scholarly journals Brain Iron Imaging Markers in the Presence of White Matter Hyperintensities

2021 ◽  
Author(s):  
Kyle D. Murray ◽  
Madalina E. Tivarus ◽  
Giovanni Schifitto ◽  
Md Nasir Uddin ◽  
Jianhui Zhong
Keyword(s):  
Monte Carlo ◽  
White Matter ◽  
White Matter Hyperintensities ◽  
Small Vessel Disease ◽  
Clinical Results ◽  
Iron Deposition ◽  
Brain Iron ◽  
Tissue Iron ◽  
Pathological Model ◽  
Brain Iron Deposition

PurposeTo investigate the relationship between pathological brain iron deposition and white matter hyperintensities (WMHs) in cerebral small vessel disease (CSVD), via Monte Carlo simulations of magnetic susceptibility imaging and a novel imaging marker called the Expected Iron Coefficient (EIC).MethodsA synthetic pathological model of a different number of impenetrable spheres at random locations was employed to represent pathological iron deposition. The diffusion process was simulated with a Monte Carlo method with adjustable parameters to manipulate sphere size, distribution, and extracellular properties. Quantitative susceptibility mapping (QSM) was performed in a clinical dataset to study CSVD to derive and evaluate QSM, R2*, the iron microenvironment coefficient (IMC), and EIC in the presence of WMHs.ResultsThe simulations show that QSM signals increase in the presence of increased tissue iron, confirming that the EIC increases with pathology. Clinical results demonstrate that while QSM, R2*, and the IMC do not show differences in brain iron, the EIC does in the context of CSVD.ConclusionThe EIC is more sensitive to subtle changes in brain iron deposition caused by pathology, even when QSM, R2*, and the IMC do not.

scholarly journals Do white matter hyperintensities mediate the association between brain iron deposition and cognitive abilities in older people?

2016 ◽  
Vol 23 (7) ◽  
pp. 1202-1209 ◽  
Author(s):  
M. Valdés Hernández ◽  
M. Allerhand ◽  
A. Glatz ◽  
L. Clayson ◽  
S. Muñoz Maniega ◽  
...  
Keyword(s):  
White Matter ◽  
Older People ◽  
Cognitive Abilities ◽  
White Matter Hyperintensities ◽  
Iron Deposition ◽  
Brain Iron ◽  
Brain Iron Deposition

scholarly journals Brain iron deposition in white matter hyperintensities: a 3-T MRI study

AGE ◽  
2012 ◽  
Vol 35 (5) ◽  
pp. 1927-1936 ◽  
Author(s):  
Shenqiang Yan ◽  
Jianzhong Sun ◽  
Yi Chen ◽  
Magdy Selim ◽  
Min Lou
Keyword(s):  
White Matter ◽  
White Matter Hyperintensities ◽  
Iron Deposition ◽  
Brain Iron ◽  
Mri Study ◽  
Brain Iron Deposition

scholarly journals Relationship between the state coagulation system, protein and fat metabolism, and Brain iron deposition in patients with cerebral small vessel disease

2018 ◽  
pp. 13-20
Author(s):  
M. Petrenko
Keyword(s):  
Functional State ◽  
Small Vessel Disease ◽  
Cerebral Small Vessel Disease ◽  
Iron Deposition ◽  
Small Vessel ◽  
Coagulation System ◽  
Thrombin Time ◽  
Brain Iron ◽  
Vessel Disease ◽  
Brain Iron Deposition

Brain iron deposition correlates with clinical manifestations of cerebral small vessel disease. Excessive iron load leads to the formation of free radicals, and nervous tissue damage. The main damaging effect of hydroxyl radicals is due to conversion of soluble fibrinogen to insoluble fibrin. There is also a possible relationship between the functional state of the liver and the early manifestations of cardiovascular disease. Objective: to investigate the relationship between the parameters of coagulation system, liver functional state, fat and protein metabolism, and brain iron deposition in patients with cerebral small vessel disease in the presence of hypertension and cerebral atherosclerosis. Materials and methods: 80 patients with diagnosed cerebral small vessel disease were selected. Patients were divided into two groups, depending on the severity of brain iron deposition. All patients underwent MRI in the T1-WI, T2-WI, TIRM, DWI, and SWI sequences. Determination of the coagulation system parameters and the biochemical analysis were carried out during routine blood test. Results: using a double-sample t test, it was determined that patients with severe brain iron deposition had higher levels of urea, triglycerides, and prolonged thrombin time. With the logistic regression analysis adjusted by the age and sex, levels of urea and the length of thrombin time were determined as the independent risk factors for severe brain iron deposition. For urea OR 1.87, CI 95% 1.31-2.65 (p = 0.02), for thrombin time OR 1.55, CI 95% 1.06-2.26 (p = 0.02). For these parameters, the risk increased when assessing only patients with ALT levels> 15 U / l. For such patients, the relationship between thrombin time and brain iron deposition increased significantly: OR 2.11, CI 95% 1.20-3.71 (p = 0.01). In this study no relationship was found between the indicators of fat metabolism, levels of fibrin and iron deposition. There is a probable relationship between the brain iron deposition and the state of coagulation system, protein metabolism and liver functional state in patients with cerebral small vessel disease.

No evidence for increased brain iron deposition in patients with ischemic white matter disease

2016 ◽  
Vol 45 ◽  
pp. 61-63 ◽  
Author(s):  
Thomas Gattringer ◽  
Michael Khalil ◽  
Christian Langkammer ◽  
Margit Jehna ◽  
Alexander Pichler ◽  
...  
Keyword(s):  
White Matter ◽  
Iron Deposition ◽  
White Matter Disease ◽  
Brain Iron ◽  
Brain Iron Deposition

Influence of White Matter Hyperintensities on Baseline and Longitudinal Amyloid-β in Cognitively Normal Individuals

2021 ◽  
pp. 1-11
Author(s):  
Fennie Choy Chin Wong ◽  
Seyed Ehsan Saffari ◽  
Chathuri Yatawara ◽  
Kok Pin Ng ◽  
Nagaendran Kandiah ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Executive Function ◽  
White Matter ◽  
White Matter Hyperintensities ◽  
Small Vessel Disease ◽  
Amyloid Β ◽  
Intracranial Volume ◽  
Linear Regression Models ◽  
Cognitively Normal

Background: The associations between small vessel disease (SVD) and cerebrospinal amyloid-β1-42 (Aβ1-42) pathology have not been well-elucidated. Objective: Baseline (BL) white matter hyperintensities (WMH) were examined for associations with month-24 (M24) and longitudinal Aβ1-42 change in cognitively normal (CN) subjects. The interaction of WMH and Aβ1-42 on memory and executive function were also examined. Methods: This study included 72 subjects from the Alzheimer’s Disease Neuroimaging Initiative. Multivariable linear regression models evaluated associations between baseline WMH/intracranial volume ratio, M24 and change in Aβ1-42 over two years. Linear mixed effects models evaluated interactions between BL WMH/ICV and Aβ1-42 on memory and executive function. Results: Mean age of the subjects (Nmales = 36) = 73.80 years, SD = 6.73; mean education years = 17.1, SD = 2.4. BL WMH was significantly associated with M24 Aβ1-42 (p = 0.008) and two-year change in Aβ1-42 (p = 0.006). Interaction between higher WMH and lower Aβ1-42 at baseline was significantly associated with worse memory at baseline and M24 (p = 0.003). Conclusion: BL WMH was associated with M24 and longitudinal Aβ1-42 change in CN. The interaction between higher WMH and lower Aβ1-42 was associated with poorer memory. Since SVD is associated with longitudinal Aβ1-42 pathology, and the interaction of both factors is linked to poorer cognitive outcomes, the mitigation of SVD may be correlated with reduced amyloid pathology and milder cognitive deterioration in Alzheimer’s disease.

Altered Functional Connectivity Patterns of Parietal Subregions Contribute to Cognitive Dysfunction in Patients with White Matter Hyperintensities

2021 ◽  
pp. 1-11
Author(s):  
Qiang Wei ◽  
Shanshan Cao ◽  
Yang Ji ◽  
Jun Zhang ◽  
Chen Chen ◽  
...  
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
White Matter Hyperintensities ◽  
Parietal Lobe ◽  
Small Vessel Disease ◽  
Anterior Cingulate ◽  
Healthy Controls ◽  
Cingulate Gyrus ◽  
Anterior Cingulate Gyrus ◽  
Resting State Functional Connectivity

Background: The white matter hyperintensities (WMHs) are considered as one of the core neuroimaging findings of cerebral small vessel disease and independently associated with cognitive deficit. The parietal lobe is a heterogeneous area containing many subregions and play an important role in the processes of neurocognition. Objective: To explore the relationship between parietal subregions alterations and cognitive impairments in WHMs. Methods: Resting-state functional connectivity (rs-FC) analyses of parietal subregions were performed in 104 right-handed WMHs patients divided into mild (n = 39), moderate (n = 37), and severe WMHs (n = 28) groups according to the Fazekas scale and 36 healthy controls. Parietal subregions were defined using tractographic Human Brainnetome Atlas and included five subregions for superior parietal lobe, six subregions for inferior parietal lobe (IPL), and three subregions for precuneus. All participants underwent a neuropsychological test battery to evaluate emotional and general cognitive functions. Results: Differences existed between the rs-FC strength of IPL_R_6_2 with the left anterior cingulate gyrus, IPL_R_6_3 with the right dorsolateral superior frontal gyrus, and the IPL_R_6_5 with the left anterior cingulate gyrus. The connectivity strength between IPL_R_6_3 and the left anterior cingulate gyrus were correlated with AVLT-immediate and AVLT-recognition test in WMHs. Conclusion: We explored the roles of parietal subregions in WMHs using rs-FC. The functional connectivity of parietal subregions with the cortex regions showed significant differences between the patients with WMHs and healthy controls which may be associated with cognitive deficits in WMHs.

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