Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
361-06-002 ISMRM Abstract

Cerebral Microbleed Detection Using Clinically Feasible Multi-shot Multi-echo Echo Planar Imaging at 3T

Primary: Neuro - Traumatic Brain Injury
Secondary: Acquisition & Reconstruction - Quantitative Imaging: head and neck
361-06-002 · Quantitative Imaging: Head and Neck II · Monday, 11 May, 5:05 PM–6:00 PM · Digital Posters Row B
Keywords: Traumatic brain injury SWI Quantitative Susceptibility Mapping (QSM) Cerebral Microbleeds Lesion Detection
Accepted
Yujia Huang1, Gaoxing Zheng1, Jill Morales1, Binu Thomas1,2, Rong Zhang3, Jimmy S Lee4, Kan Ding3, David C Zhu5, Jiaen Liu1,6
1Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, United States of America
2University of Texas at Dallas, Richardson, United States of America
3Department of Neurology, University of Texas Southwestern Medical Center, Dallas, United States of America
4Department of Radiology, Montefiore Medical Center, Bronx, United States of America
5Department of Radiology, Gruss Magnetic Resonance Research Center, Albert Einstein College of Medicine, Bronx, United States of America
6Department of Radiology, University of Texas Southwestern Medical Center, Dallas, United States of America
Presenting Author: Jimmy Lee

Synopsis

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References

1. Glushakova OY, Johnson D, Hayes RL. Delayed Increases in Microvascular Pathology after Experimental Traumatic Brain Injury Are Associated with Prolonged Inflammation, Blood–Brain Barrier Disruption, and Progressive White Matter Damage. Journal of Neurotrauma. 2014;31(13):1180-1193. doi:10.1089/neu.2013.3080 [doi]
2. Akoudad S, Wolters FJ, Viswanathan A, et al. Association of Cerebral Microbleeds With Cognitive Decline and Dementia. JAMA Neurol. 2016;73(8):934-943. doi:10.1001/jamaneurol.2016.1017 [doi]
3. Liu J, van Gelderen P, de Zwart JA, Duyn JH. Reducing motion sensitivity in 3D high-resolution T2*-weighted MRI by navigator-based motion and nonlinear magnetic field correction. NeuroImage. 2020;206:116332. doi:10.1016/j.neuroimage.2019.116332 [doi]
4. Huang Y, Chen L, Li X, Liu J. Improved test–retest reliability of \ \mathrmR_2^\ast \ and susceptibility quantification using multishot multi-echo 3D EPI. Magnetic Resonance in Medicine. 2024;91(6):2310-2319. doi:10.1002/mrm.29992 [doi]
5. Caldas J, Cardim D, Edmundson P, et al. Study protocol: Cerebral autoregulation, brain perfusion, and neurocognitive outcomes after traumatic brain injury -CAPCOG-TBI. Front Neurol. 2024;15:1465226. doi:10.3389/fneur.2024.1465226 [doi]
6. Susceptibility-weighted Imaging: Technical Essentials and Clinical Neurologic Applications. doi:10.1148/radiol.2021203071 [doi]
7. Greenberg SM, Vernooij MW, Cordonnier C, et al. Cerebral microbleeds: a guide to detection and interpretation. The Lancet Neurology. 2009;8(2):165-174. doi:10.1016/S1474-4422(09)70013-4 [doi]
8. Eckstein K, Bachrata B, Hangel G, et al. Improved susceptibility weighted imaging at ultra-high field using bipolar multi-echo acquisition and optimized image processing: CLEAR-SWI. NeuroImage. 2021;237:118175. doi:10.1016/j.neuroimage.2021.118175 [doi]
9. Bao L, Li X, Cai C, Chen Z, van Zijl PCM. Quantitative Susceptibility Mapping Using Structural Feature Based Collaborative Reconstruction (SFCR) in the Human Brain. IEEE Trans Med Imaging. 2016;35(9):2040-2050. doi:10.1109/TMI.2016.2544958 [doi]
10. Li X, Chen L, Kutten K, et al. Multi-atlas tool for automated segmentation of brain gray matter nuclei and quantification of their magnetic susceptibility. Neuroimage. 2019;191:337-349. doi:10.1016/j.neuroimage.2019.02.016 [doi]
11. van Bergen JMG, Hua J, Unschuld PG, et al. Quantitative Susceptibility Mapping Suggests Altered Brain Iron in Premanifest Huntington Disease. AJNR Am J Neuroradiol. 2016;37(5):789-796. doi:10.3174/ajnr.A4617 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/361-06-002