Magnetic Resonance Imaging and Hypoxic — Ischemic Brain Injuries

1993 ◽  
pp. 92-118
Author(s):  
J. Haddad ◽  
J. Messer
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Injuries ◽  
Resonance Imaging ◽  
Ischemic Brain

Studying Language with Functional Magnetic Resonance Imaging (fMRI)

2019 ◽  
pp. 71-93
Author(s):  
Stefan Heim ◽  
Karsten Specht
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Brain Injuries ◽  
Late Nineteenth Century ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Online Data ◽  
The Times ◽  
Study Designs

Since the discoveries of language-sensitive brain areas in the late nineteenth century, the localization of the language network in the brain has been the subject of neurolinguistics research. Especially during the times of the two world wars and until the 1980s, head and brain injuries in soldiers as well as in civil patients served as the main data source. The advent of neuroimaging techniques roughly 100 years later was a milestone, providing online data from the living brain. This chapter presents functional magnetic resonance imaging (fMRI) as the most frequently used technique, the physical basics, appropriate experimental study designs, and perspectives for novel developments for neurolinguistics research in the active and passive brain.

scholarly journals Magnetic resonance imaging spectrum of perinatal hypoxic-ischemic brain injury

2016 ◽  
Vol 26 (3) ◽  
pp. 316 ◽  
Author(s):  
Binoj Varghese ◽  
Rose Xavier ◽  
VC Manoj ◽  
MK Aneesh ◽  
PS Priya ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Brain Injury ◽  
Magnetic Resonance ◽  
Ischemic Brain Injury ◽  
Resonance Imaging ◽  
Ischemic Brain ◽  
Hypoxic Ischemic Brain Injury

scholarly journals Neurophysiologic Profiling of At-Risk Low and Very Low Birth-Weight Infants Using Magnetic Resonance Imaging

2021 ◽  
Vol 12 ◽  
Author(s):  
Ying Qi ◽  
Jingni He
Keyword(s):  
Magnetic Resonance Imaging ◽  
Birth Weight ◽  
Magnetic Resonance ◽  
Low Birth Weight ◽  
Brain Injuries ◽  
Very Low Birth Weight ◽  
Oxygen Extraction Fraction ◽  
Resonance Imaging ◽  
Low Birth Weight Infants ◽  
Brain Physiology

Low birth-weight (LBW) and very low birth-weight (VLBW) newborns have increased risks of brain injuries, growth failure, motor difficulties, developmental coordination disorders or delay, and adult-onset vascular diseases. However, relatively little is known of the neurobiologic underpinnings. To clarify the pathophysiologic vulnerabilities of such neonates, we applied several advanced techniques for assessing brain physiology, namely T2-relaxation-under-spin-tagging (TRUST) magnetic resonance imaging (MRI) and phase-contrast (PC) MRI. This enabled quantification of oxygen extraction fraction (OEF), global cerebral blood flow (CBF), and cerebral metabolic rate of oxygen (CMRO2). A total of 50 neonates (LBW-VLBW, 41; term controls, 9) participated in this study. LBW-VLBW neonates were further stratified as those with (LBW-VLBW-a, 24) and without (LBW-VLBW-n, 17) structural MRI (sMRI) abnormalities. TRUST and PC MRI studies were undertaken to determine OEF, CBF, and CMRO2. Ultimately, CMRO2 proved significantly lower (p = 0.01) in LBW-VLBW (vs term) neonates, both LBW-VLBW-a and LBW-VLBW-n subsets showing significantly greater physiologic deficits than term controls (p = 0.03 and p = 0.04, respectively). CMRO2 and CBF in LBW-VLBW-a and LBW-VLBW-n subsets did not differ significantly (p > 0.05), although OEF showed a tendency to diverge (p = 0.15). However, OEF values in the LBW-VLBW-n subset differed significantly from those of term controls (p = 0.02). Compared with brain volume or body weight, these physiologic parameters yield higher area-under-the-curve (AUC) values for distinguishing neonates of the LBW-VLBW-a subset. The latter displayed distinct cerebral metabolic and hemodynamic, whereas changes were marginal in the LBW-VLBW-n subset (i.e., higher OEF and lower CBF and CMRO2) by comparison. Physiologic imaging may therefore be useful in identifying LBW-VLBW newborns at high risk of irreversible brain damage.

Abstract W P171: Findings of Magnetic Resonance Imaging and Carotid Duplex as Predictors of Recurrent Brain Infarction -Bingo Cerebral Infarction Study 1-

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Kiyoshi Nakazaki ◽  
Shinichi Takeshima ◽  
Masaru Kuriyama
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Cerebral Infarction ◽  
Artery Stenosis ◽  
Lacunar Infarction ◽  
Resonance Imaging ◽  
Ischemic Brain ◽  
Inversion Recovery Imaging ◽  
Carotid Duplex

Introduction: To retrospectively evaluate whether findings of magnetic resonance imaging (MRI) and carotid duplex are predictors of recurrent cerebral infarction. Methods: Between 2007 and 2010, 1324 patients underwent carotid duplex, magnetic resonance angiography, fluid-attenuated inversion recovery imaging, and T2*-weighted imaging during first admission for cerebral infarction and were discharged with a modified Rankin Scale (mRS) score of 0-3. Of the 1324 patients, 1138 (86.0%) were followed up (median age, 70 years; male:female ratio, 64%:36%). Atherothrombotic infarction, lacunar infarction, cardiogenic embolism, and other infarctions occurred in 435, 430, 246, and 27 patients, respectively. Results: The median follow-up duration was 44.5 months; 84.4% patients underwent follow-up MRI. New ischemic brain events occurred in 213 patients (18.7%). Transient ischemic attack occurred as the first new ischemic brain event in 44 patients. New asymptomatic cerebral infarction appeared in 100 patients before or without new ischemic brain events. Symptomatic cerebral infarction (SCI) recurred in 172 cases (15.1%), and the median duration between discharge and recurrence was 18.6 months (range, 0.2-69.5 months). Atherothrombotic infarction, lacunar infarction, and cardiogenic embolism recurred in 64, 64, and 42 patients, respectively. At the last follow-up, mRS score was 0-3 in 1029 patients and 27 patients died. Intracranial artery stenosis and micro-bleeding were significant predictors of SCI after lacunar infarction. Pre-admission asymptomatic old cerebral infarction was a significant predictor of SCI after 3 subtypes. Internal carotid artery stenosis >50% on carotid duplex was a significant predictor of SCI after atherothrombotic infarction. Conclusion: Findings of MRI and carotid duplex may be important predictors of recurrent cerebral infarction.

scholarly journals Integrative Analysis of Circulating Metabolite Profiles and Magnetic Resonance Imaging Metrics in Patients with Traumatic Brain Injury

2020 ◽  
Vol 21 (4) ◽  
pp. 1395 ◽  
Author(s):  
Ilias Thomas ◽  
Alex M. Dickens ◽  
Jussi P. Posti ◽  
Mehrbod Mohammadian ◽  
Christian Ledig ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Brain Injury ◽  
Magnetic Resonance ◽  
Structural Changes ◽  
Brain Injuries ◽  
Brain Morphology ◽  
Learning Approaches ◽  
Resonance Imaging ◽  
Serum Samples ◽  
The Impact

Recent evidence suggests that patients with traumatic brain injuries (TBIs) have a distinct circulating metabolic profile. However, it is unclear if this metabolomic profile corresponds to changes in brain morphology as observed by magnetic resonance imaging (MRI). The aim of this study was to explore how circulating serum metabolites, following TBI, relate to structural MRI (sMRI) findings. Serum samples were collected upon admission to the emergency department from patients suffering from acute TBI and metabolites were measured using mass spectrometry-based metabolomics. Most of these patients sustained a mild TBI. In the same patients, sMRIs were taken and volumetric data were extracted (138 metrics). From a pool of 203 eligible screened patients, 96 met the inclusion criteria for this study. Metabolites were summarized as eight clusters and sMRI data were reduced to 15 independent components (ICs). Partial correlation analysis showed that four metabolite clusters had significant associations with specific ICs, reflecting both the grey and white matter brain injury. Multiple machine learning approaches were then applied in order to investigate if circulating metabolites could distinguish between positive and negative sMRI findings. A logistic regression model was developed, comprised of two metabolic predictors (erythronic acid and myo-inositol), which, together with neurofilament light polypeptide (NF-L), discriminated positive and negative sMRI findings with an area under the curve of the receiver-operating characteristic of 0.85 (specificity = 0.89, sensitivity = 0.65). The results of this study show that metabolomic analysis of blood samples upon admission, either alone or in combination with protein biomarkers, can provide valuable information about the impact of TBI on brain structural changes.

scholarly journals Repeated mild traumatic brain injuries induce persistent changes in plasma protein and magnetic resonance imaging biomarkers in the rat

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
David K. Wright ◽  
Rhys D. Brady ◽  
Alaa Kamnaksh ◽  
Jack Trezise ◽  
Mujun Sun ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Plasma Protein ◽  
Brain Injuries ◽  
Imaging Biomarkers ◽  
Resonance Imaging ◽  
Transient Nature ◽  
Neurological Abnormalities ◽  
Magnetic Resonance Imaging Mri ◽  
And Diffusion

Abstract A single mild traumatic brain injury (mTBI) typically causes only transient symptoms, but repeated mTBI (RmTBI) is associated with cumulative and chronic neurological abnormalities. Clinical management of mTBI is challenging due to the heterogeneous, subjective and transient nature of symptoms, and thus would be aided by objective biomarkers. Promising biomarkers including advanced magnetic resonance imaging (MRI) and plasma levels of select proteins were examined here in a rat model of RmTBI. Rats received either two mild fluid percussion or sham injuries administered five days apart. Rats underwent MRI and behavioral testing 1, 3, 5, 7, and 30 days after the second injury and blood samples were collected on days 1, 7, and 30. Structural and diffusion-weighted MRI revealed that RmTBI rats had abnormalities in the cortex and corpus callosum. Proteomic analysis of plasma found that RmTBI rats had abnormalities in markers indicating axonal and vascular injury, metabolic and mitochondrial dysfunction, and glial reactivity. These changes occurred in the presence of ongoing cognitive and sensorimotor deficits in the RmTBI rats. Our findings demonstrate that RmTBI can result in chronic neurological abnormalities, provide insight into potential contributing pathophysiological mechanisms, and supports the use of MRI and plasma protein measures as RmTBI biomarkers.

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