Abstract:
Multiple Sclerosis (MS) is a chronic autoimmune inflammatory disease
of the central nervous system, which can be diagnosed by magnetic
resonance imaging (MRI).
This study is an analytical study, which conducted in many diagnostic
centers from May 2015 to Mars 2018, MRI brain scan were done for 64
patients (male 18) and female(46) their age range 17 year to 46 year.
Patients known case of multiple sclerosis the aim of this study was to
evaluate the of routine MRI brain protocol for MS comparing with
modified protocol and advanced protocol. The study used image analysis
texture and reveal protocol 3 (3D volume) signal intensity increase with
age more than routine protocol (5 mm gap 1) and modified protocol
(3mm gap 0) were R2 = o.11 ,0.012 and 0.007 P1,p2 and P3 respectively.
T test used to differentiate between protocols T-test (Cl =995%) and (pvalue
= 0.05) Resulted about significant different between P1 (routine
protocol) and P2 (modified protocol) and the mean of them 38.4 and 52.2
respectively. And also there was a significant different between P1 and
P3, The mean between them 38.4 and 69.00 respectively. The study was
arrived for more accurate discrimination of signal intensity between
different brain tissues. Using texture analysis for each DICOM image,
then was used Linear discriminant analysis ,classify feature to brain
tissues ,CSF and MS.to differentiate between the classes using LDA
accuracy of classification 96.7% and sensitivity for each class is 99.7%
,96.8% and for 92.2% (brain tissues, CSF and MS respectively). This
program clearly different between these classes which match the routine
protocol. Clearly different in signal intensity between CSF, brain tissues
and MS, when using the mean, the higher signal noted for MS. The
v
results revealed the advanced protocol (3D volume) is the best in
diagnose MS and then modified protocol. Patients for follow up, the best
sequence to detected new plaque, was the volume T1 with contrast
substance. The most patients have MS have vitamin D deficiency 57%
have vitamin D deficiency and 42% not having.
