Data-tailored shape compression for interventional device tracking

Accurate localization and fast tracking of interventional tools is an area of paramount importance in procedures with real-time MR guidance. Optically detunable radiofrequency (RF) coils are a robust method for the identification of individual MR markers for MR-compatible robotics system. In this study, we describe a technique for localizing and tracking four RF coils. Each coil consists of a 3 mm diameter inductively coupled solenoid coil with a photoresistor that is optically tuned and detuned. In particular, by selecting only one marker to be MR visible per data collection repetition, this particular marker point of the manipulator is unambiguously distinguished. This technique allows simplification of both the data acquisition and the post processing algorithms. A user-programmable microcontroller times the ON/OFF state of light sources and triggers the MR scanner so that a particular image collection depicts a specific RF coil or combination. Phantom studies at 1.5T demonstrated the technique illustrating the selective observation of one or multiple markers. The described technique can use imaging to track multiple points on an interventional device, such as the shaft of steerable catheters and the end-effectors of MR-compatible manipulators.

To develop an accurate technique for simultaneously measuring the position and orientation of interventional devices using a projection-based spectrally selective refocusing pulse sequence. Projections along physical axes using spectrally selective excitation were acquired to track a catheter. A 9F passive tracking device capable of generating controllable susceptibility artifacts using susceptibility materials (titanium and graphite) was attached to the catheter. A library of projections for different orientations of the device with respect to the main magnetic field were simulated offline. Cross-correlations with these templates were computed to determine the orientation and position of the device. A phantom study was performed to evaluate the accuracy of the tracking technique. The tracking technique was also evaluated in vivo in the carotid artery of a pig. Simultaneous and accurate measurement of position and orientation of the tracking device was obtained in the phantom and in vivo studies with reasonable temporal resolution. For the phantom study, the average of absolute errors in the Z-, Y-, and X-axes are 0.37, 0.76, and 0.85 mm, respectively. The mean absolute error and standard deviation of orientation measurement are 1.5 and 1.1 degrees, respectively. This positioning technique, in conjunction with a controllable tracking device, can provide accurate tracking of interventional devices in MR-guided interventions. Magn Reson Med 76:1563-1573, 2016. © 2015 International Society for Magnetic Resonance in Medicine.

The continuous integration of innovative imaging modalities into conventional vascular surgery rooms has led to an urgent need for computer assistance solutions that support the smooth integration of imaging within the surgical workflow. In particular, endovascular interventions performed under 2D fluoroscopic or angiographic imaging only, require reliable and fast navigation support for complex treatment procedures such as endovascular aortic repair. Despite the vast variety of image-based guide wire and catheter tracking methods, an adoption of these for detecting and tracking the stent graft delivery device is not possible due to its special geometry and intensity appearance. In this paper, we present, for the first time, the automatic detection and tracking of the stent graft delivery device in 2D fluoroscopic sequences on the fly. The proposed approach is based on the robust principal component analysis and extends the conventional batch processing towards an online tracking system that is able to detect and track medical devices on the fly. The proposed method has been tested on interventional sequences of four different clinical cases. In the lack of publicly available ground truth data, we have further initiated a crowd sourcing strategy that has resulted in 200 annotations by unexperienced users, 120 of which were used to establish a ground truth dataset for quantitatively evaluating our algorithm. In addition, we have performed a user study amongst our clinical partners for qualitative evaluation of the results. Although we calculated an average error in the range of nine pixels, the fact that our tracking method functions on the fly and is able to detect stent grafts in all unfolding stages without fine-tuning of parameters has convinced our clinical partners and they all agreed on the very high clinical relevance of our method.

Motion compensation-based compression of data streams recorded from interventional device tracking