Artificial intelligence in oncologic imaging.
Journal
European journal of radiology open
ISSN: 2352-0477
Titre abrégé: Eur J Radiol Open
Pays: England
ID NLM: 101650225
Informations de publication
Date de publication:
2022
2022
Historique:
received:
15
07
2022
revised:
25
09
2022
accepted:
26
09
2022
entrez:
4
10
2022
pubmed:
5
10
2022
medline:
5
10
2022
Statut:
epublish
Résumé
Radiology is integral to cancer care. Compared to molecular assays, imaging has its advantages. Imaging as a noninvasive tool can assess the entirety of tumor unbiased by sampling error and is routinely acquired at multiple time points in oncological practice. Imaging data can be digitally post-processed for quantitative assessment. The ever-increasing application of Artificial intelligence (AI) to clinical imaging is challenging radiology to become a discipline with competence in data science, which plays an important role in modern oncology. Beyond streamlining certain clinical tasks, the power of AI lies in its ability to reveal previously undetected or even imperceptible radiographic patterns that may be difficult to ascertain by the human sensory system. Here, we provide a narrative review of the emerging AI applications relevant to the oncological imaging spectrum and elaborate on emerging paradigms and opportunities. We envision that these technical advances will change radiology in the coming years, leading to the optimization of imaging acquisition and discovery of clinically relevant biomarkers for cancer diagnosis, staging, and treatment monitoring. Together, they pave the road for future clinical translation in precision oncology.
Identifiants
pubmed: 36193451
doi: 10.1016/j.ejro.2022.100441
pii: S2352-0477(22)00048-X
pmc: PMC9525817
doi:
Types de publication
Journal Article
Langues
eng
Pagination
100441Subventions
Organisme : NCI NIH HHS
ID : P30 CA008748
Pays : United States
Informations de copyright
© 2022 The Authors. Published by Elsevier Ltd.
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