ArticleAJNR. American journal of neuroradiology2022
Stable and Discriminatory Radiomic Features from the Tumor and Its Habitat Associated with Progression-Free Survival in Glioblastoma: A Multi-Institutional Study.
Article in AJNR. American journal of neuroradiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- AI for prognosis and treatment stratification in glioblastoma neurosurgery: a systematic review.Journal of neuro-oncology · 2026Pooled it
- Predicting early recurrence of craniopharyngioma using multi-omics radiomic modeling: a retrospective cohort study.Neurosurgical review · 2026Article
- Noncontrast CT-based habitat analysis for differentiating hemorrhagic transformation from contrast extravasation after endovascular therapy of acute ischemic stroke.European radiology experimental · 2026Article
- Multimodal MRI habitat atlas for personalised re-haemorrhage risk prediction in brainstem cavernous malformations.Stroke and vascular neurology · 2026Article
- MRI-Based DeltaHabitat Radiomic Model Predicts Pathological Complete Response in Oral Cavity Cancer Treated With Neoadjuvant Chemoimmunotherapy.Cancer medicine · 2026Article
- Development and Validation of an Explainable MRI-Based Habitat Radiomics Model for Predicting p53-Abnormal Endometrial Cancer: A Multicentre Feasibility Study.Journal of imaging informatics in medicine · 2026Article
- Habitat-Derived Radiomic Features of Planning Target Volume to Determine the Local Recurrence After Radiotherapy in Patients with Gliomas: A Feasibility Study.Journal of imaging informatics in medicine · 2026Article
- Predicting aggressiveness of clear cell renal cell carcinoma via mri using artificial intelligence: implications for surgical planning in a retrospective multicenter study.Scientific reports · 2026Article
- Variability Regularized Feature Selection (VaRFS) for optimal identification of robust and discriminable features from medical imaging.Npj imaging · 2026Article
- MRI-derived habitat heterogeneity for overall survival risk stratification in IDH-wildtype, CNS WHO grade 4 glioblastoma.Frontiers in cell and developmental biology · 2026Article
- MRI-based habitat radiomics analysis for predicting clinically significant prostate cancer: a retrospective dual-center study.Frontiers in oncology · 2026Article
- Combined peritumoral radiomics and clinical features predict 12-month progression free survival in glioblastoma.Journal of neuro-oncology · 2025Article
- Preoperative prediction of WHO/ISUP grade of ccRCC using intratumoral and peritumoral habitat imaging: multicenter study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- The clinical implications and interpretability of computational medical imaging (radiomics) in brain tumors.Insights into imaging · 2025Review
- Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- High-risk habitat radiomics model based on ultrasound images for predicting lateral neck lymph node metastasis in differentiated thyroid cancer.BMC medical imaging · 2025Article
- Enhancement of the nontumor component in newly diagnosed glioblastoma as a more accurate predictor of local recurrence location: a multicenter study.Quantitative imaging in medicine and surgery · 2025Article
- Multimodal MRI radiomics based on habitat subregions of the tumor microenvironment for predicting risk stratification in glioblastoma.PloS one · 2025Article
- Habitat Analysis in Tumor Imaging: Advancing Precision Medicine Through Radiomic Subregion Segmentation.Cancer management and research · 2025Review
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Corrections and comments
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Authors and funding
9 authors at 7 institutions in 2 countries.
Funding
Abstract
background and purposeGlioblastoma is an aggressive brain tumor, with no validated prognostic biomarkers for survival before surgical resection. Although recent approaches have demonstrated the prognostic ability of tumor habitat (constituting necrotic core, enhancing lesion, T2/FLAIR hyperintensity subcompartments) derived radiomic features for glioblastoma survival on treatment-naive MR imaging scans, radiomic features are known to be sensitive to MR imaging acquisitions across sites and scanners. In this study, we sought to identify the radiomic features that are both stable across sites and discriminatory of poor and improved progression-free survival in glioblastoma tumors. MATERIALS AND
methodsWe used 150 treatment-naive glioblastoma MR imaging scans (Gadolinium-T1w, T2w, FLAIR) obtained from 5 sites. For every tumor subcompartment (enhancing tumor, peritumoral FLAIR-hyperintensities, necrosis), a total of 316 three-dimensional radiomic features were extracted. The training cohort constituted studies from 4 sites (
resultsIncorporating the most stable and discriminatory features within a linear discriminant analysis classifier yielded areas under the curve of 0.71, 0.73, and 0.76 on the test set for distinguishing poor and improved survival compared with discriminatory features alone (areas under the curve of 0.65, 0.54, 0.62) from the necrotic core, enhancing tumor, and peritumoral T2/FLAIR hyperintensity, respectively.
conclusionsIncorporating stable and discriminatory radiomic features extracted from tumors and associated habitats across multisite MR imaging sequences may yield robust prognostic classifiers of patient survival in glioblastoma tumors.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.