Artificial Intelligence Applied to Pancreatic Imaging: A Narrative Review.
CT
MRI
PET
artificial intelligence
pancreatic imaging
radiomics
Journal
Healthcare (Basel, Switzerland)
ISSN: 2227-9032
Titre abrégé: Healthcare (Basel)
Pays: Switzerland
ID NLM: 101666525
Informations de publication
Date de publication:
11 Aug 2022
11 Aug 2022
Historique:
received:
20
06
2022
revised:
31
07
2022
accepted:
08
08
2022
entrez:
26
8
2022
pubmed:
27
8
2022
medline:
27
8
2022
Statut:
epublish
Résumé
The diagnosis, evaluation, and treatment planning of pancreatic pathologies usually require the combined use of different imaging modalities, mainly, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). Artificial intelligence (AI) has the potential to transform the clinical practice of medical imaging and has been applied to various radiological techniques for different purposes, such as segmentation, lesion detection, characterization, risk stratification, or prediction of response to treatments. The aim of the present narrative review is to assess the available literature on the role of AI applied to pancreatic imaging. Up to now, the use of computer-aided diagnosis (CAD) and radiomics in pancreatic imaging has proven to be useful for both non-oncological and oncological purposes and represents a promising tool for personalized approaches to patients. Although great developments have occurred in recent years, it is important to address the obstacles that still need to be overcome before these technologies can be implemented into our clinical routine, mainly considering the heterogeneity among studies.
Identifiants
pubmed: 36011168
pii: healthcare10081511
doi: 10.3390/healthcare10081511
pmc: PMC9408381
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
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