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Updated: Feb 3, 2026
PET and MRI Guided Irradiation of a Glioblastoma Rat Model Using a Micro-irradiator
Published on: December 28, 2017
Differentiation between glioblastomas and brain metastases and regarding their primary site of malignancy using
K Askaner1, A Rydelius2, S Engelholm3
1Centre for Medical Imaging and Physiology, SUS, Malmoe, Sweden.
Background:
Differentiation between glioblastoma and brain metastasis may be challenging in conventional contrast-enhanced MRI.
Purpose:
To investigate if perfusion-weighted MRI is able to differentiate glioblastoma from metastasis and, as a second aim was to see if it was possible in the latter group, to predict the primary site of neoplasm.
Material And Methods:
Hundred and fourteen patients with newly discovered tumor lesion (76 metastases and 38 glioblastomas) underwent conventional contrast-enhanced MRI including dynamic susceptibility contrast perfusion sequence. The calculated relative cerebral blood volumes were analyzed in the solid tumor area, peritumoral area, area adjacent to peritumoral area, and normal appearing white matter in contralateral semioval center. The Student t-test was used to detect statistically significant differences in relative cerebral blood volume between glioblastomas and metastases in the aforementioned areas. Furthermore, the metastasis group was divided in four sub groups (lung-, breast-, melanoma-, and gastrointestinal origin) and using one-way ANOVA test. P-values < 0.05 were considered significant.
Results:
Relative cerebral blood volume (rCBV) in the peritumoral edema was significantly higher in glioblastomas than in metastases (mean 3.2 ± 1.4 and mean 0.9 ± 0.7), respectively, (P < 0.0001). No significant differences in the solid tumor area or the area adjacent to edema were found, (P = 0.28 and 0.21 respectively). There were no significant differences among metastases in the four groups.
Conclusion:
It is possible to differentiate glioblastomas from metastases by measuring the CBV in the peritumoral edema. It is not possible to differentiate between brain metastases from different primaries (lung-, breast-, melanoma or gastrointestinal) using CBV-measurements in the solid tumor area, peritumoral edema or area adjacent to edema.
Insights
Perfusion-weighted MRI can differentiate glioblastoma from brain metastasis by measuring relative cerebral blood volume in peritumoral edema. However, it cannot predict the primary site of metastasis based on this measurement.
Area of Science:
- Neuro-oncology
- Radiology
- Medical Imaging
Background:
- Distinguishing glioblastoma from brain metastasis using conventional MRI can be difficult.
- Advanced imaging techniques are needed for accurate differentiation.
Purpose of the Study:
- To evaluate perfusion-weighted MRI for differentiating glioblastoma from brain metastasis.
- To assess the potential of perfusion-weighted MRI in predicting the primary tumor site in cases of brain metastasis.
Main Methods:
- 114 patients with newly diagnosed brain tumors (38 glioblastomas, 76 metastases) underwent contrast-enhanced MRI with dynamic susceptibility contrast perfusion.
- Relative cerebral blood volume (rCBV) was analyzed in solid tumor, peritumoral edema, adjacent areas, and normal white matter.
- Statistical analysis included Student t-test and one-way ANOVA to compare rCBV values and identify significant differences (P < 0.05).
Main Results:
- Glioblastomas showed significantly higher rCBV in the peritumoral edema compared to metastases (mean 3.2 vs. 0.9, P < 0.0001).
- No significant differences in rCBV were found in the solid tumor area or the area adjacent to edema between glioblastomas and metastases.
- No significant differences in rCBV were observed among different primary tumor types (lung, breast, melanoma, gastrointestinal) within the metastasis group.
Conclusions:
- Perfusion-weighted MRI, specifically rCBV measurement in peritumoral edema, can effectively differentiate glioblastomas from brain metastases.
- Current perfusion-weighted MRI techniques using rCBV in the analyzed areas are insufficient to predict the primary origin of brain metastases.
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