ArticleJournal of magnetic resonance imaging : JMRI2026
Tumor Habitats Based on Multiparametric MRI Distinguish Atypical Glioblastoma From Primary Central Nervous System Lymphoma: Imaging-Pathologic Correlation.
Article in Journal of magnetic resonance imaging : JMRI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Improving MRI-based differentiation of brain metastasis, glioblastoma, and primary CNS lymphoma using deep learning.Neuroradiology · 2026Article
- Tumor Habitats Based on Multiparametric MRI Distinguish Atypical Glioblastoma From Primary Central Nervous System Lymphoma: Imaging-Pathologic Correlation.Journal of magnetic resonance imaging : JMRI · 2026Article
- Clinical value of habitat radiomics within the 2-cm edema zone surrounding the postoperative residual cavity in predicting glioma recurrence.Frontiers in oncology · 2026Article
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Authors and funding
13 authors.
Funding
Abstract
backgroundAtypical glioblastoma (GBM) (minimal or no necrosis on MRI) and primary central nervous system lymphoma (PCNSL) are difficult to distinguish on MRI; whether tumor habitat can more accurately distinguish atypical GBM from PCNSL remains uncertain. PURPOSE: To evaluate the diagnostic performance with tumor habitats, apparent diffusion coefficient (ADC), and edema index (EI) to distinguish atypical GBM from PCNSL. STUDY TYPE: Retrospective. POPULATION: One hundred twenty-five patients (63 male and 62 female) diagnosed with atypical GBM or PCNSL were included. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T, Axial ADC and T1 contrast-enhanced spin-echo inversion recovery sequence (T1-CE). ASSESSMENT: The tumor habitat was derived using T1-CE and ADC sequences. Based on this tumor habitat, EI and relative ADC (rADC), we constructed a model. STATISTICAL TESTS: Logistic regression; Akaike Information Criterion; Receiver operating characteristic (ROC) curves, calibration curves, and Decision Curve Analysis.
resultsThree tumor habitats were identified: high-enhancement cellular habitat (Habitat 1), low-enhancement cellular habitat (Habitat 2), and nonviable tissue habitat (Habitat 3). The voxel fraction of the three tumor habitats in atypical GBM and PCNSL groups shows statistically significant differences. The EI of patients in the PCNSL group was significantly higher than that of the patients in atypical GBM. A model was established incorporating the parameters Habitat 2, Habitat 3, EI, and rADCmean. The model exhibits excellent discriminative ability in the training set (AUC = 0.851, 95% CI: 0.781-0.921) and validation set (AUC = 0.807, 95% CI: 0.724-0.889). Histopathological evaluation showed that vasculogenic mimicry (VM) levels were significantly higher in the PCNSL group. Multiple linear regression analysis showed a significant correlation between habitat voxel fraction and VM levels. DATA
conclusionA model built based on tumor habitat, EI, and rADCmean can differentiate atypical GBM from PCNSL preoperatively. The differences in VM levels are one of the pathological mechanisms underlying the variations in tumor habitats between atypical GBM and PCNSL. LEVEL OF EVIDENCE: 5: TECHNICAL EFFICACY STAGE: 3.
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