Compared with conventional MP-RAGE, the proposed CE BB-ssTSE imaging, which enhances tumors while selectively suppressing blood vessels, leads to significantly better detection of small metastatic brain tumors <5 mm.
Quantitative BOLD (qBOLD), a non-invasive MRI method for assessment of hemodynamic and metabolic properties of the brain in the baseline state, provides spatial maps of deoxygenated blood volume fraction (DBV) and hemoglobin oxygen saturation (HbO) by means of an analytical model for the temporal evolution of free-induction-decay signals in the extravascular compartment. However, mutual coupling between DBV and HbO in the signal model results in considerable estimation uncertainty precluding achievement of a unique set of solutions. To address this problem, we developed an interleaved qBOLD method (iqBOLD) that combines extravascular R' and intravascular R mapping techniques so as to obtain prior knowledge for the two unknown parameters. To achieve these goals, asymmetric spin echo and velocity-selective spin-labeling (VSSL) modules were interleaved in a single pulse sequence. Prior to VSSL, arterial blood and CSF signals were suppressed to produce reliable estimates for cerebral venous blood volume fraction (CBV) as well as venous blood R (to yield HbO). Parameter maps derived from the VSSL module were employed to initialize DBV and HbO in the qBOLD processing. Numerical simulations and in vivo experiments at 3 T were performed to evaluate the performance of iqBOLD in comparison to the parent qBOLD method. Data obtained in eight healthy subjects yielded plausible values averaging 60.1 ± 3.3% for HbO and 3.1 ± 0.5 and 2.0 ± 0.4% for DBV in gray and white matter, respectively. Furthermore, the results show that prior estimates of CBV and HbO from the VSSL component enhance the solution stability in the qBOLD processing, and thus suggest the feasibility of iqBOLD as a promising alternative to the conventional technique for quantifying neurometabolic parameters.
We successfully demonstrated the feasibility of the proposed method in estimating current-induced Bz and conductivity distribution. It can be a promising, rapid imaging strategy for quantitative conductivity imaging.
Purpose
Venous cerebral blood volume (CBVv) is a major contributor to BOLD contrast, and therefore is an important parameter for understanding the underlying mechanism. Here, we propose a velocity‐selective venous spin labeling (VS‐VSL)‐prepared 3D turbo spin echo pulse sequence for whole‐brain baseline CBVv mapping.
Methods
Unlike previous CBVv measurement techniques that exploit the interrelationship between BOLD signals and CBVv, in the proposed VS‐VSL technique both arterial blood and cerebrospinal fluid (CSF) signals were suppressed before the VS pulse train for exclusive labeling of venous blood, while a single‐slab 3D turbo spin echo readout was used because of its relative immunity to magnetic field variations. Furthermore, two approximations were made to the VS‐VSL signal model for simplified derivation of CBVv. In vivo studies were performed at 3T field strength in 8 healthy subjects. The performance of the proposed VS‐VSL method in baseline CBVv estimation was first evaluated in comparison to the existing, hyperoxia‐based method. Then, data were also acquired using VS‐VSL under hypercapnic and hyperoxic gas breathing challenges for further validation of the technique.
Results
The proposed technique yielded physiologically plausible baseline CBVv values, and when compared with the hyperoxia‐based method, showed no statistical difference. Furthermore, data acquired using VS‐VSL yielded average CBVv of 2.89%/1.78%, 3.71%/2.29%, and 2.88%/1.76% for baseline, hypercapnia, and hyperoxia, respectively, in gray/white matter regions. As expected, hyperoxia had negligible effect (P > .8), whereas hypercapnia demonstrated vasodilation (P << .01).
Conclusion
Upon further validation of the quantification model, the method is expected to have merit for 3D CBVv measurements across the entire brain.
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