Quantitative mapping of cerebral deoxyhemoglobin content using MR imaging

Fujita, Norihiko; Shinohara, Masaaki; Tanaka, Hisashi; Yutani, Kenji; Nakamura, Hajime; Murase, Kenya

doi:10.1016/j.neuroimage.2003.06.002

Cited by 33 publications

(51 citation statements)

References 39 publications

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“…Hoge et al employed a graded challenge of 1.25-5% CO 2 , rather than a single 5% CO 2 inhalation, which produced a resultant increase in CBF of only 5-20% and which might have resulted in a difference in the evaluation of R 0 2 dHb . In this study, the measurement error for R 0 2 dHb was calculated to be relatively large-0.68 AE 0.34 s À1 (n ¼ 8) -from an error propagation analysis (14,26) based on the measured SNRs of the original GESFIDE and CPMG images. However, the standard deviation of the calculated R 0 2 dHb values for individual subjects in the previous studies appeared even greater than that of the directly measured R 0 2 dHb in our study, as shown in Fig.…”

Section: Discussionmentioning

confidence: 99%

“…Using a time-efficient measurement of R 2 * and R 2 with a modified spin-echo sequence -the gradient-echo sampling of FID and echo (GESFIDE) sequence (26) -An and co-workers (12,13) performed R 2 0 measurements in the brain and estimated the dHb content and venous fraction of CBV and OEF. In this study, using a modified version of their method (14), we performed quantitative mapping of baseline R 0 2 dHb . The method is briefly described below.…”

Section: Methodsmentioning

confidence: 99%

“…, where the second term on the right represents the correction term for multiexponential signal decay of brain parenchyma (14).…”

Section: Methodsmentioning

confidence: 99%

“…In this paper, we propose an alternative approach for calibrating the BOLD signal with the advantage of requiring no hypercapnic intervention. This method is based on a direct quantification of the baseline dHb content by analyzing the relaxation processes of the transverse magnetization (12)(13)(14). We show that for normal volunteers, a quantitative map of fractional CMRO 2 change in response to visual stimulation is obtained from measurements of CBF and BOLD in addition to baseline dHb quantification for calibrating the BOLD signal response.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative study of changes in oxidative metabolism during visual stimulation using absolute relaxation rates

et al. 2006

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In the context of quantitative functional MRI (fMRI), deoxyhemoglobin (dHb) content is the essential physiological parameter for calibrating the blood oxygenation level-dependent (BOLD) signal. In studies on humans, the baseline dHb content or its equivalent has been evaluated indirectly by means of carbon dioxide breathing as a physiological reference condition. In this study with normal volunteers, quantitative mapping of baseline dHb content was performed in a direct manner by measuring the reversible contribution of the effective transverse relaxation rate. The BOLD signal change in the visual cortex during 8 Hz flicker visual stimulation was calibrated based on the quantitative map of baseline dHb content. The calibrated relaxation rate change that represents the stimulation-induced fractional change of dHb content decreased by 14% within the activated visual cortex. Simultaneous measurement of cerebral blood flow (CBF) with BOLD showed an increase of 59%. From the calibrated relaxation rate and CBF changes, the cerebral metabolic rate of oxygen (CMRO2) was calculated to increase by 19-28% within the activated visual cortex. The ratio of the CBF increase to the CMRO2 increase was 2-3:1, which agreed well with results of similar quantitative fMRI studies for humans. The method proposed here for quantitative evaluation of the BOLD signal may be applicable not only to fMRI for normal human subjects, but also to physiologically altered or diseased states, because it requires no physiological perturbation.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…, where the second term on the right represents the correction term for multiexponential signal decay of brain parenchyma (14).…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantitative study of changes in oxidative metabolism during visual stimulation using absolute relaxation rates

et al. 2006

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“…To get accurate estimates of tissue parameters the signal from extracellular fluid must also be accounted for (10,19). We follow the approach of He and Yablonskiy (11) in which the signal from extracellular fluid is modeled as:…”

Section: ½4mentioning

confidence: 99%

Quantitative BOLD: The effect of diffusion

Dickson

Ash

Williams

et al. 2010

Magnetic Resonance Imaging

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Purpose: To make the quantitative blood oxygenation level-dependent (qBOLD) method more suitable for clinical application by accounting for proton diffusion and reducing acquisition times. Materials and Methods:Monte Carlo methods are used to simulate the signal from diffusing protons in the presence of a blood vessel network. A diffusive qBOLD model was then constructed using a lookup table of the results. Acquisition times are reduced by parallel imaging and by employing an integrated fieldmapping method, rather than running an additional sequence.Results: The addition of diffusion to the model is shown to have a significant impact on predicted signal formation. This is found to affect all fitted parameters when the model is applied to real data. Parallel imaging and integrated fieldmapping allowed the GESSE (gradient echo sampling of a spin echo) acquisition to be made in less than 10 minutes while maintaining high signal-to-noise ratio (SNR). Conclusion:By incorporating integrated field mapping and parallel imaging techniques, GESSE data were acquired within clinically acceptable acquisition times. These data fit closely to the diffusive qBOLD model, providing more realistic and robust measurements of T 2 and blood oxygenation than the static model.

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Quantitative BOLD: Mapping of human cerebral deoxygenated blood volume and oxygen extraction fraction: Default state

He¹,

Yablonskiy²

2006

Magnetic Resonance in Med

353

509

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The fundamental discovery by Ogawa and coworkers (1) of blood oxygenation level-dependent (BOLD) contrast in MRI opened up broad opportunities to study the hemodynamic properties of the brain. While the "dynamic" properties of BOLD contrast during functional activation have received much consideration, very little attention has been paid to the nature of BOLD contrast during the resting or baseline state of the brain. Raichle et al. (2) identified the baseline state of the normal human brain in terms of the brain tissue oxygen extraction fraction (OEF). OEF maps in subjects who are resting quietly with their eyes closed define a baseline level of neuronal activity. OEF maps in normal resting humans demonstrate remarkable uniformity despite substantial regional variations in CBF and CMRO 2 (3,4). Understanding brain function in the baseline state is important for understanding normal human performance because it accounts for most of the enormous energy budget of the brain, whereas evoked activity represents very small incremental changes (5). Such an understanding is also crucial for deciphering the consequences of baseline-state impairment by diseases of the brain such as stroke (6) and Alzheimer's disease (7,8). Importantly, the OEF has been shown to be an accurate predictor of subsequent stroke occurrence in patients with cerebrovascular disease (9,10). Previous studies were conducted using PET imaging techniques; however, such studies would be more available for research and clinical applications if they could be performed based on MRI methods. One such MRI approach is discussed in this article.The magnetic field inside practically any system that is put into an MRI scanner is always inhomogeneous. The relative scale of this inhomogeneity compared to an imaging voxel can be roughly divided into three categories: macroscopic, mesoscopic, and microscopic (11). These three types of inhomogeneities all affect MRI signal formation. The macroscopic scale refers to magnetic field changes that occur over distances that are larger than the dimensions of the imaging voxel. Macroscopic field inhomogeneities arise from magnet imperfections, body-air interfaces, large (compared to voxel size) sinuses inside the body, etc. These field inhomogeneities are mostly undesirable in MRI because they generally provide no information of physiologic or anatomic interest. Rather, they lead to effects such as signal loss in gradient-echo (GRE) imaging, and image spatial distortions in both GRE and spin-echo (SE) imaging. The microscopic scale refers to changes in magnetic field over distances that are comparable to atomic and molecular lengths (i.e., over distances that are orders of magnitude smaller than the imaging voxel dimensions). Fluctuating microscopic field inhomogeneities lead to the irreversible signal dephasing characterized by the T 2 relaxation time constant, as well as to the longitudinal magnetization changes characterized by the T 1 relaxation time constant. The mesoscopic scale refers to distances that are smaller th...

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Quantitative mapping of cerebral deoxyhemoglobin content using MR imaging

Cited by 33 publications

References 39 publications

Quantitative study of changes in oxidative metabolism during visual stimulation using absolute relaxation rates

Quantitative study of changes in oxidative metabolism during visual stimulation using absolute relaxation rates

Quantitative BOLD: The effect of diffusion

Quantitative BOLD: Mapping of human cerebral deoxygenated blood volume and oxygen extraction fraction: Default state

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