Pattern of brain abnormalities on magnetic resonance imaging in adults with epilepsy at Muhimbili National Hospital

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dc.contributor.author Atieno, R.O.
dc.date.accessioned 2021-11-10T10:05:10Z
dc.date.available 2021-11-10T10:05:10Z
dc.date.issued 2019
dc.identifier.citation Atieno,R.O. (2019). Pattern of brain abnormalities on magnetic resonance imaging in adults with epilepsy at Muhimbili National Hospital, Dar es salaam:Muhimbili University of Health and Allied Sciences en_US
dc.identifier.uri http://dspace.muhas.ac.tz:8080/xmlui/handle/123456789/2762
dc.description.abstract Background Epilepsy is a neurological disorder that presents with episodic seizures, some of which are amenable to treatment. Patients with Epilepsy have been reported to have underlying brain structural abnormalities, though little is known on magnitude and extent of these abnormalities in patients with epilepsy at our settings. The current study aimed at establishing neuroimaging findings in epilepsy that may be used to predict disease severity, prognosis and management outcome. Objective To determine the pattern of brain abnormalities on Magnetic Resonance Imaging (MRI) in adult patients with epilepsy referred to MRI unit at Muhimbili National Hospital (MNH). Materials and methods This was a prospective, cross-sectional, hospital-based study where 65 adult patients with epilepsy aged 18 years and above were consecutively enrolled after obtaining a written consent. The study was conducted for six months at Radiology and Imaging Department, MNH. Demographic and clinical information were obtained by interviewing patients and use of patients’ medical records. Information was recorded using standardized questionnaires. Brain MRI was conducted in all patients on 1.5 Tesla scanner machine and reported by the Primary investigator and radiologist and final diagnosis was reached by consensus. Statistical analysis was done using Statistical package for Social Science (SPSS) version 23. Categorical and continuous variables were analyzed using two-tailed Chi-square test student t-test, and analysis of variance (ANOVA) respectively. A p value of less than 0.05 was considered statistically significant. Results Sixty-five adult patients with epilepsy were included in this study. Twenty-seven (41.5%) were male and thirty-eight (58.5%) females. The mean age was 36.4 years, the age ranged from 18 to 65 years. Thirty (46.2 %) had underlying brain structural abnormalities on MRI. The observed brain abnormalities included: brain atrophy (10.8%) brain infarction (9.2%), white matter disease (6.2%), tumors (4.6%), focal cortical dysplasia (4.6%), mesial vi temporal sclerosis (3.1%), atriovenous malformations (3.1%), intracerebral hemorrhage (3.1 %) and infection (1.5%). There was no relationship between age, sex and brain abnormalities on MRI. There was also no relationship between types and distribution of brain abnormalities on affected lobes. On Diffusion weighted; restriction was exhibited by infection, tumors, mesial temporal sclerosis, and brain infarction. Other types of lesions showed no restriction. Conclusion Underlying structural brain abnormalities are common in adult patients with epilepsy. The most common abnormalities are brain infarction and brain atrophy of the temporal and frontal lobes. Diffusion weighted Imaging could be useful in differentiating different types of brain abnormalities. Recommendations Brain MRI should be recommended to all adult patients with epilepsy, as some of the lesions are easily amenable to treatment. MRI is useful in differentiating types of abnormalities hence helps in making accurate and precise management. Studies using larger sample size should be carried out in order to have results that could be generalized to the community. en_US
dc.language.iso en en_US
dc.publisher Muhimbili University of Health and Allied Sciences en_US
dc.subject Radiology en_US
dc.subject adults with epilepsy en_US
dc.title Pattern of brain abnormalities on magnetic resonance imaging in adults with epilepsy at Muhimbili National Hospital en_US
dc.type Thesis en_US


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