الفهرس 
AcknowledgementsOnly 14 pages are availabe for public view
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Abstract
MS diagnosis requires demonstration of disease dissemination in space (DIS) and time (DIT) and exclusion of other conditions that can mimic MS by their clinical and laboratory profile. MRI can support and substitute clinical information for MS diagnosis, allowing an earlier and accurate diagnosis and, consequently, earlier treatment.
Current MRI criteria for multiple sclerosis are based on imaging features that are characteristic of the disease, but are not sufficiently specific. Over time, revisions of the multiple sclerosis diagnostic criteria have improved the sensitivity, particularly adding the capability to confirm the diagnosis at first clinical presentation.
The aim of this study was to describe advances in brain MRI imaging used to support the diagnosis of MS and to allow accurate identification from its mimics.
In our study we evaluate 58 patients referred from the neurology department in AUH with manifestations suspicious for MS with age group from 18-50 years old. After completing their investigations ,Thirty-one (53.4%) patients were diagnosed as MS according MC Donald’s criteria with average age 33.97±10.75 and 27 patients diagnosed as MS mimics (46.6%) with average age 37.78±12.92.
MRI analysis of the examined patients revealed white matter hyperintense lesions distribution among the studied patients in T2WI and FLAIR in the periventricular, deep and juxtacortical regions which show significant increase in number of subcortical lesions in MS patients. Also infratentorial lesions were more in the MS group with no significant P value.
Dawson’s fingers were significant seen among MS patients compared with MS mimics. T1black holes were also seen more So, we recommend to use advanced pulse sequences, such as SWI and DIR, which are usually not done in routine clinical scans, enabled identification of the central vein sign and cortical lesions, that could have a role in the diagnostic criteria of MS and might help to identify features of other mimics specially SVD.
The use of computer-assisted diagnostic capabilities of recent diagnostic workstations for automated or semi-automated quantitative evaluation of MRI images in suspicious MS patients is highly recommended and should be implemented. Such quantitative studies would allow calculation of DTI parameters for different stages of MS lesions in a trial to determine relevant cut-off values is also recommended. cerebral volumetry measures and accurate calculation of MS lesion load in different pulse sequences which is very important in this disease would be of great importance in assessment of the disease course.
CONCLUSION:
MRI plays an important role in diagnosing MS in conjunction with good clinical, neurological and laboratory assessment to rule out other MS mimics.
Advanced sequences such SWI and DIR add more accuracy with high sensitivity and specificity in diagnosis of suspicious MS cases.
Quantitative DTI measurements give cut-off values in differentiating MS from its mimics with good accuracy.