Non-invasive MRI measurements of venous oxygenation, oxygen extraction fraction and oxygen consumption in neonates

NeuroImage ◽  
2014 ◽  
Vol 95 ◽  
pp. 185-192 ◽  
Author(s):  
J.B. De Vis ◽  
E.T. Petersen ◽  
T. Alderliesten ◽  
F. Groenendaal ◽  
L.S. de Vries ◽  
...  
Keyword(s):  
Oxygen Consumption ◽  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Non Invasive ◽  
Extraction Fraction ◽  
Mri Measurements

Abstract 153: Non-invasive Measurement of Cerebral Tissue Oxygen Extraction Fraction is Correlated with Microdialysis Brain Injury Biomarkers During Extracorporeal Cardiopulmonary Resuscitation

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_4) ◽  
Author(s):  
Tiffany S Ko ◽  
Julia Slovis ◽  
Lindsay Volk ◽  
Constantine D Mavroudis ◽  
Ryan W Morgan ◽  
...  
Keyword(s):  
Brain Injury ◽  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Neurological Injury ◽  
Tissue Oxygen ◽  
Cerebral Tissue ◽  
Extracorporeal Cardiopulmonary Resuscitation ◽  
Glucose Content ◽  
Non Invasive ◽  
Extraction Fraction

Introduction: Extracorporeal membrane oxygenation (ECMO) assisted CPR (ECPR) can improve outcomes after prolonged or unsuccessful resuscitative efforts, but neurological injury remains common in survivors. The lack of routine neuromonitoring during ECPR and ECMO prohibits brain-targeted management to help improve neurological outcomes. In this study, we examine the association of non-invasive, frequency-domain diffuse optical spectroscopy (FD-DOS) measurements of cerebral tissue oxygen extraction fraction (OEF), an indicator of metabolic stress, with invasively collected brain injury biomarkers to explore the utility of this monitoring modality during ECPR. Hypothesis: FD-DOS measurement of cerebral OEF is positively correlated with biomarkers of brain injury (lactate-pyruvate ratio, LPR; glycerol). Methods: Cerebral OEF was continuously monitored by FD-DOS in nine pediatric swine (8-11 kg) who underwent 30-60 minutes of manual CPR, were cannulated for ECMO, and remained on ECMO for 22-24 hours. Cerebral pyruvate, lactate, glycerol and glucose content were measured from cerebral microdialysate samples collected hourly. The correlation between OEF and microdialysis parameters were assessed using a linear mixed-effects model incorporating subject-specific random slope and intercept effects. Significance was determined at p<0.05. Results: Microdialysis parameters from 192 samples were compared against non-invasive OEF values. OEF was significantly correlated with LPR (p=0.001), and relative change in glycerol (p=0.005) and glucose (p=0.020) concentrations from baseline. Conclusions: Non-invasive FD-DOS neuromonitoring of OEF demonstrated significant correlations with invasive brain injury biomarkers; increasing OEF was associated with elevated LPR and glycerol, and diminished glucose. FD-DOS detection of critical neurometabolic stress at the bedside may facilitate brain-targeted ECMO management after cardiac arrest.

Non-invasive multiparametric qBOLD approach for robust mapping of the oxygen extraction fraction

2014 ◽  
Vol 24 (3) ◽  
pp. 231-242 ◽  
Author(s):  
Sebastian Domsch ◽  
Moritz B. Mie ◽  
Frederik Wenz ◽  
Lothar R. Schad
Keyword(s):  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Non Invasive ◽  
Extraction Fraction

scholarly journals Non-invasive imaging of oxygen extraction fraction in adults with sickle cell anaemia

Brain ◽  
2016 ◽  
Vol 139 (3) ◽  
pp. 738-750 ◽  
Author(s):  
Lori C. Jordan ◽  
Melissa C. Gindville ◽  
Allison O. Scott ◽  
Meher R. Juttukonda ◽  
Megan K. Strother ◽  
...  
Keyword(s):  
Sickle Cell ◽  
Sickle Cell Anaemia ◽  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Non Invasive ◽  
Extraction Fraction

scholarly journals A frequency-domain machine learning method for dual-calibrated fMRI mapping of oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO2)

2019 ◽  
Author(s):  
Michael Germuska ◽  
Hannah Chandler ◽  
Thomas Okell ◽  
Fabrizio Fasano ◽  
Valentina Tomassini ◽  
...  
Keyword(s):  
Machine Learning ◽  
Blood Flow ◽  
Oxygen Consumption ◽  
Oxygen Metabolism ◽  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Single Subject ◽  
Extraction Fraction ◽  
Wide Range ◽  
Calibrated Fmri

AbstractMagnetic resonance imaging (MRI) offers the possibility to non-invasively map the brain’s metabolic oxygen consumption (CMRO2), which is essential for understanding and monitoring neural function in both health and disease. However, in depth study of oxygen metabolism with MRI has so far been hindered by the lack of robust methods. One MRI method of mapping CMRO2 is based on the simultaneous acquisition of cerebral blood flow (CBF) and blood oxygen level dependent (BOLD) weighted images during respiratory modulation of both oxygen and carbon dioxide. Although this dual-calibrated methodology has shown promise in the research setting, current analysis methods are unstable in the presence of noise and/or are computationally demanding. In this paper, we present a machine learning implementation for the multi-parametric assessment of dual-calibrated fMRI data. The proposed method aims to address the issues of stability, accuracy, and computational overhead, removing significant barriers to the investigation of oxygen metabolism with MRI. The method utilizes a time-frequency transformation of the acquired perfusion and BOLD-weighted data, from which appropriate feature vectors are selected for training of machine learning regressors. The implemented machine learning methods are chosen for their robustness to noise and their ability to map complex non-linear relationships (such as those that exist between BOLD signal weighting and blood oxygenation). An extremely randomized trees (ET) regressor is used to estimate resting blood flow and a multi-layer perceptron (MLP) is used to estimate CMRO2 and the oxygen extraction fraction (OEF). Synthetic data with additive noise are used to train the regressors, with data simulated to cover a wide range of physiologically plausible parameters. The performance of the implemented analysis method is compared to published methods both in simulation and with in-vivo data (n=30). The proposed method is demonstrated to significantly reduce computation time, error, and proportional bias in both CMRO2 and OEF estimates. The introduction of the proposed analysis pipeline has the potential to not only increase the detectability of metabolic difference between groups of subjects, but may also allow for single subject examinations within a clinical context.

scholarly journals Cerebral oxygen extraction fraction (OEF): Comparison of challenge-free gradient echo QSM+qBOLD (QQ) with 15O PET in healthy adults

2020 ◽  
pp. 0271678X2097395
Author(s):  
Junghun Cho ◽  
John Lee ◽  
Hongyu An ◽  
Manu S Goyal ◽  
Yi Su ◽  
...  
Keyword(s):  
Region Of Interest ◽  
Oxygen Metabolism ◽  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Gradient Echo ◽  
Blood Oxygen Level ◽  
Non Invasive ◽  
Extraction Fraction ◽  
Respiratory Challenge ◽  
Arterial Input Functions

We aimed to validate oxygen extraction fraction (OEF) estimations by quantitative susceptibility mapping plus quantitative blood oxygen-level dependence (QSM+qBOLD, or QQ) using 15O-PET. In ten healthy adult brains, PET and MRI were acquired simultaneously on a PET/MR scanner. PET was acquired using C[15O], O[15O], and H2[15O]. Image-derived arterial input functions and standard models of oxygen metabolism provided quantification of PET. MRI included T1-weighted imaging, time-of-flight angiography, and multi-echo gradient-echo imaging that was processed for QQ. Region of interest (ROI) analyses compared PET OEF and QQ OEF. In ROI analyses, the averaged OEF differences between PET and QQ were generally small and statistically insignificant. For whole brains, the average and standard deviation of OEF was 32.8 ± 6.7% for PET; OEF was 34.2 ± 2.6% for QQ. Bland-Altman plots quantified agreement between PET OEF and QQ OEF. The interval between the 95% limits of agreement was 16.9 ± 4.0% for whole brains. Our validation study suggests that respiratory challenge-free QQ-OEF mapping may be useful for non-invasive clinical assessment of regional OEF impairment.

scholarly journals Oxygen Extraction Fraction at Maximally Vasodilated Tissue in the Ischemic Brain Estimated from the Regional CO2 Responsiveness Measured by Positron Emission Tomography

1988 ◽  
Vol 8 (2) ◽  
pp. 227-235 ◽  
Author(s):  
Iwao Kanno ◽  
Kazuo Uemura ◽  
Schuichi Higano ◽  
Matsutaro Murakami ◽  
Hidehiro Iida ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Resting State ◽  
Emission Tomography ◽  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Cross Point ◽  
Steady State Method ◽  
Extraction Fraction ◽  
Positron Emission ◽  
Vascular Responsiveness

The oxygen extraction fraction (OEF) at maximally vasodilated tissue in patients with chronic cerebrovascular disease was evaluated using positron emission tomography. The vascular responsiveness to changes in PaCO2 was measured by the H215O autoradiographic method. It was correlated with the resting-state OEF, as estimated using the 15O steady-state method. The subjects comprised 15 patients with unilateral or bilateral occlusion and stenosis of the internal carotid artery or middle cerebral artery or moyamoya disease. In hypercapnia, the scattergram between the OEF and the vascular responsiveness to changes in PaCO2 revealed a significant negative correlation in 11 of 19 studies on these patients, and the OEF at the zero cross point of the regression line with a vascular responsiveness of 0 was 0.53 ± 0.08 (n = 11). This OEF in the resting state corresponds to exhaustion of the capacity for vasodilation. The vasodilatory capacity is discussed in relation to the lower limit of autoregulation.

scholarly journals Quantifying the changes in oxygen extraction fraction and cerebral activity caused by caffeine and acetazolamide

2016 ◽  
Vol 37 (3) ◽  
pp. 825-836 ◽  
Author(s):  
Sagar Buch ◽  
Yongquan Ye ◽  
E Mark Haacke
Keyword(s):  
Oxygen Saturation ◽  
A Priori ◽  
Susceptibility Mapping ◽  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Cerebral Veins ◽  
Blood Oxygen Saturation ◽  
Vascular Reserve ◽  
Extraction Fraction ◽  
Before And After

A quantitative estimate of cerebral blood oxygen saturation is of critical importance in the investigation of cerebrovascular disease. We aimed to measure the change in venous oxygen saturation (Yv) before and after the intake of the vaso-dynamic agents caffeine and acetazolamide with high spatial resolution using susceptibility mapping. Caffeine and acetazolamide were administered on separate days to five healthy volunteers to measure the change in oxygen extraction fraction. The internal streaking artifacts in the susceptibility maps were reduced by giving an initial susceptibility value uniformly to the structure-of-interest, based on a priori information. Using this technique, Yv for normal physiological conditions, post-caffeine and post-acetazolamide was measured inside the internal cerebral veins as YNormal = 69.1 ± 3.3%, YCaffeine = 60.5 ± 2.8%, and YAcet = 79.1 ± 4.0%. This suggests that susceptibility mapping can serve as a sensitive biomarker for measuring reductions in cerebro-vascular reserve through abnormal vascular response. The percentage change in oxygen extraction fraction for caffeine and acetazolamide were found to be +27.0 ± 3.8% and −32.6 ± 2.1%, respectively. Similarly, the relative changes in cerebral blood flow in the presence of caffeine and acetazolamide were found to be −30.3% and + 31.5%, suggesting that the cerebral metabolic rate of oxygen remains stable between normal and challenged brain states for healthy subjects.

Sign in / Sign up

Export Citation Format

Share Document