Browse > Article
http://dx.doi.org/10.14316/pmp.2022.33.4.88

Contribution of Microbleeds on Microvascular Magnetic Resonance Imaging Signal  

Chang Hyun Yoo (Department of Physics and Research Institute for Basic Sciences, Graduate School, Kyung Hee University)
Junghwan Goh (Department of Physics and Research Institute for Basic Sciences, Graduate School, Kyung Hee University)
Geon-Ho Jahng (Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University)
Publication Information
Progress in Medical Physics / v.33, no.4, 2022 , pp. 88-100 More about this Journal
Abstract
Purpose: Cerebral microbleeds are more susceptible than surrounding tissues and have been associated with a variety of neurological and neurodegenerative disorders that are indicative of an underlying vascular pathology. We investigated relaxivity changes and microvascular indices in the presence of microbleeds in an imaging voxel by evaluating those before and after contrast agent injection. Methods: Monte Carlo simulations were run with a variety of conditions, including different magnetic field strengths (B0), different echo times, and different contrast agents. ΔR2* and ΔR2 and microvascular indices were calculated with varying microvascular vessel sizes and microbleed loads. Results: As B0 and the concentration of microbleeds increased, 𝜟R2* and 𝜟R2 increased. 𝜟R2* increased, but 𝜟R2 decreased slightly as the vessel radius increased. When the vessel radius was increased, the vessel size index (VSI) and mean vessel diameter (mVD) increased, and all other microvascular indices except mean vessel density (Q) increased when the concentration of microbleeds was increased. Conclusions: Because patients with neurodegenerative diseases often have microbleeds in their brains and VSI and mVD increase with increasing microbleeds, microbleeds can be altered microvascular signals in a voxel in the brain of a neurodegenerative disease at 3T magnetic resonance imaging.
Keywords
Brain; Gadolinium-chelated; Microbleed; Microvascular; Magnetic resonance imaging;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Greenberg SM, Vernooij MW, Cordonnier C, Viswanathan A, Al-Shahi Salman R, Warach S, et al. Cerebral microbleeds: a guide to detection and interpretation. Lancet Neurol. 2009;8:165-174.   DOI
2 van der Flier WM. Clinical aspects of microbleeds in Alzheimer's disease. J Neurol Sci. 2012;322:56-58.   DOI
3 Vernooij MW, Ikram MA, Wielopolski PA, Krestin GP, Breteler MM, van der Lugt A. Cerebral microbleeds: accelerated 3D T2*-weighted GRE MR imaging versus conventional 2D T2*-weighted GRE MR imaging for detection. Radiology. 2008;248:272-277.   DOI
4 Fischbach FA, Gregory DW, Harrison PM, Hoy TG, Williams JM. On the structure of hemosiderin and its relationship to ferritin. J Ultrastruct Res. 1971;37:495-503.   DOI
5 Tropres I, Grimault S, Vaeth A, Grillon E, Julien C, Payen JF, et al. Vessel size imaging. Magn Reson Med. 2001;45:397-408.   DOI
6 Lemasson B, Valable S, Farion R, Krainik A, Remy C, Barbier EL. In vivo imaging of vessel diameter, size, and density: a comparative study between MRI and histology. Magn Reson Med. 2013;69:18-26.   DOI
7 Choi HI, Ryu CW, Kim S, Rhee HY, Jahng GH. Changes in microvascular morphology in subcortical vascular dementia: a study of vessel size magnetic resonance imaging. Front Neurol. 2020;11:545450.
8 Chang SK, Kim J, Lee D, Yoo CH, Jin S, Rhee HY, et al. Mapping of microvascular architecture in the brain of an Alzheimer's disease mouse model using MRI. NMR Biomed. 2021;34:e4481.
9 Pathak AP, Ward BD, Schmainda KM. A novel technique for modeling susceptibility-based contrast mechanisms for arbitrary microvascular geometries: the finite perturber method. Neuroimage. 2008;40:1130-1143.   DOI
10 Reuter B, Venus A, Heiler P, Schad L, Ebert A, Hennerici MG, et al. Development of cerebral microbleeds in the APP23-transgenic mouse model of cerebral amyloid angiopathy-a 9.4 Tesla MRI study. Front Aging Neurosci. 2016;8:170.
11 Yoo CH, Goh J, Jahng GH, Jin S, Lee D, Cho HJ. Simulation of microvascular signal changes used on a gadolinium-chelated contrast agent at 3 T MRI in the presence of amyloid-beta plaques. J Korean Phys Soc. 2022;81:1039-1050.   DOI
12 Bennett DA, Schneider JA, Wilson RS, Bienias JL, Arnold SE. Neurofibrillary tangles mediate the association of amyloid load with clinical Alzheimer disease and level of cognitive function. Arch Neurol. 2004;61:378-384.   DOI
13 Hunter JM, Kwan J, Malek-Ahmadi M, Maarouf CL, Kokjohn TA, Belden C, et al. Morphological and pathological evolution of the brain microcirculation in aging and Alzheimer's disease. PLoS One. 2012;7:e36893.
14 Dennie J, Mandeville JB, Boxerman JL, Packard SD, Rosen BR, Weisskoff RM. NMR imaging of changes in vascular morphology due to tumor angiogenesis. Magn Reson Med. 1998;40:793-799.   DOI
15 Martikainen P, Pikkarainen M, Pontynen K, Hiltunen M, Lehtovirta M, Tuisku S, et al. Brain pathology in three subjects from the same pedigree with presenilin-1 (PSEN1) P264L mutation. Neuropathol Appl Neurobiol. 2010;36:41-54.   DOI
16 Yablonskiy DA, Haacke EM. Theory of NMR signal behavior in magnetically inhomogeneous tissues: the static dephasing regime. Magn Reson Med. 1994;32:749-763.   DOI
17 Jensen JH, Chandra R. Strong field behavior of the NMR signal from magnetically heterogeneous tissues. Magn Reson Med. 2000;43:226-236.   DOI
18 Jung HS, Jin SH, Cho JH, Han SH, Lee DK, Cho H. UTE-ΔR2-ΔR2* combined MR whole-brain angiogram using dual-contrast superparamagnetic iron oxide nanoparticles. NMR Biomed. 2016;29:690-701.   DOI
19 Weisskoff RM, Kiihne S. MRI susceptometry: image-based measurement of absolute susceptibility of MR contrast agents and human blood. Magn Reson Med. 1992;24:375-383.   DOI
20 Mahmoudi M, Sant S, Wang B, Laurent S, Sen T. Superparamagnetic iron oxide nanoparticles (SPIONs): development, surface modification and applications in chemotherapy. Adv Drug Deliv Rev. 2011;63:24-46.   DOI
21 Klohs J, Deistung A, Schweser F, Grandjean J, Dominietto M, Waschkies C, et al. Detection of cerebral microbleeds with quantitative susceptibility mapping in the ArcAbeta mouse model of cerebral amyloidosis. J Cereb Blood Flow Metab. 2011;31:2282-2292.   DOI
22 Pozrikidis C. Numerical simulation of blood and interstitial flow through a solid tumor. J Math Biol. 2010;60:75-94.   DOI