ArticleEuropean radiology2017
Glioblastoma: does the pre-treatment geometry matter? A postcontrast T1 MRI-based study.
Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Congress of neurological surgeons systematic review and evidence-based guidelines update on the role of emerging developments in the management of newly diagnosed glioblastoma.Journal of neuro-oncology · 2020Pooled it
- A three-dimensional computational analysis of magnetic resonance images characterizes the biological aggressiveness in malignant brain tumours.Journal of the Royal Society, Interface · 2018Trial
- Complementary prognostic value of hotspot-to-centroid distance (NHOCpeak) to SUVpeak in high-grade glioma.Annals of nuclear medicine · 2026Article
- Shape matters: unsupervised exploration of IDH-wildtype glioma imaging survival predictors.European radiology · 2025Article
- Nomogram of magnetic resonance imaging (MRI) histogram analysis to predict telomerase reverse transcriptase promoter mutation status in glioblastoma.Quantitative imaging in medicine and surgery · 2024Article
- A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data.Scientific data · 2023Article
- Radiomic and Volumetric Measurements as Clinical Trial Endpoints-A Comprehensive Review.Cancers · 2022Review
- Overall Survival Prediction of Glioma Patients With Multiregional Radiomics.Frontiers in neuroscience · 2022Article
- Evolutionary dynamics at the tumor edge reveal metabolic imaging biomarkers.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- A mesoscopic simulator to uncover heterogeneity and evolutionary dynamics in tumors.PLoS computational biology · 2021Article
- Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques.Cancer imaging : the official publication of the International Cancer Imaging Society · 2020Article
- Pretreatment inflammatory indices predict Bevacizumab response in recurrent Glioma.Cancer drug resistance (Alhambra, Calif.) · 2020Article
- Prognostic models based on imaging findings in glioblastoma: Human versus Machine.Scientific reports · 2019Article
- Morphological MRI-based features provide pretreatment survival prediction in glioblastoma.European radiology · 2019Observational
- Morphologic Features on MR Imaging Classify Multifocal Glioblastomas in Different Prognostic Groups.AJNR. American journal of neuroradiology · 2019Article
- Contrast enhancement predicting survival in integrated molecular subtypes of diffuse glioma: an observational cohort study.Journal of neuro-oncology · 2018Observational
- Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization.PloS one · 2017Article
- Non-standard radiotherapy fractionations delay the time to malignant transformation of low-grade gliomas.PloS one · 2017Article
- Preoperative albumin-to-globulin ratio and prognostic nutrition index predict prognosis for glioblastoma.OncoTargets and therapy · 2017Article
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29 authors.
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Abstract
backgroundThe potential of a tumour's volumetric measures obtained from pretreatment MRI sequences of glioblastoma (GBM) patients as predictors of clinical outcome has been controversial. Mathematical models of GBM growth have suggested a relation between a tumour's geometry and its aggressiveness.
methodsA multicenter retrospective clinical study was designed to study volumetric and geometrical measures on pretreatment postcontrast T1 MRIs of 117 GBM patients. Clinical variables were collected, tumours segmented, and measures computed including: contrast enhancing (CE), necrotic, and total volumes; maximal tumour diameter; equivalent spherical CE width and several geometric measures of the CE "rim". The significance of the measures was studied using proportional hazards analysis and Kaplan-Meier curves.
resultsKaplan-Meier and univariate Cox survival analysis showed that total volume [p = 0.034, Hazard ratio (HR) = 1.574], CE volume (p = 0.017, HR = 1.659), spherical rim width (p = 0.007, HR = 1.749), and geometric heterogeneity (p = 0.015, HR = 1.646) were significant parameters in terms of overall survival (OS). Multivariable Cox analysis for OS provided the later two parameters as age-adjusted predictors of OS (p = 0.043, HR = 1.536 and p = 0.032, HR = 1.570, respectively).
conclusionPatients with tumours having small geometric heterogeneity and/or spherical rim widths had significantly better prognosis. These novel imaging biomarkers have a strong individual and combined prognostic value for GBM patients. KEY POINTS: • Three-dimensional segmentation on magnetic resonance images allows the study of geometric measures. • Patients with small width of contrast enhancing areas have better prognosis. • The irregularity of contrast enhancing areas predicts survival in glioblastoma patients.
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