Radiomics and radiogenomics in gliomas: a contemporary update

G Singh, S Manjila, N Sakla, A True, AH Wardeh… - British journal of …, 2021 - nature.com
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 …

Advanced neuroimaging approaches to pediatric brain tumors

RM Nikam, X Yue, G Kaur, V Kandula, A Khair… - Cancers, 2022 - mdpi.com
Simple Summary After leukemias, brain tumors are the most common cancers in children,
and early, accurate diagnosis is critical to improve patient outcomes. Beyond the …

A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data

B Ocaña-Tienda, J Pérez-Beteta, JD Villanueva-García… - Scientific data, 2023 - nature.com
Brain metastasis (BM) is one of the main complications of many cancers, and the most
frequent malignancy of the central nervous system. Imaging studies of BMs are routinely …

The Nomogram of MRI‐based Radiomics with Complementary Visual Features by Machine Learning Improves Stratification of Glioblastoma Patients: A Multicenter …

Y Xu, X He, Y Li, P Pang, Z Shu… - Journal of Magnetic …, 2021 - Wiley Online Library
Background Glioblastomas (GBMs) represent both the most common and the most highly
malignant primary brain tumors. The subjective visual imaging features from MRI make it …

Pretreatment MR-based radiomics in patients with glioblastoma: A systematic review and meta-analysis of prognostic endpoints

Y Choi, J Jang, B Kim, KJ Ahn - European Journal of Radiology, 2023 - Elsevier
Purpose Recent studies have shown promise of MR-based radiomics in predicting the
survival of patients with untreated glioblastoma. This study aimed to comprehensively collate …

Radiomic and volumetric measurements as clinical trial Endpoints—a comprehensive review

IG Funingana, P Piyatissa, M Reinius, C McCague… - Cancers, 2022 - mdpi.com
Simple Summary The extraction of quantitative data from standard-of-care imaging
modalities offers opportunities to improve the relevance and salience of imaging biomarkers …

Prognostic models based on imaging findings in glioblastoma: Human versus Machine

D Molina-García, L Vera-Ramírez, J Pérez-Beteta… - Scientific Reports, 2019 - nature.com
Many studies have built machine-learning (ML)-based prognostic models for glioblastoma
(GBM) based on radiological features. We wished to compare the predictive performance of …

[HTML][HTML] Perioperative imaging predictors of tumor progression and pseudoprogression: a systematic review.

G Librizzi, G Lombardi, A Bertoldo, R Manara - Critical reviews in oncology …, 2024 - Elsevier
In high-grade gliomas, pseudoprogression after radiation treatment might dramatically
impact patient's management. We searched for perioperative imaging predictors of …

Morphologic features on MR imaging classify multifocal glioblastomas in different prognostic groups

J Pérez-Beteta, D Molina-García… - American Journal …, 2019 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: Multifocal glioblastomas (ie, glioblastomas with multiple
foci, unconnected in postcontrast pretreatment T1-weighted images) represent a challenge …

Correlations between DTI-derived metrics and MRS metabolites in tumour regions of glioblastoma: a pilot study

E Flores-Alvarez, EAR Piedra, GA Cruz-Priego… - Radiology and …, 2020 - sciendo.com
Conclusions. DTI and MRS biomarkers answer different questions; peritumoral oedema
represents the biggest challenge with at least ten significant correlations between DTI and …