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Objective To determine diagnostic ability of brain magnetic resonance imaging (MRI) in detection of idiopathic intracranial hypertension (IIH). Method This descriptive observational study was conducted in radiology department from Jan. 2018 to Jan. 2021, evaluating MR imaging data of all adult patients (n=107) with clinical presentations of headaches. Patients with space occupying lesions, obstructive hydrocephalus and cerebral venous sinus thrombosis were excluded. Presence of all three brain MRI findings of (i) an empty sella (with or without sellar enlargement), (ii) tortuosity of optic nerves (with or without perioptic CSF prominence) and (iii) non-dilated (or slit-like) ventricles was considered positive for IIH. Imaging was reviewed by two neuroradiologists and consensus reporting was made. Findings of IIH were confirmed by presence of high lumbar opening cerebrospinal fluid (CSF) pressure or symptomatic response towards specific medical treatment. Outcomes of brain MRIs were presented on a 2x2 contingency table. Results Sensitivity, and specificity of routine brain MRI findings in detection of IIH were calculated as 76.4% [95% confidence interval (CI), 64.62-85.91%], and 84.6% (95% CI, 69.47-94.14%) respectively. Conclusion: IIH is a known cause of headache. Detection of all three findings of empty sella, tortuosity of optic nerves and non-dilated ventricles on routine brain MRI can predict IIH with greater sensitivity and specificity.

Objective To evaluate the diagnostic utility of ‘Susceptibility Weighted Angiogram’ (SWAN) in brain magnetic resonance imaging (MRI) by identifying venous angiomas causing epileptic seizures. Method and Materials A retrospective observational study was performed in the Radiology department at King Fahad Military Medical Complex (KFMC) hospital in Dhahran from January 2016 to 2021. All consecutive adult patients who underwent brain MRIs for epilepsy with SWAN were included. Patients with brain tumors, traumatic brain injuries, and post-surgical cases were excluded. The presence of tuft of small deep parenchymal veins draining into a more prominent (transcortical or subependymal) collector vein as seen on SWAN image was considered a venous angioma and confirmed on either contrast-enhanced studies or cerebral angiograms. Two experienced neuroradiologists interpreted the studies with mutual consensus. The significance of such finding was considered if SWAN-detected venous malformation corresponded to an epileptiform focus on respective electroencephalogram (EEG). Findings were compared with incidentally detected venous angiomas in normal brain MRIs in patients without indications of seizures (control group, n=112). Proportion analysis (Z-test) was used to determine significance. Results Out of 112 patients, 64 were females (57%), and 48 were males (43%), with a mean age of 19.24 (range, 5-45 years). Twenty-three patients (epilepsy group) were found to have venous malformations while three (control group) had venous angiomas (Z-value, 3.93; P-value, 0.0008). Out of 23 patients, 20.53% were SWAN-detected venous angiomas, 5 corresponded to epileptiform foci on respective EEGs compared to none of 3 incidentally detected venous angiomas in the control group (p-value, 0.0005). Conclusion Venous angiomas are usually asymptomatic when detected incidentally. However, adding a SWAN sequence in routine brain MRI for epilepsy patients may help to detect venous angiomas, which may cause focal seizure activity in these patients.

Objectives: To evaluate diagnostic capability of brain magnetic resonance imaging (MRI) in detection of inherited neurometabolic disorders. Methods: This retrospective observational study was performed in Radiology Department at our Hospital in Dhahran, from January 2013 to January 2020. We evaluated brain MRIs of children (under 5) who were referred to pediatric neurology for clinical suspicion of neuro-developmental delay and metabolic disease. Known perinatal ischemia and birth trauma cases were excluded. Imaging criteria included: (i) bilateral symmetric white matter signal abnormality, (ii) diffusion restriction affecting bilateral deep grey nuclei with or without brainstem involvement, (iii) brain atrophy or edema with abnormal white matter signal, (iv) characteristic MR spectroscopic finding. Presence of any one of these findings was considered positive for neurometabolic disease. Two neuroradiologists interpreted MRIs with substantial interobserver agreement. Diagnoses were confirmed on biochemical/ metabolic screening and genetic testing. A 2 × 2 contingency table was used for results. Chi square test was used to determine association. Results: Out of 133 cases, 72 (49 males, 90% AR) were found to have neurometabolic disorders. Sensitivity, specificity, positive and negative predictive values were calculated as 81.94% (CI, 71.11-90.02), 67.21% (CI, 54.00-78.69), 74.68% (CI, 66.96-81.11) and 75.93% (CI, 65.16-84.17) respectively. Findings were found significant (p-value=0.0001). Conclusion: Brain MRI can help to predict inherited neurometabolic disorders considering certain findings.