Pacemakers and magnetic resonance imaging: Current status and survey in Switzerland.

Electromagnetic fields arising from magnetic resonance imaging (MRI) can cause various clinically relevant functional disturbances in patients with cardiac pacemakers. Consequently, an implanted pacemaker is generally considered a contraindication for an MRI scan. With approximately 60 million MRI scans performed worldwide per year, MRI may be indicated for an estimated majority of pacemaker patients during the lifetime of their pacemakers. The availability of MR conditional pacemakers with CE labelling is of particular advantage since they allow the safe use of pacemakers in MRI. In this article the current state of knowledge on pacemakers and MR imaging is discussed. We present the results of a survey conducted among Swiss radiologists to assess current practice in patients with pacemakers.

Is spinal stenosis assessment dependent on slice orientation? A magnetic resonance imaging study.

INTRODUCTION: Lumbar spinal stenosis (LSS) treatment is based primarily on the clinical criteria providing that imaging confirms radiological stenosis. The radiological measurement more commonly used is the dural sac cross-sectional area (DSCA). It has been recently shown that grading stenosis based on the morphology of the dural sac as seen on axial T2 MRI images, better reflects severity of stenosis than DSCA and is of prognostic value. This radiological prospective study investigates the variability of surface measurements and morphological grading of stenosis for varying degrees of angulation of the T2 axial images relative to the disc space as observed in clinical practice. MATERIALS AND METHODS: Lumbar spine TSE T2 three-dimensional (3D) MRI sequences were obtained from 32 consecutive patients presenting with either suspected spinal stenosis or low back pain. Axial reconstructions using the OsiriX software at 0°, 10°, 20° and 30° relative to the disc space orientation were obtained for a total of 97 levels. For each level, DSCA was digitally measured and stenosis was graded according to the 4-point (A-D) morphological grading by two observers. RESULTS: A good interobserver agreement was found in grade evaluation of stenosis (k = 0.71). DSCA varied significantly as the slice orientation increased from 0° to +10°, +20° and +30° at each level examined (P < 0.0001) (-15 to +32% at 10°, -24 to +143% at 20° and -29 to +231% at 30° of slice orientation). Stenosis definition based on the surface measurements changed in 39 out of the 97 levels studied, whereas the morphology grade was modified only in two levels (P < 0.01). DISCUSSION: The need to obtain continuous slices using the classical 2D MRI acquisition technique entails often at least a 10° slice inclination relative to one of the studied discs. Even at this low angulation, we found a significantly statistical difference between surface changes and morphological grading change. In clinical practice, given the above findings, it might therefore not be necessary to align the axial cuts to each individual disc level which could be more time-consuming than obtaining a single series of axial cuts perpendicular to the middle of the lumbar spine or to the most stenotic level. In conclusion, morphological grading seems to offer an alternative means of assessing severity of spinal stenosis that is little affected by image acquisition technique.

Impact of navigator timing on free-breathing submillimeter 3D coronary magnetic resonance angiography.

The purpose of this study was to investigate the impact of navigator timing on image quality in navigator-gated and real-time motion-corrected, free-breathing, three-dimensional (3D) coronary MR angiography (MRA) with submillimeter spatial image resolution. Both phantom and in vivo investigations were performed. 3D coronary MRA with real-time navigator technology was applied using variable navigator time delays (time delay between the navigator and imaging sequences) and varying spatial resolutions. Quantitative objective and subjective image quality parameters were assessed. For high-resolution imaging, reduced image quality was found as a function of increasing navigator time delay. Lower spatial resolution coronary MRA showed only minor sensitivity to navigator timing. These findings were consistent among volunteers and phantom experiments. In conclusion, for submillimeter navigator-gated and real-time motion-corrected 3D coronary MRA, shortening the time delay between the navigator and the imaging portion of the sequence becomes increasingly important for improved spatial resolution.

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Minimization of Nyquist ghosting for echo-planar imaging at ultra-high fields based on a "negative readout gradient" strategy.

PURPOSE: To improve the traditional Nyquist ghost correction approach in echo planar imaging (EPI) at high fields, via schemes based on the reversal of the EPI readout gradient polarity for every other volume throughout a functional magnetic resonance imaging (fMRI) acquisition train. MATERIALS AND METHODS: An EPI sequence in which the readout gradient was inverted every other volume was implemented on two ultrahigh-field systems. Phantom images and fMRI data were acquired to evaluate ghost intensities and the presence of false-positive blood oxygenation level-dependent (BOLD) signal with and without ghost correction. Three different algorithms for ghost correction of alternating readout EPI were compared. RESULTS: Irrespective of the chosen processing approach, ghosting was significantly reduced (up to 70% lower intensity) in both rat brain images acquired on a 9.4T animal scanner and human brain images acquired at 7T, resulting in a reduction of sources of false-positive activation in fMRI data. CONCLUSION: It is concluded that at high B(0) fields, substantial gains in Nyquist ghost correction of echo planar time series are possible by alternating the readout gradient every other volume.

On the convergence of EM-like algorithms for image segmentation using Markov random fields.

Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.