TY - JOUR
T1 - Gradient echo magnetic resonance imaging correlates with clinical measures and allows visualization of veins within multiple sclerosis lesions
AU - Luo, Jie
AU - Yablonskiy, Dmitriy A.
AU - Hildebolt, Charles F.
AU - Lancia, Samantha
AU - Cross, Anne H.
N1 - Funding Information:
Dr Cross has received research and clinical trial funding from the NIH, the U.S. Department of Defense, National MS Society USA, Consortium of Multiple Sclerosis Centers, the Barnes-Jewish Hospital Foundation, Hoffman-La Roche, and Sanofi, and honoraria or consulting fees from Hoffman-La Roche, Sanofi, Novartis, GlaxoSmithKline, Bayer Healthcare, Biogen Idec, Genzyme, Questcor, and Teva Neuroscience.
Funding Information:
The study was funded by the Department of Defense of the United States [grant MS090031]; and the National Institute of Health grants [CO6 RR020092, UL1 TR000448] (Washington University Institute of Clinical and Translational Sciences - Brain, Behavioral and Performance Unit); AHC was supported in part by The Manny and Rosalyn Rosenthal-Dr. John L. Trotter MS Center Chair in Neuroimmunology from the Barnes-Jewish Hospital Foundation.
PY - 2014/3
Y1 - 2014/3
N2 - Background: Conventional magnetic resonance imaging (MRI) methods do not quantify the severity of multiple sclerosis (MS) white matter lesions or measure pathology within normal-appearing white matter (NAWM). Objective: Gradient Echo Plural Contrast Imaging (GEPCI), a fast MRI technique producing inherently co-registered images for qualitative and quantitative assessment of MS, was used to 1) correlate with disability; 2) distinguish clinical MS subtypes; 3) determine prevalence of veins co-localized within lesions in WM. Methods: Thirty subjects representing relapsing-remitting MS (RRMS), secondary progressive MS (SPMS) and primary progressive MS (PPMS) subtypes were scanned with clinical and GEPCI protocols. Standard measures of physical disability and cognition were correlated with magnetic resonance metrics. Lesions with central veins were counted for RRMS subjects. Results: Tissue damage load (TDL-GEPCI) and lesion load (LL-GEPCI) derived with GEPCI correlated better with MS functional composite (MSFC) measures and most other neurologic measures than lesion load derived with FLAIR (LLFLAIR). GEPCI correctly classified clinical subtypes in 70% subjects. A central vein could be identified in 76% of WM lesions in RRMS subjects on GEPCI T2*-SWI images. Conclusion: GEPCI lesion metrics correlated better with neurologic disability than lesion load derived using FLAIR imaging, and showed promise in classifying clinical subtypes of MS. These improvements are likely attributable to the ability of GEPCI to quantify tissue damage.
AB - Background: Conventional magnetic resonance imaging (MRI) methods do not quantify the severity of multiple sclerosis (MS) white matter lesions or measure pathology within normal-appearing white matter (NAWM). Objective: Gradient Echo Plural Contrast Imaging (GEPCI), a fast MRI technique producing inherently co-registered images for qualitative and quantitative assessment of MS, was used to 1) correlate with disability; 2) distinguish clinical MS subtypes; 3) determine prevalence of veins co-localized within lesions in WM. Methods: Thirty subjects representing relapsing-remitting MS (RRMS), secondary progressive MS (SPMS) and primary progressive MS (PPMS) subtypes were scanned with clinical and GEPCI protocols. Standard measures of physical disability and cognition were correlated with magnetic resonance metrics. Lesions with central veins were counted for RRMS subjects. Results: Tissue damage load (TDL-GEPCI) and lesion load (LL-GEPCI) derived with GEPCI correlated better with MS functional composite (MSFC) measures and most other neurologic measures than lesion load derived with FLAIR (LLFLAIR). GEPCI correctly classified clinical subtypes in 70% subjects. A central vein could be identified in 76% of WM lesions in RRMS subjects on GEPCI T2*-SWI images. Conclusion: GEPCI lesion metrics correlated better with neurologic disability than lesion load derived using FLAIR imaging, and showed promise in classifying clinical subtypes of MS. These improvements are likely attributable to the ability of GEPCI to quantify tissue damage.
KW - CNS white matter
KW - MS clinical subtypes
KW - Multiple Sclerosis
KW - perivascular cuffs
KW - quantitative MRI
UR - http://www.scopus.com/inward/record.url?scp=84895755020&partnerID=8YFLogxK
U2 - 10.1177/1352458513495935
DO - 10.1177/1352458513495935
M3 - Article
C2 - 23836876
AN - SCOPUS:84895755020
SN - 1352-4585
VL - 20
SP - 349
EP - 355
JO - Multiple Sclerosis Journal
JF - Multiple Sclerosis Journal
IS - 3
ER -