Development and in-vitro characterization of an implantable flow sensing transducer for hydrocephalus

An implantable transducer for monitoring the flow of Cerebrospinal fluid (CSF) for the treatment of hydrocephalus has been developed which is based on measuring the heat dissipation of a local thermal source. The transducer uses passive telemetry at 13.56MHz for power supply and read out of the measured flow rate. The in vitro performance of the transducer has been characterized using artificial Cerebrospinal Fluid (CSF) with increased protein concentration and artificial CSF with 10% fresh blood. After fresh blood was added to the artificial CSF a reduction of flow rate has been observed in case that the sensitive surface of the flow sensor is close to the sedimented erythrocytes. An increase of flow rate has been observed in case that the sensitive surface is in contact with the remaining plasma/artificial CSF mix above the sediment which can be explained by an asymmetric flow profile caused by the sedimentation of erythrocythes having increased viscosity compared to artificial CSF. After removal of blood from artificial CSF, no drift could be observed in the transducer measurement which could be associated to a deposition of proteins at the sensitive surface walls of the packaged flow transducer. The flow sensor specification requirement of +−10% for a flow range between 2ml/h and 40ml/h. could be confirmed at test conditions of 37°

Prediction of dental implant torque with a fast and automatic finite element analysis: a pilot study

Despite its importance, implant removal torque can be assessed at present only after implantation. This paper presents a new technique to help clinicians preoperatively evaluate implant stability

Biomechanical model of tumor growth: application to the European ContraCancrum project

This abstract presents the biomechanical model that is used in the European ContraCancrum project, aiming at simulating tumor evolution in the brain and lung. The construction of the finite element model as well as a simulation of tumor growth are shown. The construction of the mesh is fully automatic and is therefore compatible with a clinical application. This biomechanical model will be later combined to a cellular level simulator also developed in the project

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