Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs).
DOTA PET
NET
PET
machine learning
neuroendocrine tumor
nuclear medicine
radiomics
theragnostics
Journal
Life (Basel, Switzerland)
ISSN: 2075-1729
Titre abrégé: Life (Basel)
Pays: Switzerland
ID NLM: 101580444
Informations de publication
Date de publication:
28 Jul 2023
28 Jul 2023
Historique:
received:
08
06
2023
revised:
12
07
2023
accepted:
25
07
2023
medline:
26
8
2023
pubmed:
26
8
2023
entrez:
26
8
2023
Statut:
epublish
Résumé
Nuclear medicine has acquired a crucial role in the management of patients with neuroendocrine neoplasms (NENs) by improving the accuracy of diagnosis and staging as well as their risk stratification and personalized therapies, including radioligand therapies (RLT). Artificial intelligence (AI) and radiomics can enable physicians to further improve the overall efficiency and accuracy of the use of these tools in both diagnostic and therapeutic settings by improving the prediction of the tumor grade, differential diagnosis from other malignancies, assessment of tumor behavior and aggressiveness, and prediction of treatment response. This systematic review aims to describe the state-of-the-art AI and radiomics applications in the molecular imaging of NENs.
Identifiants
pubmed: 37629503
pii: life13081647
doi: 10.3390/life13081647
pmc: PMC10455722
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
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