Purpose: To compare image quality and lesion conspicuity on abdominal computed tomographic (CT) images acquired with different x-ray tube current-time products (50-200 mAs) and reconstructed with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP) techniques. Materials and Methods: Twenty-two patients (mean age, 60.1 years +/- 7.3 [standard deviation]; age range, 52.8-67.4 years; mean weight, 78.9 kg +/- 18.3; 12 men, 10 women) gave informed consent for this prospective institutional review board-approved and HIPAA-compliant study, which involved the acquisition of four additional image series at multidetector CT. Images were acquired at different tube current-time products (200, 150, 100, and 50 mAs) and encompassed an abdominal lesion over a 10-cm scan length. Images were reconstructed separately with FBP and with three levels of ASIR-FBP blending. Two radiologists reviewed FBP and ASIR images for image quality in a blinded and randomized manner. Volume CT dose index (CTDIvol), dose-length product, patient weight, objective noise, and CT numbers were recorded. Data were analyzed by using analysis of variance and the Wilcoxon signed rank test. Results: CTDI vol values were 16.8, 12.6, 8.4, and 4.2 mGy for 200, 150, 100, and 50 mAs, respectively (P < .001). Subjective noise was graded as below average at 150 mAs and average at 100 and 50 mAs for ASIR images, as compared with FBP images, on which noise was graded as average at 150 mAs, above average at 100 mAs, and unacceptable at 50 mAs. A substantial blotchy image appearance was noted in four of 22 image series acquired at 4.2 mGy with 70% ASIR. Lesion conspicuity was significantly better at 4.2 mGy on ASIR than on FBP images (observed P < .044), and overall diagnostic confidence changed from unacceptable on FBP to acceptable on ASIR images. Conclusion: ASIR lowers noise and improves diagnostic confidence in and conspicuity of subtle abdominal lesions at 8.4 mGy when images are reconstructed with 30% ASIR blending and at 4.2 mGy in patients weighing 90 kg or less when images are reconstructed with 50% or 70% ASIR blending. (C) RSNA, 2010

Spectral Computed Tomography (Spectral CT), and in particular fast kVp switching dual-energy computed tomography, is an imaging modality that extends the capabilities of conventional computed tomography (CT). Spectral CT enables the estimation of the full linear attenuation curve of the imaged subject at each voxel in the CT volume, instead of a scalar image in Hounsfield units. Because the space of linear attenuation curves in the energy ranges of medical applications can be accurately described through a two-dimensional manifold, this decomposition procedure would be, in principle, limited to two materials. This paper describes an algorithm that overcomes this limitation, allowing for the estimation of N-tuples of material-decomposed images. The algorithm works by assuming that the mixing of substances and tissue types in the human body has the physicochemical properties of an ideal solution, which yields a model for the density of the imaged material mix. Under this model the mass attenuation curve of each voxel in the image can be estimated, immediately resulting in a material-decomposed image triplet. Decomposition into an arbitrary number of pre-selected materials can be achieved by automatically selecting adequate triplets from an application-specific material library. The decomposition is expressed in terms of the volume fractions of each constituent material in the mix; this provides for a straightforward, physically meaningful interpretation of the data. One important application of this technique is in the digital removal of contrast agent from a dual-energy exam, producing a virtual nonenhanced image, as well as in the quantification of the concentration of contrast observed in a targeted region, thus providing an accurate measure of tissue perfusion.

Coronary CT Angiography (CTA) is limited in patients with calcified plaque and stents. CTA is unable to confidently differentiate fibrous from lipid plaque. Fast switched dual energy CTA offers certain advantages. Dual energy CTA removes calcium thereby improving visualization of the lumen and potentially providing a more accurate measure of stenosis. Dual energy CTA directly measures calcium burden (calcium hydroxyapatite) thereby eliminating a separate non-contrast series for Agatston Scoring. Using material basis pairs, the differentiation of fibrous and lipid plaques is also possible. Patency of a previously stented coronary artery is difficult to visualize with CTA due to resolution constraints and localized beam hardening artifacts. Monochromatic 70 keV or Iodine images coupled with Virtual Non-stent images lessen beam hardening artifact and blooming. Virtual removal of stainless steel stents improves assessment of in-stent re-stenosis. A beating heart phantom with 'cholesterol' and 'fibrous' phantom coronary plaques were imaged with dual energy CTA. Statistical classification methods (SVM, kNN, and LDA) distinguished 'cholesterol' from 'fibrous' phantom plaque tissue. Applying this classification method to 16 human soft plaques, a lipid 'burden' may be useful for characterizing risk of coronary disease. We also found that dual energy CTA is more sensitive to iodine contrast than conventional CTA which could improve the differentiation of myocardial infarct and ischemia on delayed acquisitions. These phantom and patient acquisitions show advantages with using fast switched dual energy CTA for coronary imaging and potentially extends the use of CT for addressing problem areas of non-invasive evaluation of coronary artery disease.

In a conventional X-ray CT system, where an object is scanned with a selected incident x-ray spectrum, or kVp, the reconstructed images only approximate the linear X-ray attenuation coefficients of the imaged object at an effective energy of the incident X-ray beam. The errors are primarily the result of beam hardening due to the polychromatic nature of the X-ray spectrum. Modem clinical CT scanners can reduce this error by a process commonly referred to as spectral calibration. Spectral calibration linearizes the measured projection value to the thickness of water. However, beam hardening from bone and contrast agents can still induce shading and streaking artifacts and cause CT number inaccuracies in the image. In this paper, we present a dual kVp scanning method, where during the scan, the kVp is alternately switching between target low and high preset values, typically 80kVp and 140 kVp, with a period less than 1ms. The measured projection pairs are decomposed into the density integrals of two basis materials in projection space. The reconstructed density images are further processed to obtain monochromatic attenuation coefficients of the object at any desired energy. Energy levels yielding optimized monochromatic images are explored, and their analytical representations are derived.

Dual energy CT cardiac imaging is challenging due to cardiac motion and the resolution requirements of clinical applications. In this paper we investigate dual energy CT imaging via fast kVp switching acquisitions of a novel dynamic cardiac phantom. The described cardiac phantom is realistic in appearance with pneumatic motion control driven by an ECG waveform. In the reported experiments the phantom is driven off a 60 beats per minute simulated ECG waveform. The cardiac phantom is inserted into a phantom torso cavity. A fast kVp switching axial step and shoot acquisition is detailed. The axial scan time at each table position exceeds one heart cycle so as to enable retrospective gating. Gating is performed as a mechanism to mitigate the resolution impact of heart motion. Processing of fast kVp data is overviewed and the resulting kVp, material decomposed density, and monochromatic reconstructions are presented. Imaging results are described in the context of potential clinical cardiac applications.

Linear discriminate analysis (LDA) is applied to dual kVp CT and used for tissue characterization. The potential to quantitatively model both malignant and benign, hypo-intense liver lesions is evaluated by analysis of portal-phase, intravenous CT scan data obtained on human patients. Masses with an a priori classification are mapped to a distribution of points in basis material space. The degree of localization of tissue types in the material basis space is related to both quantum noise and real compositional differences. The density maps are analyzed with LDA and studied with system simulations to differentiate these factors. The discriminant analysis is formulated so as to incorporate the known statistical properties of the data. Effective kVp separation and mAs relates to precision of tissue localization. Bias in the material position is related to the degree of X-ray scatter and partial-volume effect. Experimental data and simulations demonstrate that for single energy (HU) imaging or image-based decomposition pixel values of water-like tissues depend on proximity to other iodine-filled bodies. Beam-hardening errors cause a shift in image value on the scale of that difference sought between in cancerous and cystic lessons. In contrast, projection-based decomposition or its equivalent when implemented on a carefully calibrated system can provide accurate data. On such a system, LDA may provide novel quantitative capabilities for tissue characterization in dual energy CT.

Purpose: To present a cone beam helical image reconstruction algorithm for CT diagnostic imaging at dynamically variable pitches and its optimization in dose efficiency. Method and Materials: The ray‐wise 3D weighted helical cone beam filtered backprojection (CB‐FBP) algorithm is extended to carry out image reconstruction at dynamically variable helical pitch, in which the filtering process is carried out in the cone‐parallel geometry along the tangential direction of the helical source trajectory. Consequently, the filtering paths are straight lines at dynamically invariable pitch, but become curves at dynamically variable helical pitches. In addition, since the pitch variation may be caused by either acceleration or deceleration, the filtering paths can be curves containing inflexions. The FORBILD head and thorax phantoms are utilized to evaluate the performance of the extended algorithm. The dynamical variation range of normalized helical pitch in the evaluation is between 0.5:1 and 1.5, which is quite large from the perspective of clinical applications. Moreover, the optimization in dose efficiency is studied by evaluating the noise characteristics at various transitions of helical pitches. Results: The phantom study shows that, at a wide variation of helical pitches, the extended ray‐wise 3D weighted helical CB‐FBP algorithm can provide a well‐balanced imaging performance over reconstruction accuracy, spatial resolution and noise characteristics, while a large field of view can be maintained. Meanwhile, the noise uniformity of the presented algorithm can be improved by optimizing the ray‐wise 3D weighting parameters with the dynamic variation of helical pitch during the scan. Conclusion: Based on the experimental evaluation, especially its robustness over a large variation range of helical pitches, it is expected that the extended ray‐wise 3D weighted CB‐FBP algorithm can meet the challenges posed by advanced clinical applications, in which helical scanning and image reconstruction at dynamically variable pitches and maintenance of noise characteristics are demanded.