Nomogram incorporating preoperative MRI-VASARI features for differentiating intracranial extraventricular ependymoma from glioblastoma.

Background: Intracranial extraventricular ependymoma (IEE) and glioblastoma (GBM) may have similar imaging findings but different prognosis. This study aimed to develop and validate a nomogram based on magnetic resonance imaging (MRI) Visually AcceSAble Rembrandt Images (VASARI) features for preoperatively differentiating IEE from GBM. Methods: The clinical data and the MRI-VASARI features of patients with confirmed IEE (n=114) and confirmed GBM (n=258) in a multicenter cohort were retrospectively analyzed. Predictive models for differentiating IEE from GBM were built using a multivariate logistic regression method. A nomogram was generated and the performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Results: The predictors identified in this study consisted of six VASARI features and four clinical features. Compared with the individual models, the combined model incorporating clinical and VASARI features had the highest area under the curve (AUC) value [training set: 0.99, 95% confidence interval (CI): 0.98-1.00; validation set: 0.97, 95% CI: 0.94-1.00] in comparison to the clinical model. The nomogram was well calibrated with significant clinical benefit according to the calibration curve and decision curve analyses. Conclusions: The nomogram combining clinical and MRI-VASARI characteristics was robust for differentiating IEE from GBM preoperatively and may potentially assist in diagnosis and treatment of brain tumors.

Magnetic resonance imaging findings of intracranial extraventricular ependymoma: A retrospective multi-center cohort study of 114 cases.

BACKGROUND: Intracranial extraventricular ependymoma (IEE) is an ependymoma located in the brain parenchyma outside the ventricles. IEE has overlapping clinical and imaging characteristics with glioblastoma multiforme (GBM) but different treatment strategy and prognosis. Therefore, an accurate preoperative diagnosis is necessary for optimizing therapy for IEE. METHODS: A retrospective multicenter cohort of IEE and GBM was identified. MR imaging characteristics assessed with the Visually Accessible Rembrandt Images (VASARI) feature set and clinicopathological findings were recorded. Independent predictors for IEE were identified using multivariate logistic regression, which was used to construct a diagnostic score for differentiating IEE from GBM. RESULTS: Compared to GBM, IEE tended to occur in younger patients. Multivariate logistic regression analysis identified seven independent predictors for IEE. Among them, 3 predictors including tumor necrosis rate (F7), age, and tumor-enhancing margin thickness (F11), demonstrated higher diagnostic performance with an Area Under Curve (AUC) of more than 70% in distinguishing IEE from GBM. The AUC was 0.85, 0.78, and 0.70, with sensitivity of 92.98%, 72.81%, and 96.49%, and specificity of 65.50%, 73.64%, and 43.41%, for F7, age, and F11, respectively. CONCLUSION: We identified specific MR imaging features such as tumor necrosis and thickness of enhancing tumor margins that could help to differentiate IEE from GBM. Our study results should be helpful to assist in diagnosis and clinical management of this rare brain tumor.

Skull angiosarcoma associated with a calcified chronic subdural hematoma.

Angiosarcoma is an uncommon, aggressive endothelial-cell tumor that usually affects the skin, and involvement of the skull is rare. Here, we describe a case of skull angiosarcoma associated with a calcified chronic subdural hematoma (CSDH). HIGHLIGHTSA very rare case of skull angiosarcoma associated with a calcified chronic subdural hematoma is presented.An asymptomatic subdural hematoma with an atypical history and radiological features should prompt further investigation.Contrast MRI images should to be obtained early to differentiate a subdural hematoma from other pathologies.

Intelligent Diagnosis and Analysis of Brain Lymphoma Based on DSC Imaging Features.

Currently, DSC has been extensively studied in the diagnosis, differential diagnosis, and prognosis evaluation of brain lymphoma, but it has not obtained a uniform standard. By combining DSC imaging features, this study investigated the imaging features and diagnostic value of several types of tumors such as primary brain lymphoma. At the same time, this study obtained data from brain lymphoma patients by data collection and set up different groups to conduct experimental studies to explore the correlation between IVIMMRI perfusion parameters and DSC perfusion parameters in brain lymphoma. Through experimental research, it can be seen that the combination of two perfusion imaging techniques can more fully reflect the blood flow properties of the lesion, which is beneficial to determine the nature of the lesion.

[The study of the correlation of middle meatus volume and maxillary fungal ball].

OBJECTIVE: Observing the anatomic variation and measuring the bone volume of meatus and nasal cavity by analyzing the expression of paranasal sinus CT. Searching whether these variation and volume data are related to maxillary fungal ball. METHOD: Measuring the double side bone volume of middle meatus,nasal cavity and the rate of middle meatus volume in the same side of nasal cavity respectively in the normal group, the maxillary fungal ball group. Observing the anatomic variation and statistically evaluating the anatomic variation and volume of nasal cavity and nasal meatus. RESULT: In the maxillary fungal ball group, the affected side and the contralateral side volume of middle meatus,nasal cavity and the rate of middle meatus volume in the nasal cavity had no statistical difference (P>0.05); Comparing the middle meatus volume and the rate of middle meatus of the maxillary fungus ball group affected side and normal group,there was statistical difference (P<0. 05). In the maxillary fungal ball group and the normal group, the morbidity of deviation septum were 24. 24% and 33. 33%, the morbidity of OMC variation were 30. 3% and 26. 67% (P<0.05), the morbidity of nasal anatomic variation were 54. 55% and 60.00%, there was no statistical difference (P>0.05). CONCLUSION: Maybe there is a correlation between the enlarged bone middle meatus and the maxillary fungal ball. There is no relationship between the nasal anatomic variation and the maxillary fungal ball.