{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T08:24:06Z","timestamp":1777105446235,"version":"3.51.4"},"reference-count":39,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T00:00:00Z","timestamp":1755648000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2026,1]]},"abstract":"ABSTRACT<\/jats:title>\n \n Background<\/jats:title>\n Atypical 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.<\/jats:p>\n <\/jats:sec>\n \n Purpose<\/jats:title>\n To evaluate the diagnostic performance with tumor habitats, apparent diffusion coefficient (ADC), and edema index (EI) to distinguish atypical GBM from PCNSL.<\/jats:p>\n <\/jats:sec>\n \n Study Type<\/jats:title>\n Retrospective.<\/jats:p>\n <\/jats:sec>\n \n Population<\/jats:title>\n One hundred twenty\u2010five patients (63 male and 62 female) diagnosed with atypical GBM or PCNSL were included.<\/jats:p>\n <\/jats:sec>\n \n Field Strength\/Sequence<\/jats:title>\n 1.5\u2009T and 3.0\u2009T, Axial ADC and T1 contrast\u2010enhanced spin\u2010echo inversion recovery sequence (T1\u2010CE).<\/jats:p>\n <\/jats:sec>\n \n Assessment<\/jats:title>\n The tumor habitat was derived using T1\u2010CE and ADC sequences. Based on this tumor habitat, EI and relative ADC (rADC), we constructed a model.<\/jats:p>\n <\/jats:sec>\n \n Statistical Tests<\/jats:title>\n Logistic regression; Akaike Information Criterion; Receiver operating characteristic (ROC) curves, calibration curves, and Decision Curve Analysis.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Three tumor habitats were identified: high\u2010enhancement cellular habitat (Habitat 1), low\u2010enhancement cellular habitat (Habitat 2), and nonviable tissue habitat (Habitat 3). The voxel fraction of the three tumor habitats in atypical\n GBM<\/jats:styled-content>\n and\n PCNSL<\/jats:styled-content>\n groups shows statistically significant differences. The\n EI<\/jats:styled-content>\n of patients in the\n PCNSL<\/jats:styled-content>\n group was significantly higher than that of the patients in atypical\n GBM<\/jats:styled-content>\n . A model was established incorporating the parameters Habitat 2, Habitat 3,\n EI<\/jats:styled-content>\n , and\n rADCmean<\/jats:styled-content>\n . The model exhibits excellent discriminative ability in the training set (\n AUC<\/jats:styled-content>\n \u2009=\u20090.851, 95%\n CI<\/jats:styled-content>\n : 0.781\u20130.921) and validation set (\n AUC<\/jats:styled-content>\n \u2009=\u20090.807, 95%\n CI<\/jats:styled-content>\n : 0.724\u20130.889). Histopathological evaluation showed that vasculogenic mimicry (\n VM<\/jats:styled-content>\n ) levels were significantly higher in the\n PCNSL<\/jats:styled-content>\n group. Multiple linear regression analysis showed a significant correlation between habitat voxel fraction and\n VM<\/jats:styled-content>\n levels.\n <\/jats:p>\n <\/jats:sec>\n \n Data Conclusion<\/jats:title>\n A 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.<\/jats:p>\n <\/jats:sec>\n \n Level of Evidence<\/jats:title>\n 5.<\/jats:p>\n <\/jats:sec>\n \n Technical Efficacy Stage<\/jats:title>\n 3.<\/jats:p>\n <\/jats:sec>","DOI":"10.1002\/jmri.70080","type":"journal-article","created":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T09:09:26Z","timestamp":1755680966000},"page":"142-154","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Tumor Habitats Based on Multiparametric\n MRI<\/scp>\n Distinguish Atypical Glioblastoma From Primary Central Nervous System Lymphoma: Imaging\u2010Pathologic Correlation"],"prefix":"10.1002","volume":"63","author":[{"given":"Meng\u2010nan","family":"Sun","sequence":"first","affiliation":[{"name":"Medical Imaging Center The First Affiliated Hospital of Jinan University Guangzhou 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