Detectability of motions in AAA with ECG-gated CTA: A quantitative study

Purpose: ECG-gated CT enables the visualization of motions caused by the beating of the heart. Although ECG gating is frequently used in cardiac CT imaging, this technique is also very promising for evaluating vessel wall motion of the aortic artery and the motions of (stent grafts inside) abdominal aortic aneurysms (AAA). Late stent graft failure is a serious complication in endovascular repair of aortic aneurysms. Better understanding of the motion characteristics of stent grafts will be beneficial for designing future devices. In addition, these data can be valuable in predicting stent graft failure in patients. To be able to reliably quantify the motion, however, it is of importance to know the performance and limitations of ECG gating, especially when the motions are small, as is the case in AAA. Since the details of the reconstruction algorithms are proprietary information on the CT manufacturers and not in the public domain, empirical experiments are required. The goal of this study is to investigate as to what extent the motions in AAA can be measured using ECG-gated CT. The authors quantitatively investigate four aspects of motion in ECG-gated CT: The detectability of the motion of objects at different amplitudes and different periodic motions, the temporal resolution, and the volume gaps that occur as a function of heart rate.\ud \ud Methods: They designed an experiment on a standard static phantom to empirically determine temporal resolution. To investigate motion amplitude and frequency, as well as patient heart rate, they designed dynamic experiments in which a home-made phantom driven by a motion unit moves in a predetermined pattern.\ud \ud Results: The duration of each ECG-gated phase was found to be 185 ms, which corresponds to half of the rotation time and is thus in accordance with half scan reconstruction applied by the scanner. By using subpixel localization, motions become detectable from amplitudes of as small as 0.4 mm in the x direction and 0.7 mm in the z direction. With the rotation time used in this study, motions up to 2.7 Hz can be reliably detected. The reconstruction algorithm fills volume gaps with noisy data using interpolation, but objects within these gaps remain hidden.\ud \ud Conclusions: This study gives insight into the possibilities and limitations for measuring small motions using ECG-gated CT. Application of the experimental method is not restricted to the CT scanner of a single manufacturer. From the results, they conclude that ECG-gated CTA is a suitable technique for studying the expected motions of the stent graft and vessel wall in AAA.\u

Spectral image utility for target detection applications

In a wide range of applications, images convey useful information about scenes. The “utility” of an image is defined with reference to the specific task that an observer seeks to accomplish, and differs from the “fidelity” of the image, which seeks to capture the ability of the image to represent the true nature of the scene. In remote sensing of the earth, various means of characterizing the utility of satellite and airborne imagery have evolved over the years. Recent advances in the imaging modality of spectral imaging have enabled synoptic views of the earth at many finely sampled wavelengths over a broad spectral band. These advances challenge the ability of traditional earth observation image utility metrics to describe the rich information content of spectral images. Traditional approaches to image utility that are based on overhead panchromatic image interpretability by a human observer are not applicable to spectral imagery, which requires automated processing. This research establishes the context for spectral image utility by reviewing traditional approaches and current methods for describing spectral image utility. It proposes a new approach to assessing and predicting spectral image utility for the specific application of target detection. We develop a novel approach to assessing the utility of any spectral image using the target-implant method. This method is not limited by the requirements of traditional target detection performance assessment, which need ground truth and an adequate number of target pixels in the scene. The flexibility of this approach is demonstrated by assessing the utility of a wide range of real and simulated spectral imagery over a variety ii of target detection scenarios. The assessed image utility may be summarized to any desired level of specificity based on the image analysis requirements. We also present an approach to predicting spectral image utility that derives statistical parameters directly from an image and uses them to model target detection algorithm output. The image-derived predicted utility is directly comparable to the assessed utility and the accuracy of prediction is shown to improve with statistical models that capture the non-Gaussian behavior of real spectral image target detection algorithm outputs. The sensitivity of the proposed spectral image utility metric to various image chain parameters is examined in detail, revealing characteristics, requirements, and limitations that provide insight into the relative importance of parameters in the image utility. The results of these investigations lead to a better understanding of spectral image information vis-à-vis target detection performance that will hopefully prove useful to the spectral imagery analysis community and represent a step towards quantifying the ability of a spectral image to satisfy information exploitation requirements