Linking gradient echo plural contrast imaging metrics of tissue microstructure with Alzheimer disease

Author(s):  
Dmitriy A. Yablonskiy ◽  
Tammie L. Benzinger ◽  
John C. Morris
2016 ◽  
Vol 43 (6Part4) ◽  
pp. 3343-3344
Author(s):  
B Cai ◽  
J Wen ◽  
Y Rao ◽  
C Tsien ◽  
J Huang ◽  
...  

PLoS ONE ◽  
2019 ◽  
Vol 14 (7) ◽  
pp. e0219705 ◽  
Author(s):  
Wei Bian ◽  
Adam B. Kerr ◽  
Eric Tranvinh ◽  
Sherveen Parivash ◽  
Benjamin Zahneisen ◽  
...  

NeuroImage ◽  
2010 ◽  
Vol 51 (3) ◽  
pp. 1089-1097 ◽  
Author(s):  
Pascal Sati ◽  
Anne H. Cross ◽  
Jie Luo ◽  
Charles F. Hildebolt ◽  
Dmitriy A. Yablonskiy

2021 ◽  
Author(s):  
Victoria Levasseur ◽  
Biao Xiang ◽  
Amber Salter ◽  
Dmitriy Yablonskiy ◽  
Anne H Cross

Background: Multiple sclerosis (MS) lesions typically form around a central vein that can be visualized with FLAIR* MRI, creating the central vein sign (CVS) which may reflect lesion pathophysiology. Herein we used Gradient Echo Plural Contrast Imaging (GEPCI) MRI to simultaneously visualize CVS and measure tissue damage in MS lesions. We examined CVS in relation to tissue integrity in white matter (WM) lesions and among MS subtypes. Subjects and Methods: Thirty relapsing remitting MS (RRMS) subjects and 38 progressive MS (PMS) subjects were scanned with GEPCI protocol. GEPCI T2*SWI images were generated to visualize CVS. Two investigators independently evaluated WM lesions for CVS and measured lesion volumes. To estimate tissue damage severity, total lesion volume, mean lesion volume, R2t* based tissue damage score (TDS) of individual lesions and tissue damage load (TDL) were measured for CVS positive, CVS negative , and confluent lesions. Spearman correlations were made between MRI and clinical data. A paired t-test was used to compare measurements of CVS positive versus CVS negative lesions in each individual. Results: 398 of 548 lesions meeting inclusion criteria showed CVS. Most patients had > 40% CVS positive lesions. CVS positive lesions were present in similar proportion among MS subtypes. Interobserver agreement was high for CVS detection. CVS positive and confluent lesions had higher average and total volumes versus CVS negative lesions. CVS positive and confluent lesions had more tissue damage than CVS negative lesions based on TDL and mean TDS. Conclusion: CVS occurred in RRMS and PMS in similar proportions. CVS positive lesions had greater tissue damage and larger size than CVS negative lesions.


2015 ◽  
Vol 169 (1-3) ◽  
pp. 36-45 ◽  
Author(s):  
Daniel Mamah ◽  
Jie Wen ◽  
Jie Luo ◽  
Xialing Ulrich ◽  
Deanna M. Barch ◽  
...  

2019 ◽  
Vol 184 (Supplement_1) ◽  
pp. 218-227 ◽  
Author(s):  
Serguei V Astafiev ◽  
Jie Wen ◽  
David L Brody ◽  
Anne H Cross ◽  
Andrey P Anokhin ◽  
...  

AbstractResearch objectivesIt is widely accepted that mild traumatic brain injury (mTBI) causes injury to the white matter, but the extent of gray matter (GM) damage in mTBI is less clear.MethodsWe tested 26 civilian healthy controls and 14 civilian adult subacute-chronic mTBI patients using quantitative features of MRI-based Gradient Echo Plural Contrast Imaging (GEPCI) technique. GEPCI data were reconstructed using previously developed algorithms allowing the separation of R2t*, a cellular-specific part of gradient echo MRI relaxation rate constant, from global R2* affected by BOLD effect and background gradients.ResultsSingle-subject voxel-wise analysis (comparing each mTBI patient to the sample of 26 control subjects) revealed GM abnormalities that were not visible on standard MRI images (T1w and T2w). Analysis of spatial overlap for voxels with low R2t* revealed tissue abnormalities in multiple GM regions, especially in the frontal and temporal regions, that are frequently damaged after mTBI. The left posterior insula was the region with abnormalities found in the highest proportion (50%) of mTBI patients.ConclusionsOur data suggest that GEPCI quantitative R2t* metric has potential to detect abnormalities in GM cellular integrity in individual TBI patients, including abnormalities that are not detectable by a standard clinical MRI.


NeuroImage ◽  
2018 ◽  
Vol 178 ◽  
pp. 403-413 ◽  
Author(s):  
Shrinath Kadamangudi ◽  
David Reutens ◽  
Surabhi Sood ◽  
Viktor Vegh

2014 ◽  
Vol 5 (7) ◽  
pp. 2113 ◽  
Author(s):  
Brendan F. Kennedy ◽  
Robert A. McLaughlin ◽  
Kelsey M. Kennedy ◽  
Lixin Chin ◽  
Andrea Curatolo ◽  
...  

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