Tasks for artificial intelligence in prostate MRI.

Artificial Intelligence Humans Magnetic Resonance Imaging / methods Male Prospective Studies Prostate / diagnostic imaging Prostatic Neoplasms / diagnostic imaging
Artificial intelligence Deep learning Machine learning Magnetic resonance imaging Prostatic neoplasms

Journal

European radiology experimental
ISSN: 2509-9280
Titre abrégé: Eur Radiol Exp
Pays: England
ID NLM: 101721752

Informations de publication

Date de publication:
31 07 2022
Historique:
received: 02 02 2022
accepted: 18 05 2022
entrez: 30 7 2022
pubmed: 31 7 2022
medline: 3 8 2022
Statut: epublish

Résumé

The advent of precision medicine, increasing clinical needs, and imaging availability among many other factors in the prostate cancer diagnostic pathway has engendered the utilization of artificial intelligence (AI). AI carries a vast number of potential applications in every step of the prostate cancer diagnostic pathway from classifying/improving prostate multiparametric magnetic resonance image quality, prostate segmentation, anatomically segmenting cancer suspicious foci, detecting and differentiating clinically insignificant cancers from clinically significant cancers on a voxel-level, and classifying entire lesions into Prostate Imaging Reporting and Data System categories/Gleason scores. Multiple studies in all these areas have shown many promising results approximating accuracies of radiologists. Despite this flourishing research, more prospective multicenter studies are needed to uncover the full impact and utility of AI on improving radiologist performance and clinical management of prostate cancer. In this narrative review, we aim to introduce emerging medical imaging AI paper quality metrics such as the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) and Field-Weighted Citation Impact (FWCI), dive into some of the top AI models for segmentation, detection, and classification.

Identifiants

DOI: 10.1186/s41747-022-00287-9 PMID: 35908102 PMC: PMC9339059
pubmed: 35908102
doi: 10.1186/s41747-022-00287-9
pii: 10.1186/s41747-022-00287-9
pmc: PMC9339059
doi:

Types de publication

Journal Article Review Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

33

Informations de copyright

© 2022. The Author(s) under exclusive licence to European Society of Radiology.

Références

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Auteurs

Mason J Belue (MJ)

Molecular Imaging Branch, National Cancer Institute, National Institutes of Health Bethesda, 10 Center Dr., MSC 1182, Building 10, Room B3B85, Bethesda, MD, 20892-1088, USA.

Baris Turkbey (B)

Molecular Imaging Branch, National Cancer Institute, National Institutes of Health Bethesda, 10 Center Dr., MSC 1182, Building 10, Room B3B85, Bethesda, MD, 20892-1088, USA. turkbeyi@mail.nih.gov.

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Classifications MeSH

questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Algorithmes › Intelligence artificielle › Tasks for artificial intelligence in prostate MRI.
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Tasks for artificial intelligence in prostate MRI.
questionsmedicales.fr › Diagnostic › Techniques et procédures diagnostiques › Imagerie diagnostique › Tomographie › Imagerie par résonance magnétique › Tasks for artificial intelligence in prostate MRI.
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études de cohortes › Études prospectives › Tasks for artificial intelligence in prostate MRI.
questionsmedicales.fr › Tissus › Glandes exocrines › Prostate › Tasks for artificial intelligence in prostate MRI.
questionsmedicales.fr › Maladies urogénitales › Tumeurs de l'appareil urogénital › Tumeurs de l'appareil génital mâle › Tumeurs de la prostate › Tasks for artificial intelligence in prostate MRI.