The Experts below are selected from a list of 19329 Experts worldwide ranked by ideXlab platform
Alan J Huang - One of the best experts on this subject based on the ideXlab platform.
-
three dimensional whole brain perfusion quantification using pseudo continuous arterial spin labeling mri at multiple post labeling delays accounting for both arterial transit time and Impulse Response Function
NMR in Biomedicine, 2014Co-Authors: Qin Qin, Alan J Huang, Jun Hua, John E Desmond, Robert D Stevens, Peter C M Van ZijlAbstract:Measurement of cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit the ASL-based perfusion kinetic curves, an empirical 3-parameter model that characterizes the effective Impulse Response Function (IRF) is introduced, which allows determination of CBF, arterial transit time (ATT), and T1,eff. The accuracy and precision of the proposed model is compared with more complicated models with 4 or 5 parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling (PCASL) images were acquired on a clinical 3 Tesla scanner in 10 normal volunteers using a 3D multi-shot gradient- and spin-echo (GRASE) scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the 3-parameter model and other models that contain 2, 4 or 5 unknown parameters. For the 2-parameter model, T1,eff values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicate that: 1) the estimated CBF values using the 2-parameter model show appreciable dependence on the assumed T1,eff values; 2) the proposed 3-parameter model achieves the optimal balance between the goodness of fit and the model complexity when compared among the models with explicit IRF fitting; 3) both the 2-parameter model using fixed blood T1 values for T1,eff and the 3-parameter model provide reasonable fitting results. Using the proposed 3-parameter model, the estimated CBF values (46±14 mL/100g/min) and ATT values (ATT = 1.4±0.3 s) averaged from different brain regions are close to the literature reports; the estimated T1,eff values (T1,eff = 1.9±0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.
-
three dimensional whole brain perfusion quantification using pseudo continuous arterial spin labeling mri at multiple post labeling delays accounting for both arterial transit time and Impulse Response Function
NMR in Biomedicine, 2014Co-Authors: Alan J Huang, John E Desmond, Robert D Stevens, Peter C M Van ZijlAbstract:: Measurement of the cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit arterial spin labeling-based perfusion kinetic curves, an empirical three-parameter model which characterizes the effective Impulse Response Function (IRF) is introduced, which allows the determination of CBF, the arterial transit time (ATT) and T(1,eff). The accuracy and precision of the proposed model were compared with those of more complicated models with four or five parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling images were acquired on a clinical 3-T scanner in 10 normal volunteers using a three-dimensional multi-shot gradient and spin echo scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the three-parameter model and other models that contain two, four or five unknown parameters. For the two-parameter model, T(1,eff) values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicated that: (i) the estimated CBF values using the two-parameter model show appreciable dependence on the assumed T(1,eff) values; (ii) the proposed three-parameter model achieves the optimal balance between the goodness of fit and model complexity when compared among the models with explicit IRF fitting; (iii) both the two-parameter model using fixed blood T1 values for T(1,eff) and the three-parameter model provide reasonable fitting results. Using the proposed three-parameter model, the estimated CBF (46 ± 14 mL/100 g/min) and ATT (1.4 ± 0.3 s) values averaged from different brain regions are close to the literature reports; the estimated T(1,eff) values (1.9 ± 0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.
Peter C M Van Zijl - One of the best experts on this subject based on the ideXlab platform.
-
three dimensional whole brain perfusion quantification using pseudo continuous arterial spin labeling mri at multiple post labeling delays accounting for both arterial transit time and Impulse Response Function
NMR in Biomedicine, 2014Co-Authors: Alan J Huang, John E Desmond, Robert D Stevens, Peter C M Van ZijlAbstract:: Measurement of the cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit arterial spin labeling-based perfusion kinetic curves, an empirical three-parameter model which characterizes the effective Impulse Response Function (IRF) is introduced, which allows the determination of CBF, the arterial transit time (ATT) and T(1,eff). The accuracy and precision of the proposed model were compared with those of more complicated models with four or five parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling images were acquired on a clinical 3-T scanner in 10 normal volunteers using a three-dimensional multi-shot gradient and spin echo scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the three-parameter model and other models that contain two, four or five unknown parameters. For the two-parameter model, T(1,eff) values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicated that: (i) the estimated CBF values using the two-parameter model show appreciable dependence on the assumed T(1,eff) values; (ii) the proposed three-parameter model achieves the optimal balance between the goodness of fit and model complexity when compared among the models with explicit IRF fitting; (iii) both the two-parameter model using fixed blood T1 values for T(1,eff) and the three-parameter model provide reasonable fitting results. Using the proposed three-parameter model, the estimated CBF (46 ± 14 mL/100 g/min) and ATT (1.4 ± 0.3 s) values averaged from different brain regions are close to the literature reports; the estimated T(1,eff) values (1.9 ± 0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.
Peter C M Van Zijl - One of the best experts on this subject based on the ideXlab platform.
-
three dimensional whole brain perfusion quantification using pseudo continuous arterial spin labeling mri at multiple post labeling delays accounting for both arterial transit time and Impulse Response Function
NMR in Biomedicine, 2014Co-Authors: Qin Qin, Alan J Huang, Jun Hua, John E Desmond, Robert D Stevens, Peter C M Van ZijlAbstract:Measurement of cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit the ASL-based perfusion kinetic curves, an empirical 3-parameter model that characterizes the effective Impulse Response Function (IRF) is introduced, which allows determination of CBF, arterial transit time (ATT), and T1,eff. The accuracy and precision of the proposed model is compared with more complicated models with 4 or 5 parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling (PCASL) images were acquired on a clinical 3 Tesla scanner in 10 normal volunteers using a 3D multi-shot gradient- and spin-echo (GRASE) scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the 3-parameter model and other models that contain 2, 4 or 5 unknown parameters. For the 2-parameter model, T1,eff values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicate that: 1) the estimated CBF values using the 2-parameter model show appreciable dependence on the assumed T1,eff values; 2) the proposed 3-parameter model achieves the optimal balance between the goodness of fit and the model complexity when compared among the models with explicit IRF fitting; 3) both the 2-parameter model using fixed blood T1 values for T1,eff and the 3-parameter model provide reasonable fitting results. Using the proposed 3-parameter model, the estimated CBF values (46±14 mL/100g/min) and ATT values (ATT = 1.4±0.3 s) averaged from different brain regions are close to the literature reports; the estimated T1,eff values (T1,eff = 1.9±0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.
Qin Qin - One of the best experts on this subject based on the ideXlab platform.
-
three dimensional whole brain perfusion quantification using pseudo continuous arterial spin labeling mri at multiple post labeling delays accounting for both arterial transit time and Impulse Response Function
NMR in Biomedicine, 2014Co-Authors: Qin Qin, Alan J Huang, Jun Hua, John E Desmond, Robert D Stevens, Peter C M Van ZijlAbstract:Measurement of cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit the ASL-based perfusion kinetic curves, an empirical 3-parameter model that characterizes the effective Impulse Response Function (IRF) is introduced, which allows determination of CBF, arterial transit time (ATT), and T1,eff. The accuracy and precision of the proposed model is compared with more complicated models with 4 or 5 parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling (PCASL) images were acquired on a clinical 3 Tesla scanner in 10 normal volunteers using a 3D multi-shot gradient- and spin-echo (GRASE) scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the 3-parameter model and other models that contain 2, 4 or 5 unknown parameters. For the 2-parameter model, T1,eff values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicate that: 1) the estimated CBF values using the 2-parameter model show appreciable dependence on the assumed T1,eff values; 2) the proposed 3-parameter model achieves the optimal balance between the goodness of fit and the model complexity when compared among the models with explicit IRF fitting; 3) both the 2-parameter model using fixed blood T1 values for T1,eff and the 3-parameter model provide reasonable fitting results. Using the proposed 3-parameter model, the estimated CBF values (46±14 mL/100g/min) and ATT values (ATT = 1.4±0.3 s) averaged from different brain regions are close to the literature reports; the estimated T1,eff values (T1,eff = 1.9±0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.
John E Desmond - One of the best experts on this subject based on the ideXlab platform.
-
three dimensional whole brain perfusion quantification using pseudo continuous arterial spin labeling mri at multiple post labeling delays accounting for both arterial transit time and Impulse Response Function
NMR in Biomedicine, 2014Co-Authors: Qin Qin, Alan J Huang, Jun Hua, John E Desmond, Robert D Stevens, Peter C M Van ZijlAbstract:Measurement of cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit the ASL-based perfusion kinetic curves, an empirical 3-parameter model that characterizes the effective Impulse Response Function (IRF) is introduced, which allows determination of CBF, arterial transit time (ATT), and T1,eff. The accuracy and precision of the proposed model is compared with more complicated models with 4 or 5 parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling (PCASL) images were acquired on a clinical 3 Tesla scanner in 10 normal volunteers using a 3D multi-shot gradient- and spin-echo (GRASE) scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the 3-parameter model and other models that contain 2, 4 or 5 unknown parameters. For the 2-parameter model, T1,eff values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicate that: 1) the estimated CBF values using the 2-parameter model show appreciable dependence on the assumed T1,eff values; 2) the proposed 3-parameter model achieves the optimal balance between the goodness of fit and the model complexity when compared among the models with explicit IRF fitting; 3) both the 2-parameter model using fixed blood T1 values for T1,eff and the 3-parameter model provide reasonable fitting results. Using the proposed 3-parameter model, the estimated CBF values (46±14 mL/100g/min) and ATT values (ATT = 1.4±0.3 s) averaged from different brain regions are close to the literature reports; the estimated T1,eff values (T1,eff = 1.9±0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.
-
three dimensional whole brain perfusion quantification using pseudo continuous arterial spin labeling mri at multiple post labeling delays accounting for both arterial transit time and Impulse Response Function
NMR in Biomedicine, 2014Co-Authors: Alan J Huang, John E Desmond, Robert D Stevens, Peter C M Van ZijlAbstract:: Measurement of the cerebral blood flow (CBF) with whole-brain coverage is challenging in terms of both acquisition and quantitative analysis. In order to fit arterial spin labeling-based perfusion kinetic curves, an empirical three-parameter model which characterizes the effective Impulse Response Function (IRF) is introduced, which allows the determination of CBF, the arterial transit time (ATT) and T(1,eff). The accuracy and precision of the proposed model were compared with those of more complicated models with four or five parameters through Monte Carlo simulations. Pseudo-continuous arterial spin labeling images were acquired on a clinical 3-T scanner in 10 normal volunteers using a three-dimensional multi-shot gradient and spin echo scheme at multiple post-labeling delays to sample the kinetic curves. Voxel-wise fitting was performed using the three-parameter model and other models that contain two, four or five unknown parameters. For the two-parameter model, T(1,eff) values close to tissue and blood were assumed separately. Standard statistical analysis was conducted to compare these fitting models in various brain regions. The fitted results indicated that: (i) the estimated CBF values using the two-parameter model show appreciable dependence on the assumed T(1,eff) values; (ii) the proposed three-parameter model achieves the optimal balance between the goodness of fit and model complexity when compared among the models with explicit IRF fitting; (iii) both the two-parameter model using fixed blood T1 values for T(1,eff) and the three-parameter model provide reasonable fitting results. Using the proposed three-parameter model, the estimated CBF (46 ± 14 mL/100 g/min) and ATT (1.4 ± 0.3 s) values averaged from different brain regions are close to the literature reports; the estimated T(1,eff) values (1.9 ± 0.4 s) are higher than the tissue T1 values, possibly reflecting a contribution from the microvascular arterial blood compartment.
