Evidence map›Paper›PMID 32025619›Full record

ArticleEuropean journal of hybrid imaging2020

Competencies and training of radiographers and technologists for PET/MR imaging - a study from the UK MR-PET network.

Marius Ovidiu Mada, Paula Hindmarch, James Stirling, James Davies, David Brian, Anna Barnes, Alexander Hammers, Nick Gulliver, Karl Herholz, John O'Brien and 1 more

Abstract read
In one paragraph

Article in European journal of hybrid imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

11 authors.

Marius Ovidiu MadaUniversity of Cambridge, Wolfson Brain Imaging Centre, Box 65, Adrian Way, Cambridge, CB20QQ UK.ORCID 0000-0002-9903-3835
Paula Hindmarch2Positron Emission Tomography Centre, Newcastle University, Building 15, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 6BE UK.
James Stirling3King's College London, PET Centre, 1st Floor Lambeth Wing, St Thomas' Hospital, London, SE1 7EH UK.
James Davies4Invicro, Burlington Danes Building, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN UK.
David Brian5University of Edinburgh, Edinburgh Imaging Facility QMRI, Queens Medical Research Institute, 47 Little France Crescent, Edinburgh, EH16 4TJ UK.
Anna Barnes6UCL Hospitals NHS Foundation Trust, 235 Euston Road, London, NW1 2BU UK.
Alexander Hammers3King's College London, PET Centre, 1st Floor Lambeth Wing, St Thomas' Hospital, London, SE1 7EH UK.
Nick Gulliver7Department of Nuclear Medicine & PET-CT, King's College Hospital NHS Foundation Trust, Denmark Hill, London, SE5 9RS UK.
Karl Herholz8University of Manchester, Wolfson Molecular Imaging Centr, 27 Palantine Road, Manchester, M20 3LJ UK.
John O'Brien9University Department of Psychiatry, University of Cambridge, Cambridge Biomedical Campus, Box 189, Adrian Way, Cambridge, CB20QQ UK.
John-Paul TaylorNewcastle University, Institute of Neuroscience, Biomedical Research Building, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL UK.

Funding

Medical Research Council G0701127Medical Research Council MR/L023784/2Medical Research Council MR/M024873/1Medical Research Council MR/N013042/1Medical Research Council MR/N025792/1Wellcome Trust
6 · The paper itself

Abstract

backgroundAfter the success of PET/CT as a clinical diagnostic tool, the introduction of PET/MRI is a natural development aimed at further improving combined diagnostic imaging and reduced ionising radiation dose for half-body imaging. As with PET and CT, the combination of PET and MRI presents a series of issues that need to be addressed regarding workforce training and education. At present, there is a lack of agreement over the competencies, training requirements and educational pathways needed for PET/MRI operation. In the UK, following the establishment of the MR-PET imaging network, a task force was created to investigate the status of the workforce training, identify gaps and make recommendations regarding staff training. To do this, we ran a national survey on the status of the workforce training and the local practices across the UK's seven PET/MRI sites, reviewed the literature, and convened a panel of experts, to assess all the evidence and make recommendations regarding PET/MRI competencies and training of nuclear medicine technologists and radiographers.

resultsThere is limited literature available specifically on competencies and training for technologists and radiographers. The recommendations on the topic needed revisiting and adapting to the UK MR-PET network. The online survey confirmed the need for developing PET/MRI competencies and training pathways. Local organisational structures and practices were shared across the seven sites, based on models derived from experience outside the UK. The panel of experts agreed on the need for PET/MRI competencies and training strategies. Professional organisations started collaborative discussions with partners from both Nuclear Medicine and Radiography to set training priorities. Multidisciplinary collaboration and partnership were suggested as a key to a successful implementation of competencies and training.

conclusionsThe report identified the need for establishing competencies for the PET/MRI workforce, particularly for technologists and radiographers. It also helped defining these competencies as well as identifying the demand for bespoke training and the development of local and national courses to be implemented to fulfil this new training need.

Indexed as

CompetenciesHybrid imaging practitionerNuclear medicine technologistsPET/MRIRadiographersTraining

Identifiers

PMID32025619
PMCPMC6976550

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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.