Role of MR-CSF Flowmetry in Diagnosis and Differentiation of ventriculomegaly

Document Type : Original Article

Authors

1 Radiodiagnosis Department, Faculty of Medicine- Zagazig University, Egypt

2 Radio-diagnosis department /Faculty of medicine/Zagazig university

3 radiodiagnosis ,faculity of medicine ,zagazig university

4 Assistant Professor of Radiodiagnosis, Radiodiagnosis department, Faculty of medicine, Zagazig university, Zagazig, Egypt

Abstract

Background: Hydrocephalus is the buildup of fluid within the ventricular system of the brain due to disturbance of cerebrospinal fluid (CSF) formation, flow, or absorption. The excess CSF associated with hydrocephalus can cause a range of functional cerebral disorders. This study aims to assess the role of CSF flowmetry in the diagnosis and differentiation between different causes of ventriculomegaly.

Methods: This cross-sectional study was performed on 46 patients, 36 cases divided into four subgroups based on their clinical & MRI findings as follows: Normal pressure Hydrocephalus (NPH) group, aqueductal stenosis group, atrophic changes (related to aging) group, other neurological diseases group; subdivided into ventriculoperitoneal (VP) shunt, Chiari malformation type I, and evacodilatation (caused by brain tissue volume loss rather than intraventricular tumor) secondary to treated tumor. And final group consisted of 10 patients free from any medical disease or radiological finding and were considered the control group; all cases were subjected to complete history taking, clinical examination, MR, and CSF flowmetry examination.

Results: The best cutoff of SV in the diagnosis of atrophic neurological lesions versus NPH was ≤44.5 µL/cycle with the area under curve 0.923 with overall accuracy of 91.3% (p<0.001).

Conclusion: CSF flowmetry is a reliable, comprehensive technique for the localization of level of obstruction, differentiation between brain atrophic changes and NPH, evaluation of VP shunt function , shunt responsiveness, and objective follow-up of different neurological diseases due to its high predictive value by which we can evaluate clinical course prior to and after surgery

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