Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging

AAK Abdel Razek, A Alksas, M Shehata… - Insights into …, 2021 - Springer
This article is a comprehensive review of the basic background, technique, and clinical
applications of artificial intelligence (AI) and radiomics in the field of neuro-oncology. A …

Meningioma MRI radiomics and machine learning: systematic review, quality score assessment, and meta-analysis

L Ugga, T Perillo, R Cuocolo, A Stanzione, V Romeo… - Neuroradiology, 2021 - Springer
Purpose To systematically review and evaluate the methodological quality of studies using
radiomics for diagnostic and predictive purposes in patients with intracranial meningioma …

An artificial intelligence framework integrating longitudinal electronic health records with real-world data enables continuous pan-cancer prognostication

O Morin, M Vallières, S Braunstein, JB Ginart… - Nature Cancer, 2021 - nature.com
Despite widespread adoption of electronic health records (EHRs), most hospitals are not
ready to implement data science research in the clinical pipelines. Here, we develop …

Detection of diagnostic and prognostic methylation-based signatures in liquid biopsy specimens from patients with meningiomas

GA Herrgott, JM Snyder, R She, TM Malta… - Nature …, 2023 - nature.com
Recurrence of meningiomas is unpredictable by current invasive methods based on
surgically removed specimens. Identification of patients likely to recur using noninvasive …

Multiplatform genomic profiling and magnetic resonance imaging identify mechanisms underlying intratumor heterogeneity in meningioma

ST Magill, HN Vasudevan, K Seo… - Nature …, 2020 - nature.com
Meningiomas are the most common primary intracranial tumors, but the molecular drivers of
meningioma tumorigenesis are poorly understood. We hypothesized that investigating …

Artificial intelligence in brain tumour surgery—an emerging paradigm

S Williams, H Layard Horsfall, JP Funnell… - Cancers, 2021 - mdpi.com
Simple Summary Artificial intelligence (AI) is the branch of computer science that enables
machines to learn, reason, and problem solve. In recent decades, AI has been developed …

Radiotherapy for meningiomas

WC Chen, HK Perlow, A Choudhury, MP Nguyen… - Journal of neuro …, 2022 - Springer
Meningiomas are the most common primary central nervous system neoplasm. Despite
promising recent progress in elucidating the genomic landscape and underlying biology of …

A spotlight on the role of radiomics and machine-learning applications in the management of intracranial meningiomas: a new perspective in neuro-oncology: a review

L Brunasso, G Ferini, L Bonosi, R Costanzo, S Musso… - Life, 2022 - mdpi.com
Background: In recent decades, the application of machine learning technologies to medical
imaging has opened up new perspectives in neuro-oncology, in the so-called radiomics …

A clinical semantic and radiomics nomogram for predicting brain invasion in WHO grade II meningioma based on tumor and tumor-to-brain interface features

N Li, Y Mo, C Huang, K Han, M He, X Wang… - Frontiers in …, 2021 - frontiersin.org
Background Brain invasion in meningioma has independent associations with increased
risks of tumor progression, lesion recurrence, and poor prognosis. Therefore, this study …

Machine learning using multiparametric magnetic resonance imaging radiomic feature analysis to predict Ki-67 in World Health Organization grade I meningiomas

O Khanna, AF Kazerooni, CJ Farrell… - …, 2021 - journals.lww.com
BACKGROUND Although World Health Organization (WHO) grade I meningiomas are
considered “benign” tumors, an elevated Ki-67 is one crucial factor that has been shown to …