Author Of 2 Presentations
P0648 - The central vein sign as a biomarker for MS in the infratentorial brain (ID 920)
Abstract
Background
The central vein sign (CVS) is a novel imaging biomarker for the differential diagnosis of multiple sclerosis (MS). In studies at 7.0 tesla MRI, the percentage of supratentorial white matter lesions (WMLs) with CVS vary between 80% to 100% in MS patient brains. Similar results were reported at 3.0 tesla (3T) MRI in optimized sequences, such as T2*-weighted 3D echo-planar-imaging sequence and SWAN-venule. The value of the CVS for infratentorial brain remains unknown.
Objectives
The aim of this study was to determine the proportion of WMLs positive for the CVS in the brainstem and cerebellum of MS patients.
Methods
We included subjects with clinically defined MS, that showed at least one infratentorial lesion larger than 3 mm in 3D-FLAIR. Patients were scanned in a 3T MRI system (GE Medical Systems, discovery MR750) using a 32-channel coil array. MRI included 3D T2-weighted FLAIR and post-contrast SWAN-venule: [FOV = 22 cm x 16 cm; number of slices= 126; voxel resolution, 0.4 mm x 0.4 mm x 0.8 mm; TR = 47 msec; TE = 28 msec; flip angle (FA) = 8 degrees; ETL = 9; AT = 7.38 min]. The CVS, defined as a thin hypointense line or a hypointense small dot visualized in two planes, was recorded on SWAN-venule by two trained raters.
Results
Thirty MRIs were analyzed, three were excluded for motion artefacts. A total of 91 focal lesions were detected in FLAIR, 22 in the cerebellum and 69 in brainstem. Out of 91 lesions, 83 (91%) were visible in SWAN-venule and 83% were positive for the CVS.
Conclusions
The infratentorial brain is a cardinal compartment for MS diagnosis, SWAN-venule detects infratentorial WMLs and highlights the CVS in most plaques at 3.0 T MRI. The CVS could be used to discriminate MS lesions from its radiological infratentorial mimics.
P0649 - The Central Vein Sign discriminates multiple sclerosis from its radiological mimics in the clinical setting (ID 1503)
Abstract
Background
The “central vein sign” (CVS) in white matter lesions (WMLs) is a current radiological biomarker of multiple sclerosis (MS). Using magnetic susceptibility-based sequences, the CVS was observed in 80-100% of lesions at 7.0 tesla Magnetic Resonance Imaging (MRI) in the research setting. Recently, similar detection rate was reported at 3.0 Tesla (3T) MRI in the clinical setting using susceptibility-weighted angiography (SWAN)-venule sequence. Some data suggest that using 3D T2*EPI/ FLAIR*, the CVS may be useful to differentiate MS from other neurological diseases with focal WMLs.
Objectives
The objective of our study was to determine if the CVS detected in SWAN-venule at 3T MRI discriminates MS from its radiological mimics.
Methods
Subjects were scanned on a 3T MRI system (Discovery MR750, GE, Milwaukee, USA) using a 32-channel head coil. We performed post-contrast 3D-FLAIR and SWAN-venule sequences [FOV = 22 cm x 16 cm; number of slices= 126; voxel resolution, 0.4 mm x 0.4 mm x 0.8 mm; TR = 47 msec; TE = 28 msec; flip angle = 8° ; ETL = 9; AT = 7.38 min]. MRIs with focal supratentorial WMLs visible in FLAIR, larger than 3 mm and smaller than 15 mm, were included. The CVS, defined as a thin hypointense line or a hypointense small dot centering a WML, was recorded blinded to the diagnosis on SWAN-venule by one junior neuroradiologist and two trained MS raters.
Results
Twenty people with MS and 24 subjects with non-MS WMLs: 9 migraine, 6 Neuromyelitis Optica spectrum disease (NMOs), 5 Susac Syndrome (SS), and 4 with other vascular diseases (2 primary angiitis of the central nervous system, 1 small vessels disease, and 1 Lupus), were included. A total of 380 WMLs were detected in the MS group, and 427 WMLs in the non-MS group (215 migraine, 52 NMOs, 83 SS, and 77 in other vascular diseases). The CVS was detected in 86% of MS WMLs compared to 23% of WMLs of other diseases (25% of migraine, 21% of NMOs, 22% of other vascular diseases).
Conclusions
The use of SWAN-venule sequence for the identification of CVS on 3T MRI helps differentiate MS WMLs from other WMLs that mimic MS.