Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
460-02-011 ISMRM Abstract

Establishing Normative Adult Iron Levels by Brain Region Using Clinically Integrated AI Analytics on QSM Imaging

Accepted
Hashem Zamanian 1, Stephan Erberich2, Bethany L Sussman3, Eamon K Doyle4, John C Wood5,6, Matthew T Borzage3,7,8
1The Saban Research Institute, Children's Hospital Los Angeles, Los Angeles, United States of America
2Radiology, Keck School of Medicine, University of Southern California, Los Angeles, United States of America
3Pediatrics, Division of Neonatology, Children's Hospital Los Angeles, Los Angeles, United States of America
4Division of Cardiology, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, United States of America
5USC, Los Angeles, United States of America
6Children's Hospital Los Angeles, Los Angeles, United States of America
7Alfred E. Mann Department of Biomedical Engineering, University of Southern California, Los Angeles, United States of America
8USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, United States of America
Presenting Author: Hashem Zamanian

Synopsis

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References

1. Zamanian H, Doyle E, Wood J, Tamrazi B, Borzage M, Erberich S. Clinically integrated MRI-QSM analysis and reporting system to establish brain tissue iron levels in pediatrics. Proc ISMRM 2025, Honolulu, Hawaii, USA.
2. Zamanian H, Doyle E, Borzage M, Tamrazi B, Wood J, Nelson M, Erberich S. PACS-integrated AI computer vision system to establish brain tissue iron levels in pediatrics. Proc CARS 2025, Berlin, Germany.
3. Ranganathan S, Salcudean H, Zamanian H, Liu J, Torres I, Doyle E, Wood J, Borzage M. Evaluation of iron deposition in deep brain nuclei associated with Fontan circulation using quantitative susceptibility mapping. Proc PAS 2025.
4. Karsa A, Shmueli K. SEGUE: A speedy region-growing algorithm for unwrapping estimated phase. IEEE Trans Med Imaging 2019; 38(6): 1347-1357.
5. Vardhanabhuti V, Gunter JL. V-SHARP: A novel method for background field removal in quantitative susceptibility mapping. Magn Reson Med 2015; 73(3): 1070-1077.
6. Lai KW, Aggarwal M, van Zijl P, Li X, Sulam J. Learned proximal networks for quantitative susceptibility mapping. Proc MICCAI 2020 (Springer).
7. Fonov V, Evans AC, McKinstry RC, Almli CR, Collins DL. Unbiased nonlinear average age-appropriate brain templates from birth to adulthood. NeuroImage 2011; 54(1): 313–327.

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