Advances in neuro-oncology imaging

KJ Langen, N Galldiks, E Hattingen… - Nature Reviews …, 2017 - nature.com
Despite the fact that MRI has evolved to become the standard method for diagnosis and
monitoring of patients with brain tumours, conventional MRI sequences have two key …

Multimodality brain tumor imaging: MR imaging, PET, and PET/MR imaging

JR Fink, M Muzi, M Peck, KA Krohn - Journal of Nuclear Medicine, 2015 - Soc Nuclear Med
Standard MR imaging and CT are routinely used for anatomic diagnosis in brain tumors.
Pretherapy planning and posttreatment response assessments rely heavily on gadolinium …

T2–FLAIR mismatch, an imaging biomarker for IDH and 1p/19q status in lower-grade gliomas: a TCGA/TCIA project

SH Patel, LM Poisson, DJ Brat, Y Zhou, L Cooper… - Clinical cancer …, 2017 - AACR
Purpose: Lower-grade gliomas (WHO grade II/III) have been classified into clinically relevant
molecular subtypes based on IDH and 1p/19q mutation status. The purpose was to …

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

L Macyszyn, H Akbari, JM Pisapia, X Da… - Neuro …, 2015 - academic.oup.com
Background MRI characteristics of brain gliomas have been used to predict clinical outcome
and molecular tumor characteristics. However, previously reported imaging biomarkers have …

Glioblastoma multiforme: exploratory radiogenomic analysis by using quantitative image features

O Gevaert, LA Mitchell, AS Achrol, J Xu, S Echegaray… - Radiology, 2014 - pubs.rsna.org
Purpose To derive quantitative image features from magnetic resonance (MR) images that
characterize the radiographic phenotype of glioblastoma multiforme (GBM) lesions and to …

Multi-channel 3D deep feature learning for survival time prediction of brain tumor patients using multi-modal neuroimages

D Nie, J Lu, H Zhang, E Adeli, J Wang, Z Yu, LY Liu… - Scientific reports, 2019 - nature.com
High-grade gliomas are the most aggressive malignant brain tumors. Accurate pre-operative
prognosis for this cohort can lead to better treatment planning. Conventional survival …

Outcome prediction in patients with glioblastoma by using imaging, clinical, and genomic biomarkers: focus on the nonenhancing component of the tumor

R Jain, LM Poisson, D Gutman, L Scarpace, SN Hwang… - Radiology, 2014 - pubs.rsna.org
Purpose To correlate patient survival with morphologic imaging features and hemodynamic
parameters obtained from the nonenhancing region (NER) of glioblastoma (GBM), along …

Imaging of intratumoral heterogeneity in high-grade glioma

LS Hu, A Hawkins-Daarud, L Wang, J Li, KR Swanson - Cancer letters, 2020 - Elsevier
Abstract High-grade glioma (HGG), and particularly Glioblastoma (GBM), can exhibit
pronounced intratumoral heterogeneity that confounds clinical diagnosis and management …

Behind the numbers: decoding molecular phenotypes with radiogenomics—guiding principles and technical considerations

MD Kuo, N Jamshidi - Radiology, 2014 - pubs.rsna.org
Behind the Numbers: Decoding Molecular Phenotypes with Radiogenomics—Guiding Principles
and Technical Considerations | Radiology RSNA "skipMainNavigation" …

Clinical measures, radiomics, and genomics offer synergistic value in AI-based prediction of overall survival in patients with glioblastoma

A Fathi Kazerooni, S Saxena, E Toorens, D Tu… - Scientific Reports, 2022 - nature.com
Multi-omic data, ie, clinical measures, radiomic, and genetic data, capture multi-faceted
tumor characteristics, contributing to a comprehensive patient risk assessment. Here, we …