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Radiological and Clinical Findings of Multiple Cerebellar Liponeurocytoma: A Case Report.

ABSTRACT: Background: Cerebellar liponeurocytoma is an extremely rare benign tumor which generally occurs in cerebellum and is almost always solitary. Multifocal cerebellar liponeurocytoma is exceedingly rare, only 8 cases has been reported so far. Herein we present the 9th case of multifocal cerebellar liponeurocytoma in a 70-year-old woman with the complete clinical course and comprehensive imaging findings. Case Presentation: A 70-year-old woman presented with a history of intermittent headache for 5 years. Computed tomography (CT) and magnetic resonance imaging (MRI) of the brain have been performed and suggested a diagnosis of teratoma based on the imaging findings. After the surgical resection of the lesion, histopathological and immunohistochemical analyses revealed neuronal, glial, and lipomatous components and confirmed the diagnosis of multifocal cerebellar liponeurocytoma after surgical resection. During the 2-year follow-up period, the patient showed no signs of recurrence or metastasis. Conclusion: We described the radiological characteristics and clinical course of an exceedingly rare case of multifocal cerebellar liponeurocytoma in the cerebellar vermis and temporal lobe. The clear multifocality makes this case unusual.

SUBMITTER: Wang S

PROVIDER: S-EPMC8293275 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundChest X-ray offers high sensitivity and acceptable specificity as a tuberculosis screening tool, but in areas with a high burden of tuberculosis, there is often a lack of radiological expertise to interpret chest X-ray. Computer-aided detection systems based on artificial intelligence are therefore increasingly used to screen for tuberculosis-related abnormalities on digital chest radiographies. The CAD4TB software has previously been shown to demonstrate high sensitivity for chest X-ray tuberculosis-related abnormalities, but it is not yet calibrated for the detection of non-tuberculosis abnormalities. When screening for tuberculosis, users of computer-aided detection need to be aware that other chest pathologies are likely to be as prevalent as, or more prevalent than, active tuberculosis. However, non--tuberculosis chest X-ray abnormalities detected during chest X-ray screening for tuberculosis remain poorly characterized in the sub-Saharan African setting, with only minimal literature.Case presentationIn this case series, we report on four cases with non-tuberculosis abnormalities detected on CXR in TB TRIAGE + ACCURACY (ClinicalTrials.gov Identifier: NCT04666311), a study in adult presumptive tuberculosis cases at health facilities in Lesotho and South Africa to determine the diagnostic accuracy of two potential tuberculosis triage tests: computer-aided detection (CAD4TB v7, Delft, the Netherlands) and C-reactive protein (Alere Afinion, USA). The four Black African participants presented with the following chest X-ray abnormalities: a 59-year-old woman with pulmonary arteriovenous malformation, a 28-year-old man with pneumothorax, a 20-year-old man with massive bronchiectasis, and a 47-year-old woman with aspergilloma.ConclusionsSolely using chest X-ray computer-aided detection systems based on artificial intelligence as a tuberculosis screening strategy in sub-Saharan Africa comes with benefits, but also risks. Due to the limitation of CAD4TB for non-tuberculosis-abnormality identification, the computer-aided detection software may miss significant chest X-ray abnormalities that require treatment, as exemplified in our four cases. Increased data collection, characterization of non-tuberculosis anomalies and research on the implications of these diseases for individuals and health systems in sub-Saharan Africa is needed to help improve existing artificial intelligence software programs and their use in countries with high tuberculosis burden.

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Radiological and Clinical Findings of Multiple Cerebellar Liponeurocytoma: A Case Report.

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