Blood oxygen saturation assessment in vivo using T2 * estimation

Li, Debiao; Wang, Yi; Waight, David J.

doi:10.1002/mrm.1910390503

Cited by 89 publications

(82 citation statements)

References 17 publications

(25 reference statements)

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“…These values are slightly different from those given in Ref. 10 and contain the experimental results of Li et al (29) for the T* 2 values of blood at 1.5T in dependence of the oxygenation. In Ref.…”

Section: Appendixcontrasting

confidence: 97%

A qualitative test of the balloon model for BOLD‐based MR signal changes at 3T

Mildner¹,

Norris²,

Schwarzbauer³

et al. 2001

Magn. Reson. Med.

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The aim of this study was to adapt the balloon model for BOLDbased MR signal changes to a magnetic field strength of 3T and to examine its validity. The simultaneous measurement of BOLD and diffusion-weighted BOLD responses was performed. The amplitude of the BOLD peak was found to be similar for all subjects when a short visual stimulus of 6 sec was used. The rise-time to the BOLD peak and the shape and depth of the poststimulus undershoot varied significantly. A fit of the experimental BOLD responses was found to be possible by use of parameters within a reasonable physiological range. The relations between these parameters and their influence on the modeled BOLD responses is discussed. A prediction of the balloon model is the occurrence of a BOLD overshoot, i.e., a lag between the changes of the blood volume and the blood flow after the start of the stimulation. Functional MRI is based on measuring the local changes in the blood oxygenation level dependent (BOLD) contrast that occur as a consequence of neuronal activation in the brain (1-3). The change in the MR signal is determined by alterations in the concentration of paramagnetic deoxyhemoglobin, which modifies the effective transverse relaxation time T* 2 . Increases in oxygen consumption and blood volume lead to an increase in the deoxyhemoglobin content and hence to a decreased MR signal, whereas increases in blood flow have the opposite effect (4). Although considerable progress has been made in measuring the changes in oxygen consumption (5-7), blood volume (8,9), and cerebral blood flow (6,10,11), the transient response in the BOLD signal is still not completely understood. It can be divided into three intervals: the fast response (12-15), during which the signal change is negative, the period of elevated signal, and the poststimulus undershoot (3). In order to understand the origins of these signal changes it is desirable to relate the BOLD signal directly to the relevant physiological parameters.The most prominent approach developed to date for modeling the BOLD signal under nonsteady-state conditions is given by the balloon model of Buxton et al. (10). Based on the experimental work of Mandeville et al. (8), who showed that changes in blood volume occur subsequent to changes in blood flow, it considers the vasculature contributing to the BOLD signal as a swelling balloon. The basis of the model is a differential equation system for the blood volume and the total deoxyhemoglobin content, combined with an expression for the total signal change. The results of simulations for the intra-and extravascular signal contributions (16,17) and the oxygen limitation model (18) were used in order to derive time courses for the BOLD signal response.In order to study the time courses of the deoxyhemoglobin concentration and the blood volume in detail it is advantageous if the contributions of the intra-and extravascular spaces can be evaluated separately. This may be achieved by using a weak diffusion weighting to suppress the signal from the intravascular comp...

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Section: Appendixcontrasting

confidence: 97%

A qualitative test of the balloon model for BOLD‐based MR signal changes at 3T

Mildner¹,

Norris²,

Schwarzbauer³

et al. 2001

Magn. Reson. Med.

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“…11 The locally increased ratio of deoxyhaemoglobin to oxyhaemoglobin in cortical and medullary veins might be an expression of ischaemia and represent the degree of hypoperfusion and oxygen extraction. 20,21 Several studies have indeed shown an association between T 2 * signal drop and increased oxygen extraction fraction. 20,21 Since the oxygen extraction fraction is increased in the ischaemic penumbra, some authors suggested that prominent hypointense veins on SWI could possibly represent the penumbra.…”

Section: Discussionmentioning

confidence: 99%

“…20,21 Several studies have indeed shown an association between T 2 * signal drop and increased oxygen extraction fraction. 20,21 Since the oxygen extraction fraction is increased in the ischaemic penumbra, some authors suggested that prominent hypointense veins on SWI could possibly represent the penumbra. 4,7 Such a penumbra may diminish, as reperfusion is achieved via intervention, or a new perfusion balance is achieved through collateral veins.…”

Section: Discussionmentioning

confidence: 99%

Prominent cortical and medullary veins on susceptibility-weighted images of acute ischaemic stroke

Payabvash¹,

Benson²,

Taleb³

et al. 2016

The British Journal of Radiology

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Objective: To determine the clinical and imaging implications of prominent cortical and medullary veins on susceptibility-weighted images (SWI) of patients with acute stroke. Methods: Consecutive patients with acute ischaemic stroke who had SWI scan within 24 h of symptom onset or time last-seen-well were included. The SWI series were reviewed for the presence of prominent cortical and medullary veins and were graded independently by two neuroradiologists. The correlations between prominent vein grades with different imaging and clinical variables were determined. Results: Among 213 patients, prominent SWI cortical and medullary veins were identified in 35 (16.4%) patients and 20 (9.4%) patients, respectively. There was fair interobserver agreement (k 5 0.314-0.338, p # 0.001) for grading, and moderate agreement (k 5 0.406-0.413, p # 0.001) for the presence of prominent veins. Both prominent cortical and medullary veins were associated with the presence of arterial occlusion (rho 5 0.232, p 5 0.001; rho 5 0.180, p 5 0.008; respectively) and larger infarct volume (rho 5 0.445, p , 0.001; rho 5 0.167, p 5 0.015; respectively). However, neither cortical nor medullary cortical veins were associated with the severity of symptoms at admission or clinical outcome. Prominent cortical veins were independent predictors of arterial occlusion (p 5 0.018), whereas prominent medullary veins were more strongly associated with larger infarct volumes (p , 0.001). Conclusion: There were small but significant correlations between cortical and medullary veins on SWI with arterial occlusion and large infarct volume in acute ischaemic stroke. Advances in knowledge: In consecutive patients with acute ischaemic stroke within anterior and posterior circulation territories, prominent cortical and medullary veins on SWI series are associated with imaging biomarkers of poor clinical outcome (i.e. large infarct volume and major arterial occlusion).

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“…Li et al (44) have also estimated human blood R* 2 as a function of oxygenation level with a gradient-echo sequence. Although the sample Hct is not reported in their study, the exponential relaxation rate constant, R* 2 , that they report for fully oxygenated blood seems to be somewhat large at 7.2 sec -1 for a blood sample with normal Hct level.…”

Section: Discussionmentioning

confidence: 99%

Water proton MR properties of human blood at 1.5 Tesla: Magnetic susceptibility,T₁,T₂,T, and non‐Lorentzian signal behavior

Spees¹,

Yablonskiy²,

Oswood³

et al. 2001

Magnetic Resonance in Med

432

509

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Knowledge of the 1 H magnetic properties of blood is important for developing models of the MR signal behavior in, for instance, the BOLD effect (1). Such models of free induction decay (FID) or spin echo (SE) experiments require accurate knowledge of the blood susceptibility and relaxation parameters as a function of blood oxygenation level. The blood signal is especially important in situations where the volume of interest contains large vessels and a major signal component arises directly from the MR behavior of bulk blood.It is widely assumed, and has been used in several modeling reports, that blood relaxation in the FID experiment can be described as pure Lorentzian behavior of the blood signal magnitude: S(t) ϰ exp(-R* 2 ⅐ t). It is shown herein that a substantial oxygenation-level-dependent non-Lorentzian component is an attribute of the bulk blood signal relaxation.As a note on nomenclature, the reader is reminded that exponential signal decay in the time domain (S(t) ϰ exp(-R* 2 ⅐ t)) leads to a Lorentzian lineshape (S() ϰ R* 2 / R* 2 2 ϩ 2 ) in the frequency domain. Herein we use the term "Lorentzian behavior" to describe frequency domain and time domain signal characteristics interchangeably. Likewise, Gaussian signal decay in the time domain (S(t) ϰ exp(-AR* ⅐ t 2 )) leads to a Gaussian lineshape (S() ϰ exp(-2 /4AR*)) in the frequency domain. As will be shown in this work, a Gaussian component arises in empirical modeling of the first 100 msec of the blood time domain signal magnitude. However, this is only a useful approximation. Time domain data demonstrate small (less than 2%) but significant systematic deviations from our empirical model, a simple product of Lorentzian and Gaussian components. To emphasize the fact that our empirical model does not fully account for the blood signal's relaxation characteristics (and that the model is not based on a biophysical model of blood magnetic properties) we use the generic phrase "non-Lorentzian signal behavior" to indicate as yet unexplained deviations from pure exponential/Lorentzian characteristics.Studies of the magnetic properties of human blood have been undertaken previously, and the results were insightful (2-13). However, as BOLD-related functional MRI (fMRI) procedures increase in precision, there is need to ensure the quantitative nature of the blood MR parameters upon which interpretation of experimental results may depend. Previous blood MR literature describes varying degrees of mismatch between the experimental conditions used for in vitro studies and human blood in situ. These differences include temperature (6,13,14), pH (13), and the settling of erythrocytes from plasma in the case of static samples (3,5-7,10 -12,14). Further, the relaxation rate constants in whole blood depend on magnetic field strength (3,6); hence it is important to determine these relaxation parameters at magnetic field strengths typical of human imaging systems.Of the in vitro studies cited herein, only two ensured a continuous mixing of the blood sample in order t...

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Blood oxygen saturation assessment in vivo using T₂ * estimation

Cited by 89 publications

References 17 publications

A qualitative test of the balloon model for BOLD‐based MR signal changes at 3T

A qualitative test of the balloon model for BOLD‐based MR signal changes at 3T

Prominent cortical and medullary veins on susceptibility-weighted images of acute ischaemic stroke

Water proton MR properties of human blood at 1.5 Tesla: Magnetic susceptibility,T₁,T₂,T, and non‐Lorentzian signal behavior

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Blood oxygen saturation assessment in vivo using T2 * estimation

Cited by 89 publications

References 17 publications

A qualitative test of the balloon model for BOLD‐based MR signal changes at 3T

A qualitative test of the balloon model for BOLD‐based MR signal changes at 3T

Prominent cortical and medullary veins on susceptibility-weighted images of acute ischaemic stroke

Water proton MR properties of human blood at 1.5 Tesla: Magnetic susceptibility,T1,T2,T, and non‐Lorentzian signal behavior

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Blood oxygen saturation assessment in vivo using T₂ * estimation

Water proton MR properties of human blood at 1.5 Tesla: Magnetic susceptibility,T₁,T₂,T, and non‐Lorentzian signal behavior