ArticleAJNR. American journal of neuroradiology2019
Morphologic Features on MR Imaging Classify Multifocal Glioblastomas in Different Prognostic Groups.
Article in AJNR. American journal of neuroradiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Non-invasive Prediction of Meningioma Tumor Grade by Quantification of Shape-based Radiomics Features and Surface Regularity.Clinical neuroradiology · 2026Article
- Different risk factors for multiple and unifocal gliomas: a comparative study of radiological, pathological and clinical characteristics.Frontiers in oncology · 2025Article
- Patterns of care and survival in patients with multifocal glioblastoma: A Danish cohort study.Neuro-oncology practice · 2024Article
- Artificial intelligence-based MRI radiomics and radiogenomics in glioma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Review
- RETROSPECTIVE EVALUATION OF MRI PATTERN OF GLIOBLASTOMA IN A TERTIARY HOSPITAL IN NIGERIA.Annals of Ibadan postgraduate medicine · 2023Article
- Review
- On the Prognosis of Multifocal Glioblastoma: An Evaluation Incorporating Volumetric MRI.Current oncology (Toronto, Ont.) · 2021Article
- Decoding and Systematization of Medical Imaging Features of Multiple Human Malignancies.Radiology. Imaging cancer · 2020Article
- Molecular characteristics and clinical features of multifocal glioblastoma.Journal of neuro-oncology · 2020Article
- Resection versus biopsy in the treatment of multifocal glioblastoma: a weighted survival analysis.Journal of neuro-oncology · 2020Article
- Prognostic factors affecting outcome of multifocal or multicentric glioblastoma: A scoping review.Journal of neurosciences in rural practiceArticle
Corrections and comments
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeMultifocal glioblastomas (ie, glioblastomas with multiple foci, unconnected in postcontrast pretreatment T1-weighted images) represent a challenge in clinical practice due to their poor prognosis. We wished to obtain imaging biomarkers with prognostic value that have not been found previously. MATERIALS AND
methodsA retrospective review of 1155 patients with glioblastomas from 10 local institutions during 2006-2017 provided 97 patients satisfying the inclusion criteria of the study and classified as having multifocal glioblastomas. Tumors were segmented and morphologic features were computed using different methodologies: 1) measured on the largest focus, 2) aggregating the different foci as a whole, and 3) recording the extreme value obtained for each focus. Kaplan-Meier, Cox proportional hazards, correlations, and Harrell concordance indices (c-indices) were used for the statistical analysis.
resultsAge (
conclusionsA prognostic model incorporating imaging findings on pretreatment postcontrast T1-weighted MRI classified patients with glioblastoma into different prognostic groups.
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