Artificial Intelligence Imaging for Predicting High-risk Molecular Markers of Gliomas.
Clin Neuroradiol
; 34(1): 33-43, 2024 Mar.
Article
em En
| MEDLINE
| ID: mdl-38277059
ABSTRACT
Gliomas, the most prevalent primary malignant tumors of the central nervous system, present significant challenges in diagnosis and prognosis. The fifth edition of the World Health Organization Classification of Tumors of the Central Nervous System (WHO CNS5) published in 2021, has emphasized the role of high-risk molecular markers in gliomas. These markers are crucial for enhancing glioma grading and influencing survival and prognosis. Noninvasive prediction of these high-risk molecular markers is vital. Genetic testing after biopsy, the current standard for determining molecular type, is invasive and time-consuming. Magnetic resonance imaging (MRI) offers a non-invasive alternative, providing structural and functional insights into gliomas. Advanced MRI methods can potentially reflect the pathological characteristics associated with glioma molecular markers; however, they struggle to fully represent gliomas' high heterogeneity. Artificial intelligence (AI) imaging, capable of processing vast medical image datasets, can extract critical molecular information. AI imaging thus emerges as a noninvasive and efficient method for identifying high-risk molecular markers in gliomas, a recent focus of research. This review presents a comprehensive analysis of AI imaging's role in predicting glioma high-risk molecular markers, highlighting challenges and future directions.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Encefálicas
/
Glioma
Tipo de estudo:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Clin Neuroradiol
Assunto da revista:
NEUROLOGIA
/
RADIOLOGIA
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
China