Lateral ventricles of brain: a morphometric study by computerized tomography

Author: 
Maheen Nazir, Bashir Ahmad Shah, Rabiya Amin and BasitAslam

Background: Understanding the normal and abnormal anatomy of the lateral ventricular system of brain is helpful for clinicians, neurosurgeons, and radiologists in day-to-day clinical practice1.The two major changes that may occur in elderly individual without neurologic deficits is enlargement of ventricles and cortical atrophy2. The lateral ventricular system of the brain undergoes changes with age and varies with gender3. Accurate assessment of lateral brain ventricular size is important for evaluating changes due to growth, ageing, intrinsic and extrinsic pathologies4. Present study was carried out with the objectives of determining Normal Lateral ventricular size based on age and sex on brain CT which may help in defining the normal range of lateral ventricles and diagnosis of disease.
Aims and Objectives: Lateral ventricular measurements were taken to establish baseline reference values, linear dimension and their relationship with age and sex on Computed Tomography so that it can help in day to day clinical practice and can rule out changes due to intrinsic and extrinsic pathologies.
Materials and Methods: This study was conducted in the Postgraduate Department of Anatomy in collaboration with the Department of Radiodiagnosis and Imaging of Government Medical College and Associated Hospitals, Srinagar for a period of 18 months, on patients presenting for CT brain. Total of 300 cases were studied. Data obtained from the study was analyzed and results were calculated.
Observations and Result: The left lateral ventricle was larger than the right one and both were larger in males and largest in sixth and seventh decade.
Conclusion:
The present study has defined the morphometric measurements of the brain ventricles which is not only of academic interest, but also important to help radiologists on the correct interpretation of image examinations and for clinicians to diagnose conditions like Alzheimer’s, schizophrenia, hydrocephalus and Parkinson’s disease.

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DOI: 
http://dx.doi.org/10.24327/ijcar.2020.23071.4562
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