ArticleNeuroImage. Clinical2016
Population-based MRI atlases of spatial distribution are specific to patient and tumor characteristics in glioblastoma.
Article in NeuroImage. Clinical, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
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Who cites it
51 citing papers in PubMed.
- An MRI Atlas of Regional Brain Vulnerability to Metastatic Disease.medRxiv : the preprint server for health sciences · 2026Article
- CT Radiomics-Based Machine Learning Model for Predicting Capsular and Neural Invasion in Thyroid Carcinoma: Diagnostic Accuracy Study.JMIR medical informatics · 2026Article
- Data-driven probabilistic mapping of the spatial and molecular landscape of glioma.Brain communications · 2026Article
- Personalized chronotherapy in glioblastoma: integrating circadian profiling and PK-PD modelling to optimize temozolomide timing.NPJ precision oncology · 2025Article
- Impact of gliomas in different brain hemispheres on anxiety and the prognosis of neurosurgical patients.Scientific reports · 2025Article
- Sex-Based Differences in Outcomes for Glioblastoma Patients Treated with Hypofractionated Chemoradiotherapy.Cancers · 2025Article
- Cyclodextrin-Based Formulations as a Promising Strategy to Overcome the Blood-Brain Barrier: Historical Overview and Prospects in Glioblastoma Treatment.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Sex-Related Differences in Glioblastoma: A Single-Center Retrospective Cohort Study.Biomedicines · 2025Article
- Decoding Glioblastoma Heterogeneity: Neuroimaging Meets Machine Learning.Neurosurgery · 2025Review
- Machine learning-based prognostic subgrouping of glioblastoma: A multicenter study.Neuro-oncology · 2025Article
- Effects of different hemispheric gliomas on depression and prognosis in neurosurgery patients.Irish journal of medical science · 2025Article
- The radiogenomic and spatiogenomic landscapes of glioblastoma and their relationship to oncogenic drivers.Communications medicine · 2025Article
- Do clinical outcomes in individuals with malignant gliomas differ between sexes?Brain & spine · 2025Article
- Prognostic and predictive determinants in high-grade gliomas: integrating tumor-intrinsic biology with patient and system-level factors.Frontiers in neurology · 2025Review
- Sex-Specific Differences in Patients withAJNR. American journal of neuroradiology · 2024Article
- Spatial distribution patterns and factors influencing rural tourism destinations: An empirical study of China's agritainment resorts.PloS one · 2024Article
- Histopathologically confirmed radiation-induced damage of the brain - an in-depth analysis of radiation parameters and spatio-temporal occurrence.Radiation oncology (London, England) · 2023Article
- Article
- New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction.International journal of cancer · 2023Article
- SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry.Science advances · 2023Article
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9 authors.
Funding
Abstract
background and purposeIn treating glioblastoma (GB), surgical and chemotherapeutic treatment guidelines are, for the most part, independent of tumor location. In this work, we compiled imaging data from a large cohort of GB patients to create statistical atlases illustrating the disease spatial frequency as a function of patient demographics as well as tumor characteristics. MATERIALS AND
methodsTwo-hundred-six patients with pathology-proven glioblastoma were included. Of those, 65 had pathology-proven recurrence and 113 had molecular subtype and genetic information. We used validated software to segment the tumors in all patients and map them from patient space into a common template. We then created statistical maps that described the spatial location of tumors with respect to demographics and tumor characteristics. We applied a chi-square test to determine whether pattern differences were statistically significant.
resultsThe most frequent location for glioblastoma in our patient population is the right temporal lobe. There are statistically significant differences when comparing patterns using demographic data such as gender (p = 0.0006) and age (p = 0.006). Small and large tumors tend to occur in separate locations (p = 0.0007). The tumors tend to occur in different locations according to their molecular subtypes (p < 10(- 6)). The classical subtype tends to spare the frontal lobes, the neural subtype tend to involve the inferior right frontal lobe. Although the sample size is limited, there was a difference in location according to EGFR VIII genotype (p < 10(- 4)), with a right temporal dominance for EFGR VIII negative tumors, and frontal lobe dominance in EGFR VIII positive tumors.
conclusionsSpatial location of GB is an important factor that correlates with demographic factors and tumor characteristics, which should therefore be considered when evaluating a patient with GB and might assist in personalized treatment.
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