Neural parameters estimation for brain tumor growth modeling

Understanding the dynamics of brain tumor progression is essential for optimal treatment planning. Cast in a mathematical formulation, it is typically viewed as evaluation of a system of partial differential equations, wherein the physiological processes that govern the growth of the tumor are considered. To personalize the model, i.e. find a relevant set of parameters, with respect to the tumor dynamics of a particular patient, the model is informed from empirical data, e.g., medical images obtained from diagnostic modalities, such as magnetic-resonance imaging. Existing model-observation coupling schemes require a large number of forward integrations of the biophysical model and rely on simplifying assumption on the functional form, linking the output of the model with the image information. In this work, we propose a learning-based technique for the estimation of tumor growth model parameters from medical scans. The technique allows for explicit evaluation of the posterior distribution of the parameters by sequentially training a mixture-density network, relaxing the constraint on the functional form and reducing the number of samples necessary to propagate through the forward model for the estimation. We test the method on synthetic and real scans of rats injected with brain tumors to calibrate the model and to predict tumor progression

Predicting the Location of Glioma Recurrence After a Resection Surgery

International audienceWe propose a method for estimating the location of glioma recurrence after surgical resection. This method consists of a pipeline including the registration of images at different time points, the estimation of the tumor infiltration map, and the prediction of tumor regrowth using a reaction-diffusion model. A data set acquired on a patient with a low-grade glioma and post surgery MRIs is considered to evaluate the accuracy of the estimated recurrence locations found using our method. We observed good agreement in tumor volume prediction and qualitative matching in regrowth locations. Therefore, the proposed method seems adequate for modeling low-grade glioma recurrence. This tool could help clinicians anticipate tumor regrowth and better characterize the radiologically non-visible infiltrative extent of the tumor. Such information could pave the way for model-based personalization of treatment planning in a near future

A generative approach for image-based modeling of tumor growth

22nd International Conference, IPMI 2011, Kloster Irsee, Germany, July 3-8, 2011. ProceedingsExtensive imaging is routinely used in brain tumor patients to monitor the state of the disease and to evaluate therapeutic options. A large number of multi-modal and multi-temporal image volumes is acquired in standard clinical cases, requiring new approaches for comprehensive integration of information from different image sources and different time points. In this work we propose a joint generative model of tumor growth and of image observation that naturally handles multi-modal and longitudinal data. We use the model for analyzing imaging data in patients with glioma. The tumor growth model is based on a reaction-diffusion framework. Model personalization relies only on a forward model for the growth process and on image likelihood. We take advantage of an adaptive sparse grid approximation for efficient inference via Markov Chain Monte Carlo sampling. The approach can be used for integrating information from different multi-modal imaging protocols and can easily be adapted to other tumor growth models.German Academy of Sciences Leopoldina (Fellowship Programme LPDS 2009-10)Academy of Finland (133611)National Institutes of Health (U.S.) (NIBIB NAMIC U54-EB005149)National Institutes of Health (U.S.) (NCRR NAC P41- RR13218)National Institutes of Health (U.S.) (NINDS R01-NS051826)National Institutes of Health (U.S.) (NIH R01-NS052585)National Institutes of Health (U.S.) (NIH R01-EB006758)National Institutes of Health (U.S.) (NIH R01-EB009051)National Institutes of Health (U.S.) (NIH P41-RR014075)National Science Foundation (U.S.) (CAREER Award 0642971

Effects of oxidative stress on the erythrocyte Na+,K+ ATPase activity in female hyperthyroid patients

This study was planned to determine the effects of free-radical-induced damage on the Na+,K+-ATPase activity of erythrocytes during hyperthyroidism and 4 wk after propylthiouracil ( PTU) therapy (400 mg/d). The levels of plasma thiobarbituric acid-reactive substances (TBARS) as a marker of lipid peroxidation, erythrocyte glutathione ( GSH) concentration as an antioxidant, blood ATP concentration, and erythrocyte membrane Na+,K+-ATPase activity were determined in female hyperthyroid patients ( n = 22, mean age 40.5 +/-6.5 yr). Before the PTU therapy, plasma TBARS concentration was significantly higher and the levels of blood ATP and erythrocyte GSH and the activity of membrane Na+,K-(+)-ATPase were significantly lower in the hyperthyroid patients ( n = 15 women, mean age 40.8 +/-7.3 yr). Four weeks after PTU therapy, plasma TBARS concentration was decreased, and levels of erythrocyte GSH and blood ATP and of Na+,K+-ATPase activity of erythrocytes were elevated in the treated patients. There was a significant positive correlation between blood ATP concentration and Na+,K+-ATPase activity, and a negative correlation between plasma TBARS concentration and Na+,K+-ATPase activity before PTU. Our results might help to clarify the effects of the oxidative mechanisms on the erythrocyte membrane Na+,K+-ATPase activity in hyperthyroid patients

THE RELATIONSHIP BETWEEN PREPTIN, FORKHEAD BOX PROTEIN O1 AND MECHANISTIC TARGET OF RAPAMYCIN LEVELS IN PREDIABETIC PATIENTS

Prediabetes is a state of high risk for developing some metabolic disorders. Previous studies have shown that components of some mediators involved in glucose metabolism regulation may have a profound effect during developing prediabetes state. This study investigates the effect of some novel prediabetic-related factors in prediabetes individuals for the first time. Sixty prediabetes (American Diabetes Association criteria) and 25 healthy control subjects were enrolled in the study. Systemic and chronic inflammatory diseases, coronary heart disease, and malignant disease patients were excluded. Anthropometric measurements and fasting glucose, insulin, homeostasis model assessment of insulin resistance (HOMA-IR), lipid profile, preptin, and serum and leuckocyte levels of FOXO-1 and mTOR were determined. The findings showed an elevated level of leukocyte mTOR in the Impaired Glucose Tolerance (IGT) group and leukocyte FOXO-1 in the Impaired Fasting Glucose (IFG) and IGT groups compared to the control group. Moreover, higher levels of serum, and leukocyte FOXO-1 in the control group, and leukocyte mTOR level in the IFG group were detected in females compared to males. There was a positive correlation between all of the studied serum parameters, and a positive correlation between basal glucose concentration and leukocyte mTOR and FOXO-1. According to our results, elevated serum and cellular levels of mTOR in the IGT group and FOXO-1 in IFG and IGT groups may be triggered by increased glucose concentration. Indeed, mTOR-mediated variations in cellular level from female patients and FOXO-1-mediated variations of male patients indicated that these factors might play a critical role in glucose intolerance

Role of plasma viscosity and plasma homocysteine level on hyperinsulinemic obese female subjects

Obesity is associated with atherosclerotic risk factors, including reduced blood flow, endothelial dysfunction, lipid disorders and hyperinsulinemia. In recent years, several studies have demonstrated that elevated homocysteine is a risk factor for atherosclerosis. This study was aimed at determining whether any relationship between plasma viscosity and homocysteine levels in patients with normo and hyperinsulinemic obese patients. Obese women (n = 75) and healthy, age-matched non-obese women (n = 70) was included in our study. Plasma viscosity, tHcy, insulin level, total-C, LDL-C, HDL-C, triglyceride and glucose level were significantly higher in obese subjects than in non-obese subjects. Obese subjects were also divided into two groups, according to the basal insulin levels as normo and hyper insulinemic. Hyperinsulinemic obese subjects had significantly higher PV level compared with normoinsulinemic subjects. When correlation analyses were performed normoinsulinemic obese subjects, significant correlations were found between PV and total-C (r: 0.776) and insulin level (r: 0.752), BMI (r: 0.580), HOMA-IR (r: 0.510). PV was positively correlated with total-C (r: 0.485), insulin level (r: 0.624), BMI (r: 0.624) and HOMA-IR ratio (r: 0.707), in hyperinsulinemic obese subjects. Hcy was positively correlated BMI in both groups. In conclusion that, it is point out that elevated homocysteine and increased PV are two factors that may act separately and probably do not affect each other

Susceptibility of erythrocyte lipids to oxidation and erythrocyte antioxidant status in myocardial infarction

Objective: We evaluated the erythrocyte lipid susceptibility to oxidation and erythrocyte antioxidant status in patients with myocardial infarction (MI)

Effects of N-acetylcysteine on lung glutathione levels in rats after burn injury

This sturdy ws designed to determine the effect of N-acetylcysteine (NAG, a natural hydroxyl radical scavenger) treatment an levels of pulmonary malondialdehyde (MDA, file end product of lipid peroxidation) and glutathione (GSH, a natural antioxidant) in thermally injured rats. Severe skill scald injury (30 percent TBSA) caused a significant decrease in GSH levels, and a significant increase in MDA levels ill lung tissue both at 1 h and 1 day postburn injury