Abstract
Background/Aim: The differential diagnosis of solitary brain tumors poses challenges for clinicians and radiologists, often leading to invasive biopsy procedures. Therefore, this study aimed to evaluate the variations in edema volume and diffusion characteristics between the tumor core and peritumoral zone in cases of glioblastoma, brain metastasis, and central nervous system lymphoma. The aim was to identify additional parameters for conventional magnetic resonance imaging (MRI) that could aid in the differential diagnosis.
Methods: A total of 39 patients (13 with central nervous system lymphoma, 13 with glioblastoma, and 13 with brain metastases) were included in this retrospective cohort study. Apparent diffusion coefficient (ADC) values were calculated from the ADC maps obtained from Brain MRI for both the lesion and peritumoral region. Additionally, the largest diameter of the vasogenic edema-mass complex was measured using T2 sequences. In the contrast-enhanced series, the largest diameter of the metastatic lesion was measured. The edema-mass ratio was determined by dividing the diameter of the edema-mass complex by the diameter of the mass.
Results: There was a statistically significant difference in the edema-mass ratio among the tumor types (P=0.008). Further analysis using Bonferroni correction revealed that this difference was primarily due to glioblastoma. Compared to patients with lymphoma and brain metastases, lesions diagnosed as glioblastoma exhibited a lower edema-mass ratio. Additionally, a statistically significant difference was observed in the ADC value measured from the lesion according to the tumor type (P=0.017). It was determined that lesions associated with central nervous system lymphoma had lower ADC values than those with glioblastoma.
Conclusion: Including lesional and perilesional ADC values obtained through diffusion-weighted examination and edema mass ratio measurements may enhance the accuracy of differential diagnosis. Utilizing these imaging characteristics in a multiparametric approach, as suggested by this research, can improve the accuracy of diagnosing malignant cancers, thereby enabling better patient management and treatment decisions.