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Spatial and soft tissue information provided by magnetic resonance imaging can be very valuable during image-guided procedures, where usually only real-time two-dimensional (2D) x-ray images are available. Registration of 2D x-ray images to three-dimensional (3D) magnetic resonance imaging (MRI) data, acquired prior to the procedure, can provide optimal information to guide the procedure. However, registering x-ray images to MRI data is not a trivial task because of their fundamental difference in tissue contrast. This paper presents a technique that generates pseudo-computed tomography (CT) data from multi-spectral MRI acquisitions which is sufficiently similar to real CT data to enable registration of x-ray to MRI with comparable accuracy as registration of x-ray to CT. The method is based on a k-nearest-neighbors (kNN)-regression strategy which labels voxels of MRI data with CT Hounsfield Units. The regression method uses multi-spectral MRI intensities and intensity gradients as features to discriminate between various tissue types. The efficacy of using pseudo-CT data for registration of x-ray to MRI was tested on ex vivo animal data. 2D-3D registration experiments using CT and pseudo-CT data of multiple subjects were performed with a commonly used 2D-3D registration algorithm. On average, the median target registration error for registration of two x-ray images to MRI data was approximately 1 mm larger than for x-ray to CT registration. The authors have shown that pseudo-CT data generated from multi-spectral MRI facilitate registration of MRI to x-ray images. From the experiments it could be concluded that the accuracy achieved was comparable to that of registering x-ray images to CT data.

There is a growing interest in performing intravascular interventions guided by MR imaging--a technique which offers the possibility of flow measurements during the intervention. For a reliable assessment of the haemodynamic significance of a stenosis, the flow and the pressure decay within the stenosis should both be measured. We have developed an optical, MR-compatible, pressure sensor (Annupres) that uses a novel annular element. Existing optical pressure sensors measure pressures unilaterally, thus giving rise to artefacts because of the dependence of the measurement on the angular orientation of the aperture. The annular element, however, measures blood pressure on all sides, and we show that by using circularly polarized light this pressure measurement is intrinsically insensitive to rotation of the sensor around its long axis. The Annupres sensor has been tested in an experimental set-up, and was able to measure pressures from 50 mmHg to 180 mmHg reliably with an accuracy of 1.5%.