Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

Photodamage to Oxygen Evolving Complex - An Initial Event in Photoinhibition of Photosystem II.

Photosystem II (PSII) of oxygenic photosynthesis is susceptible to photoinhibition. Photoinhibition is defined as light induced damage resulting in turnover of the D1 protein subunit of the reaction center of PSII. Both visible and ultraviolet (UV) light cause photoinhibition. Photoinhibition induced by UV light damages the oxygen evolving complex (OEC) via absorption of UV photons by the Mn ion(s) of OEC. Under visible light, most of the earlier hypotheses assume that photoinhibition occurs when the rate of photon absorption by PSII antenna exceeds the use of the absorbed energy in photosynthesis. However, photoinhibition occurs at all light intensities with the same efficiency per photon. The aim of my thesis work was to build a model of photoinhibition that fits the experimental features of photoinhibition. I studied the role of electron transfer reactions of PSII in photoinhibition and found that changing the electron transfer rate had only minor influence on photoinhibition if light intensity was kept constant. Furthermore, quenching of antenna excitations protected less efficiently than it would protect if antenna chlorophylls were the only photoreceptors of photoinhibition. To identify photoreceptors of photoinhibition, I measured the action spectrum of photoinhibition. The action spectrum showed resemblance to the absorption spectra of Mn model compounds suggesting that the Mn cluster of OEC acts as a photoreceptor of photoinhibition under visible light, too. The role of Mn in photoinhibition was further supported by experiments showing that during photoinhibition OEC is damaged before electron transfer activity at the acceptor side of PSII is lost. Mn enzymes were found to be photosensitive under visible and UV light indicating that Mn-containing compounds, including OEC, are capable of functioning as photosensitizers both in visible and UV light. The experimental results above led to the Mn hypothesis of the mechanism of continuous-light-induced photoinhibition. According to the Mn hypothesis, excitation of Mn of OEC results in inhibition of electron donation from OEC to the oxidized primary donor P680+ both under UV and visible light. P680 is oxidized by photons absorbed by chlorophyll, and if not reduced by OEC, P680+ may cause harmful oxidation of other PSII components. Photoinhibition was also induced with intense laser pulses and it was found that the photoinhibitory efficiency increased in proportion to the square of pulse intensity suggesting that laser-pulse-induced photoinhibition is a two-photon reaction. I further developed the Mn hypothesis suggesting that the initial event in photoinhibition under both continuous and pulsed light is the same: Mn excitation that leads to the inhibition of electron donation from OEC to P680+. Under laser-pulse-illumination, another Mn-mediated inhibitory photoreaction occurs within the duration of the same pulse, whereas under continuous light, secondary damage is chlorophyll mediated. A mathematical model based on the Mn hypothesis was found to explain photoinhibition under continuous light, under flash illumination and under the combination of these two.

Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

Computed Tomography (CT) represents the standard imaging modality for tumor volume delineation for radiotherapy treatment planning of retinoblastoma despite some inherent limitations. CT scan is very useful in providing information on physical density for dose calculation and morphological volumetric information but presents a low sensitivity in assessing the tumor viability. On the other hand, 3D ultrasound (US) allows a highly accurate definition of the tumor volume thanks to its high spatial resolution but it is not currently integrated in the treatment planning but used only for diagnosis and follow-up. Our ultimate goal is an automatic segmentation of gross tumor volume (GTV) in the 3D US, the segmentation of the organs at risk (OAR) in the CT and the registration of both modalities. In this paper, we present some preliminary results in this direction. We present 3D active contour-based segmentation of the eye ball and the lens in CT images; the presented approach incorporates the prior knowledge of the anatomy by using a 3D geometrical eye model. The automated segmentation results are validated by comparing with manual segmentations. Then, we present two approaches for the fusion of 3D CT and US images: (i) landmark-based transformation, and (ii) object-based transformation that makes use of eye ball contour information on CT and US images.

Visuo-motor pathways in humans revealed by event-related fMRI.

Whether different brain networks are involved in generating unimanual responses to a simple visual stimulus presented in the ipsilateral versus contralateral hemifield remains a controversial issue. Visuo-motor routing was investigated with event-related functional magnetic resonance imaging (fMRI) using the Poffenberger reaction time task. A 2 hemifield x 2 response hand design generated the "crossed" and "uncrossed" conditions, describing the spatial relation between these factors. Both conditions, with responses executed by the left or right hand, showed a similar spatial pattern of activated areas, including striate and extrastriate areas bilaterally, SMA, and M1 contralateral to the responding hand. These results demonstrated that visual information is processed bilaterally in striate and extrastriate visual areas, even in the "uncrossed" condition. Additional analyses based on sorting data according to subjects' reaction times revealed differential crossed versus uncrossed activity only for the slowest trials, with response strength in infero-temporal cortices significantly correlating with crossed-uncrossed differences (CUD) in reaction times. Collectively, the data favor a parallel, distributed model of brain activation. The presence of interhemispheric interactions and its consequent bilateral activity is not determined by the crossed anatomic projections of the primary visual and motor pathways. Distinct visuo-motor networks need not be engaged to mediate behavioral responses for the crossed visual field/response hand condition. While anatomical connectivity heavily influences the spatial pattern of activated visuo-motor pathways, behavioral and functional parameters appear to also affect the strength and dynamics of responses within these pathways.

Prediction of 18-month survival in patients with primary myelodysplastic syndrome. A regression model and scoring system based on the combination of chromosome findings and the Bournemouth score.

The predictive potential of six selected factors was assessed in 72 patients with primary myelodysplastic syndrome using univariate and multivariate logistic regression analysis of survival at 18 months. Factors were age (above median of 69 years), dysplastic features in the three myeloid bone marrow cell lineages, presence of chromosome defects, all metaphases abnormal, double or complex chromosome defects (C23), and a Bournemouth score of 2, 3, or 4 (B234). In the multivariate approach, B234 and C23 proved to be significantly associated with a reduction in the survival probability. The similarity of the regression coefficients associated with these two factors means that they have about the same weight. Consequently, the model was simplified by counting the number of factors (0, 1, or 2) present in each patient, thus generating a scoring system called the Lausanne-Bournemouth score (LB score). The LB score combines the well-recognized and easy-to-use Bournemouth score (B score) with the chromosome defect complexity, C23 constituting an additional indicator of patient outcome. The predicted risk of death within 18 months calculated from the model is as follows: 7.1% (confidence interval: 1.7-24.8) for patients with an LB score of 0, 60.1% (44.7-73.8) for an LB score of 1, and 96.8% (84.5-99.4) for an LB score of 2. The scoring system presented here has several interesting features. The LB score may improve the predictive value of the B score, as it is able to recognize two prognostic groups in the intermediate risk category of patients with B scores of 2 or 3. It has also the ability to identify two distinct prognostic subclasses among RAEB and possibly CMML patients. In addition to its above-described usefulness in the prognostic evaluation, the LB score may bring new insights into the understanding of evolution patterns in MDS. We used the combination of the B score and chromosome complexity to define four classes which may be considered four possible states of myelodysplasia and which describe two distinct evolutional pathways.

Decoding stimulus-related information from single-trial EEG responses based on voltage topographies

Neuroimaging studies typically compare experimental conditions using average brain responses, thereby overlooking the stimulus-related information conveyed by distributed spatio-temporal patterns of single-trial responses. Here, we take advantage of this rich information at a single-trial level to decode stimulus-related signals in two event-related potential (ERP) studies. Our method models the statistical distribution of the voltage topographies with a Gaussian Mixture Model (GMM), which reduces the dataset to a number of representative voltage topographies. The degree of presence of these topographies across trials at specific latencies is then used to classify experimental conditions. We tested the algorithm using a cross-validation procedure in two independent EEG datasets. In the first ERP study, we classified left- versus right-hemifield checkerboard stimuli for upper and lower visual hemifields. In a second ERP study, when functional differences cannot be assumed, we classified initial versus repeated presentations of visual objects. With minimal a priori information, the GMM model provides neurophysiologically interpretable features - vis à vis voltage topographies - as well as dynamic information about brain function. This method can in principle be applied to any ERP dataset testing the functional relevance of specific time periods for stimulus processing, the predictability of subject's behavior and cognitive states, and the discrimination between healthy and clinical populations.

Predicting the potential for lightning activity in mediterranean storms based on the WRF model dynamic and microphysical fields

A new parameter is introduced: the lightning potential index (LPI), which is a measure of the potential for charge generation and separation that leads to lightning flashes in convective thunderstorms. The LPI is calculated within the charge separation region of clouds between 0 C and 20 C, where the noninductive mechanism involving collisions of ice and graupel particles in the presence of supercooled water is most effective. As shown in several case studies using the Weather Research and Forecasting (WRF) model with explicit microphysics, the LPI is highly correlated with observed lightning. It is suggested that the LPI may be a useful parameter for predicting lightning as well as a tool for improving weather forecasting of convective storms and heavy rainfall.

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.

Sex differences in urinary levels of several biological indicators of exposure: a simulation study using a compartmental based toxicokinetic model

Toxicokinetic modeling is a useful tool to describe or predict the behavior of a chemical agent in the human or animal organism. A general model based on four compartments was developed in a previous study in order to quantify the effect of human variability on a wide range of biological exposure indicators. The aim of this study was to adapt this existing general toxicokinetic model to three organic solvents, which were methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1,-trichloroethane, and to take into account sex differences. We assessed in a previous human volunteer study the impact of sex on different biomarkers of exposure corresponding to the three organic solvents mentioned above. Results from that study suggested that not only physiological differences between men and women but also differences due to sex hormones levels could influence the toxicokinetics of the solvents. In fact the use of hormonal contraceptive had an effect on the urinary levels of several biomarkers, suggesting that exogenous sex hormones could influence CYP2E1 enzyme activity. These experimental data were used to calibrate the toxicokinetic models developed in this study. Our results showed that it was possible to use an existing general toxicokinetic model for other compounds. In fact, most of the simulation results showed good agreement with the experimental data obtained for the studied solvents, with a percentage of model predictions that lies within the 95% confidence interval varying from 44.4 to 90%. Results pointed out that for same exposure conditions, men and women can show important differences in urinary levels of biological indicators of exposure. Moreover, when running the models by simulating industrial working conditions, these differences could even be more pronounced. In conclusion, a general and simple toxicokinetic model, adapted for three well known organic solvents, allowed us to show that metabolic parameters can have an important impact on the urinary levels of the corresponding biomarkers. These observations give evidence of an interindividual variablity, an aspect that should have its place in the approaches for setting limits of occupational exposure.