Attenuation Correction Using Template PET Registration for Brain PET: A Proof-of-Concept Study.

NeuroLF is a dedicated brain PET system with an octagonal prism shape housed in a scanner head that can be positioned around a patient's head. Because it does not have MR or CT capabilities, attenuation correction based on an estimation of the attenuation map is a crucial feature. In this article, we demonstrate this method on [18F]FDG PET brain scans performed with a low-resolution proof of concept prototype of NeuroLF called BPET. We perform an affine registration of a template PET scan to the uncorrected emission image, and then apply the resulting transform to the corresponding template attenuation map. Using a whole-body PET/CT system as reference, we quantitively show that this method yields comparable image quality (0.893 average correlation to reference scan) to using the reference µ-map as obtained from the CT scan of the imaged patient (0.908 average correlation). We conclude from this initial study that attenuation correction using template registration instead of a patient CT delivers similar results and is an option for patients undergoing brain PET.

Optimisation of current injection protocol based on a region of interest.

OBJECTIVE: Electrical impedance tomography has the potential to image fast neural activity associated with physiological or epileptic activity throughout the brain. These applications pose a particular challenge as expected voltage changes on the electrodes are less than 1% and geometrical constraints of the body under investigation mean that electrodes can not be evenly distributed around its boundary. Unlike other applications, however, information regarding the location of expected activity is typically available. An informative method for choosing current paths that maximise sensitivity to specific regions is desirable. APPROACH: Two electrode addressing protocol generation methods based on current density vectors concentrated in a region of interest have been proposed. One focuses solely on maximising its magnitude while the other considers its distribution. The quality of reconstructed images using these protocols was assessed in a simulation study conducted in a human and rat mesh and compared to the protocol that maximises distance between injecting electrodes. MAIN RESULTS: When implementing the protocol that focused on maximising magnitude, the current density concentrated in a region of interest increased by up to a factor of 3. When the distribution of the current was maximised, the spread of current density vectors increased by up to fivefold. For the small conductivity changes expected in the applications explored, image quality was best when implementing the protocol that maximised current density. The average image error when using this protocol was 7% better than when employing other protocols. SIGNIFICANCE: We conclude that for fast neural EIT applications, the protocol that maximises current density is the best protocol to implement.

Are patient specific meshes required for EIT head imaging?

Head imaging with electrical impedance tomography (EIT) is usually done with time-differential measurements, to reduce time-invariant modelling errors. Previous research suggested that more accurate head models improved image quality, but no thorough analysis has been done on the required accuracy. We propose a novel pipeline for creation of precise head meshes from magnetic resonance imaging and computed tomography scans, which was applied to four different heads. Voltages were simulated on all four heads for perturbations of different magnitude, haemorrhage and ischaemia, in five different positions and for three levels of instrumentation noise. Statistical analysis showed that reconstructions on the correct mesh were on average 25% better than on the other meshes. However, the stroke detection rates were not improved. We conclude that a generic head mesh is sufficient for monitoring patients for secondary strokes following head trauma.

Correction of electrode modelling errors in multi-frequency EIT imaging.

The differentiation of haemorrhagic from ischaemic stroke using electrical impedance tomography (EIT) requires measurements at multiple frequencies, since the general lack of healthy measurements on the same patient excludes time-difference imaging methods. It has previously been shown that the inaccurate modelling of electrodes constitutes one of the largest sources of image artefacts in non-linear multi-frequency EIT applications. To address this issue, we augmented the conductivity Jacobian matrix with a Jacobian matrix with respect to electrode movement. Using this new algorithm, simulated ischaemic and haemorrhagic strokes in a realistic head model were reconstructed for varying degrees of electrode position errors. The simultaneous recovery of conductivity spectra and electrode positions removed most artefacts caused by inaccurately modelled electrodes. Reconstructions were stable for electrode position errors of up to 1.5 mm standard deviation along both surface dimensions. We conclude that this method can be used for electrode model correction in multi-frequency EIT.

Correcting electrode modelling errors in EIT on realistic 3D head models.

Electrical impedance tomography (EIT) is a promising medical imaging technique which could aid differentiation of haemorrhagic from ischaemic stroke in an ambulance. One challenge in EIT is the ill-posed nature of the image reconstruction, i.e., that small measurement or modelling errors can result in large image artefacts. It is therefore important that reconstruction algorithms are improved with regard to stability to modelling errors. We identify that wrongly modelled electrode positions constitute one of the biggest sources of image artefacts in head EIT. Therefore, the use of the Fréchet derivative on the electrode boundaries in a realistic three-dimensional head model is investigated, in order to reconstruct electrode movements simultaneously to conductivity changes. We show a fast implementation and analyse the performance of electrode position reconstructions in time-difference and absolute imaging for simulated and experimental voltages. Reconstructing the electrode positions and conductivities simultaneously increased the image quality significantly in the presence of electrode movement.

A fast parallel solver for the forward problem in electrical impedance tomography.

Electrical impedance tomography (EIT) is a noninvasive imaging modality, where imperceptible currents are applied to the skin and the resulting surface voltages are measured. It has the potential to distinguish between ischaemic and haemorrhagic stroke with a portable and inexpensive device. The image reconstruction relies on an accurate forward model of the experimental setup. Because of the relatively small signal in stroke EIT, the finite-element modeling requires meshes of more than 10 million elements. To study the requirements in the forward modeling in EIT and also to reduce the time for experimental image acquisition, it is necessary to reduce the run time of the forward computation. We show the implementation of a parallel forward solver for EIT using the Dune-Fem C++ library and demonstrate its performance on many CPU's of a computer cluster. For a typical EIT application a direct solver was significantly slower and not an alternative to iterative solvers with multigrid preconditioning. With this new solver, we can compute the forward solutions and the Jacobian matrix of a typical EIT application with 30 electrodes on a 15-million element mesh in less than 15 min. This makes it a valuable tool for simulation studies and EIT applications with high precision requirements. It is freely available for download.

Stroke type differentiation using spectrally constrained multifrequency EIT: evaluation of feasibility in a realistic head model.

We investigate the application of multifrequency electrical impedance tomography (MFEIT) to imaging the brain in stroke patients. The use of MFEIT could enable early diagnosis and thrombolysis of ischaemic stroke, and therefore improve the outcome of treatment. Recent advances in the imaging methodology suggest that the use of spectral constraints could allow for the reconstruction of a one-shot image. We performed a simulation study to investigate the feasibility of imaging stroke in a head model with realistic conductivities. We introduced increasing levels of modelling errors to test the robustness of the method to the most common sources of artefact. We considered the case of errors in the electrode placement, spectral constraints, and contact impedance. The results indicate that errors in the position and shape of the electrodes can affect image quality, although our imaging method was successful in identifying tissues with sufficiently distinct spectra.

Gbetagamma inhibits Galpha GTPase-activating proteins by inhibition of Galpha-GTP binding during stimulation by receptor.

Gbetagamma subunits modulate several distinct molecular events involved with G protein signaling. In addition to regulating several effector proteins, Gbetagamma subunits help anchor Galpha subunits to the plasma membrane, promote interaction of Galpha with receptors, stabilize the binding of GDP to Galpha to suppress spurious activation, and provide membrane contact points for G protein-coupled receptor kinases. Gbetagamma subunits have also been shown to inhibit the activities of GTPase-activating proteins (GAPs), both phospholipase C (PLC)-betas and RGS proteins, when assayed in solution under single turnover conditions. We show here that Gbetagamma subunits inhibit G protein GAP activity during receptor-stimulated, steady-state GTPase turnover. GDP/GTP exchange catalyzed by receptor requires Gbetagamma in amounts approximately equimolar to Galpha, but GAP inhibition was observed with superstoichiometric Gbetagamma. The potency of inhibition varied with the GAP and the Galpha subunit, but half-maximal inhibition of the GAP activity of PLC-beta1 was observed with 5-10 nM Gbetagamma, which is at or below the concentrations of Gbetagamma needed for regulation of physiologically relevant effector proteins. The kinetics of GAP inhibition of both receptor-stimulated GTPase activity and single turnover, solution-based GAP assays suggested a competitive mechanism in which Gbetagamma competes with GAPs for binding to the activated, GTP-bound Galpha subunit. An N-terminal truncation mutant of PLC-beta1 that cannot be directly regulated by Gbetagamma remained sensitive to inhibition of its GAP activity, suggesting that the Gbetagamma binding site relevant for GAP inhibition is on the Galpha subunit rather than on the GAP. Using fluorescence resonance energy transfer between cyan or yellow fluorescent protein-labeled G protein subunits and Alexa532-labeled RGS4, we found that Gbetagamma directly competes with RGS4 for high-affinity binding to Galpha(i)-GDP-AlF4.