Robotic manipulators have emerged and are continuously evolving as a valuable tool in medical applications. This work introduces a new biomedical application for robotics: multimodality imaging by facilitating scanning of spatially localized bio-sensing and co-registration. Established or currently emerging molecular and near cellular modalities, such as optical and magnetic resonance spectroscopy, offer new opportunities for assessing tissue pathophysiology in situ. The limited tissue penetration of those modalities can be addressed by locally placing the sensor, i.e. with a minimally invasive trans-needle or trans-catheter approach. Herein, we describe the use of a robotic manipulator to scan the area of interest by carrying such a sensor for generating 1-D scans while registering them to a guiding modality. The approach is demonstrated by using a miniature RF coil for collecting proton MR spectra (MRS) and scanning an area of interest on phantoms with the manipulator. MRI is used to guide this procedure as well as co-register MR imaging and spectroscopy. LineScans on two compartment phantoms demonstrated a clear spatial distribution of the resonances originating from those compartments in agreement with the scout guiding MR images. The system described herein, is a generalized platform for performing MR-guided multimodality and multilevel sensing.

A new, sample independent optimization criterion for minimizing the effect of the imaging gradients, including the directional awareness they create, is defined for diffusion tensor imaging (DTI) experiments. The DTI linear algebraic framework is expanded to a normed space to design optimal diffusion gradient schemes (DGS) in an integral fashion without separating the magnitude and direction of the DGS vectors. The feasible space of DGS vectors, for which the estimation equations are determinate, thus a hard constraint for the optimization, is parametrized. Newly generated optimal DGSs demonstrate on an isotropic sample and an ex-vivo baboon brain that the optimization goals are reached as well as a significant increase in estimation performance.

The aim of this work is to develop a seven degree of freedom (DOF) remotely controlled manipulator to perform minimally invasive interventions with real-time magnetic resonance imaging (MRI) guidance inside clinical cylindrical scanners. Control of the device is based on MR images collected pre-operatively and in real-time during the procedure. A user interface fuses all sensor information for man-in-the-loop control. Stereotactic guidance uses multislice and/or three-dimensional MR images to set a trajectory of insertion. Free-handed (or manual) guidance uses a master/slave control device, which replicates the kinematics structure of the arm, to control its movement. The control software checks any motion of the manipulator whether it is within an allowable volume extracted from MR images. The device control is performed with a host/target computer configuration. The system is connected to the MR scanner to receive the MR images and send the coordinates of the end-effector for dynamic control of the imaged plane. The manipulator compatibility with the MR environment and image-guided maneuvering was tested on a 1.5 Tesla MR scanner