Accurate reconstruction of the three-dimensional (3D) geometry of a myocardial infarct from two-dimensional (2D) multi-slice image sequences has important applications in the clinical evaluation and treatment of patients with ischemic cardiomyopathy. However, this reconstruction is challenging because the resolution of common clinical scans used to acquire infarct structure, such as short-axis, late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) images, is low, especially in the out-of-plane direction. In this study, we propose a novel technique to reconstruct the 3D infarct geometry from low resolution clinical images. Our methodology is based on a function called logarithm of odds (LogOdds), which allows the broader class of linear combinations in the LogOdds vector space as opposed to being limited to only a convex combination in the binary label space. To assess the efficacy of the method, we used high-resolution LGE-CMR images of 36 human hearts in vivo, and 3 canine hearts ex vivo. The infarct was manually segmented in each slice of the acquired images, and the manually segmented data were downsampled to clinical resolution. The developed method was then applied to the downsampled image slices, and the resulting reconstructions were compared with the manually segmented data. Several existing reconstruction techniques were also implemented, and compared with the proposed method. The results show that the LogOdds method significantly outperforms all the other tested methods in terms of region overlap.
We present an image-guided intervention system based on tracked 3D elasticity imaging (EI) to provide a novel
interventional modality for registration with pre-operative CT. The system can be integrated in both laparoscopic and
robotic partial nephrectomies scenarios, where this new use of EI makes exact intra-operative execution of pre-operative
planning possible. Quick acquisition and registration of 3D-B-Mode and 3D-EI volume data allows intra-operative
registration with CT and thus with pre-defined target and critical regions (e.g. tumors and vasculature). Their real-time
location information is then overlaid onto a tracked endoscopic video stream to help the surgeon avoid vessel damage
and still completely resect tumors including safety boundaries.
The presented system promises to increase the success rate for partial nephrectomies and potentially for a wide range of
other laparoscopic and robotic soft tissue interventions. This is enabled by the three components of robust real-time
elastography, fast 3D-EI/CT registration, and intra-operative tracking. With high quality, robust strain imaging (through
a combination of parallelized 2D-EI, optimal frame pair selection, and optimized palpation motions), kidney tumors that
were previously unregistrable or sometimes even considered isoechoic with conventional B-mode ultrasound can now be
imaged reliably in interventional settings. Furthermore, this allows the transformation of planning CT data of kidney
ROIs to the intra-operative setting with a markerless mutual-information-based registration, using EM sensors for intraoperative
motion tracking.
Overall, we present a complete procedure and its development, including new phantom models - both ex vivo and
synthetic - to validate image-guided technology and training, tracked elasticity imaging, real-time EI frame selection,
registration of CT with EI, and finally a real-time, distributed software architecture. Together, the system allows the
surgeon to concentrate on intervention completion with less time pressure.
Non-invasive estimation of regional cardiac function is important for assessment of myocardial contractility.
The use of MR tagging technique enables acquisition of intra-myocardial tissue motion by placing a spatially
modulated pattern of magnetization whose deformation with the myocardium over the cardiac cycle can be
imaged. Quantitative computation of parameters such as wall thickening, shearing, rotation, torsion and strain
within the myocardium is traditionally achieved by processing the tag-marked MR image frames to 1) segment
the tag lines and 2) detect the correspondence between points across the time-indexed frames. In this paper,
we describe our approach to solving this problem using the Large Deformation Diffeomorphic Metric Mapping
(LDDMM) algorithm in which tag-line segmentation and motion reconstruction occur simultaneously. Our
method differs from earlier proposed non rigid registration based cardiac motion estimation methods in that
our matching cost incorporates image intensity overlap via the L2 norm and the estimated tranformations are
diffeomorphic. We also present a novel method of generating synthetic tag line images with known ground truth
and motion characteristics that closely follow those in the original data; these can be used for validation of
motion estimation algorithms. Initial validation shows that our method is able to accurately segment tag-lines
and estimate a dense 3D motion field describing the motion of the myocardium in both the left and the right
ventricle.
Interventional cardiac MRI has been undergoing rapid development because of the availability of MRI compatible
interventional catheters, and the increased performance of the MRI systems. Intravascular techniques do not require an
open access scanner, and hence higher imaging performance during procedures can be achieved. Now, with the
availability of a short, relatively open cylindrical bore scanner high imaging performance is also available to guide
direct surgical procedures.
KEYWORDS: Magnetic resonance imaging, Heart, Image segmentation, Image registration, Image fusion, 3D image processing, X-rays, Tissues, In vivo imaging, 3D acquisition
The utility of X-ray fused with MRI (XFM) using external fiducial markers to perform targeted endomyocardial injections in infarcted hearts of swine was tested. Endomyocardial injections of feridex-labeled mesenchymal stromal cells (Fe-MSC) were performed in the previously infarcted hearts of 12 Yucatan miniswine (33-67 kg). Animals had pre-injection cardiac MRI, XFM-guided endomyocardial injection of Fe-MSC suspension spiked with tissue dye, and post-injection MRI. 24 hours later, after euthanasia, the hearts were excised, sliced and stained with TTC. During the injection procedure, operators were provided with 3D surfaces of endocardium, epicardium, myocardial wall thickness and infarct registered with live XF images to facilitate device navigation and choice of injection location. 130 injections were performed in hearts where diastolic wall thickness ranged from 2.6 to 17.7 mm. Visual inspection of the pattern of dye staining on TTC stained heart slices correlated (r=0.98) with XFM-derived injection locations mapped onto delayed hyperenhancement MRI and the susceptibility artifacts seen on the post-injection T2*-weighted gradient echo MRI. The in vivo target registration error was 3.17±2.61 mm (n=64) and 75% of injections were within 4 mm of the predicted location. 3D to 2D registration of XF and MR images using external fiducial markers enables accurate targeted endomyocardial injection in a swine model of myocardial infarction. The present data suggest that the safety and efficacy of this approach for performing targeted endomyocardial delivery should be evaluated further clinically.
We present our co-registration results of two complementary imaging modalities, MRI and X-ray angiography (XA), using dual modality fiducial markers. Validation experiments were conducted using a vascular phantom with eight fiducial markers around its periphery. Gradient-distortion-corrected 3D MRI was used to image the phantom and determine the 3D locations of the markers. XA imaging was performed at various C-arm orientations. These images were corrected for geometric distortion, and projection parameters were optimized using a calibration phantom. Closed-form 3D-to-3D rigid-body registration was performed between the MR markers and a 3D reconstruction of the markers from multiple XA images. 3D-to-2D registration was performed using a single XA image by projecting the MR markers onto the XA image and iteratively minimizing the 2D errors between the projected markers and their observed locations in the image. The RMS registration error was 0.77 mm for the 3D-to-3D registration, and 1.53 pixels for the 3D-to-2D registration. We also showed that registration can be performed at a large IS where many markers are visible, then the image can be zoomed in maintaining the registration. This requires calibration of imperfections in the zoom operation of the image intensifier. When we applied the registration used for an IS of 330 mm to an image acquired with an IS of 130 mm, the error was 42.16 pixels before zoom correction and 3.37 pixels after. This method offers the possibility of new therapies where the soft-tissue contrast of MRI and the high-resolution imaging of XA are both needed.
KEYWORDS: Heart, 3D modeling, Motion models, Angiography, Motion measurement, Arteries, Magnetic resonance imaging, 3D image processing, Solids, 3D acquisition
Respiratory motion compensation for cardiac imaging requires knowledge of the heart's motion and deformation during breathing. We propose a method for measuring the natural tidal respiratory motion of the heart using free breathing coronary angiograms. A 3D deformation field describing the cardiac and respiratory motion of the coronary arteries is recovered from a biplane acquisition. Cardiac and respiratory phase are assigned to the images from an ECG signal synchronized to the image acquisition, and from the diaphragmatic displacement as observed in the images. The resulting motion field is decomposed into cardiac and respiratory components by fitting the field with periodic 2D parametric functions, where one dimension spans one cardiac cycle, and the second dimension spans one respiratory cycle. The method is applied to patient datasets, and an analysis of respiratory motion of the heart is presented.
A method for 3D temporal tracking of a 3D coronary tree model through a sequence of biplane cineangiography images has been developed. A registration framework is formulated in which the coronary tree centerline model deforms in an external potential field defined by a multiscale analysis response map computed from the angiogram images. To constrain the procedure and to improve convergence, a set of three motion models is hierarchically used: a 3D rigid-body transformation, a 3D affine transformation, and a 3D B-spline deformation field. This 3D motion tracking approach has significant advantages over 2D methods: (1) coherent deformation of a single 3D coronary reconstruction preserves the topology of the arterial tree; (2) constraints on arterial length and regularity, which lack meaning in 2D projection space, are directly applicable in 3D; and (3) tracking arterial segments through occlusions and crossings in the projection images is simplified with knowledge of the 3D relationship of the arteries. The method has been applied to patient data and results are presented.
KEYWORDS: Real time imaging, 3D image processing, Magnetic resonance imaging, Volume rendering, Stereoscopy, Visualization, Medium wave, Laser scanners, 3D scanning, Data acquisition
A system has been developed to produce live 3D volume renderings from an MR scanner. Whereas real-time 2D MR imaging has been demonstrated by several groups, 3D volumes are currently rendered off-line to gain greater understanding of anatomical structures. For example, surgical planning is sometimes performed by viewing 2D images or 3D renderings from previously acquired image data. A disadvantage of this approach is misregistration which could occur if the anatomy changes due to normal muscle contractions or surgical manipulation. The ability to produce volume renderings in real-time and present them in the magnet room could eliminate this problem, and enable or benefit other types of interventional procedures. The system uses the data stream generated by a fast 2D multi- slice pulse sequence to update a volume rendering immediately after a new slice is available. We demonstrate some basic types of user interaction with the rendering during imaging at a rate of up to 20 frames per second.
Although several methods exist for the analysis of tagged MRI images of the left ventricle (LV), analysis of the right ventricle (RV) remains challenging due to its complex anatomy and significant through plane motion. We present here preliminary results of our new motion analysis method, both for RV and LV, in healthy human volunteers. In this method, following standard myocardial and tag segmentation of cardiac gated cine tagged MR images; a 4D B-spline based parametric motion field was computed for a volume of interest encompassing both ventricles. Using this motion field, 3D displacements and strains were calculated on the RV and LV. We observed that for both chambers the circumferential strain (Ecc) decreased with a constant rate throughout systole. The systolic strain rate displayed spatial similarity not only for the LV but also for the RV. For RV free wall, mean systolic Ecc was -0.19 +/- 0.05 with an average coefficient of variability of 20%. The 4D B-spline based motion analysis technique for tagged MRI yields compatible results for the LV and gives consistent circumferential strain measures for the RV free wall. Tagged MRI based RV mechanical analysis can be used along with LV results for a more complete cardiac evaluation.
In this study the effects of different pacing protocols on left ventricular (LV) torsion was evaluated over the full cardiac cycle. A systolic and diastolic series of Magnetic Resonance Imaging scans were combined and used to calculate the torsion of the LV. The asynchronous contraction resulting from ventricular pacing interferes with the temporal evolution of LV torsion. From these experiments we have shown that measuring torsion is an extremely sensitive indicator of the existence of ectopic excitation. The torsion of the left ventricle was investigated under three different protocols: (1) Right atrial pacing, (2) Right ventricular pacing and (3) Simultaneous pacing from the right ventricular apex and left ventricular base. The temporal evolution of torsion was determined from tagged magnetic resonance images and was evaluated over the full cardiac cycle. The peak twist Tmax for the RA paced heart was 11.09 (+/- 3.54) degrees compared to 6.06 (+/- 1.65) degrees and 6.09 (+/- 0.68) degrees for the RV and Bi-V paced hearts respectively. While biventricular pacing has been shown to increase the synchrony of contraction, it does not preserve the normal physiological twist patterns of the heart.
We have developed a software tool for interactive visualization and 4D segmentation of multiple sets of images. The segmentation process uses a predefined anatomical template of the structure of interest represented as a polygonal mesh in 3D. This can be obtained from a library of normal or diseased anatomies, or if available, a surface generated from the patient's previous studies can be used. The user then deforms the template so that it correctly delineates the region of interest in the underlying images. These deformations can be constrained to maintain spatial and temporal smoothness as is expected in the underlying anatomy. A unique feature of this analysis package is that multiple non-coplanar image sets can be used concurrently to generate accurate contours. This feature is particularly useful in contouring long axis and short axis images of the heart simultaneously. By generating a reliable segmentation from a substrate of images in space and time, we can automatically contour the structure in the remaining images through appropriate interpolation, and thereby significantly reduce the total segmentation time.
A major issue in cardiac imaging is the assessment of cardiac function and particularly the identification of ischemic or infarcted tissues. We present in this article a method to reconstruct the motion of the left ventricle (LV) using 4D planispheric transformations of time and space combined in a first step with B-spline tensor products. Because of the 4D modeling, (1) the use of planispheric coordinates makes the numerical evaluation more stable as compared to prolate spheroidal coordinates, the equivalent focal point being much further from the apical area of the heart. (2) In the temporal modeling, a simple adaptation is possible to changing temporal dynamics such as introduced by ectopic pacing or rapid filling after systole. (3) Finally, the strain analysis and displacement parameters that are used for the spatial modeling are computed at any point of the LV volume. Experiments are conducted on a normal and a pathological LV (posterior infarct) in order to assess the tuning of the parameters of the method. The mean RMS-distance error is less than 0.5 mm for both LVs. Finally, the motion is analyzed as smooth zeroth (displacement) and first order parameters (strain).
In recent years, with development of new MRI techniques, noninvasive evaluation of global and regional cardiac function is becoming a reality. One of the methods used for this purpose is MRI tagging. In tagging, spatially encoded magnetic saturation planes, tags, are created within tissues. These act as temporary markers and move with the tissue. In cardiac tagging, tag deformation pattern provides useful qualitative and quantitative information about the functional properties of underlying myocardium. The measured deformation of a single tag plane contains only unidirectional information of the past motion. In order to track the motion of a cardiac material point, this sparse, single dimensional data has to be combined with similar information gathered from other tag sets and all time frames. Previously, several methods have been developed which rely on the specific geometry of the chambers. Here, we employ an image plane based, simple cartesian coordinate system and provide a stepwise method to describe the heart motion using a four-dimensional tensor product of B-splines. The proposed displacement and forward motion fields exhibited sub-pixel accuracy. Since our motion fields are parametric and based on an image plane based coordinate system, trajectories or other derived values (velocity, acceleration, strains...) can be calculated for any desired point on the MRI images. This method is sufficiently general so that the motion of any tagged structure can be tracked.
Rapid analysis of large multi-dimensional data sets is critical for the successful implementation of a comprehensive MR cardiac exam. We have developed a software package for the analysis and visualization of cardiac MR data. The program allows interactive visualization of time and space stacks of MRI data, automatic segmentation of myocardial borders and myocardial tagging patterns, and visualization of functional parameters such a motion, strain, and blood flow, mapped as colors in an interactive dynamic 3D volume rendering of the beating heart.
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