Evidence map›Paper›PMID 40800826›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2025

IRONMAP: Iron network mapping and analysis protocol for detecting over-time brain iron abnormalities in neurological disease.

Jack A Reeves, Fahad Salman, Michael G Dwyer, Niels Bergsland, Sarah Muldoon, Bianca Weinstock-Guttman, Robert Zivadinov, Ferdinand Schweser

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Jack A ReevesBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States.ORCID https://orcid.org/0009-0002-4079-5664
Fahad SalmanBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States.
Michael G DwyerBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States.
Niels BergslandBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States.
Sarah MuldoonDepartment of Mathematics, University at Buffalo, State University of New York, Buffalo, NY, United States.
Bianca Weinstock-GuttmanJacobs Neurological Institute, Buffalo, NY, United States.
Robert ZivadinovBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States.
Ferdinand SchweserBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States.

Funding

University of Buffalo Clinical and Translational Science Institute - Supplement SchulyerUL1TR001412 · NCATS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI MURPHY, TIMOTHY F · 2015 to 2024
$33.8M
Deep Gray Matter Iron and Disease Progression in Multiple SclerosisR01NS114227 · NINDS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI SCHWESER, FERDINAND · 2021 to 2024
$1.5M
Acquisition of High Performance Data and Computing Infrastructure to Advance Biomedical ResearchS10OD024973 · OD · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI FURLANI, THOMAS · 2019 to 2019
$1.0M
NCATS NIH HHS UL1 TR001412NIH HHS S10 OD024973NINDS NIH HHS R01 NS114227
6 · The paper itself

Abstract

Altered iron levels, detected using iron-sensitive MRI techniques such as quantitative susceptibility mapping (QSM), are observed in neurological disorders and may play a crucial role in disease pathophysiology. However, brain iron changes occur slowly, even in neurological diseases, and can be influenced by physiological or environmental factors that are difficult to quantify in the research or clinical settings. Therefore, novel analysis methods are needed to improve sensitivity to disease-related iron changes beyond conventional region-based approaches. This study introduces IRONMAP, Iron Network Mapping and Analysis Protocol, which is a novel network-based analysis method to evaluate over-time changes in magnetic susceptibility. With this technique, we analyzed short-term (<1 year) longitudinal QSM data from a cohort of people with multiple sclerosis (pwMS) and healthy controls (HCs) and assessed disease-related network patterns, comparing the new approach to a conventional per-region rate-of-change method. IRONMAP revealed over-time, MS-related brain iron abnormalities that were undetectable using the rate-of-change approach. IRONMAP was applicable at the per-subject level, improving binary classification of pwMS vs. HCs compared to rate-of-change data alone (areas under the curve: 0.773 vs. 0.636, p = 0.024). Further analysis revealed that the observed IRONMAP-derived HC network structure closely aligned with simulated networks based on healthy aging-related susceptibility data, suggesting that disruptions in normal aging-related iron changes may contribute to the network differences seen in pwMS. IRONMAP is applicable to various neurological diseases, including Alzheimer's disease and Parkinson's disease, and can be used between any set of brain regions. Our proposed technique may allow for the study of brain iron abnormalities over shorter timeframes than previously possible.

Indexed as

brain irondeep gray mattermultiple sclerosisnetwork neuroscienceneurological disordersquantitative susceptibility mapping

Identifiers

PMID40800826
PMCPMC12319938

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.