ArticleJournal of neuro-oncology2021
Quantitative mapping of individual voxels in the peritumoral region of IDH-wildtype glioblastoma to distinguish between tumor infiltration and edema.
Article in Journal of neuro-oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06492486 (Glioma Adaptive Radiotherapy With Development of an Artificial Intelligence Workflow), which is not on this map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Glioma Adaptive Radiotherapy With Development of an Artificial Intelligence Workflow
Who cites it
25 citing papers in PubMed.
- Prognostic impact of RANO resect group classification post-chemoradiotherapy in IDH-wildtype glioblastoma.Journal of neuro-oncology · 2026Article
- Grading of glioma and prediction of IDH mutation status via longitudinal relaxation time in rotating frame mapping on 5-T magnetic resonance imaging: added value to amide proton transfer-weighted imaging.Quantitative imaging in medicine and surgery · 2026Article
- Voxel-accurate MRI-microscopy Correlation Enables AI-powered Prediction of Brain Disease States.Theranostics · 2026Article
- Radiomic analysis of the peritumoral zone identifies imaging signatures of glioma invasion associated with HSP70 expression.Frontiers in oncology · 2026Article
- Radiomics-based quantification of tumor infiltration in the non-enhancing peritumoral region on postoperative MRI is associated with survival in glioblastoma.Scientific reports · 2025Article
- Surgical decision making in the era of supramarginal glioma resections: a current perspective and narrative review.CNS oncology · 2025Review
- Pilot research on predicting the sub-volume with high risk of tumor recurrence inside peritumoral edema using the ratio-maxiADC/meanADC from the advanced MRI.Discover oncology · 2025Article
- Clinical outcome and deep learning imaging characteristics of patients treated by radio-chemotherapy for a "molecular" glioblastoma.The oncologist · 2025Article
- Precision Surgery for Glioblastomas.Journal of personalized medicine · 2025Review
- Artificial intelligence uncertainty quantification in radiotherapy applications - A scoping review.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2024Article
- Deep Learning Segmentation of Infiltrative and Enhancing Cellular Tumor at Pre- and Posttreatment Multishell Diffusion MRI of Glioblastoma.Radiology. Artificial intelligence · 2024Article
- Artificial Intelligence Uncertainty Quantification in Radiotherapy Applications - A Scoping Review.medRxiv : the preprint server for health sciences · 2024Article
- Evolving concepts in margin strategies and adaptive radiotherapy for glioblastoma: A new future is on the horizon.Neuro-oncology · 2024Review
- Exploring the association of glioma tumor residuals from incongruent [European journal of nuclear medicine and molecular imaging · 2024Article
- Review
- Multimodality MRI Radiomics Based on Machine Learning for Identifying True Tumor Recurrence and Treatment-Related Effects in Patients with Postoperative Glioma.Neurology and therapy · 2023Article
- Classification of brain lesions using a machine learning approach with cross-sectional ADC value dynamics.Scientific reports · 2023Article
- Conventional and Advanced Magnetic Resonance Imaging Assessment of Non-Enhancing Peritumoral Area in Brain Tumor.Cancers · 2023Review
- Imaging-Based Patterns of Failure following Re-Irradiation for Recurrent/Progressive High-Grade Glioma.Journal of personalized medicine · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
purposeThe peritumoral region (PTR) in glioblastoma (GBM) represents a combination of infiltrative tumor and vasogenic edema, which are indistinguishable on magnetic resonance imaging (MRI). We developed a radiomic signature by using imaging data from low grade glioma (LGG) (marker of tumor) and PTR of brain metastasis (BM) (marker of edema) and applied it on the GBM PTR to generate probabilistic maps.
methods270 features were extracted from T1-weighted, T2-weighted, and apparent diffusion coefficient maps in over 3.5 million voxels of LGG (36 segments) and BM (45 segments) scanned in a 1.5T MRI. A support vector machine classifier was used to develop the radiomics model from approximately 50% voxels (downsampled to 10%) and validated with the remaining. The model was applied to over 575,000 voxels of the PTR of 10 patients with GBM to generate a quantitative map using Platt scaling (infiltrative tumor vs. edema).
resultsThe radiomics model had an accuracy of 0.92 and 0.79 in the training and test set, respectively (LGG vs. BM). When extrapolated on the GBM PTR, 9 of 10 patients had a higher percentage of voxels with a tumor-like signature over radiological recurrence areas. In 7 of 10 patients, the areas under curves (AUC) were > 0.50 confirming a positive correlation. Including all the voxels from the GBM patients, the infiltration signature had an AUC of 0.61 to predict recurrence.
conclusionA radiomic signature can demarcate areas of microscopic tumors from edema in the PTR of GBM, which correlates with areas of future recurrence.
Indexed as
Identifiers
33905055What OpenQuestion holds
Registered trials
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.