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 Identification of Collaterally Perfused Areas following Focal Cerebral Ischemia in the Rat by Comparison of Gradient Echo and Diffusion-Weighted MRI

1995 ◽  
Vol 15 (4) ◽  
pp. 578-586 ◽  
Author(s):  
S. A. Roussel ◽  
N. van Bruggen ◽  
M. D. King ◽  
D. G. Gadian
Keyword(s):  
Signal Intensity ◽  
Magnetic Resonance Images ◽  
Core Area ◽  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Great Promise ◽  
Gradient Echo ◽  
The Core ◽  
Extraction Fraction ◽  
Diffusion Weighted

Diffusion-weighted (DW) and gradient echo (GE) magnetic resonance images were acquired before and after occlusion of the middle cerebral artery (MCA) in the rat. Upon occlusion, an increase in DW imaging signal intensity was observed in a core area within the MCA territory, most likely reflecting cytotoxic edema. The signal from GE images, which is sensitive to changes in the absolute amount of deoxyhemoglobin, decreased following ischemia within a region that extended beyond the core area observed with DW imaging. This hypointensity is attributed to increases in blood volume and/or oxygen extraction fraction, which result from a decrease in perfusion pressure in the collaterally perfused area. The evolution of the GE imaging signal intensity from different regions was studied for 3.5 h following the occlusion. In the core area, the GE imaging signal returned towards baseline values after ∼1–2 h, while it remained stable in the surrounding area. This feature may reflect a decrease in hematocrit due to microcirculatory defect and/or a decrease in the oxygen extraction fraction due to ongoing infarction of the tissue and may indicate that tissue recovery is severely compromised. The combined use of DW and GE imaging offers great promise for the noninvasive identification of specific pathological events with high spatial resolution.

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.

scholarly journals Measurement of End-Capillary Po2 with Positron Emission Tomography

1988 ◽  
Vol 8 (3) ◽  
pp. 403-410 ◽  
Author(s):  
N. M. Alpert ◽  
R. B. Buxton ◽  
J. A. Correia ◽  
R. M. Katz ◽  
R. H. Ackerman
Keyword(s):  
Positron Emission Tomography ◽  
Oxygen Saturation ◽  
Normal Subjects ◽  
Oxygen Metabolism ◽  
Emission Tomography ◽  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Protein Levels ◽  
Extraction Fraction ◽  
Positron Emission

The analysis of positron emission tomography measurements of oxygen metabolism has been extended to provide a quantitative estimate of end-capillary Po2. The principle of this extension rests on the idea that the oxygen extraction fraction can be used to calculate the end-capillary oxygen saturation of the blood. The relation between oxygen saturation and Po2 is obtained through the oxygen dissociation curve. Our studies show that in addition to the local oxygen extraction fraction, arterial Po2 and pH values are needed in the calculation, whereas fairly large variations in factors such as Pco2, hematocrit, hemoglobin, and plasma protein levels have little or no effect. Rough estimates of end-capillary Po2 can be made using standard o2 dissociation nomograms. Blood gas and acid-base properties of blood have been known for decades, making it possible to account accurately for individual differences that may be encountered when studying patients. Measurements in nine normal subjects yielded a mean end-capillary Po2 value of 31.2 mm Hg. The ability to make a quantitative visualization of altered patterns of end-capillary Po2 provides an additional dimension to the investigation of stroke disease and tumor metabolism.

Noninvasive measurement of renal oxygen extraction fraction under the influence of respiratory challenge

2016 ◽  
Vol 44 (1) ◽  
pp. 230-237 ◽  
Author(s):  
Chengyan Wang ◽  
Rui Zhang ◽  
Rui Wang ◽  
Li Jiang ◽  
Xiaodong Zhang ◽  
...  
Keyword(s):  
Noninvasive Measurement ◽  
Oxygen Extraction Fraction ◽  
Oxygen Extraction ◽  
Extraction Fraction ◽  
Respiratory Challenge ◽  
Renal Oxygen

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.

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