Biomedical subjects

Karam Sidaros

Publications and source records attributed to Karam Sidaros.

4 recordsLinked to original sources

PubMed2006

Slice profile optimization in arterial spin labeling using presaturation and optimized RF pulses.

OBJECTIVE: An important source of error in arterial spin labeling (ASL) is incomplete static tissue subtraction due to imperfect slice profiles. This effect can be reduced by saturating the spins in the imaging area prior to labeling. In this study, the use of optimized presaturation is compared with the use of optimized RF pulses for minimizing this error. MATERIALS AND METHODS: Different methods for optimizing presaturation were simulated by numerical solution of the Bloch equation. Presaturation was optimized by changing the number of presaturation pulses, their position in the pulse sequence and the area of the crusher gradients following each saturation pulse. It was also investigated whether the use of optimized presaturation could reduce the tag gap needed to ensure complete static tissue subtraction. Simulation results were verified using phantom and in vivo studies at 3T. RESULTS: In proximal inversion with control for off-resonance effects, optimized presaturation could reduce the necessary tag gap to 15% of the imaging slab for experiments using standard RF pulses, while c-FOCI RF pulses could reduce it to 11%. In flow-sensitive alternating inversion recovery, a single presaturation pulse could reduce the inversion width to 122% of the imaging slab and neither multiple presaturation pulses nor optimized RF pulses could reduce it further. CONCLUSION: Optimized presaturation can reduce the necessary inversion width to the same level as if using optimized RF pulses and can, therefore, be used to optimize ASL sensitivity. Furthermore, optimized presaturation can reduce the B(1)-dependent sensitivity in static tissue subtraction.

Adult↗

PubMed2006

Noninvasive measurements of regional cerebral perfusion in preterm and term neonates by magnetic resonance arterial spin labeling.

Magnetic resonance arterial spin labeling (ASL) at 3 Tesla has been investigated as a quantitative technique for measuring regional cerebral perfusion (RCP) in newborn infants. RCP values were measured in 49 healthy neonates: 32 preterm infants born before 34 wk of gestation and 17 term-born neonates. Examinations were performed on unsedated infants at postmenstrual age of 39-40 wk in both groups. Due to motion, reliable data were obtained from 23 preterm and 6 term infants. Perfusion in the basal ganglia (39 and 30 mL/100 g/min for preterm and term neonates, respectively) was significantly higher (p < 0.0001) than in cortical gray matter (19 and 16 mL/100 g/min) and white matter (15 and 10 mL/100 g/min), both in preterm neonates at term-equivalent age and in term neonates. Perfusion was significantly higher (p = 0.01) in the preterm group than in the term infants, indicating that RCP may be influenced by developmental and postnatal ages. This study demonstrates, for the first time, that noninvasive ASL at 3T may be used to measure RCP in healthy unsedated preterm and term neonates. ASL is, therefore, a viable tool that will allow serial studies of RCP in high-risk neonates.

Cerebrovascular Circulation↗

PubMed2005

Non-white noise in fMRI: does modelling have an impact?

The sources of non-white noise in Blood Oxygenation Level Dependent (BOLD) functional magnetic resonance imaging (fMRI) are many. Familiar sources include low-frequency drift due to hardware imperfections, oscillatory noise due to respiration and cardiac pulsation and residual movement artefacts not accounted for by rigid body registration. These contributions give rise to temporal autocorrelation in the residuals of the fMRI signal and invalidate the statistical analysis as the errors are no longer independent. The low-frequency drift is often removed by high-pass filtering, and other effects are typically modelled as an autoregressive (AR) process. In this paper, we propose an alternative approach: Nuisance Variable Regression (NVR). By inclusion of confounding effects in a general linear model (GLM), we first confirm that the spatial distribution of the various fMRI noise sources is similar to what has already been described in the literature. Subsequently, we demonstrate, using diagnostic statistics, that removal of these contributions reduces first and higher order autocorrelation as well as non-normality in the residuals, thereby improving the validity of the drawn inferences. In addition, we also compare the performance of the NVR method to the whitening approach implemented in SPM2.

Algorithms↗

PubMed2004

Hypercapnic normalization of BOLD fMRI: comparison across field strengths and pulse sequences.

The blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal response to neural stimulation is influenced by many factors that are unrelated to the stimulus. These factors are physiological, such as the resting venous cerebral blood volume (CBV(v)) and vessel size, as well as experimental, such as pulse sequence and static magnetic field strength (B(0)). Thus, it is difficult to compare task-induced fMRI signals across subjects, field strengths, and pulse sequences. This problem can be overcome by normalizing the neural activity-induced BOLD fMRI response by a global hypercapnia-induced BOLD signal. To demonstrate the effectiveness of the BOLD normalization approach, gradient-echo BOLD fMRI at 1.5, 4, and 7 T and spin-echo BOLD fMRI at 4 T were performed in human subjects. For neural stimulation, subjects performed sequential finger movements at 2 Hz, while for global stimulation, subjects breathed a 5% CO(2) gas mixture. Under all conditions, voxels containing primarily large veins and those containing primarily active tissue (i.e., capillaries and small veins) showed distinguishable behavior after hypercapnic normalization. This allowed functional activity to be more accurately localized and quantified based on changes in venous blood oxygenation alone. The normalized BOLD signal induced by the motor task was consistent across different magnetic fields and pulse sequences, and corresponded well with cerebral blood flow measurements. Our data suggest that the hypercapnic normalization approach can improve the spatial specificity and interpretation of BOLD signals, allowing comparison of BOLD signals across subjects, field strengths, and pulse sequences. A theoretical framework for this method is provided.

Adult↗