A rare tumor in the sellar region: ganglioglioma, a case report and a general overview.

BACKGROUND: Gangliogliomas are rare mixed neuronal-glial tumors of the central nervous system, accounting for less than 2% of intracranial tumors. CASE DESCRIPTION: This report presents a rare case of ganglioglioma in the sellar region of a 3-year-old and 5-month-old pediatric patient. The patient underwent surgical intervention initially through a transnasal transsphenoidal approach and subsequently through a transcranial pterional craniotomy approach. Subsequently, radiotherapy and chemotherapy were administered for residual tumor tissue. The purpose of this report is to highlight the presence of ganglioglioma as a distinct diagnosis in sellar region tumors, discuss the surgical, radiotherapy, and/or chemotherapy treatment options for sellar region gangliogliomas based on the literature, and contribute the patient's follow-up and treatment outcomes to the existing literature. CONCLUSION: Complete tumor resection may not be feasible in sellar region gangliogliomas, especially in pediatric cases, due to endocrinological and vision-related complications. In cases where complete resection is not possible, radiotherapy and/or chemotherapy may be considered. However, the optimal treatment approach has not yet been established, and further research is needed.

Predicting Isocitrate Dehydrogenase Mutation Status of Grade 2-4 Gliomas with Diffusion Tensor Imaging (DTI) Parameters Derived from Model-Based DTI and Model-Free Q-Sampling Imaging Reconstructions.

OBJECTIVE: To determine whether diffusion tensor imaging (DTI) parameters acquired with model-based DTI and model-free generalized Q-sampling imaging (GQI) reconstructions may noninvasively predict isocitrate dehydrogenase (IDH) mutational status in patients with grade 2-4 gliomas. METHODS: Forty patients with known IDH genotype (28 IDH wild-type; 12 IDH mutant) who underwent preoperative DTI evaluation on a 3-Tesla magnetic resonance imaging scanner were analyzed retrospectively. Absolute values obtained from model-based and model-free reconstructions were compared. Using the intraclass correlation coefficient, interobserver agreement was assessed for various sampling techniques. Variables having statistically significant distributions between IDH groups were subjected to a receiver operating characteristic (ROC) analysis. Using multivariable logistic regression analysis, independent predictors, if present, were identified and a model was developed. RESULTS: Six imaging parameters (3 from model-based DTI and 3 from model-free GQI reconstructions) showed statistically significant differences between groups (P < 0.001, power >0.97), with very high correlation to each other (P < 0.001). Age difference between the groups was statistically significant (P < 0.001). The optimal logistic regression model comprised a GQI-based parameter and age, which were independent predictors as well, producing an area under the ROC curve, accuracy, sensitivity, and specificity of 0.926, 85%, 75%, and 89.3%, respectively. Using the GQI reconstruction feature alone with a cut-off of 1.60, an 85% of accuracy was also achieved with ROC analysis. CONCLUSIONS: The imaging parameters acquired from model-based DTI and model-free GQI reconstructions, combined with the clinical variable age, may have the ability to noninvasively predict the IDH genotype in gliomas, either alone or in particular combinations.