, Strasbourg, France.
Cindy RollandICube, CNRS, University of Strasbourg, Strasbourg, France.
Julien BertLaTIM, INSERM UMR1101, Univ Brest, Brest, France.
Nicolas PadoyICube, CNRS, University of Strasbourg, Strasbourg, France.
Université de Strasbourg · FRCentre National de la Recherche Scientifique · FRInstitut de Chirurgie Guidée par l'Image · FRLaboratoire de Traitement de l'Information Médicale · FR

Funding

Agence Nationale de la Recherche ANR-10-IAHU-02Agence Nationale de la Recherche ANR-19-CE45-0011
6 · The paper itself

Abstract

purposeHybrid surgeries, allowing real-time visualization of patient inner anatomy, are possible through the use of intraoperative X-ray imaging. However, the intensive use of X-rays can have undesired consequences for the clinicians or the patient in the operating room (OR).

methodsIn this paper, we provide a tool to visualize the X-rays and to optimally place protective shields in the hybrid operating room to reduce the clinician's dose according to their most sensitive body parts. We first acquire measurements in a hybrid operating room with dosimeters placed at different locations on a mannequin simulating a clinician. We demonstrate that a small displacement of a protective shield has significant consequences on the dose received by a clinician. Then, we reproduce the scene virtually and use Monte Carlo simulations to estimate the dose received by the clinician. Finally, we optimally place protective shields with a Nelder-Mead-based numerical optimization algorithm.

resultsThe results show a high sensitivity of the clinician's dose to protective shield placement. Numerical optimization of the shields' placement can help to reduce the dose and show a decrease between 79 and 89% of the exposition when comparing no external shield protection and our optimal external shield position.

conclusionOur work can help to raise awareness of the risks induced by X-rays during intraoperative surgery and reduce the dose received by the clinicians. In future work, our approach can be linked with human pose estimation algorithms to trace surgeons' moves, estimate dynamically the dose and summarize it in a surgical report, giving the dose for important organs.

Indexed as

X-RaysHumansMonte Carlo MethodPhantoms, ImagingRadiation DosageRadiographyDosimetryGradient-free optimizationMonte Carlo simulationRadiation protection

Identifiers

PMID35877018
OpenAlexW4287218202

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.