Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

Hierarchical Markov Random Fields Applied to Model Soft Tissue Deformations on Graphics Hardware

Many methodologies dealing with prediction or simulation of soft tissue deformations on medical image data require preprocessing of the data in order to produce a different shape representation that complies with standard methodologies, such as mass–spring networks, finite element method s (FEM). On the other hand, methodologies working directly on the image space normally do not take into account mechanical behavior of tissues and tend to lack physics foundations driving soft tissue deformations. This chapter presents a method to simulate soft tissue deformations based on coupled concepts from image analysis and mechanics theory. The proposed methodology is based on a robust stochastic approach that takes into account material properties retrieved directly from the image, concepts from continuum mechanics and FEM. The optimization framework is solved within a hierarchical Markov random field (HMRF) which is implemented on the graphics processor unit (GPU See Graphics processing unit ).

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Evaluation of a Bayesian MCMC Random Effects Inference Methodology for Capture-Mark-Recapture Data

Monte Carlo simulation was used to evaluate properties of a simple Bayesian MCMC analysis of the random effects model for single group Cormack-Jolly-Seber capture-recapture data. The MCMC method is applied to the model via a logit link, so parameters p, S are on a logit scale, where logit(S) is assumed to have, and is generated from, a normal distribution with mean μ and variance σ2 . Marginal prior distributions on logit(p) and μ were independent normal with mean zero and standard deviation 1.75 for logit(p) and 100 for μ ; hence minimally informative. Marginal prior distribution on σ2 was placed on τ2=1/σ2 as a gamma distribution with α=β=0.001 . The study design has 432 points spread over 5 factors: occasions (t) , new releases per occasion (u), p, μ , and σ . At each design point 100 independent trials were completed (hence 43,200 trials in total), each with sample size n=10,000 from the parameter posterior distribution. At 128 of these design points comparisons are made to previously reported results from a method of moments procedure. We looked at properties of point and interval inference on μ , and σ based on the posterior mean, median, and mode and equal-tailed 95% credibility interval. Bayesian inference did very well for the parameter μ , but under the conditions used here, MCMC inference performance for σ was mixed: poor for sparse data (i.e., only 7 occasions) or σ=0 , but good when there were sufficient data and not small σ .

Consistent estimation of the fixed effects ordered logit model

The paper considers panel data methods for estimating ordered logit models with individual-specific correlated unobserved heterogeneity. We show that a popular approach is inconsistent, whereas some consistent and efficient estimators are available, including minimum distance and generalized method-of-moment estimators. A Monte Carlo study reveals the good properties of an alternative estimator that has not been considered in econometric applications before, is simple to implement and almost as efficient. An illustrative application based on data from the German Socio-Economic Panel confirms the large negative effect of unemployment on life satisfaction that has been found in the previous literature.

Identification and estimation of thresholds in the fixed effects ordered logit model

This paper proposes a new estimator for the fixed effects ordered logit model. In contrast to existing methods, the new procedure allows estimating the thresholds. The empirical relevance and simplicity of implementation is illustrated in an application on the effect of unemployment on life satisfaction.

Analyzing spatio-temporal patterns of genuine cross-correlations

In multivariate time series analysis, the equal-time cross-correlation is a classic and computationally efficient measure for quantifying linear interrelations between data channels. When the cross-correlation coefficient is estimated using a finite amount of data points, its non-random part may be strongly contaminated by a sizable random contribution, such that no reliable conclusion can be drawn about genuine mutual interdependencies. The random correlations are determined by the signals' frequency content and the amount of data points used. Here, we introduce adjusted correlation matrices that can be employed to disentangle random from non-random contributions to each matrix element independently of the signal frequencies. Extending our previous work these matrices allow analyzing spatial patterns of genuine cross-correlation in multivariate data regardless of confounding influences. The performance is illustrated by example of model systems with known interdependence patterns. Finally, we apply the methods to electroencephalographic (EEG) data with epileptic seizure activity.

Thermal model for optimization of vascular laser tissue soldering

Laser tissue soldering (LTS) is a promising technique for tissue fusion based on a heat-denaturation process of proteins. Thermal damage of the fused tissue during the laser procedure has always been an important and challenging problem. Particularly in LTS of arterial blood vessels strong heating of the endothelium should be avoided to minimize the risk of thrombosis. A precise knowledge of the temperature distribution within the vessel wall during laser irradiation is inevitable. The authors developed a finite element model (FEM) to simulate the temperature distribution within blood vessels during LTS. Temperature measurements were used to verify and calibrate the model. Different parameters such as laser power, solder absorption coefficient, thickness of the solder layer, cooling of the vessel and continuous vs. pulsed energy deposition were tested to elucidate their impact on the temperature distribution within the soldering joint in order to reduce the amount of further animal experiments. A pulsed irradiation with high laser power and high absorbing solder yields the best results.

Estimation of axon counts in a rat model of glaucoma: comparison of fixed-pattern sampling with targeted sampling

Full axon counting of optic nerve cross-sections represents the most accurate method to quantify axonal damage, but such analysis is very labour intensive. Recently, a new method has been developed, termed targeted sampling, which combines the salient features of a grading scheme with axon counting. Preliminary findings revealed the method compared favourably with random sampling. The aim of the current study was to advance our understanding of the effect of sampling patterns on axon counts by comparing estimated axon counts from targeted sampling with those obtained from fixed-pattern sampling in a large collection of optic nerves with different severities of axonal injury.

An Urn Model for Cascading Failures on a Lattice

A cascading failure is a failure in a system of interconnected parts, in which the breakdown of one element can lead to the subsequent collapse of the others. The aim of this paper is to introduce a simple combinatorial model for the study of cascading failures. In particular, having in mind particle systems and Markov random fields, we take into consideration a network of interacting urns displaced over a lattice. Every urn is Pólya-like and its reinforcement matrix is not only a function of time (time contagion) but also of the behavior of the neighboring urns (spatial contagion), and of a random component, which can represent either simple fate or the impact of exogenous factors. In this way a non-trivial dependence structure among the urns is built, and it is used to study default avalanches over the lattice. Thanks to its flexibility and its interesting probabilistic properties, the given construction may be used to model different phenomena characterized by cascading failures such as power grids and financial networks.

Estimating the number of motor units using random sums with independently thinned terms

The problem of estimating the numbers of motor units N in a muscle is embedded in a general stochastic model using the notion of thinning from point process theory. In the paper a new moment type estimator for the numbers of motor units in a muscle is denned, which is derived using random sums with independently thinned terms. Asymptotic normality of the estimator is shown and its practical value is demonstrated with bootstrap and approximative confidence intervals for a data set from a 31-year-old healthy right-handed, female volunteer. Moreover simulation results are presented and Monte-Carlo based quantiles, means, and variances are calculated for N in{300,600,1000}.

Ventricular-arterial coupling in a rat model of reduced arterial compliance provoked by hypervitaminosis D and nicotine

The vitamin D(3) and nicotine (VDN) model is one of isolated systolic hypertension (ISH) in which arterial calcification raises arterial stiffness and vascular impedance. The effects of VDN treatment on arterial and cardiac hemodynamics have been investigated; however, a complete analysis of ventricular-arterial interaction is lacking. Wistar rats were treated with VDN (VDN group, n = 9), and a control group (n = 10) was included without the VDN. At week 8, invasive indexes of cardiac function were obtained using a conductance catheter. Simultaneously, aortic pressure and flow were measured to derive vascular impedance and characterize ventricular-vascular interaction. VDN caused significant increases in systolic (138 +/- 6 vs. 116 +/- 13 mmHg, P < 0.01) and pulse (42 +/- 10 vs. 26 +/- 4 mmHg, P < 0.01) pressures with respect to control. Total arterial compliance decreased (0.12 +/- 0.08 vs. 0.21 +/- 0.04 ml/mmHg in control, P < 0.05), and pulse wave velocity increased significantly (8.8 +/- 2.5 vs. 5.1 +/- 2.0 m/s in control, P < 0.05). The arterial elastance and end-systolic elastance rose significantly in the VDN group (P < 0.05). Wave reflection was augmented in the VDN group, as reflected by the increase in the wave reflection coefficient (0.63 +/- 0.06 vs. 0.52 +/- 0.05 in control, P < 0.05) and the amplitude of the reflected pressure wave (13.3 +/- 3.1 vs. 8.4 +/- 1.0 mmHg in control, P < 0.05). We studied ventricular-arterial coupling in a VDN-induced rat model of reduced arterial compliance. The VDN treatment led to development of ISH and provoked alterations in cardiac function, arterial impedance, arterial function, and ventricular-arterial interaction, which in many aspects are similar to effects of an aged and stiffened arterial tree.

Orthotopic transplantation of v-src-expressing glioma cell lines into immunocompetent mice: establishment of a new transplantable in vivo model for malignant glioma

OBJECT: The aim of this study was to develop and characterize a new orthotopic, syngeneic, transplantable mouse brain tumor model by using the cell lines Tu-9648 and Tu-2449, which were previously isolated from tumors that arose spontaneously in glial fibrillary acidic protein (GFAP)-v-src transgenic mice. METHODS: Striatal implantation of a 1-microl suspension of 5000 to 10,000 cells from either clone into syngeneic B6C3F1 mice resulted in tumors that were histologically identified as malignant gliomas. Prior subcutaneous inoculations with irradiated autologous cells inhibited the otherwise robust development of a microscopically infiltrating malignant glioma. Untreated mice with implanted tumor cells were killed 12 days later, when the resultant gliomas were several millimeters in diameter. Immunohistochemically, the gliomas displayed both the astroglial marker GFAP and the oncogenic form of signal transducer and activator of transcription-3 (Stat3). This form is called tyrosine-705 phosphorylated Stat3, and is found in many malignant entities, including human gliomas. Phosphorylated Stat3 was particularly prominent, not only in the nucleus but also in the plasma membrane of peripherally infiltrating glioma cells, reflecting persistent overactivation of the Janus kinase/Stat3 signal transduction pathway. The Tu-2449 cells exhibited three non-random structural chromosomal aberrations, including a deletion of the long arm of chromosome 2 and an apparently balanced translocation between chromosomes 1 and 3. The GFAP-v-src transgene was mapped to the pericentromeric region of chromosome 18. CONCLUSIONS: The high rate of engraftment, the similarity to the high-grade malignant glioma of origin, and the rapid, locally invasive growth of these tumors should make this murine model useful in testing novel therapies for human malignant gliomas.

Exogenous surfactant application in a rat lung ischemia reperfusion injury model: effects on edema formation and alveolar type II cells

BACKGROUND: Prophylactic exogenous surfactant therapy is a promising way to attenuate the ischemia and reperfusion (I/R) injury associated with lung transplantation and thereby to decrease the clinical occurrence of acute lung injury and acute respiratory distress syndrome. However, there is little information on the mode by which exogenous surfactant attenuates I/R injury of the lung. We hypothesized that exogenous surfactant may act by limiting pulmonary edema formation and by enhancing alveolar type II cell and lamellar body preservation. Therefore, we investigated the effect of exogenous surfactant therapy on the formation of pulmonary edema in different lung compartments and on the ultrastructure of the surfactant producing alveolar epithelial type II cells. METHODS: Rats were randomly assigned to a control, Celsior (CE) or Celsior + surfactant (CE+S) group (n = 5 each). In both Celsior groups, the lungs were flush-perfused with Celsior and subsequently exposed to 4 h of extracorporeal ischemia at 4 degrees C and 50 min of reperfusion at 37 degrees C. The CE+S group received an intratracheal bolus of a modified natural bovine surfactant at a dosage of 50 mg/kg body weight before flush perfusion. After reperfusion (Celsior groups) or immediately after sacrifice (Control), the lungs were fixed by vascular perfusion and processed for light and electron microscopy. Stereology was used to quantify edematous changes as well as alterations of the alveolar epithelial type II cells. RESULTS: Surfactant treatment decreased the intraalveolar edema formation (mean (coefficient of variation): CE: 160 mm3 (0.61) vs. CE+S: 4 mm3 (0.75); p < 0.05) and the development of atelectases (CE: 342 mm3 (0.90) vs. CE+S: 0 mm3; p < 0.05) but led to a higher degree of peribronchovascular edema (CE: 89 mm3 (0.39) vs. CE+S: 268 mm3 (0.43); p < 0.05). Alveolar type II cells were similarly swollen in CE (423 microm3(0.10)) and CE+S (481 microm3(0.10)) compared with controls (323 microm3(0.07); p < 0.05 vs. CE and CE+S). The number of lamellar bodies was increased and the mean lamellar body volume was decreased in both CE groups compared with the control group (p < 0.05). CONCLUSION: Intratracheal surfactant application before I/R significantly reduces the intraalveolar edema formation and development of atelectases but leads to an increased development of peribronchovascular edema. Morphological changes of alveolar type II cells due to I/R are not affected by surfactant treatment. The beneficial effects of exogenous surfactant therapy are related to the intraalveolar activity of the exogenous surfactant.