A pragmatic evidence-based approach to post-mortem perinatal imaging.

Autopsy Diagnostic imaging Foetus Pregnancy loss Radiology

Journal

Insights into imaging
ISSN: 1869-4101
Titre abrégé: Insights Imaging
Pays: Germany
ID NLM: 101532453

Informations de publication

Date de publication:
15 Jul 2021
Historique:
received: 20 04 2021
accepted: 24 06 2021
entrez: 15 7 2021
pubmed: 16 7 2021
medline: 16 7 2021
Statut: epublish

Résumé

Post-mortem imaging has a high acceptance rate amongst parents and healthcare professionals as a non-invasive method for investigating perinatal deaths. Previously viewed as a 'niche' subspecialty, it is becoming increasingly requested, with general radiologists now more frequently asked to oversee and advise on appropriate imaging protocols. Much of the current literature to date has focussed on diagnostic accuracy and clinical experiences of individual centres and their imaging techniques (e.g. post-mortem CT, MRI, ultrasound and micro-CT), and pragmatic, evidence-based guidance for how to approach such referrals in real-world practice is lacking. In this review, we summarise the latest research and provide an approach and flowchart to aid decision-making for perinatal post-mortem imaging. We highlight key aspects of the maternal and antenatal history that radiologists should consider when protocolling studies (e.g. antenatal imaging findings and history), and emphasise important factors that could impact the diagnostic quality of post-mortem imaging examinations (e.g. post-mortem weight and time interval). Considerations regarding when ancillary post-mortem image-guided biopsy tests are beneficial are also addressed, and we provide key references for imaging protocols for a variety of cross-sectional imaging modalities.

Identifiants

pubmed: 34264420
doi: 10.1186/s13244-021-01042-1
pii: 10.1186/s13244-021-01042-1
pmc: PMC8282801
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

101

Subventions

Organisme : Medical Research Council
ID : MR/R002118/1
Pays : United Kingdom
Organisme : National Institute for Health Research
ID : NIHR-300099
Organisme : National Institute for Health Research
ID : ICA-CDRF-2017-03-53
Organisme : National Institute for Health Research
ID : NIHR-CDF-2017-10-037

Informations de copyright

© 2021. The Author(s).

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Auteurs

Susan C Shelmerdine (SC)

Great Ormond Street Hospital for Children NHS Foundation Trust, London, WC1N 3JH, UK. susan.shelmerdine@gosh.nhs.uk.
UCL Great Ormond Street Institute of Child Health, London, UK. susan.shelmerdine@gosh.nhs.uk.
Great Ormond Street Hospital NIHR Biomedical Research Centre, London, UK. susan.shelmerdine@gosh.nhs.uk.

J Ciaran Hutchinson (JC)

Great Ormond Street Hospital for Children NHS Foundation Trust, London, WC1N 3JH, UK.
UCL Great Ormond Street Institute of Child Health, London, UK.
Great Ormond Street Hospital NIHR Biomedical Research Centre, London, UK.

Celine Lewis (C)

Population, Policy and Practice Department, UCL GOS Institute of Child Health, London, UK.
North Thames Genomic Laboratory Hub, Great Ormond Street Hospital, London, UK.

Ian C Simcock (IC)

Great Ormond Street Hospital for Children NHS Foundation Trust, London, WC1N 3JH, UK.
UCL Great Ormond Street Institute of Child Health, London, UK.
Great Ormond Street Hospital NIHR Biomedical Research Centre, London, UK.

Thivya Sekar (T)

Great Ormond Street Hospital for Children NHS Foundation Trust, London, WC1N 3JH, UK.
UCL Great Ormond Street Institute of Child Health, London, UK.
Great Ormond Street Hospital NIHR Biomedical Research Centre, London, UK.

Neil J Sebire (NJ)

Great Ormond Street Hospital for Children NHS Foundation Trust, London, WC1N 3JH, UK.
UCL Great Ormond Street Institute of Child Health, London, UK.
Great Ormond Street Hospital NIHR Biomedical Research Centre, London, UK.

Owen J Arthurs (OJ)

Great Ormond Street Hospital for Children NHS Foundation Trust, London, WC1N 3JH, UK.
UCL Great Ormond Street Institute of Child Health, London, UK.
Great Ormond Street Hospital NIHR Biomedical Research Centre, London, UK.

Classifications MeSH