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We combined the neuroanatomists' approach of defining a fascicle as all fibers passing through its compact stem with diffusion-weighted tractography to investigate the cortical terminations of two association tracts, the inferior fronto-occipital fasciculus (IFOF) and the uncinate fasciculus (UF), which have recently been implicated in the ventral language circuitry. The aim was to provide a detailed and quantitative description of their terminations in 60 healthy subjects and to do so to apply an anatomical stem-based virtual dissection, mimicking classical post-mortem dissection, to extract with minimal a priori the IFOF and UF from tractography datasets. In both tracts, we consistently observed more extensive termination territories than their conventional definitions, within the middle and superior frontal, superior parietal and angular gyri for the IFOF and the middle frontal gyrus and superior, middle and inferior temporal gyri beyond the temporal pole for the UF. We revealed new insights regarding the internal organization of these tracts by investigating for the first time the frequency, distribution and hemispheric asymmetry of their terminations. Interestingly, we observed a dissociation between the lateral right-lateralized and medial left-lateralized fronto-occipital branches of the IFOF. In the UF, we observed a rightward lateralization of the orbito-frontal and temporal branches. We revealed a more detailed map of the terminations of these fiber pathways that will enable greater specificity for correlating with diseased populations and other behavioral measures. The limitations of the diffusion tensor model in this study are also discussed. We conclude that anatomical stem-based virtual dissection with diffusion tractography is a fruitful method for studying the structural anatomy of the human white matter pathways.

A classical developmental model for the left hemisphere specialization for language has been proposed based on the observation of a positive correlation coefficient between the value of an index of asymmetry between the left and right planum temporale surface areas and the size of the right planum temporale. Here, we demonstrate that such correlation is a mathematical artefact and thus should not serve as a basis for establishing models of language hemispheric dominance.

The alignment accuracy and impact on functional maps of four spatial normalization procedures have been compared using a set of high resolution brain MRIs and functional PET volumes acquired in 20 subjects. Simple affine (AFF), fifth order polynomial warp (WRP), discrete cosine basis functions (SPM), and a movement model based on full multi grid (FMG) approaches were applied on the same dataset for warping individual volumes onto the Human Brain Atlas (HBA) template. Intersubject averaged structural volumes and tissue probability maps were compared across normalization methods and to the standard brain. Thanks to the large number of degrees of freedom of the technique, FMG was found to provide enhanced alignment accuracy as compared to the other three methods, both for the grey and white matter tissues; WRP and SPM exhibited very similar performances whereas AFF had the lowest registration accuracy. SPM, however, was found to perform better than the other methods for the intra-cerebral cerebrospinal fluid (mainly in the ventricular compartments). Limited differences in terms of activation morphology and detection sensitivity were found between low resolution functional maps (FWHM approximately 10 mm) spatially normalized with the four methods, which overlapped in 42.8% of the total activation volume. These findings suggest that the functional variability is much larger than the anatomical one and that precise alignment of anatomical features has low influence on the resulting intersubject functional maps. When increasing the spatial resolution to approximately 6 mm, however, differences in localization of activated areas appear as a consequence of the different spatial normalization procedure used, restricting the overlap of the normalized activated volumes to only 6.2%., (Copyright 2002 Wiley-Liss, Inc.)

Functional activations of the human brain cortex were observed with a standard 1.5-tesla MR imaging system using a long time echo fast low-angle shot sequence. Neural activation increases regional cerebral blood flow resulting in increased capillaries and venous blood oxygenation. Processing requires adapted algorithms because the time course of intensity signal showed fluctuations of the baseline. The use of a 'follow-up' method to generate activation maps is proposed. Brain activation was detected in striate cortex during photic stimulation and in sensorimotor areas while subjects were moving their hands. In mental imagery tasks, we observed a primary and secondary visual cortex activation during memory recall of the flashing light. Motor ideation showed an activation of the rolandic areas.

Current methods for detecting activation foci in positron emission tomography difference images include a low pass filtering step aimed at improving the signal-to-noise ratio. However, we show that detection sensitivity depends both on the activation signal and the filter sizes. Therefore, we propose to improve current detection methods by using a multifiltering strategy that is shown to be more sensitive when various kinds of signals are present in the brain activation images.

This study used xenon 133 inhalation and single-photon computed tomography to measure regional cerebral blood flow during a quiet resting condition, a simple auditory task, and an auditory phonemic discrimination task in 3 age-matched groups of children suffering from developmental language disabilities: expressive dysphasia, expressive-receptive dysphasia, and attention-deficit hyperactivity disorder. An absence of left hemisphere activation was observed in the expressive-receptive group during the phonemic discrimination task as compared to both expressive and attention-deficit hyperactivity disorder children, together with an absence of left inferior parietal region activation in dysphasics as compared to hyperactive children. These results favor the hypothesis of an abnormal lateralization for language in dysphasic children and point toward possible different pathologic localizations in the different clinical subtypes of dysphasia.

The authors propose a new method for the analysis of brain activation images that aims at detecting activated volumes rather than pixels. The method is based on Poisson process modeling, hierarchical description, and multiscale detection (MSD). Its performances have been assessed using both Monte Carlo simulated images and experimental PET brain activation data. As compared to other methods, the MSD approach shows enhanced sensitivity with a controlled overall type I error, and has the ability to provide an estimate of the spatial limits of the detected signals. It is applicable to any kind of difference image for which the spatial autocorrelation function can be approximated by a stationary Gaussian function.

Abstract In this study, we compare regional cerebral blood flow (rCBF) while French monolingual subjects listen to continuous speech in an unknown language, to lists of French words, or to meaningful and distorted stories in French. Our results show that, in addition to regions devoted to single-word comprehension, processing of meaningful stories activates the left middle temporal gyrus, the left and right temporal poles, and a superior prefrontal area in the left frontal lobe. Among these regions, only the temporal poles remain activated whenever sentences with acceptable syntax and prosody are presented.

We present a new method for the analysis of individual brain positron emission tomography (PET) activation maps that looks for activated areas of a certain size rather than pixels with maximum values. High signal-to-noise-ratio pixel clusters (HSC) are identified and their sizes are statistically tested with respect to a Monte-Carlo-derived distribution of cluster sizes in pure noise images. From multiple HSC size tests, a strategy is proposed for control of the overall type I error. The sensitivity and specificity of this method have been assessed using realistic Monte Carlo simulations of brain activation maps. When compared with the gamma 2 statistic of the local maxima distribution, the proposed method showed enhanced sensitivity, particularly for signals of low magnitude and/or large size. Its potential for the individual analysis of PET activation studies is presented in two sets of subjects who underwent two cognitive protocols. Although it can be viewed as an alternative to the classical stereotactic averaging approach, this new method is intended to be a first step toward the analysis of single-subject PET activation studies.

The authors propose a method for the 3-D reconstruction of the brain from anisotropic magnetic resonance imaging (MRI) brain data. The method essentially consists in two original algorithms both for segmentation and for interpolation of the MRI data. The segmentation process is performed in three steps. A gray level thresholding of the white and gray matter tissue is performed on the brain MR raw data. A global white matter segmentation is automatically performed with a global 3-D connectivity algorithm which takes into account the anisotropy of the MRI voxel. The gray matter is segmented with a local 3-D connectivity algorithm. Mathematical morphology tools are used to interpolate slices. The whole process gives an isotropic binary representation of both gray and white matter which are available for 3-D surface rendering. The power and practicality of this method have been tested on four brain datasets. The segmentation algorithm favorably compares to a manual one. The interpolation algorithm was compared to the shaped-based method both quantitatively and qualitatively.

The specific activity (SA) of free methionine was measured in plasma and in different regions of the rat brain at 15, 30, or 60 min after intravenous infusion of L-[14C-methyl]methionine. Within these time periods, an apparent steady state of labeled free methionine in plasma and in brain was reached. However, the brain-to-plasma free methionine SA ratio was found to be approximately 0.5, showing that an isotopic equilibrium between brain and plasma was not attained. This suggests the presence of an endogenous source of brain free methionine (likely originating from protein breakdown), in addition to the plasma source. The contribution of this endogenous source to the content of free methionine varies significantly among the different brain regions. Our results indicate that the regional rates of protein synthesis measured with L-[11C-methyl]methionine using positron emission tomography would be underestimated, since the local fraction of brain methionine derived from protein degradation would not be considered.

Linear compartmental models are used to describe the disposition of radio-labelled compounds in regions of interest in the mammalian body, based on a time sequence of measurements from a positron emission tomograph (PET). In this paper we show how closed form solutions for the model equations have been incorporated into a computer program for simulation and parameter estimation. A typical PET data example is included to illustrate the implementation and compare the closed form method with a numerical ode solution method.

To test the hypothesis that cerebral metabolism is altered in myotonic dystrophy (MyD), we investigated cerebral glucose kinetics and utilization in 11 adult patients with MyD and 14 healthy controls, using 18F-labeled 2-fluoro-2-deoxy-D-glucose (FDG) and dynamic positron emission tomography. Estimation of rate constants in MyD revealed a reduction of FDG delivery to the brain. Cortical glucose utilization rate was reduced by about 20% in MyD. These findings may be related to the presence of neurologic impairment in MyD and prompt further investigations on the metabolic and clinical features of brain dysfunction in this disease.

We present a method for brain single photon emission computed tomography (SPECT) analysis based on individual registration of anatomical (CT) and functional (133Xe regional cerebral blood flow) images and on the definition of three-dimensional functional regions of interest. Registration of CT and SPECT is performed through adjustment of CT-defined cortex limits to the SPECT image. Regions are defined by sectioning a cortical ribbon on the CT images, copied over the SPECT images and pooled through slices to give 3D cortical regions of interest. The proposed method shows good intra- and interobserver reproducibility (regional intraclass correlation coefficient approximately 0.98), and good accuracy in terms of repositioning (approximately 3.5 mm) as compared to the SPECT image resolution (14 mm). The method should be particularly useful for analysing SPECT studies when variations in brain anatomy (normal or abnormal) must be accounted for.

We have compared various methods of in vivo NMR spectral parameter estimation, namely a nonlinear fit of the free induction decay signal in the time domain (NLTD), a nonlinear fit of the fast Fourier transform of the FID data in the frequency domain using either a continuous Lorentzian model (NLLM) or a Fourier-sampled model (NLFM), and a time-domain linear prediction method using singular value decomposition (LPSVD). Monte Carlo simulations of 31P and 13C in vivo experiments were used to assess the bias and statistical uncertainties of spectral parameters obtained with each method. In the 31P case, all methods appear to be equivalent except the LPSVD method that led to significantly biased peak amplitudes (up to 28%). In the 13C case, the only methods able to recover the glycogen peak were the NLTD method and its equivalent in the frequency domain (NLFM). In both the 31P and the 13C cases simulations demonstrated that 256 data points were sufficient. These results demonstrate the feasibility and the robustness of a nonlinear fit of the FID data in the time domain, and we illustrate this on 31P and 13C data sets obtained in humans.

Thirty-nine patients with liver tumors were examined using MRI at 0.5 T before and after intravenous bolus injection of either 0.1 mmol/kg (n = 18) or 0.2 mmol/kg (n = 21) of Gadolinium-Dota, using spin-echo T1-and T2-weighted sequences before injections and spin-echo or gradient-echo sequences after injection. When contrast-to-noise (C/N) data were normalized relative to time, optimal mean C/N was observed after gadolinium injection. However, subjective study and case-by-case C/N measurement showed better contrast for SE 2000/60 and CT with injection in 62% and 42% of cases, respectively.

We present measurements performed on the time-of-flight positron emission tomograph CEA-LETI-TTV03 with the EEC Emission Phantom. The transaxial resolution for a direct plane in the reconstructed image (Ramp filter, fc = 0.25 mm-1) was found to be 6.2 mm (radial and tangential) at center, 6.8 mm (radial) and 6.1 mm (tangential) at 45 mm from the center and 8.6 (radial) and 5.3 (tangential) mm at 90 mm from the center; in an image reconstructed with a Hanning filter at the same frequency cut-off and with a scatter correction, these values are degraded to 7.1 mm (tangential) and 7.2 mm (radial) at center, 7.6 mm (radial) and 6.9 mm (radial) at 45 mm from the center and 9.5 mm (radial) and 6.1 mm (tangential) at 90 mm from the center. Values were identical for direct and cross planes and correcting from the scatter radiation did not modify the resolution. Recovery coefficients for a 17 cm diameter sphere were equal to 0.85 in a direct plane and 1. for a cross plane, this being due to the axial resolution which is 9.1 mm and 7.1 mm at 5.5 cm from the center for direct and cross planes respectively. With 10 mCi in the phantom simulating abdominal imaging the maximum recorded coincidences on a cross plane was 84.4 kevents/sec, 50.2 kevents/sec on a direct plane and 343.4 kevents/sec for the entire machine. The dead time losses in terms of trues were equal to 24% and 17% for direct and cross planes respectively while the single rate was 19900/sec/detector. Scatter fraction, evaluated using a uniform cylinder, was found to be 15% for a cross plane.

The in vivo quantification of myocardial muscarinic receptors has been obtained in six closed-chest dogs by using positron emission tomography. The dogs were injected with a trace amount of 11C-labeled methylquinuclidinyl benzilate (MQNB), a nonmetabolized antagonist of the muscarinic receptor. This was followed 30 minutes later by an injection of an excess of unlabeled MQNB (displacement experiment). Two additional injections of unlabeled MQNB with [11C]MQNB (coinjection experiment) and without [11C]MQNB (second displacement experiment) were administered after 70 and 120 minutes, respectively. This protocol allowed a separate evaluation of the quantity of available receptors (B'max) as well as the association and dissociation rate constants (k+1 and k-1) in each dog. The parameters were calculated by using a nonlinear mathematical model in regions of interest over the left ventricle and the interventricular septum. The average value of B'max was 42 +/- 11 pmol/ml tissue, the rate constants k+1, k-1, and Kd were 0.6 +/- 0.1 ml.pmol-1.min-1, 0.27 +/- 0.03 ml.pmol-1.min-1, and 0.49 +/- 0.14 pmol.ml-1, respectively, taking into account the MQNB reaction volume estimated to 0.15 ml/ml tissue. Although [11C]MQNB binding would appear irreversible, our findings indicate that the association of the antagonist is very rapid and that the dissociation is far from negligible. The dissociated ligand, however, has a high probability of rebinding to a free receptor site instead of escaping into the microcirculation. We deduce that the positron emission tomographic images obtained after injecting a trace amount of [11C]MQNB are more representative of blood flow than of receptor density or affinity. We also suggest a simplified protocol consisting of a tracer injection of [11C]MQNB and a second injection of an excess of cold MQNB, which is sufficient to measure B'max and Kd in humans.

The authors compared 16 nondepressed obsessive-compulsive patients (OCS) with 8 normal controls (NC) of similar age for resting-state regional cerebral glucose metabolic rates (rCMRglu) using positron emission tomography with the fluorodeoxyglucose method. OCS were rated for clinical data, and a neuropsychological battery was administered to 14 patients on the day of the scan. Absolute rCMRglu for whole cortex, and normalized prefrontal lateral cortex metabolic rates, were both significantly lower in OCS than in NC. No significant difference between treated (n = 10) and drug-free (n = 6) OCS was found for those variables. OCS were significantly impaired in the neuropsychological tasks assessing memory and attention. The rCMRglu for prefrontal lateral cortex were negatively correlated to Stroop-test subscores. This "frontal-oriented" task assessed the ability of OCS to inhibit immediate but inappropriate responses. These results suggest, in OCS, a modification of the general activating systems of cortical function and a relationship between the lateral prefrontal rCMRglu decrease and a selective attention deficit.

Identifiability problem is a very important topic in the framework of model justification and not accounting for it during the modeling procedure can lead to meaningless results. While studying the receptor-ligand model parameter estimation from dynamic positron emission tomography data, each of the three possible conclusions to the identifiability problem (i.e., unidentifiable model, multiple solutions, or unique solution) are reached depending on the experimental protocol used. The identification of the model parameters from data obtained with a single tracer injection leads to disappointing numerical results since most of the parameters have to be considered as unidentifiable. A protocol including two injections, a first injection of the labeled ligand and a second injection of the cold ligand (displacement experiment) leads to two very different numerical solutions, which is surprising since such multiplicity of solutions was not indicated by a preliminary theoretical identifiability study. We show that a three-injections protocol, including both a displacement and coinjection experiment, allows to determine which of these two solutions is biologically valid.

Measurements of cerebral glucose utilization rates in similar populations of human subjects under similar conditions vary considerably because of methods used in data collection and analysis. Using data acquired in two patients, we evaluated the effects of time schedule of data collection, region of interest size, method of attenuation correction, and input function shape on LCMRglu determined by dynamic positron emission tomographic scanning and calculation of rate constants. These different strategies of data acquisition and analysis produced variations of 3 to 14% in calculated LCMRglu. These factors, in conjunction with the well described effects of instrument resolution and sensitivity may account for data discrepancies in the literature.

A general method for estimating the precision of parameters resulting from the use of various experimental designs (rate of injection and rate of tomographic data collection) in emission tomography studies is proposed. The sensitivity matrix of the study model and an estimate of the statistical uncertainty of the tomographic data are used to compute the covariance matrix of the parameters. The determinant of this covariance matrix (proportional to the total volume of uncertainty of the model parameters) serves as a criterion to be minimized. The method is applied to a three-compartment, three-transfer rate constant for glucose metabolism using dynamic positron emission tomography, and a comparison of various current protocols is made with simulated data. The results show that higher rates of injection and higher rates of tomographic data collection at early times lead to smaller statistical uncertainties for the estimates of rate constants. However, for the range of rate constants encountered in practice, differences are insignificant when an initial scan duration less than 30 s is used, without regarding the injection duration.

Methods of parameter estimation are proposed for the analysis of dynamic experiments in which the input function is noisy. Noise in the input function leads to uncertainties in the calculated model-predicted values, and therefore the covariance matrix of the residuals is a function of the model parameters. These statistical uncertainties in the model-predicted values significantly change the nature of the fitting process and the quality of the results. The proposed optimisation methods use weighted least-squares criteria, and three choices for the weighting matrix are considered. The proposed weighting matrices, in order of complexity are: (1) the identity matrix (no weighting), (2) the covariance matrix of the data (ignoring the noise in the input function), and (3) the full covariance matrix of the residuals (incorporating both the noise in the data and the noise in the input function). The methodology is applied to dynamic emission tomography studies of the heart, where the blood (input) and tissue tracer concentrations at each time are derived from two regions of interest in the same tomographic slice. Computer stimulations of compartmental systems show that parameters and their covariance matrix are more accurately estimated when the full covariance matrix of the residuals is used as a weighting matrix rather than either of the other two methods. For the practical example considered, parameter bias was increased by a factor of at least four when the noise in the input function was ignored, and one parameter had a bias of 24% when the unweighted least-squares criterion was used.

A correction for loss of events due to dead time in dynamic positron emission tomography (PET) is presented. The model employs a paralysing dead time to describe the behaviour of a tomograph over the range of event rates normally encountered in patient studies (up to 200 000 events/s per detector layer). The Donner 280-crystal positron tomograph has a dead time of 1.8 microseconds/event for observed count rates less than 200 000 events/s. The dead time correction factor is 1.8 at 180 000 events/s. The correction is applied to projection data and region of interest analysis of dynamic PET studies, and formulae for the covariances between corrected projection data and between counts in regions of interest in different images from the same dynamic study are established. At 180 000 events/s, the variance of the actual (corrected) number of events in a region containing 3.34 X 10(5) actual events is predicted from the model to be 3.86 X 10(6) (events)2, more than 10 times the variance that would be expected from a naive assumption of Poisson statistics. These statistical results are verified experimentally. An error of 25% is observed in myocardial flow if dead time compensation is not applied, showing the necessity for this correction.

The general framework and various criteria for experimental design optimisation are presented. The methodology is applied to the estimation of receptor-ligand reaction model parameters with dynamic positron emission tomography data. The possibility of improving parameter estimation using a new experimental design combining an injection of the beta+-labelled ligand and an injection of the cold ligand is investigated. Numerical simulations predict a remarkable improvement in the accuracy of the parameter estimates with this new experimental design and particularly the possibility of separate estimations of the association constant (k+1) and of the receptor density (B'max) in a single experiment. Simulation predictions are validated using experimental PET data in which parameter uncertainties are reduced by factors ranging from 17 to 1000.

The effectiveness of a shaped filter in the detection of mediastinal and retrocardiac abnormalities on 140-kVp posteroanterior chest radiographs was measured by observer-performance testing. A set of 100 radiographs (the filtered and nonfiltered radiographs of 50 patients) were randomly selected from 1000 radiographs obtained from 500 outpatients or hospitalized patients. Five observers independently interpreted the set of radiographs, with one observer interpreting the set twice. Observer performance in detecting abnormalities in the mediastinum and the retrocardiac lung were analyzed by using receiver-operating characteristic techniques. The results indicate that the use of a filter has no significant overall diagnostic advantage (areas under the receiver-operating characteristic curves were 0.90 for the filtered radiographs and 0.89 for the unfiltered radiographs). No significant differences were found in the analysis of the various types or locations of lesions in the mediastinum.

We performed dynamic positron emission tomographic (PET) studies of glucose utilization, using (18F) 2-fluoro-2-deoxy-D-glucose (FDG), in patients with probable Alzheimer's disease (AD) and healthy age-matched controls, to evaluate blood-brain-barrier glucose transport and glucose utilization rates in the disease. We found no significant differences in rate constants for glucose transport (k1 and k2) and phosphorylation (k3), nor for the vascular fraction (fv), between the 2 groups, although k3 and fv were relatively depressed in temporal cortex in AD. Absolute rates of glucose use were depressed in temporal and parietal cortex, and relative rCMRglc rates were lower in frontal, temporal, parietal, and occipital cortices. These data suggest that in AD bidirectional glucose transport is intact, and that temporal-parietal hypometabolism is present upon a background of widespread cortical metabolic impairment.