Magnetic Susceptibility Source Separation Solely from Gradient Echo Data: Histological Validation
Year: 2022
Type: article
Abstract: Quantitative susceptibility mapping (QSM) facilitates mapping of the bulk magnetic susceptibility of tissue from the phase of complex gradient echo (GRE) MRI data. QSM phase processing combined with an R2* model of magnitude of multiecho gradient echo data (R2*QSM) allows separation of dia- and para-magnetic components (e.g., myelin and iron) that contribute constructively to R2* value but destructively to the QSM value of a voxel. This R2*QSM technique is validated against quantitative histology—optical density of myelin basic protein and Perls’ iron histological stains of rim and core of 10 ex vivo multiple sclerosis lesions, as well as neighboring normal appearing white matter. We found that R2*QSM source maps are in good qualitative agreement with histology, e.g., showing increased iron concentration at the edge of the rim+ lesions and myelin loss in the lesions’ core. Furthermore, our results indicate statistically significant correlation between paramagnetic and diamagnetic tissue components estimated with R2*QSM and optical densities of Perls’ and MPB stains. These findings provide direct support for the use of R2*QSM magnetic source separation based solely on GRE complex data to characterize MS lesion composition.
Source: Tomography
Authors: Alexey V. Dimov, Kelly M. Gillen, Thanh D. Nguyen, Jerry Kang, Ria Sharma, David Pitt, Susan A. Gauthier, Yi Wang
Institutions: Weill Cornell Medicine, Yale University, Cornell University
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,885
Awards: G1044130170, G1346814702, G1468724583, 3.0T Magnetic Resonance Imaging System for Preclinical, Translational and Clinical Research, G2787109523, G4125342063, Quantitative Susceptibility Mapping (QSM) as a Non-Invasive Imaging Biomarker for Predicting Neurodegeneration in Alzheimer's Disease, G8899472212, G9000019920, G9000161574, Yale Clinical and Translational Science Award, G965732680
OpenAlex ID: W4282915264
