Lhermitte-Duclos disease presenting with positron emission tomography-magnetic resonance fusion imaging: a case report

<p>Abstract</p> <p>Introduction</p> <p>Lhermitte-Duclos disease or dysplastic gangliocytoma of the cerebellum is an extremely rare tumor. It is a slowly enlarging mass within the cerebellar cortex. The majority of cases are diagnosed in the third or fourth decade of life.</p> <p>Case presentation</p> <p>We report the case of a 37-year-old Caucasian woman who underwent positron emission tomography-computed tomography with fluorine-18-fluorodeoxyglucose for evaluation of a solitary lung node. No pathological uptake was detected in the solitary lung node but the positron emission tomography-computed tomography of her brain showed intense tracer uptake, suggestive of a malignant neoplasm, in a mass in her left cerebellar lobe. Our patient had experienced two years of occipital headache and movement disorder. Subsequently, magnetic resonance imaging was performed with contrast agent administration, showing a large subtentorial mass in her left cerebellar hemisphere, with compression and dislocation of the fourth ventricle. Metabolic data provided by positron emission tomography and morphological magnetic resonance imaging views were fused in post-processing, allowing a diagnosis of dysplastic gangliocytoma with increased glucose metabolism. Total resection of the tumor was performed and histological examination confirmed the diagnosis of Lhermitte-Duclos disease.</p> <p>Conclusions</p> <p>Our case indicates that increased uptake of fluorine-18-fluorodeoxyglucose may be misinterpreted as a neoplastic process in the evaluation of patients with Lhermitte-Duclos disease, but supports the usefulness of integrated positron emission tomography-magnetic resonance imaging in the exact pathophysiologic explanation of this disease and in making the correct diagnosis. However, an accurate physical examination and exact knowledge of clinical data is of the utmost importance.</p

State of charge Kalman filter estimator for automotive batteries

A state of charge estimator for rechargeable batteries that operate under variable and repetitive charging and discharging conditions is proposed. The estimator is based on a state-space dynamic model of the battery which is obtained by modelling the kinetic of reactions and the diffusion phenomena. By using the terminal current and voltage measurements, an extended Kalman filter estimates the concentrations of the main chemical species which are averaged on the thickness of the active material in order to obtain the state of charge of the battery. The estimator is tested on experimental data derived from typical operating conditions of Nickel–Metal Hydride batteries used in automotive hybrid vehicles

An Integrated LTV-MPC Lateral Vehicle Dynamics Control: Simulation results

In this work we present the integration of a Linear-time-varying Model-predictive-control (LTV-MPC), designed to stabilize a vehicle during sudden lane change or excessive entry-speed in curve, with a slip controller that converts the desired longitudinal tire force variation to pressure variation in the brake system. The lateral controller is designed using a 3DOF vehicle model taking into account both yaw rate and side slip angle of vehicle while the slip controller is a gain scheduled proportional controller with feedforward action. The performances are validated through simulation: in particular, the authors use a proprietary simulator calibrated on an oversteering sport commercial car and commercial simulator calibrated on a standard light car. Simulation results show the benefits of the control methodology in that very effective steering manoeuvres can be obtained as a result of this feedback policy while satisfying input constraints and show the importance of the introduction of inputs constraints in the control strategy design

A preliminary study to integrate LTV-MPC lateral vehicle dynamics control with a slip control

In this paper we present the integration of a Linear-Time-Varying Model-Predictive-Control (LTV-MPC), designed to stabilize a vehicle during sudden lane change or excessive speed-entry in curve, with a slip controller that converts the desired longitudinal tire force variation in pressure variation in the brake system. The lateral controller is designed using a three-degrees-of-freedom vehicle model taking into account both yaw rate and side slip angle of vehicle while the slip controller is a nonlinear gain scheduling P with feedforward action. The performances are validated with SIL technique, in particular, the authors use a proprietary simulator calibrated on an oversteering sport commercial car. Simulation results show the benefits of the control methodology used

LTV-MPC for Yaw Rate Control and Side Slip Control with Dynamically Constrained Differential Braking

In this paper a novel vehicle lateral dynamic control approach is presented. A differential braking control law based on vehicle planar motion has been designed using a two-degrees-of-freedom vehicle model. On the basis of the estimate of tire longitudinal forces we estimate the range of lateral forces which the tire can exert. Using this constraints a model predictive control (MPC) based on a two-track model is designed in order to stabilize the vehicle. The performances are estimated comparing the results with standard manoeuvers. Simulation results show the benefits of the control methodology used: in particular we show how very effective distribution of braking torque are obtained as a result of this feedback policy