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Research ArticlePediatric Neuroimaging

Quantitative Susceptibility Mapping with Source Separation in Normal Brain Development of Newborns

MinJung Jang, Alexey V. Dimov, Kushal Kapse, Jonathan Murnick, Zachary Grinspan, Alan Wu, Arindam RoyChoudhury, Yi Wang, Pascal Spincemaille, Thanh D. Nguyen, Catherine Limperopoulos and Zungho Zun
American Journal of Neuroradiology February 2025, 46 (2) 380-389; DOI: https://doi.org/10.3174/ajnr.A8488
MinJung Jang
aFrom the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
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Alexey V. Dimov
aFrom the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
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Kushal Kapse
bInstitute for the Developing Brain (K.K., J.M., C.L.), Division of Diagnostic Imaging and Radiology, Children’s National Hospital, Washington, DC
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  • ORCID record for Kushal Kapse
Jonathan Murnick
bInstitute for the Developing Brain (K.K., J.M., C.L.), Division of Diagnostic Imaging and Radiology, Children’s National Hospital, Washington, DC
cDepartment of Pediatrics (J.M., C.L.), School of Medicine and Health Sciences, George Washington University, Washington, DC
dDepartment of Radiology, School of Medicine and Health Sciences (J.M., C.L.), George Washington University, Washington, DC
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Zachary Grinspan
eDepartment of Pediatrics (Z.G.), Weill Cornell Medicine, New York, New York
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Alan Wu
fDepartment of Population Health Sciences (A.W., A.R.), Weill Cornell Medicine, New York, New York
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Arindam RoyChoudhury
fDepartment of Population Health Sciences (A.W., A.R.), Weill Cornell Medicine, New York, New York
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Yi Wang
aFrom the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
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Pascal Spincemaille
aFrom the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
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Thanh D. Nguyen
aFrom the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
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Catherine Limperopoulos
bInstitute for the Developing Brain (K.K., J.M., C.L.), Division of Diagnostic Imaging and Radiology, Children’s National Hospital, Washington, DC
cDepartment of Pediatrics (J.M., C.L.), School of Medicine and Health Sciences, George Washington University, Washington, DC
dDepartment of Radiology, School of Medicine and Health Sciences (J.M., C.L.), George Washington University, Washington, DC
gDivision of Fetal and Transitional Medicine (C.L.), Children’s National Hospital, Washington, DC
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Zungho Zun
aFrom the Department of Radiology (M.J., A.V.D., Y.W., P.S., T.D.N., Z.Z.), Weill Cornell Medicine, New York, New York
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Abstract

BACKGROUND AND PURPOSE: Quantitative susceptibility mapping is an emerging method for characterizing tissue composition and studying myelination and iron deposition. However, accurate assessment of myelin and iron content in the neonate brain using this method is challenging because these 2 susceptibility sources of opposite signs (myelin, negative; iron, positive) occupy the same voxel, with minimal and comparable content in both sources. In this study, susceptibilities were measured in the healthy neonate brain using susceptibility source separation.

MATERIALS AND METHODS: Sixty-nine healthy neonates without clinical indications were prospectively recruited for MRI. All neonates underwent gradient-echo imaging for quantitative susceptibility mapping. Positive (paramagnetic) and negative (diamagnetic) susceptibility sources were separated using additional information from R2* with linear modeling performed for the neonate brain. Average susceptibility maps were generated by normalizing all susceptibility maps to an atlas space. Mean regional susceptibility measurements were obtained in the cortical GM, WM, deep GM, caudate nucleus, putamen, globus pallidus, thalamus, and the 4 brain lobes.

RESULTS: A total of 65 healthy neonates (mean postmenstrual age, 42.8 [SD, 2.3] weeks; 34 females) were studied. The negative susceptibility maps visually demonstrated high signals in the thalamus, brainstem, and potentially myelinated WM regions, whereas the positive susceptibility maps depicted high signals in the GM compared with all WM regions, including both myelinated and unmyelinated WM. The WM exhibited significantly lower mean positive susceptibility and significantly higher mean negative susceptibility than cortical GM and deep GM. Within the deep GM, the thalamus showed a significantly lower mean negative susceptibility than the other nuclei, and the putamen and globus pallidus showed significant associations with neonate age in positive and/or negative susceptibility. Among the 4 brain lobes, the occipital lobe showed a significantly higher mean positive susceptibility and a significantly lower mean negative susceptibility than the frontal lobe.

CONCLUSIONS: This study demonstrates regional variations and temporal changes in positive and negative susceptibilities of the neonate brain, potentially associated with myelination and iron deposition patterns in normal brain development. It suggests that quantitative susceptibility mapping with source separation may be used for early identification of delayed myelination or iron deficiency.

ABBREVIATIONS:

CGM
cortical gray matter
DGM
deep gray matter
PMA
postmenstrual age
QSM
quantitative susceptibility mapping
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American Journal of Neuroradiology: 46 (2)
American Journal of Neuroradiology
Vol. 46, Issue 2
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MinJung Jang, Alexey V. Dimov, Kushal Kapse, Jonathan Murnick, Zachary Grinspan, Alan Wu, Arindam RoyChoudhury, Yi Wang, Pascal Spincemaille, Thanh D. Nguyen, Catherine Limperopoulos, Zungho Zun
Quantitative Susceptibility Mapping with Source Separation in Normal Brain Development of Newborns
American Journal of Neuroradiology Feb 2025, 46 (2) 380-389; DOI: 10.3174/ajnr.A8488

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Susceptibility Mapping in Newborn Brain Development
MinJung Jang, Alexey V. Dimov, Kushal Kapse, Jonathan Murnick, Zachary Grinspan, Alan Wu, Arindam RoyChoudhury, Yi Wang, Pascal Spincemaille, Thanh D. Nguyen, Catherine Limperopoulos, Zungho Zun
American Journal of Neuroradiology Feb 2025, 46 (2) 380-389; DOI: 10.3174/ajnr.A8488
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