One of the major risk factors for global death and disability is alcohol, tobacco, and illicit drug use. While there is increasing knowledge with respect to individual factors promoting the initiation and maintenance of substance use disorders (SUDs), disease trajectories involved in losing and regaining control over drug intake (ReCoDe) are still not well described. Our newly formed German Collaborative Research Centre (CRC) on ReCoDe has an interdisciplinary approach funded by the German Research Foundation (DFG) with a 12‐year perspective. The main goals of our research consortium are (i) to identify triggers and modifying factors that longitudinally modulate the trajectories of losing and regaining control over drug consumption in real life, (ii) to study underlying behavioral, cognitive, and neurobiological mechanisms, and (iii) to implicate mechanism‐based interventions. These goals will be achieved by: (i) using mobile health (m‐health) tools to longitudinally monitor the effects of triggers (drug cues, stressors, and priming doses) and modify factors (eg, age, gender, physical activity, and cognitive control) on drug consumption patterns in real‐life conditions and in animal models of addiction; (ii) the identification and computational modeling of key mechanisms mediating the effects of such triggers and modifying factors on goal‐directed, habitual, and compulsive aspects of behavior from human studies and animal models; and (iii) developing and testing interventions that specifically target the underlying mechanisms for regaining control over drug intake.

New therapies, such as cell implants, will in future require teleoperators capable of repeatable positioning accuracy of 10µm and better. This paper describes the design of a Stewart platform (hexapod robot system) which can be used for precision microsurgery in a number of different medical disciplines. The system design is discussed in detail and an overview of potential applications is given. Also, results are reported on the application in neuroendoscopy

Surgical planning and navigation systems are vital for minimally invasive endoscopic surgeries but it is challenging to track the position and orientation of intrabody surgical instruments in these procedures. In order to address this problem, we propose a tracking system including multiple-sensor integration and data fusion. The proposed tracking approach is free of the constraints of line-of-sight, less subject to environmental distortion, and with higher update rate. By incorporating electromagnetic and inertial sensors, the system yields continuous 6-DOF information. Based on a system dynamic model and estimation theories, a new multisensor fusion algorithm, cascade orientation and position-estimation algorithm, is proposed for the integrated tracking device. The experimental results show that the proposed algorithms achieve accurate orientation and position tracking with robustness.

Purpose Three‐dimensional (3D) printing allows for the fabrication of medical devices with complex geometries, such as soft actuators and robots that can be used in image‐guided interventions. This study investigates flexible and rigid 3D‐printing materials in terms of their impact on multimodal medical imaging. Methods The generation of artifacts in clinical computer tomography (CT) and magnetic resonance (MR) imaging was evaluated for six flexible and three rigid materials, each with a cubical and a cylindrical geometry, and for one exemplary flexible fluidic actuator. Additionally, CT Hounsfield units (HU) were quantified for various parameter sets iterating peak voltage, x‐ray tube current, slice thickness, and convolution kernel. Results We found the image artifacts caused by the materials to be negligible in both CT and MR images. The HU values mainly depended on the elemental composition of the materials and applied peak voltage was ranging between 80 and 140 kVp. Flexible, nonsilicone‐based materials were ranged between 51 and 114 HU. The voltage dependency was less than 29 HU. Flexible, silicone‐based materials were ranged between 60 and 365 HU. The voltage‐dependent influence was as large as 172 HU. Rigid materials ranged between −69 and 132 HU. The voltage‐dependent influence was <33 HU. Conclusions All tested materials may be employed for devices placed in the field of view during CT and MR imaging as no significant artifacts were measured. Moreover, the material selection in CT could be based on the desired visibility of the material depending on the application. Given the wide availability of the tested materials, we expect our results to have a positive impact on the development of devices and robots for image‐guided interventions.