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We present a method that estimates three-dimensional statistical maps for electroencephalogram (EEG) source localization. The maps assess the likelihood that a point in the brain contains a dipolar source, under the hypothesis of one, two or three activated sources. This is achieved by examining all combinations of one to three dipoles on a coarse grid and attributing to each combination a score based on an F statistic. The probability density function of the statistic under the null hypothesis is estimated nonparametrically, using bootstrap resampling. A theoretical F distribution is then fitted to the empirical distribution in order to allow correction for multiple comparisons. The maps allow for the systematic exploration of the solution space for dipolar sources. They permit to test whether the data support a given solution. They do not rely on the assumption of uncorrelated source time courses. They can be compared to other statistical parametric maps such as those used in functional magnetic resonance imaging (fMRI). Results are presented for both simulated and real data. The maps were compared with LORETA and MUSIC results. For the real data consisting of an average of epileptic spikes, we observed good agreement between the EEG statistical maps, intracranial EEG recordings, and fMRI activations. Index Terms--Bootstrap resampling, dipole modeling, EEG/MEG source analysis, electroencephalography, inverse problems, model selection, source scanning, statistical map.

Monte Carlo-based PET simulators are powerful tools for accurately generating projections of tracer distributions for given scanner specifications and attenuating media distributions. High activity-related phenomena, such as the randoms contribution as well as block and system deadtimes constitute a large source of artefact and must therefore be integrated within the simulation model along with the [gamma]-ray interaction within the tissue or the scanner material. We present here the features of a Monte Carlo simulator, dedicated to full ring tomographs, which is able to generate scattered, unscattered, and randoms distributions from voxelized phantom descriptions, and which accounts for the data losses due to system deadtime. Simulations of the count rate performance of the ECAT Exact H[R.sup.+] operating in 2-D and 3-D modes were found to be in good agreement with experimental measurements obtained for a wide range of activity levels and distributions. Index Terms--Count rate performances, deadtime, Monte Carlo simulations, positron emission tomography, randoms, singles rate.

Dissolution dynamic nuclear polarisation (dDNP) of 13C‐labelled pyruvate in magnetic resonance spectroscopy/imaging (MRS/MRSI) has the potential for monitoring tumour progression and treatment response. Pyruvate delivery, its metabolism to lactate and efflux were investigated in rat P22 sarcomas following simultaneous intravenous administration of hyperpolarised 13C‐labelled pyruvate (13C1‐pyruvate) and urea (13C‐urea), a nonmetabolised marker. A general mathematical model of pyruvate‐lactate exchange, incorporating an arterial input function (AIF), enabled the losses of pyruvate and lactate from tumour to be estimated, in addition to the clearance rate of pyruvate signal from blood into tumour, Kip, and the forward and reverse fractional rate constants for pyruvate‐lactate signal exchange, kpl and klp. An analogous model was developed for urea, enabling estimation of urea tumour losses and the blood clearance parameter, Kiu. A spectral fitting procedure to blood time‐course data proved superior to assuming a gamma‐variate form for the AIFs. Mean arterial blood pressure marginally correlated with clearance rates. Kiu equalled Kip, indicating equivalent permeability of the tumour vasculature to urea and pyruvate. Fractional loss rate constants due to effluxes of pyruvate, lactate and urea from tumour tissue into blood (kpo, klo and kuo, respectively) indicated that T1s and the average flip angle, θ, obtained from arterial blood were poor surrogates for these parameters in tumour tissue. A precursor‐product model, using the tumour pyruvate signal time‐course as the input for the corresponding lactate signal time‐course, was modified to account for the observed delay between them. The corresponding fractional rate constant, kavail, most likely reflected heterogeneous tumour microcirculation. Loss parameters, estimated from this model with different TRs, provided a lower limit on the estimates of tumour T1 for lactate and urea. The results do not support use of hyperpolarised urea for providing information on the tumour microcirculation over and above what can be obtained from pyruvate alone. The results also highlight the need for rigorous processes controlling signal quantitation, if absolute estimations of biological parameters are required. [ABSTRACT FROM AUTHOR]