ArticleBMC cancer2024
Prospective longitudinal analysis of imaging-based spatiotemporal tumor habitats in glioblastoma, IDH-wild type: implication in patient outcome using multiparametric physiologic MRI.
Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02613988 (Early Response Assessment Using on 3T Advanced MR Imaging as Predictor of Long-term Treatment Response in Newly Diagnosed Glioblastomas), which is not on this map. Cited by 4 papers.
What it found
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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.
Early Response Assessment Using on 3T Advanced MR Imaging as Predictor of Long-term Treatment Response in Newly Diagnosed Glioblastomas
Who cites it
4 citing papers in PubMed.
- Evaluating the Impact of Habitat Analysis via IVIM and DCE-MRI on Neoadjuvant Chemotherapy Outcomes in Osteosarcoma Patients: A Preliminary Study.Journal of imaging informatics in medicine · 2026Article
- Application of a MRI model based on tumor microenvironment habitat and peritumoral features in preoperative differentiation of rectal cancer T1-2/T3: a multicenter study.Frontiers in medicine · 2026Article
- Role of dynamic contrast-enhanced and dynamic susceptibility contrast imaging in evaluating the biological features of glioma.Quantitative imaging in medicine and surgery · 2025Article
- CT-Based Habitat Radiomics Combining Multi-Instance Learning for Early Prediction of Post-Neoadjuvant Lymph Node Metastasis in Esophageal Squamous Cell Carcinoma.Bioengineering (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundPhysiologic MRI-based tumor habitat analysis has the potential to predict patient outcomes by identifying the spatiotemporal habitats of glioblastoma. This study aims to prospectively validate the cut-off for tumor progression obtained from tumor habitat analysis based on physiologic MRI in ascertaining time-to-progression (TTP) and the site of progression in glioblastoma patients following concurrent chemoradiotherapy (CCRT).
methodsIn this prospective study (ClinicalTrials.gov ID: NCT02613988), we will recruit patients with IDH-wild type glioblastoma who underwent CCRT and obtained immediate post-operative and three serial post-CCRT MRI scans within a three-month interval, conducted using diffusion-weighted imaging and dynamic susceptibility contrast imaging. Voxels from cerebral blood volume and apparent diffusion coefficient maps will be grouped using k-means clustering into three spatial habitats (hypervascular cellular, hypovascular cellular, and nonviable tissue). The spatiotemporal habitats of the tumor will be evaluated by comparing changes in each habitat between the serial MRI scans (post-operative and post-CCRT #1, #2, and #3). Associations between spatiotemporal habitats and TTP will be analyzed using cox proportional hazard modeling. The site of progression will be matched with spatiotemporal habitats. DISCUSSION: The perfusion- and diffusion-derived tumor habitat in glioblastoma is expected to stratify TTP and may serve as an early predictor for tumor progression in patients with IDH wild-type glioblastoma.
trial registrationClinicalTrials.gov ID: NCT02613988.
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