Advances in Abbreviated Breast MRI and Ultrafast Imaging.


Journal

Seminars in roentgenology
ISSN: 1558-4658
Titre abrégé: Semin Roentgenol
Pays: United States
ID NLM: 0053252

Informations de publication

Date de publication:
Apr 2022
Historique:
received: 13 12 2021
revised: 15 01 2022
accepted: 16 01 2022
entrez: 6 5 2022
pubmed: 7 5 2022
medline: 11 5 2022
Statut: ppublish

Résumé

Abbreviated breast MRI is an emerging technique that is being incorporated into clinical practice for breast cancer imaging and screening. Conventional breast MRI includes barriers such as high examination cost and lengthy examination times which make its use in the screening setting challenging. Abbreviated MRI aims to address these pitfalls by reducing overall examination time and increasing accessibility to MRI while preserving diagnostic accuracy. Sequences selected for abbreviated MRI protocols allow for preserved accuracy in breast cancer detection and characterization. Novel techniques such as ultrafast imaging are being used to provide kinetic information from early post-contrast imaging.

Identifiants

pubmed: 35523528
pii: S0037-198X(22)00004-9
doi: 10.1053/j.ro.2022.01.004
pii:
doi:

Substances chimiques

Contrast Media 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

145-148

Informations de copyright

Published by Elsevier Inc.

Auteurs

Shalin Patel (S)

Department of Radiology, New York University Grossman School of Medicine, New York, NY. Electronic address: shalin.patel2@nyulangone.org.

Laura Heacock (L)

Department of Radiology, New York University Grossman School of Medicine, New York, NY.

Yiming Gao (Y)

Department of Radiology, New York University Grossman School of Medicine, New York, NY.

Kristin Elias (K)

Greenwich Radiology Group, Greenwich, CT.

Linda Moy (L)

Department of Radiology, New York University Grossman School of Medicine, New York, NY.

Samantha Heller (S)

Department of Radiology, New York University Grossman School of Medicine, New York, NY.

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Classifications MeSH