Related Experiment Video
Updated: Feb 26, 2026
Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
Published on: September 13, 2022
Differentiating Primary Central Nervous System Lymphomas From Glioblastomas and Inflammatory Demyelinating
Jian-Bo Wen1, Wei-Yuan Huang, Wei-Xing-Zi Xu
1From the *Department of Radiology, Huashan Hospital, Fudan University, Shanghai; and Departments of †Radiology and ‡Radiotherapy, Hainan General Hospital, Hainan, China.
The relative minimum apparent diffusion coefficient (rADCmin) effectively differentiates primary central nervous system lymphomas (PCNSLs) from glioblastomas (GBMs) and inflammatory demyelinating pseudotumors (IDPs). This diffusion-weighted imaging metric aids in diagnosing brain tumors and can supplement conventional MRI findings.
Area of Science:
- Neuroradiology
- Oncology
- Medical Imaging
Background:
- Differentiating primary central nervous system lymphomas (PCNSLs) from other brain lesions like glioblastomas (GBMs) and inflammatory demyelinating pseudotumors (IDPs) is crucial for accurate diagnosis and treatment.
- Diffusion-weighted imaging (DWI) offers valuable insights into tissue microstructure, potentially aiding in lesion characterization.
Purpose of the Study:
- To assess the diagnostic performance of the relative minimum apparent diffusion coefficient (rADCmin) derived from DWI in distinguishing PCNSLs from GBMs and IDPs.
- To determine the efficacy of rADCmin as a quantitative imaging biomarker in neuro-oncology.
Main Methods:
- Retrospective analysis of MRI scans from 82 patients (39 PCNSLs, 35 GBMs, 8 IDPs).
- Calculation of rADCmin by normalizing the minimum apparent diffusion coefficient (ADCmin) of the lesion to that of normal white matter.
- Comparison of rADCmin values using ANOVA and evaluation of diagnostic performance via receiver operating characteristic (ROC) curve analysis.
Main Results:
- PCNSLs exhibited significantly lower rADCmin values (0.675 ± 0.113) compared to GBMs (0.765 ± 0.059) and IDPs (0.834 ± 0.067).
- rADCmin demonstrated significant diagnostic capability in differentiating PCNSLs from non-PCNSL lesions (P < 0.001).
- The optimal cutoff value for rADCmin was 0.722, yielding a sensitivity of 74.5% and specificity of 74.1% (AUC = 0.803). A strong negative correlation was found between rADCmin and tumor cellularity (r = -0.755).
Conclusions:
- The rADCmin value is a valuable tool for differentiating PCNSL from GBM and IDP.
- ADC values, particularly rADCmin, can serve as a useful adjunct to conventional contrast-enhanced MRI.
- These findings suggest that DWI metrics can assist in improving diagnostic accuracy and informing treatment planning for CNS tumors.
