Radiomics for precision medicine in glioblastoma

K Aftab, FB Aamir, S Mallick, F Mubarak… - Journal of neuro …, 2022 - Springer
Introduction Being the most common primary brain tumor, glioblastoma presents as an
extremely challenging malignancy to treat with dismal outcomes despite treatment. Varying …

The peritumoral brain zone in glioblastoma: where we are and where we are going

M Giambra, A Di Cristofori, S Valtorta… - Journal of …, 2023 - Wiley Online Library
Glioblastoma (GBM) is the most aggressive and invasive primary brain tumor. Current
therapies are not curative, and patients' outcomes remain poor with an overall survival of …

High-grade glioma treatment response monitoring biomarkers: a position statement on the evidence supporting the use of advanced MRI techniques in the clinic, and …

TC Booth, EC Wiegers, EAH Warnert… - Frontiers in …, 2022 - frontiersin.org
Objective To summarize evidence for use of advanced MRI techniques as monitoring
biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods …

Structural connectome quantifies tumour invasion and predicts survival in glioblastoma patients

Y Wei, C Li, Z Cui, RC Mayrand, J Zou, ALKC Wong… - Brain, 2023 - academic.oup.com
Glioblastoma is characterized by diffuse infiltration into the surrounding tissue along white
matter tracts. Identifying the invisible tumour invasion beyond focal lesion promises more …

A Systematic Review on Recent Advancements in Deep Learning and Mathematical Modeling for Efficient Detection of Glioblastoma

M Salman, PK Das, SK Mohanty - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In medical facilities, the glioblastoma detection and growth patterns are critical yet
challenging tasks. It is important for early diagnosis and therapy planning to save lives …

Radiomics-based neural network predicts recurrence patterns in glioblastoma using dynamic susceptibility contrast-enhanced MRI

KY Shim, SW Chung, JH Jeong, I Hwang, CK Park… - Scientific reports, 2021 - nature.com
Glioblastoma remains the most devastating brain tumor despite optimal treatment, because
of the high rate of recurrence. Distant recurrence has distinct genomic alterations compared …

The role of computational methods for automating and improving clinical target volume definition

J Unkelbach, T Bortfeld, CE Cardenas… - Radiotherapy and …, 2020 - Elsevier
Abstract Treatment planning in radiotherapy distinguishes three target volume concepts: the
gross tumor volume (GTV), the clinical target volume (CTV), and the planning target volume …

Discrimination between glioblastoma and solitary brain metastasis using conventional MRI and diffusion-weighted imaging based on a deep learning algorithm

Q Yan, F Li, Y Cui, Y Wang, X Wang, W Jia, X Liu… - Journal of Digital …, 2023 - Springer
This study aims to develop and validate a deep learning (DL) model to differentiate
glioblastoma from single brain metastasis (BM) using conventional MRI combined with …

Quantitative mapping of individual voxels in the peritumoral region of IDH-wildtype glioblastoma to distinguish between tumor infiltration and edema

A Dasgupta, B Geraghty, PJ Maralani, N Malik… - Journal of Neuro …, 2021 - Springer
Purpose The peritumoral region (PTR) in glioblastoma (GBM) represents a combination of
infiltrative tumor and vasogenic edema, which are indistinguishable on magnetic resonance …

Artificial intelligence-based locoregional markers of brain peritumoral microenvironment

Z Riahi Samani, D Parker, H Akbari, RL Wolf, S Brem… - Scientific Reports, 2023 - nature.com
In malignant primary brain tumors, cancer cells infiltrate into the peritumoral brain structures
which results in inevitable recurrence. Quantitative assessment of infiltrative heterogeneity in …