Radiomics and radiogenomics in gliomas: a contemporary update.
Journal
British journal of cancer
ISSN: 1532-1827
Titre abrégé: Br J Cancer
Pays: England
ID NLM: 0370635
Informations de publication
Date de publication:
08 2021
08 2021
Historique:
received:
28
11
2020
accepted:
31
03
2021
revised:
10
03
2021
pubmed:
8
5
2021
medline:
17
12
2021
entrez:
7
5
2021
Statut:
ppublish
Résumé
The natural history and treatment landscape of primary brain tumours are complicated by the varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low-grade lesions), as well as the dilemmas with identification of radiation necrosis, tumour progression, and pseudoprogression on MRI. Radiomics and radiogenomics promise to offer precise diagnosis, predict prognosis, and assess tumour response to modern chemotherapy/immunotherapy and radiation therapy. This is achieved by a triumvirate of morphological, textural, and functional signatures, derived from a high-throughput extraction of quantitative voxel-level MR image metrics. However, the lack of standardisation of acquisition parameters and inconsistent methodology between working groups have made validations unreliable, hence multi-centre studies involving heterogenous study populations are warranted. We elucidate novel radiomic and radiogenomic workflow concepts and state-of-the-art descriptors in sub-visual MR image processing, with relevant literature on applications of such machine learning techniques in glioma management.
Identifiants
pubmed: 33958734
doi: 10.1038/s41416-021-01387-w
pii: 10.1038/s41416-021-01387-w
pmc: PMC8405677
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
641-657Informations de copyright
© 2021. The Author(s).
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