Consensus recommendations for a dynamic susceptibility contrast MRI protocol for use in high-grade gliomas

JL Boxerman, CC Quarles, LS Hu, BJ Erickson… - Neuro …, 2020 - academic.oup.com
Despite the widespread clinical use of dynamic susceptibility contrast (DSC) MRI, DSC-MRI
methodology has not been standardized, hindering its utilization for response assessment in …

Advanced MR techniques for preoperative glioma characterization: Part 1

L Hirschler, N Sollmann… - Journal of Magnetic …, 2023 - Wiley Online Library
Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors
with dismal outcomes due to their infiltrative properties, still rely on conventional structural …

[HTML][HTML] High-grade glioma treatment response monitoring biomarkers: a position statement on the evidence supporting the use of advanced MRI techniques in the …

OM Henriksen, M del Mar Álvarez-Torres… - Frontiers in …, 2022 - frontiersin.org
Objective Summarize evidence for use of advanced MRI techniques as monitoring
biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods …

[HTML][HTML] Biologically-based mathematical modeling of tumor vasculature and angiogenesis via time-resolved imaging data

DA Hormuth, CM Phillips, C Wu, EABF Lima… - Cancers, 2021 - mdpi.com
Simple Summary The recruitment of new vasculature via angiogenesis is a critical
component of tumor development, which fundamentally influences tumor growth and …

[HTML][HTML] Magnetic resonance imaging of primary adult brain tumors: state of the art and future perspectives

M Martucci, R Russo, F Schimperna, G D'Apolito… - Biomedicines, 2023 - mdpi.com
MRI is undoubtedly the cornerstone of brain tumor imaging, playing a key role in all phases
of patient management, starting from diagnosis, through therapy planning, to treatment …

FDA-approved machine learning algorithms in neuroradiology: a systematic review of the current evidence for approval

AG Yearley, CMW Goedmakers, A Panahi… - Artificial Intelligence in …, 2023 - Elsevier
Over the past decade, machine learning (ML) and artificial intelligence (AI) have become
increasingly prevalent in the medical field. In the United States, the Food and Drug …

[HTML][HTML] Precise enhancement quantification in post-operative MRI as an indicator of residual tumor impact is associated with survival in patients with glioblastoma

A Garcia-Ruiz, P Naval-Baudin, M Ligero… - Scientific Reports, 2021 - nature.com
Glioblastoma is the most common primary brain tumor. Standard therapy consists of
maximum safe resection combined with adjuvant radiochemotherapy followed by …

MRI brain tumor medical images analysis using deep learning techniques: a systematic review

SAY Al-Galal, IFT Alshaikhli, MM Abdulrazzaq - Health and Technology, 2021 - Springer
The substantial progress of medical imaging technology in the last decade makes it
challenging for medical experts and radiologists to analyze and classify. Medical images …

[HTML][HTML] From research to clinical practice: a European neuroradiological survey on quantitative advanced MRI implementation

E Manfrini, M Smits, S Thust, S Geiger, Z Bendella… - European …, 2021 - Springer
Abstract Objective Quantitative MRI (qMRI) methods provide versatile neuroradiological
applications and are a hot topic in research. The degree of their clinical implementation is …

Moving toward a consensus DSC-MRI protocol: validation of a low–flip angle single-dose option as a reference standard for brain tumors

KM Schmainda, MA Prah, LS Hu… - American Journal …, 2019 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: DSC-MR imaging using preload, intermediate (60°) flip
angle and postprocessing leakage correction has gained traction as a standard …