RESUMEN
Hypercapnia and hyperoxia give rise to vasodilation and vasoconstriction, respectively. This study investigates the influence of hypercapnia and hyperoxia on venous vessel size in the human brain. Venous vessel radii were measured in response to hypercapnia and hyperoxia. The venous vessel radii were determined by calculation of the changes in R2 * and R2 that are induced by breathing 6% CO2 or pure oxygen. The experimental paradigm consisted of two 3-min intervals of inhaling 6% CO2 or 100% O2 interleaved with three 2-min intervals of breathing air. Hypercapnic and hyperoxic experiments were performed on eight subjects on a 3T scanner. Parametric maps of mean venous vessel radius were calculated from the changes in R2 * and R2 , which were measured by simultaneous acquisition of gradient-echo and spin-echo signals. The mean venous vessel radii in hypercapnia were 7.3±0.3 µm in gray matter and 6.6±0.5 µm in white matter. The corresponding vessel radii in hyperoxia were 5.6±0.2 µm in gray matter and 5.4±0.2 µm in white matter. These results show that the venous vessel radius was larger in hypercapnia than that in hyperoxia in both gray matter and white matter (P<0.005), which agrees with the hypothesis that hypercapnia causes vasodilation and hyperoxia induces vasoconstriction.
Asunto(s)
Algoritmos , Venas Cerebrales/patología , Hipercapnia/patología , Hiperoxia/patología , Interpretación de Imagen Asistida por Computador/métodos , Imagenología Tridimensional/métodos , Angiografía por Resonancia Magnética/métodos , Adulto , Femenino , Humanos , Aumento de la Imagen/métodos , Masculino , Tamaño de los Órganos , Reproducibilidad de los Resultados , Sensibilidad y Especificidad , Adulto JovenRESUMEN
Two cerebral blood volume (CBV)-weighted fMRI techniques, gray matter nulled (GMN) and vascular space occupancy (VASO)-dependent techniques at spatial resolution of 2 × 2 × 5 mm(3), were compared in the study investigating functional responses in the human visual cortex to stimulation in normoxia (inspired O(2) = 21%) and mild hypoxic hypoxia (inspired O(2) = 12%). GMN and VASO signals and T(2)* were quantified in activated voxels. While the CBV-weighted signal changes in voxels activated by visual stimulation were similar in amplitude in both fMRI techniques in both oxygenation conditions, the number of activated voxels during hypoxic hypoxia was significantly reduced by 72 ± 22% in GMN fMRI and 66 ± 23% in VASO fMRI. T(2)* prolonged in GMN and VASO activated voxels in normoxia by 1.6 ± 0.5 ms and 1.7 ± 0.5 ms, respectively. In hypoxia, however, T(2)* shortened in GMN-activated voxels by 0.7 ± 0.6 ms (p < 0.001 relative to normoxia), but prolonged in VASO-activated ones by 1.1 ± 0.6 ms (p < 0.05 relative to normoxia). The data show that the hemodynamic responses to visual stimulation were not affected by hypoxic hypoxia, but T(2)* increases by both CBV-weighted fMRI techniques were smaller in activated voxels in hypoxia. The mechanisms influencing GMN fMRI signal in both oxygenation conditions were explored by simulating effects of the oxygen extraction fraction (OEF) and partial voluming with cerebral spinal fluid (CSF) and white matter in imaging voxels. It is concluded that while GMN fMRI data point to increased, rather than decreased OEF during visual stimulation in hypoxia, partial voluming by CSF is likely to affect the CBV quantification by GMN fMRI under the experimental conditions used.
Asunto(s)
Encéfalo/irrigación sanguínea , Hipoxia/fisiopatología , Imagen por Resonancia Magnética , Estimulación Luminosa , Adulto , Determinación del Volumen Sanguíneo , Femenino , Humanos , Masculino , Persona de Mediana Edad , Adulto JovenRESUMEN
Diffusion-weighted images acquired with the echo-planar imaging technique are highly sensitive to eddy current induced geometric distortions that vary with the magnitude and direction of the diffusion sensitizing gradients. Such distortions cause misalignment of images acquired with different diffusion strengths and orientations. This in turn can result in errors when calculating maps of the apparent diffusion coefficient and diffusion tensor. Previous correction methods either require separate calibration data or only deal with low-order errors. In this study, we demonstrate a method that can correct for higher-order errors. The method relies on collecting pairs of images with diffusion sensitizing gradients reversed. This paired data are first corrected for shifts and linear distortion and then combined to cancel higher-order errors. All acquired data contribute to the final results. The method has been tested by simulation, on phantoms, on adult volunteers, and on neonatal brain examinations.