Armin Horst Pfoh

Design and image quality results from volumetric CT with a flat-panel imager

Preliminary MTF and LCD results obtained on several volumetric computed tomography (VCT) systems, employing amorphous flat panel technology, are presented. Constructed around 20-cm x 20-cm, 200-mm pitch amorphous silicon x-ray detectors, the prototypes use standard vascular or CT x-ray sources. Data were obtained from closed-gantry, benchtop and C-arm-based topologies, over a full 360 degrees of rotation about the target object. The field of view of the devices is approximately 15 cm, with a magnification of 1.25-1.5, providing isotropic resolution at isocenter of 133-160 mm. Acquisitions have been reconstructed using the FDK algorithm, modified by motion corrections also developed by GE. Image quality data were obtained using both industry standard and custom resolution phantoms as targets. Scanner output is compared on a projection and reconstruction basis against analogous output from a dedicated simulation package, also developed at GE. Measured MTF performance is indicative of a significant advance in isotropic image resolution over commercially available systems. LCD results have been obtained, using industry standard phantoms, spanning a contrast range of 0.3-1%. Both MTF and LCD measurements agree with simulated data.

Cardiac-state-driven CT image reconstruction algorithm for cardiac imaging

Multi-slice CT scanners use EKG gating to predict the cardiac phase during slice reconstruction from projection data. Cardiac phase is generally defined with respect to the RR interval. The implicit assumption made is that the duration of events in a RR interval scales linearly when the heart rate changes. Using a more detailed EKG analysis, we evaluate the impact of relaxing this assumption on image quality. We developed a reconstruction algorithm that analyzes the associated EKG waveform to extract the natural cardiac states. A wavelet transform was used to decompose each RR-interval into P, QRS, and T waves. Subsequently, cardiac phase was defined with respect to these waves instead of a percentage or time delay from the beginning or the end of RR intervals. The projection data was then tagged with the cardiac phase and processed using temporal weights that are function of their cardiac phases. Finally, the tagged projection data were combined from multiple cardiac cycles using a multi-sector algorithm to reconstruct images. The new algorithm was applied to clinical data, collected on a 4-slice (GE LightSpeed Qx/i) and 8-slice CT scanner (GE LightSpeed Plus), with heart rates of 40 to 80 bpm. The quality of reconstruction is assessed by the visualization of the major arteries, e.g. RCA, LAD, LC in the reformat 3D images. Preliminary results indicate that Cardiac State Driven reconstruction algorithm offers better image quality than their RR-based counterparts.

Novel reconstruction algorithm for multiphasic cardiac imaging using multislice helical CT

Cardiac imaging is still a challenge to CT reconstruction algorithms due to the dynamic nature of the heart. We have developed a new reconstruction technique, called the Flexible Algorithm, which achieves high temporal resolution while it is robust to heart-rate variations. The Flexible Algorithm, first, retrospectively tags helical CT views with corresponding cardiac phases obtained from associated EKG. Next, it determines a set of views for each slice, a stack of which covers the entire heart. Subsequently, the algorithm selects an optimum subset of views to achieve the highest temporal resolution for the desired cardiac phase. Finally, it spatiotemporally filters the views in the selected subsets to reconstruct slices. We tested the performance of our algorithm using both a dynamic analytical phantom and clinical data. Preliminary results indicate that the Flexible Algorithm obtains improved spatiotemporal resolution for a large range of heart rates and variations than standard algorithms do. By providing improved image quality at any desired cardiac phase, and robustness to heart rate variations, the Flexible Algorithm enables cardiac applications in CT, including those that benefit from multiphase information.

Four-dimensional x-ray attenuation model of the human heart and the coronary vasculature and its use for the assessment of cardiac CT imaging technology

Using helical, multi-detector computed tomography (CT) imaging technology operating at sub-second scanning speeds, clinicians are investigating the capabilities of CT for cardiac imaging. In this paper, we describe the application of novel modeling tools to assess CT system capability. These tools allow us to quantify the capabilities of both hardware and software algorithms for cardiac imaging. The model consists of a human thorax, a dynamic model of a human heart, and a complete physics-based, CT system model. The use of the model to predict image quality is demonstrated by varying both the reconstruction algorithm (half-scan, sector-based) and CT system parameters (axial detector resolution). The mathematical tools described provide a means to rapidly evaluate new reconstruction algorithms and CT system designs for cardiac imaging.

Four-dimensional x-ray attenuation model of the human heart and the coronary vasculature for assessment of CT system capability

With the introduction of helical, multi-detector computed tomography (CT) scanners having sub-second scanning speeds, clinicians are currently investigating the role of CT in cardiac imaging. In this paper, we describe a four-dimensional (4D) x-ray attenuation model of a human heart and the use of this model to assess the capabilities of both hardware and software algorithms for cardiac imaging. We developed a model of the human thorax, composed of several analytical structures, and a model of the human heart, constructed from several elliptical surfaces. A model for each coronary vessel consists of a torus placed at a suitable location on the hearts surface. The motion of the heart during the cardiac cycle was implemented by applying transformational operators to each surface composing the heart. We used the 4D model of the heart to generate forward projection data, which then became input into a model of a CT imaging system. The use of the model to predict image quality is demonstrated by varying both the reconstruction algorithm (sector-based, half-scan) and CT system parameters (gantry speed, spatial resolution). The mathematical model of the human heart, while having limitations, provides a means to rapidly evaluate new reconstruction algorithms and CT system designs for cardiac imaging.

Cone-beam volumetric CT imagers: simulations for rapid prototype system design and prediciton of image quality

A framework for rapid and reliable design of Volumetric Computed Tomography (VCT) systems is presented. This work uses detailed system simulation tools to model standard and anthropomorphic phantoms in order to simulate the CT image and choose optimal system specifications. CT systems using small-pitch, 2-D flat area detectors, initially developed for x-ray projection imaging, have been proposed to implement Volume CT for clinical applications. Such systems offer many advantages, but there are also many trade-offs not fully understood that affect image quality. Although many of these effects have been studied in the literature for traditional CT applications, there are unique interactions for very high-resolution flat-panel detectors that are proposed for volumetric CT. To demonstrate the process we describe an example that optimizes the parameters to achieve high detectability for thin slices. The VCT system was modeled over a range of operating parameters, including: tube voltage, tube current, tube focal spot size, detector cell size, number of views, and scintillator thickness. The response surface, which captures the effects of system components on image quality, was calculated. Optimal and robust designs can be achieved by determining an operating point from the response equations, given the constraints. We verify the system design with images from standard and low contrast phantoms. Eventually this design tool could be used, in conjunction with clinical researchers, to specify VCT scanner designs, optimize imaging protocols, and quantify image accuracy and repeatability.