Helical cardiac cone beam CT reconstruction with large area detectors: a simulation study

Simulation tools for two-dimensional experiments in x-ray computed tomography using the FORBILD head phantom

Mathematical phantoms are essential for the development and early stage evaluation of image reconstruction algorithms in x-ray computed tomography (CT). This note offers tools for computer simulations using a two-dimensional (2D) phantom that models the central axial slice through the FORBILD head phantom. Introduced in 1999, in response to a need for a more robust test, the FORBILD head phantom is now seen by many as the gold standard. However, the simple Shepp-Logan phantom is still heavily used by researchers working on 2D image reconstruction. Universal acceptance of the FORBILD head phantom may have been prevented by its significantly higher complexity: software that allows computer simulations with the Shepp-Logan phantom is not readily applicable to the FORBILD head phantom. The tools offered here address this problem. They are designed for use with Matlab®, as well as open-source variants, such as FreeMat and Octave, which are all widely used in both academia and industry. To get started, the interested user can simply copy and paste the codes from this PDF document into Matlab® M-files.

Adaptive two-pass cone-beam artifact correction using a FOV-preserving two-source geometry: a simulation study

The evolution to ever wider detector arrays that are able to cover whole organs with a single circular gantry sweep has revitalized the research efforts toward finding improved axial scanning algorithms and protocols. The authors propose a computed tomography scan and reconstruction concept using two sources, a single detector and a two-pass cone-beam correction method, as an integral part of the reconstruction. Compared with standard circular acquisition and reconstruction methods, the new concept excels with improved coverage and very low cone-beam artifact level also for short scan acquisitions, which makes it especially attractive for cardiac applications.

Improvement of cardiac CT reconstruction using local motion vector fields

The motion of the heart is a major challenge for cardiac imaging using CT. A novel approach to decrease motion blur and to improve the signal to noise ratio is motion compensated reconstruction which takes motion vector fields into account in order to correct motion. The presented work deals with the determination of local motion vector fields from high contrast objects and their utilization within motion compensated filtered back projection reconstruction. Image registration is applied during the quiescent cardiac phases. Temporal interpolation in parameter space is used in order to estimate motion during strong motion phases. The resulting motion vector fields are during image reconstruction. The method is assessed using a software phantom and several clinical cases for calcium scoring. As a criterion for reconstruction quality, calcium volume scores were derived from both, gated cardiac reconstruction and motion compensated reconstruction throughout the cardiac phases using low pitch helical cone beam CT acquisitions. The presented technique is a robust method to determine and utilize local motion vector fields. Motion compensated reconstruction using the derived motion vector fields leads to superior image quality compared to gated reconstruction. As a result, the gating window can be enlarged significantly, resulting in increased SNR, while reliable Hounsfield units are achieved due to the reduced level of motion artefacts. The enlargement of the gating window can be translated into reduced dose requirements.

Quantification of left ventricular function and mass in cardiac Dual-Source CT (DSCT) exams: comparison of manual and semiautomatic segmentation algorithms

The purpose of our study was to evaluate reliability of left ventricular (LV) function and mass quantification in cardiac DSCT exams comparing manual contour tracing and a region-growing-based semiautomatic segmentation analysis software. Thirty-three consecutive patients who underwent cardiac DSCT exams were included. Axial 1-mm slices were used for the semiautomated technique, and short-axis 8-mm slice thickness multiphase image reconstructions were the basis for manual contour tracing. Left ventricular volumes, ejection fraction and myocardial mass were assessed by both segmentation methods. Length of time needed for both techniques was also recorded. Left ventricular functional parameters derived from semiautomatic contour detection algorithm were not statistically different from manual tracing and showed an excellent correlation (p<0.001). The semiautomatic contour detection algorithm overestimated LV mass (180.30+/-44.74 g) compared with manual contour tracing (156.07+/-46.29 g) (p<0.001). This software allowed a significant reduction of the time needed for global LV assessment (mean 174.16+/-71.53 s, p<0.001). Objective quantification of LV function using the evaluated region-growing-based semiautomatic segmentation analysis software is feasible, accurate, reliable and time-effective. However, further improvements are needed to equal results achieved by manual contour tracing, especially with regard to LV mass quantification.

Aortic valve area assessment: multidetector CT compared with cine MR imaging and transthoracic and transesophageal echocardiography

PURPOSE

To prospectively compare the accuracy of multidetector computed tomographic (CT) measurements of the aortic valve area (AVA) with transesophageal echocardiography (TEE) and cine magnetic resonance (MR) measurements of this area for preoperative examination of patients undergoing cardiac surgery, with transthoracic echocardiography (TTE) as the reference standard.

MATERIALS AND METHODS

After giving informed consent for the institutional review board-approved study protocol, 48 patients (33 men, 15 women; mean age, 62 years+/-13 [standard deviation]) with (n=27) or without (n=21) aortic stenosis underwent multidetector CT, cine MR, TTE, and TEE before undergoing cardiac surgery. AVAs derived with manual planimetry by using cine short-axis multidetector CT, MR, and TEE images obtained through the aortic valve were compared among each other and with AVAs measured by using continuity equation TTE at regression and Bland-Altman analyses. The diagnostic accuracy of multidetector CT for detection of aortic stenosis was compared with that of TTE by using kappa statistics and receiver operating characteristic curves.

RESULTS

Multidetector CT-derived AVA correlated highly with MR-derived (r=0.98, P<.001), TEE-derived (r=0.98, P<.001), and TTE-derived (r=0.96, P<.001) AVA. Multidetector CT planimetry AVAs (mean AVA+/-standard deviation, 2.5 cm2+/-1.7) were not significantly different from MR planimetry (2.4 cm2+/-1.8, P>.99) or TEE planimetery (2.5 cm2+/-1.7, P=.21) AVAs, but they were significantly larger than TTE-derived AVAs (2.0 cm2+/-1.5, P<.001). With TTE as the reference standard, multidetector CT correctly (kappa=0.88, P<.001) depicted all 21 normal, six of eight mildly stenotic (AVA>or=1.2 cm2 and <2.0 cm2), seven of eight moderately stenotic (AVA>or= 0.8 cm2 and <1.2 cm2), and 10 of 11 severely stenotic (AVA<0.8 cm2) valves. It also correctly depicted all 14 bicuspid valves identified with TEE, eight of which were missed with TTE.

CONCLUSION

Multidetector CT enables accurate noninvasive assessment of the AVA.

CEnPiT: Helical cardiac CT reconstruction

Computer tomography (CT) scanners with an increasing number of detector rows offer the potential of shorter scanning times. Nevertheless, the reconstruction problem becomes more challenging, since cone beam artifacts are likely to enter. Here, we consider helical cardiac CT. We analyze how a relationship can be established between exact reconstruction algorithms and the demand to perform a cardiac gating. Utilizing the redundancies requires the consideration of all kinds of Radon planes. For the reconstruction algorithm proposed here, we separate the data into two parts. The first part contains contributions of Radon planes, which are measured with a large number of redundancies. The second part contains the remaining contributions. As it turns out, the second part contributes rather to the low-frequency contents of trans-axial slices. Therefore, we propose to perform a gated back-projection only for the first part, while the second part is back-projected in an ungated way. Data from the complete source trajectory are employed in the reconstruction process in contrary to conventional helical cardiac reconstruction methods. Moreover, all different types of Radon planes are taken into account in the reconstruction, though an ECG-dependent cardiac gating is applied. The reconstruction results, which we present for clinical and simulated data, demonstrate the high potential of CEnPiT for helical cardiac CT with large cone angle systems.

Aperture weighted cardiac reconstruction for cone-beam CT

Multi-row detectors together with fast rotating gantries made cardiac imaging possible for CT. Due to the cardiac motion, ECG gating has to be integrated into the reconstruction of the data measured on a low pitch helical trajectory. Since the first multi-row scanners were introduced, it has been shown that approximative true cone-beam reconstruction methods are most suitable for the task of retrospectively gated cardiac volume CT. In this paper, we present the aperture weighted cardiac reconstruction (AWCR), which is a three-dimensional reconstruction algorithm of the filtered back-projection type. It is capable of handling all illumination intervals of an object point, which occur as a consequence of a low pitch helical cone-beam acquisition. Therefore, this method is able to use as much redundant data as possible, resulting in an improvement of the image homogeneity, the signal to noise ratio and the temporal resolution. Different optimization techniques like the heart rate adaptive cardiac weighting or the automatic phase determination can be adopted to AWCR. The excellent image quality achieved by AWCR is presented for medical datasets acquired with both a 40-slice and a 64-slice cone-beam CT scanner.

Image reconstruction

We give an overview of the role of Physics in Medicine and Biology in the development of tomographic reconstruction algorithms. We focus on imaging modalities involving ionizing radiation, CT, PET and SPECT, and cover a wide spectrum of reconstruction problems, starting with classical 2D tomography in the 1970s up to 4D and 5D problems involving dynamic imaging of moving organs.

Direct cone-beam cardiac reconstruction algorithm with cardiac banding artifact correction

Multislice helical computed tomography (CT) is a promising noninvasive technique for coronary artery imaging. Various factors can cause inconsistencies in cardiac CT data, which can result in degraded image quality. These inconsistencies may be the result of the patient physiology (e.g., heart rate variations), the nature of the data (e.g., cone-angle), or the reconstruction algorithm itself. An algorithm which provides the best temporal resolution for each slice, for example, often provides suboptimal image quality for the entire volume since the cardiac temporal resolution (TRc) changes from slice to slice. Such variations in TRc can generate strong banding artifacts in multiplanar reconstruction images or three-dimensional images. Discontinuous heart walls and coronary arteries may compromise the accuracy of the diagnosis. A beta-blocker is often used to reduce and stabilize patients' heart rate but cannot eliminate the variation. In order to obtain robust and optimal image quality, a software solution that increases the temporal resolution and decreases the effect of heart rate is highly desirable. This paper proposes an ECG-correlated direct cone-beam reconstruction algorithm (TCOT-EGR) with cardiac banding artifact correction (CBC) and disconnected projections redundancy compensation technique (DIRECT). First the theory and analytical model of the cardiac temporal resolution is outlined. Next, the performance of the proposed algorithms is evaluated by using computer simulations as well as patient data. It will be shown that the proposed algorithms enhance the robustness of the image quality against inconsistencies by guaranteeing smooth transition of heart cycles used in reconstruction.

Region-of-interest reconstruction of motion-contaminated data using a weighted backprojection filtration algorithm

The recently developed weighted backprojection filtration (WBPF) algorithm using data redundancy has capabilities that make this algorithm an attractive candidate for reconstructing images from motion-contaminated projection data. First, the WBPF algorithm is capable of reconstructing region-of-interest (ROI) images from reduced-scan fan-beam data, which have less data than the short-scan data required to reconstruct the entire field of view (FOV). Second, this algorithm can reconstruct ROI images from truncated data. Using phantom simulation studies, we demonstrate how these unique capabilities can be exploited to reduce the amount of motion-contaminated data used for reconstruction. In particular, we use examples from cardiac imaging to illustrate how off-center phantom positioning combined with phase-interval ROI reconstruction can result in the suppression of motion artifacts. In terms of temporal resolution, reduced-scan reconstruction with 45% of a full-scan dataset can be used to improve the temporal resolution of a short-scan reconstruction by 25.8% if ungated data are used. For data gated at 66 beats per minute, reduced-scan reconstruction with 45% of a full-scan dataset can be used to improve the temporal resolution of a short-scan reconstruction by 7.9%. As a result of our studies, we believe that the WBPF algorithm demonstrates the potential for reconstructing quality ROI images from motion-contaminated fan-beam data.