Towards cardiac C-arm computed tomography

Cardiac interventional procedures would benefit tremendously from sophisticated three-dimensional image guidance. Such procedures are typically performed with C-arm angiography systems, and tomographic imaging is currently available only by using preprocedural computed tomography (CT) or magnetic resonance imaging (MRI) scans. Recent developments in C-arm CT (Angiographic CT) allow three-dimensional (3-D) imaging of low contrast details with angiography imaging systems for noncardiac applications. We propose a new approach for cardiac imaging that takes advantage of this improved contrast resolution and is based on intravenous contrast injection. The method is an analogue to multisegment reconstruction in cardiac CT adapted to the much slower rotational speed of C-arm CT. Motion of the heart is considered in the reconstruction process by retrospective electrocardiogram (ECG)-gating, using only projections acquired at a similar heart phase. A series of N almost identical rotational acquisitions is performed at different heart phases to obtain a complete data set at a minimum temporal resolution of 1/N of the heart cycle time. First results in simulation, using an experimental phantom, and in preclinical in vivo studies showed that excellent image quality can be achieved.     

Tomographic reconstruction of dynamic cardiac image sequences.

In this paper, we propose an approach for the reconstruction of dynamic images from a gated cardiac data acquisition. The goal is to obtain an image sequence that can show simultaneously both cardiac motion and time-varying image activities. To account for the cardiac motion, the cardiac cycle is divided into a number of gate intervals, and a time-varying image function is reconstructed for each gate. In addition, to cope with the under-determined nature of the problem, the time evolution at each pixel is modeled by a B-spline function. The dynamic images for the different gates are then jointly determined using maximum a posteriori estimation, in which a motion-compensated smoothing prior is introduced to exploit the similarity among the different gates. The proposed algorithm is evaluated using a dynamic version of the 4-D gated mathematical cardiac torso phantom simulating a gated single photon emission computed tomography perfusion acquisition with Technitium-99m labeled Teboroxime. We thoroughly evaluated the performance of the proposed algorithm using several quantitative measures, including signal-to-noise ratio analysis, bias-variance plot, and time activity curves. Our results demonstrate that the proposed joint reconstruction approach can improve significantly the accuracy of the reconstruction.     

3-D freehand echocardiography for automatic left ventricle reconstruction and analysis based on multiple acoustic windows

A new method is proposed to reconstruct and analyze the left ventricle (LV) from multiple acoustic window three-dimensional (3-D) ultrasound acquired using a transthoracic 3-D rotational probe. Prior research in this area has been based on one acoustic window acquisition. However, the data suffers from several limitations that degrade the reconstruction and reduce the clinical value of interpretation, such as the presence of shadow due to bone (ribs) and air (in the lungs) and motion of the probe during the acquisition. In this paper, we show how to overcome these limitations by automatically fusing information from multiple acoustic window sparse-view acquisitions and using a position sensor to track the probe in real time. Geometric constraints of the object shape, and spatiotemporal information relating to the image acquisition process, are used in new algorithms for 1) grouping endocardial edge cues from an initial image segmentation and 2) defining a novel reconstruction method that utilizes information from multiple acoustic windows. The new method has been validated on a phantom and three real heart data sets. In the phantom study, one finger of a latex glove was scanned from two acoustic windows and reconstructed using the new method. The volume error was measured to be less than 4%. In the clinical case study, 3-D ultrasound and magnetic resonance imaging (MRI) scanning were performed on the same healthy volunteers. Quantitative ejection fractions (EFs) and volume-time curves over a cardiac cycle were estimated using the new method and compared to cardiac MRI measurements. This showed that the new method agrees better with MRI measurements than the previous approach we have developed based on a single acoustic window. The EF errors of the new method with respect to MRI measurements were less than 6%. A more extensive clinical validation is required to establish whether these promising first results translate to a method suitable for routine clinical use.     

ECG-correlated imaging of the heart with subsecond multislice spiral CT

The new spiral multislice computed tomography (CT) scanners and the significant increase in rotation speed offer great potential for cardiac imaging with X-ray CT. We have therefore developed the dedicated cardiac reconstruction algorithms 180 degrees multislice cardio interpolation (MCI) and 180 degrees multislice cardio delta (MCD) and here offer further details and validation. The algorithm 180 degreesMCI is an electrocardiogram (ECG)-correlated filtering (or weighting) algorithm in both the cardiac phase and in the z-position. Effective scan times (absolute temporal resolution) of as low as t(eff) = 56 ms are possible, assuming M 4 simultaneously measured slices at a rotation time of t(rot) = 0.5 s and S < or = d < or = 3S for the table feed d per rotation, where S denotes the collimated slice thickness. The relative temporal resolution w (fraction of the heart cycle depicted in the image), which is the more important parameter in cardiac imaging, will then be as low as w = 12.5% of the heart cycle. The second approach, 180 degreesMCD, is an ECG-correlated partial scan reconstruction of 180 degrees + delta data with delta < phi (fan-angle). Its absolute temporal resolution lies in the order of 250 ms (for the central ray, i.e., for the center of rotation), and the relative temporal resolution w increases with increasing heart rate, e.g., from typically w = 25% at fH = 60 min(-1) to w = 50% at fH = 120 min(-1), assuming again t(rot) = 0.5 s. For validation purposes, we have done simulations of a virtual cardiac motion phantom, measurements of a dedicated cardiac calibration and motion phantom, and we have reconstructed patient data with simultaneously acquired ECG. Both algorithms significantly improve the image quality compared with the standard reconstruction algorithms 180 degrees multislice linear interpolation (MLI) and 180 degrees multislice filtered interpolation (MFI). However, 180 degreesMCI is clearly superior to 180 degreesMCD for all heart rates. This is best illustrated by multiplanar reformations (MPR) or other three-dimensional (3-D) displays of the volume. 180 degreesMCI, due to its higher temporal resolution, is best for spatial and temporal four-dimensional (4-D) tracking of the anatomy. A tunable scanner rotation time to avoid resonance behavior of the heart rate and the scanner's rotation and shorter rotation times would be of further benefit.     

TRIO a technique for reconstruction using intensity order: application to undersampled MRI

Long acquisition times are still a limitation for many applications of magnetic resonance imaging (MRI), specially in 3-D and dynamic imaging. Several undersampling reconstruction techniques have been proposed to overcome this problem. These techniques are based on acquiring less samples than specified by the Nyquist criterion and estimating the nonacquired data by using some sort of prior information. Most of these reconstruction methods use prior information based on estimations of the pixel intensities of the images and therefore they are prone to introduce spatial or temporal blurring. Instead of using the pixel intensities, we propose to use information that allows us to sort the pixels of an image from darkest to brightest. The set of order relations which sort the pixels of an image has been called intensity order. The intensity order of an image can be estimated from low-resolution images, adjacent slices in volumetric acquisitions, temporal correlation in dynamic sequences or from prior reconstructions. Our technique for reconstruction using intensity order (TRIO) consists of looking for an image that satisfies the intensity order and minimizes the discrepancy between the acquired and reconstructed data. Results show that TRIO can effectively reconstruct 2-D-cine cardiac MR images (under-sampling factor of 4), estimating correctly the temporal evolution of the objects. Furthermore, TRIO is used as a second stage reconstruction after reconstructing with other techniques, keyhole, sliding window and k-t BLAST, to estimate the order information. In all cases the images are improved by TRIO.     

Dynamic X-ray computed tomography

Dynamic computed tomography (CT) imaging aims at reconstructing image sequences where the dynamic nature of the living human body is of primary interest. The main applications concerned are image-guided interventional procedures, functional studies and cardiac imaging. The introduction of ultra-fast rotating gantries along with multi-row detectors and in near future area detectors allows huge progress toward the imaging of moving organs with low-contrast resolution. This paper gives an overview of the different concepts used in dynamic CT. A new reconstruction algorithm based on a voxel-specific dynamic evolution compensation is also presented. It provides four-dimensional image sequences with accurate spatio-temporal information, where each frame is reconstructed using a long-scan acquisition mode on several half-turns. In the same time, this technique permits to reduce the dose delivered per rotation while keeping the same signal to noise ratio for every frame using an adaptive motion-compensated temporal averaging. Results are illustrated on simulated data.     

Multislice helical CT: image temporal resolution

A multislice helical computed tomography (CT) halfscan (HS) reconstruction algorithm is proposed for cardiac applications. The imaging performances (in terms of the temporal resolution, z-axis resolution, image noise, and image artifacts) of the HS algorithm are compared to the existing algorithms using theoretical models and clinical data. A theoretical model of the temporal resolution performance (in terms of the temporal sensitivity profile) is established for helical CT, in general, i.e., for any number of detector rows and any reconstruction algorithm used. It is concluded that the HS reconstruction results in improved image temporal resolution than the corresponding 180 degrees LI (linear interpolation) reconstruction and is more immune to the inconsistent data problem induced by cardiac motions. The temporal resolution of multislice helical CT with the HS algorithm is comparable to that of single-slice helical CT with the HS algorithm. In practice, the 180 degrees LI and HS-LI algorithms can be used in parallel to generate two image sets from the same scan acquisition, one (180 degrees LI) for improved z-resolution and noises, and the other (HS-LI) for improved image temporal resolution.     

Registration and tracking to integrate X-ray and MR images in an XMR facility

We describe a registration and tracking technique to integrate cardiac X-ray images and cardiac magnetic resonance (MR) images acquired from a combined X-ray and MR interventional suite (XMR). Optical tracking is used to determine the transformation matrices relating MR image coordinates and X-ray image coordinates. Calibration of X-ray projection geometry and tracking of the X-ray C-arm and table enable three-dimensional (3-D) reconstruction of vessel centerlines and catheters from bi-plane X-ray views. We can, therefore, combine single X-ray projection images with registered projection MR images from a volume acquisition, and we can also display 3-D reconstructions of catheters within a 3-D or multi-slice MR volume. Registration errors were assessed using phantom experiments. Errors in the combined projection images (two-dimensional target registration error--TRE) were found to be 2.4 to 4.2 mm, and the errors in the integrated volume representation (3-D TRE) were found to be 4.6 to 5.1 mm. These errors are clinically acceptable for alignment of images of the great vessels and the chambers of the heart. Results are shown for two patients. The first involves overlay of a catheter used for invasive pressure measurements on an MR volume that provides anatomical context. The second involves overlay of invasive electrode catheters (including a basket catheter) on a tagged MR volume in order to relate electrophysiology to myocardial motion in a patient with an arrhythmia. Visual assessment of these results suggests the errors were of a similar magnitude to those obtained in the phantom measurements.     

Modeling and optimization of rotational C-arm stereoscopic X-rayangiography

Stereoscopy can be an effective method for obtaining three-dimensional (3-D) spatial information from two-dimensional (2-D) projection X-ray images, without the need for tomographic reconstruction. This much-needed information is missed in many X-ray diagnostic and interventional procedures, such as the treatment of vascular aneurysms. Fast C-arm X-ray systems can obtain multiple angle sequences of stereoscopic image pairs from a single contrast injection and a single breath hold. To advance this solution, we developed a model of stereo angiography, performed perception experiments and related results to optimal acquisition. The model described horizontal disparity for the C-arm geometry that agreed very well with measurements from a geometric phantom. The perceptual accommodation-convergence conflict and geometry limited the effective stereoscopic field of view (SFOV). For a typical large image intensifier system, it was 28 cm x 31 cm at the center of rotation (COR). In the model, blurring from finite focal-spot size and C-arm motion reduced depth resolution on the digital display. Near the COR, the predicted depth resolution was 3-11 mm for a viewing angle of 7 degrees , which agreed favorably with results from recently published studies. The model also described how acquisition parameters affected spatial warping of curves of equal apparent depth. Pincushioning and the difference between the acquisition and display geometry were found to introduce additional distortions to stereo displays. Preference studies on X-ray angiograms indicated that the ideal viewing angle should be small (1-2 degrees), which agreed with some previously published work. Perceptual studies indicated that stereo angiograms should have high artery contrast and that digital processing to increase contrast improved stereopsis. Digital subtraction angiograms, with different motion errors between the left and right-eye views, gave artifacts that confused stereopsis. The addition of background to subtracted images reduced this effect and provided other features for improved depth perception. Using the modeling results and typical clinical angiography requirements, we recommend acquisition protocols and engineering specifications that are achievable on current high-end systems.     

Tomographic reconstruction using an adaptive tetrahedral mesh defined by a point cloud

Medical images in nuclear medicine are commonly represented in three dimensions as a stack of two-dimensional images that are reconstructed from tomographic projections. Although natural and straightforward, this may not be an optimal visual representation for performing various diagnostic tasks. A method for three-dimensional (3-D) tomographic reconstruction is developed using a point cloud image representation. A point cloud is a set of points (nodes) in space, where each node of the point cloud is characterized by its position and intensity. The density of the nodes determines the local resolution allowing for the modeling of different parts of the image with different resolution. The reconstructed volume, which in general could be of any resolution, size, shape, and topology, is represented by a set of nonoverlapping tetrahedra defined by the nodes. The intensity at any point within the volume is defined by linearly interpolating inside a tetrahedron from the values at the four nodes that define the tetrahedron. This approach creates a continuous piecewise linear intensity over the reconstruction domain. The reconstruction provides a distinct multiresolution representation, which is designed to accurately and efficiently represent the 3-D image. The method is applicable to the acquisition of any tomographic geometry, such as parallel-, fan-, and cone-beam; and the reconstruction procedure can also model the physics of the image detection process. An efficient method for evaluating the system projection matrix is presented. The system matrix is used in an iterative algorithm to reconstruct both the intensity and location of the distribution of points in the point cloud. Examples of the reconstruction of projection data generated by computer simulations and projection data experimentally acquired using a Jaszczak cardiac torso phantom are presented. This work creates a framework for voxel-less multiresolution representation of images in nuclear medicine.     

Estimation of images and nonrigid deformations in gated emission CT

In this paper, we propose and test a new iterative algorithm to simultaneously estimate the nonrigid motion vector fields and the emission images for a complete cardiac cycle in gated cardiac emission tomography. We model the myocardium as an elastic material whose motion does not generate large amounts of strain. As a result, our method is based on minimizing an objective function consisting of the negative logarithm of a maximum likelihood image reconstruction term, the standard biomechanical model of strain energy, and an image matching term that ensures a measure of agreement of intensities between frames. Simulations are obtained using data for the four-dimensional (4-D) NCAT phantom. The data models realistic noise levels in a typical gated myocardial perfusion SPECT study. We show that our simultaneous algorithm produces images with improved spatial resolution characteristics and noise properties compared with those obtained from postsmoothed 4-D maximum likelihood methods. The simulations also demonstrate improved motion estimates over motion estimation using independently reconstructed images.     

Motion correction in dual gated cardiac PET using mass-preserving image registration

Respiratory and cardiac motion leads to image degradation in positron emission tomography (PET) studies of the human heart. In this paper we present a novel approach to motion correction based on dual gating and mass-preserving hyperelastic image registration. Thereby, we account for intensity modulations caused by the highly nonrigid cardiac motion. This leads to accurate and realistic motion estimates which are quantitatively validated on software phantom data and carried over to clinically relevant data using a hardware phantom. For patient data, the proposed method is first evaluated in a high statistic (20 min scans) dual gating study of 21 patients. It is shown that the proposed approach properly corrects PET images for dual-cardiac as well as respiratory-motion. In a second study the list mode data of the same patients is cropped to a scan time reasonable for clinical practice (3 min). This low statistic study not only shows the clinical applicability of our method but also demonstrates its robustness against noise obtained by hyperelastic regularization.     

Estimation of deformation gradient and strain from cine-PC velocitydata [cardiac magnetic resonance imaging]

Phase contrast magnetic resonance imaging (MRI) can provide in vivo myocardial velocity field measurements. These data allow densely spaced material points to be tracked throughout the whole heart cycle using, for example, the Fourier tracking algorithm. To process the tracking results for myocardial deformation and strain quantification, the authors developed a method that is based on fitting the tracking results to an appropriate local deformation model. They further analyzed the accuracy and precision of the method and provided performance predictions for several local models. In order to validate the method and the theoretical performance analysis, the authors conducted controlled computer simulations and a phantom study. The results agreed well with expectations. Human heart data were also acquired and analyzed, and provided encouraging results. At the signal-to-noise ratio (SNR) level and spatial resolution expected in clinical settings, the study predicts strain quantification accuracy and precision that may allow the technique to become a practical and powerful noninvasive approach for the study of cardiac function, although clinically acceptable data acquisition strategies for three-dimensional (3-D) data are still a challenge     

Simultaneous MR-Compatible Emission and Transmission Imaging for PET Using Time-of-Flight Information

Quantitative positron emission tomography (PET) imaging relies on accurate attenuation correction. Predicting attenuation values from magnetic resonance (MR) images is difficult because MR signals are related to proton density and relaxation properties of tissues. Here, we propose a method to derive the attenuation map from a transmission scan. An annulus transmission source is positioned inside the field-of-view of the PET scanner. First a blank scan is acquired. The patient is injected with FDG and placed inside the scanner. 511-keV photons coming from the patient and the transmission source are acquired simultaneously. Time-of-flight information is used to extract the coincident photons originating from the annulus. The blank and transmission data are compared in an iterative reconstruction method to derive the attenuation map. Simulations with a digital phantom were performed to validate the method. The reconstructed attenuation coefficients differ less than 5% in volumes of interest inside the lungs, bone, and soft tissue. When applying attenuation correction in the reconstruction of the emission data a standardized uptake value error smaller than 9% was obtained for all tissues. In conclusion, our method can reconstruct the attenuation map and the emission data from a simultaneous scan without prior knowledge about the anatomy or the attenuation coefficients of the tissues.     

Three-dimensional motion tracking of coronary arteries in biplane cineangiograms

A three-dimensional (3-D) method for tracking the coronary arteries through a temporal sequence of biplane X-ray angiography images is presented. A 3-D centerline model of the coronary vasculature is reconstructed from a biplane image pair at one time frame, and its motion is tracked using a coarse-to-fine hierarchy of motion models. Three-dimensional constraints on the length of the arteries and on the spatial regularity of the motion field are used to overcome limitations of classical two-dimensional vessel tracking methods, such as tracking vessels through projective occlusions. This algorithm was clinically validated in five patients by tracking the motion of the left coronary tree over one cardiac cycle. The root mean square reprojection errors were found to be submillimeter in 93% (54/58) of the image pairs. The performance of the tracking algorithm was quantified in three dimensions using a deforming vascular phantom. RMS 3-D distance errors were computed between centerline models tracked in the X-ray images and gold-standard centerline models of the phantom generated from a gated 3-D magnetic resonance image acquisition. The mean error was 0.69 (+/- 0.06) mm over eight temporal phases and four different biplane orientations.     

Identification of reduced-order thermal therapy models using thermal MR images: theory and validation

In this paper, we develop and validate a method to identify computationally efficient site- and patient-specific models of ultrasound thermal therapies from MR thermal images. The models of the specific absorption rate of the transduced energy and the temperature response of the therapy target are identified in the reduced basis of proper orthogonal decomposition of thermal images, acquired in response to a mild thermal test excitation. The method permits dynamic reidentification of the treatment models during the therapy by recursively utilizing newly acquired images. Such adaptation is particularly important during high-temperature therapies, which are known to substantially and rapidly change tissue properties and blood perfusion. The developed theory was validated for the case of focused ultrasound heating of a tissue phantom. The experimental and computational results indicate that the developed approach produces accurate low-dimensional treatment models despite temporal and spatial noises in MR images and slow image acquisition rate.     

2D motion aided sampling and reconstruction

In this paper we consider the problem of generating data which is sufficient for super resolution reconstruction. The method considered here is by inducing motion on the (low resolution) image acquisition device which then generates a number of low resolution images – this is the data we use for the super resolution reconstruction. Our main concern is in investigating a number of motion types and providing the conditions which will guarantee the feasibility of the super resolution reconstruction from data available.     

Regression-based cardiac motion prediction from single-phase CTA

State of the art cardiac computed tomography (CT) enables the acquisition of imaging data of the heart over the entire cardiac cycle at concurrent high spatial and temporal resolution. However, in clinical practice, acquisition is increasingly limited to 3-D images. Estimating the shape of the cardiac structures throughout the entire cardiac cycle from a 3-D image is therefore useful in applications such as the alignment of preoperative computed tomography angiography (CTA) to intra-operative X-ray images for improved guidance in coronary interventions. We hypothesize that the motion of the heart is partially explained by its shape and therefore investigate the use of three regression methods for motion estimation from single-phase shape information. Quantitative evaluation on 150 4-D CTA images showed a small, but statistically significant, increase in the accuracy of the predicted shape sequences when using any of the regression methods, compared to shape-independent motion prediction by application of the mean motion. The best results were achieved using principal component regression resulting in point-to-point errors of 2.3±0.5 mm, compared to values of 2.7±0.6 mm for shape-independent motion estimation. Finally, we showed that this significant difference withstands small variations in important parameter settings of the landmarking procedure.     

Estimation of the heart respiratory motion with applications for cone beam computed tomography imaging: a simulation study

Computed tomography (CT) reconstruction methods assume imaging of static objects; object movement during projection data acquisition causes tomogram artifacts. The continuously moving heart, therefore, represents a complicated imaging case. The associated problems due to the heart beating can be overcome either by using very short projection acquisition times, during which the heart may be considered static, or by ECG-gated acquisition. In the latter case, however, the acquisition of a large number of projections may not be completed in a single breath hold, thus heart displacement occurs as an additional problem. This problem has been addressed by applying heart motion models in various respiratory motion compensation algorithms. Our paper focuses on cone beam computed tomography (CBCT), performed in conjunction with isocentric, fluoroscopic equipment, and continuous ECG and respiratory monitoring. Such equipment is used primarily for in-theater three-dimensional (3-D) imaging and benefits particularly from the recent developments in flat panel detector technologies. The objectives of this paper are: (i) to develop a model for the motion of the heart due to respiration during the respiratory cycle; (ii) to apply this model to the tomographic reconstruction algorithm, in order to account for heart movement due to respiration in the reconstruction; and (iii) to initially evaluate this method by means of simulation studies. Based on simulation studies, we were able to demonstrate that heart displacement due to respiration can be estimated from the same projection data, required for a CBCT reconstruction. Our paper includes semiautomatic segmentation of the heart on the X-ray projections and reconstruction of a convex 3-D-heart object that performs the same motion as the heart during respiration, and use of this information into the CBCT reconstruction algorithm. The results reveal significant image quality improvements in cardiac image reconstruction.     

A Super-Resolution Framework for 3-D High-Resolution and High-Contrast Imaging Using 2-D Multislice MRI

A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. A comparison with previously published SRR methods shows favorable characteristics in the proposed approach.