Comparison of Peritumoral Edema on T2-Weighted MRI among Different Types of Intracranial Tumors
DOI:
https://doi.org/10.70749/ijbr.v4i5.3128Keywords:
Peritumoral Edema, Intracranial Tumors, T2-weighted MRI, Glioblastoma, Brain Metastasis, MRI BrainAbstract
Background: Peritumoral edema is a common imaging feature associated with intracranial tumors and significantly contributes to neurological morbidity and disease progression. T2-weighted Magnetic Resonance Imaging (MRI) is highly sensitive in detecting edema and plays a crucial role in differentiating tumor types based on edema characteristics. Objective: To compare peritumoral edema on T2-weighted MRI among different types of intracranial tumors and evaluate its association with tumor characteristics. Methodology: A cross-sectional analytical study was conducted on 104 patients for the duration of 4 months, from January 2026 to April 2026, diagnosed with intracranial tumors on MRI. Data variables included age, gender, tumor type, tumor size, tumor location, tumor surface characteristics, presence of hemorrhage, T2 signal intensity, neurological symptoms, edema volume, and edema-to-tumor ratio. Statistical analysis was performed using SPSS version 26. Independent sample t-test, one-way ANOVA, chi-square test, and Pearson correlation analysis were applied. A p-value ≤ 0.05 was considered statistically significant. Results: Among 104 patients, 60 (57.7%) had malignant tumors and 44 (42.3%) had benign tumors. The mean edema volume was significantly higher in malignant tumors compared to benign tumors (47.36 ± 12.40 ml vs. 25.38 ± 8.50 ml; p < 0.001). Similarly, the edema-to-tumor ratio was significantly greater in malignant tumors (2.03 ± 0.45) than in benign tumors (0.69 ± 0.25; p < 0.001). One-way ANOVA showed significant variation in edema volume among tumor types (F = 18.60, p < 0.001), with glioblastoma and metastatic tumors demonstrating the highest edema burden. Pearson correlation analysis revealed a strong positive correlation between tumor size and edema volume (r = 0.72, p < 0.001). Chi-square analysis showed a significant association between tumor type and T2 signal intensity (p < 0.001). Conclusion: Peritumoral edema is significantly more extensive in malignant intracranial tumors compared to benign tumors. T2-weighted MRI provides valuable diagnostic information regarding edema characteristics and may assist in differentiating tumor types and assessing tumor aggressiveness.
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References
1. Batchelor, T. T., Reardon, D. A., De Groot, J. F., Wick, W., & Weller, M. (2014). Antiangiogenic therapy for glioblastoma: Current status and future prospects. Clinical Cancer Research, 20(22), 5612-5619.
https://doi.org/10.1158/1078-0432.ccr-14-0834
2. Jain, R. K. (2003). Molecular regulation of vessel maturation. Nature Medicine, 9(6), 685-693.
https://doi.org/10.1038/nm0603-685
3. Weller, M., Van den Bent, M., Hopkins, K., Tonn, J. C., Stupp, R., Falini, A., Cohen-Jonathan-Moyal, E., Frappaz, D., Henriksson, R., Balana, C., Chinot, O., Ram, Z., Reifenberger, G., Soffietti, R., & Wick, W. (2014). EANO guideline for the diagnosis and treatment of anaplastic gliomas and glioblastoma. The Lancet Oncology, 15(9), e395-e403.
https://doi.org/10.1016/s1470-2045(14)70011-7
4. Louis, D. N., Perry, A., Reifenberger, G., Von Deimling, A., Figarella-Branger, D., Cavenee, W. K., Ohgaki, H., Wiestler, O. D., Kleihues, P., & Ellison, D. W. (2016). The 2016 World Health Organization classification of tumors of the central nervous system: A summary. Acta Neuropathologica, 131(6), 803-820.
https://doi.org/10.1007/s00401-016-1545-1
5. Ostrom, Q. T., Gittleman, H., Fulop, J., Liu, M., Blanda, R., Kromer, C., Wolinsky, Y., Kruchko, C., & Barnholtz-Sloan, J. S. (2015). CBTRUS statistical report: Primary brain and central nervous system tumors diagnosed in the United States in 2008-2012. Neuro-Oncology, 17(suppl 4), iv1-iv62.
https://doi.org/10.1093/neuonc/nov189
6. Sergentanis, T. N., Tsivgoulis, G., Perlepe, C., Ntanasis-Stathopoulos, I., Tzanninis, I., Sergentanis, I. N., & Psaltopoulou, T. (2015). Obesity and risk for brain/CNS tumors, gliomas and meningiomas: A meta-analysis. PLOS ONE, 10(9), e0136974.
https://doi.org/10.1371/journal.pone.0136974
7. National Cancer Institute. Adult central nervous system tumors treatment (PDQ®)–health professional version. Bethesda: NCI; 2020.
8. Wen, P. Y., & Kesari, S. (2008). Malignant gliomas in adults. New England Journal of Medicine, 359(5), 492-507.
https://doi.org/10.1056/nejmra0708126
9. Ferrara, N. (2004). Vascular endothelial growth factor: Basic science and clinical progress. Endocrine Reviews, 25(4), 581-611.
https://doi.org/10.1210/er.2003-0027
10. Osborn, A. G., Salzman, K. L., & Jhaveri, M. D. (2016). Inside front cover. Diagnostic Imaging: Brain, ix.
https://doi.org/10.1016/b978-0-323-37754-6.50006-3
11. Smirniotopoulos, J. G., Murphy, F. M., Rushing, E. J., Rees, J. H., & Schroeder, J. W. (2007). Patterns of contrast enhancement in the brain and meninges. RadioGraphics, 27(2), 525-551.
https://doi.org/10.1148/rg.272065155
12. Law, M., Yang, S., Wang, H., Babb, J. S., Johnson, G., Cha, S., ... & Zagzag, D. (2003). Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging. American journal of neuroradiology, 24(10), 1989-1998.
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