This PDF file contains the front matter associated with SPIE Proceedings Volume 8313, including the Title Page, Copyright information, Table of Contents, Introduction, an Overview Paper of the 40 year history of this meeting, and the Conference Committee listing.

X-ray scatter is a common cause of image artifacts for cone-beam CT systems due to the expanded field of view and degrades the quantitative accuracy of measured Hounsfield Units (HU). Due to the strong dependency of scatter on the object being scanned, it is crucial to measure the scatter signal for each object. We propose to use a beam pass array (BPA) composed of parallel-holes within a tungsten plate to measure scatter for a dedicated breast CT system. A complete study of the performance of the BPA was conducted. The goal of this study was to explore the feasibility of measuring and compensating for the scatter signal for each individual object. Different clinical study schemes were investigated, including a full rotation scan with BPA and discrete projections acquired with BPA followed by interpolation for full rotation. Different sized cylindrical phantoms and a breast shaped polyethylene phantom were used to test for the robustness of the proposed method. Physically measured scatter signals were converted into scatter to primary ratios (SPRs) at discrete locations through the projection image. A complete noise-free 2D SPR was generated from these discrete measurements. SPR results were compared to Monte Carlo simulation results and scatter corrected CT images were quantitatively evaluated for "cupping" artifact. With the proposed method, a reduction of up to 47 HU of "cupping" was demonstrated. In conclusion, the proposed BPA method demonstrated effective and accurate objectspecific scatter correction with the main advantage of dose-sparing compared to beam stop array (BSA) approaches.

A system using a wide slot beam and simple anti-scatter grid has been designed to provide a localized map of tissue type that could be overlaid on the simultaneous conventional transmission image to provide an inexpensive, low dose adjunct to conventional screening mammography. The system was demonstrated to differentiate between scatter peak angles corresponding to adipose tissue and carcinoma. Adequate intensity in the coherent scatter image can be achieved at a dose commonly used for screening mammography. Depth information is obtainable from the stereoscopic viewing angles. Phantom imaging measurements and Monte Carlo simulations show good agreement.

Digital breast tomosynthesis (DBT) is a promising alternative approach to overcome the limitations of tissue superposition found in full-field 2D digital mammography. However, due to the absence of anti-scatter grids in DBT, accurate scatter estimation for each projection is necessary for modelling the image reconstruction stage. In this work we identify the limitations associated with scatter estimation using spatial invariant scatter kernels, in particular at the edge region where such methods result in scatter overestimation. Such approaches show an overestimation of scatter-to-primary ratio of over 50% at the edges when compared with results from direct Monte Carlo simulation. This problem was found to increase with projection angle. Simulation work presented here shows that this overestimation in scatter is largely due to air gap between the lower curved breast edge and the detector. We propose a new fast, accurate scatter field estimator for use in DBT which not only considers the breast thickness and primary incidence angle, but also accounts for scatter exiting the breast edge region and traversing an air gap prior to absorption in the detector. The new proposed scatter estimator represents an alternative approach to this problem which reduces discrepancies at the edge of a breast phantom. Moreover, the time required for generating scatter has dropped from approximately 12 hours using Monte Carlo simulations for 1010 photons to just a few minutes per projection. The insertion of scatter from the compression paddle to aforementioned methodologies is also discussed.

In digital breast tomosynthesis (DBT), a reconstruction of the breast is generated from projections acquired over a limited range of x-ray tube angles. There are two principal schemes for acquiring projections, continuous tube motion and step-and-shoot motion. Although continuous tube motion has the benefit of reducing patient motion by lowering scan time, it has the drawback of introducing blurring artifacts due to focal spot motion. The purpose of this work is to determine the optimal scan time which minimizes this trade-off. To this end, the filtered backprojection reconstruction of a sinusoidal input is calculated. At various frequencies, the optimal scan time is determined by the value which maximizes the modulation of the reconstruction. Although prior authors have studied the dependency of the modulation on focal spot motion, this work is unique in also modeling patient motion. It is shown that because continuous tube motion and patient motion have competing influences on whether scan time should be long or short, the modulation is maximized by an intermediate scan time. This optimal scan time decreases with object velocity and increases with exposure time. To optimize step-and-shoot motion, we calculate the scan time for which the modulation attains the maximum value achievable in a comparable system with continuous tube motion. This scan time provides a threshold below which the benefits of step-and-shoot motion are justified. In conclusion, this work optimizes scan time in DBT systems with patient motion and either continuous tube motion or step-and-shoot motion by maximizing the modulation of the reconstruction.

The stationary Digital Breast Tomosynthesis System (s-DBT) has the advantage over the conventional DBT systems as there is no motion blurring in the projection images associated with the x-ray source motion. We have developed a prototype s-DBT system by retrofitting a Hologic Selenia Dimensions rotating gantry tomosynthesis system with a distributed carbon nanotube (CNT) x-ray source array. The linear array consists of 31 x-ray generating focal spots distributed over a 30 degree angle. Each x-ray beam can be electronically activated allowing the flexibility and easy implementation of novel tomosynthesis scanning with different scanning parameters and configurations. Here we report the initial results of investigation on the imaging quality of the s-DBT system and its dependence on the acquisition parameters including the number of projections views, the total angular span of the projection views, the dose distribution between different projections, and the total dose. A mammography phantom is used to visually assess image quality. The modulation transfer function (MTF) of a line wire phantom is used to evaluate the system spatial resolution. For s-DBT the in-plan system resolution, as measured by the MTF, does not change for different configurations. This is in contrast to rotating gantry DBT systems, where the MTF degrades for increased angular span due to increased focal spot blurring associated with the x-ray source motion. The overall image quality factor, a composite measure of the signal difference to noise ratio (SdNR) for mass detection and the z-axis artifact spread function for microcalcification detection, is best for the configuration with a large angular span, an intermediate number of projection views, and an even dose distribution. These results suggest possible directions for further improvement of s-DBT systems for high quality breast cancer imaging.

Dual-energy contrast-enhanced digital breast tomosynthesis (DE CE-DBT) image quality is affected by a large parameter space including the tomosynthesis acquisition geometry, imaging technique factors, the choice of reconstruction algorithm, and the subject breast characteristics. The influence of most of these factors on reconstructed image quality is well understood for DBT. However, due to the contrast agent uptake kinetics in CE imaging, the subject breast characteristics change over time, presenting a challenge for optimization . In this work we experimentally evaluate the sensitivity of the reconstructed image quality to timing of the low-energy and high-energy images and changes in iodine concentration during image acquisition. For four contrast uptake patterns, a variety of acquisition protocols were tested with different timing and geometry. The influence of the choice of reconstruction algorithm (SART or FBP) was also assessed. Image quality was evaluated in terms of the lesion signal-difference-to-noise ratio (LSDNR) in the central slice of DE CE-DBT reconstructions. Results suggest that for maximum image quality, the low- and high-energy image acquisitions should be made within one x-ray tube sweep, as separate low- and high-energy tube sweeps can degrade LSDNR. In terms of LSDNR per square-root dose, the image quality is nearly equal between SART reconstructions with 9 and 15 angular views, but using fewer angular views can result in a significant improvement in the quantitative accuracy of the reconstructions due to the shorter imaging time interval.

Digital breast tomosynthesis (DBT) is a novel x-ray imaging technique that provides 3D structural information of the breast. In contrast to 2D mammography, DBT minimizes tissue overlap potentially improving cancer detection and reducing number of unnecessary recalls. The addition of a contrast agent to DBT and mammography for lesion enhancement has the benefit of providing functional information of a lesion, as lesion contrast uptake and washout patterns may help differentiate between benign and malignant tumors. This study used a task-based method to determine the optimal imaging approach by analyzing six imaging paradigms in terms of their ability to resolve iodine at a given dose: contrast enhanced mammography and tomosynthesis, temporal subtraction mammography and tomosynthesis, and dual energy subtraction mammography and tomosynthesis. Imaging performance was characterized using a detectability index d', derived from the system task transfer function (TTF), an imaging task, iodine contrast, and the noise power spectrum (NPS). The task modeled a 5 mm lesion containing iodine concentrations between 2.1 mg/cc and 8.6 mg/cc. TTF was obtained using an edge phantom, and the NPS was measured over several exposure levels, energies, and target-filter combinations. Using a structured CIRS phantom, d' was generated as a function of dose and iodine concentration. In general, higher dose gave higher d', but for the lowest iodine concentration and lowest dose, dual energy subtraction tomosynthesis and temporal subtraction tomosynthesis demonstrated the highest performance.

Digital breast tomosynthesis (DBT) is a three-dimensional (3D) x-ray imaging modality that has recently been employed to increase lesion conspicuity through the removal of overlying tissue. Recently, a great deal of work has been devoted to the development of contrast enhanced (CE) DBT. Radio-opaque contrast agents (e.g. iodine) are injected into patients with suspicious breast lesions, with the goal of differentiating malignant tumors from benign by imaging the contrast uptake signature associated with angiogenesis. Either temporal subtraction (TS) or dual energy (DE) subtraction may be performed to further remove structural noise from the images. The current work quantifies the change in power-law noise after either DE subtraction or TS using structured breast tissue equivalent phantoms. Additionally, iodine contrast filled phantoms were used to determine the effect of x-ray energy and image subtraction technique on the signaldifference- to-noise ratio (SDNR). Finally, we investigate the improvement in imaging performance of an amorphous selenium (a-Se) direct conversion flat panel detector with increased a-Se thickness.

Breast CT (BCT) using a photon counting detector (PCD) has a number of advantages that can potentially improve clinical performance. Previous computer simulation studies showed that the signal to noise ratio (SNR) for microcalcifications is higher with energy weighted photon counting BCT as compared to cesium iodide energy integrating detector (CsI-EID) based BCT. CsI-EID inherently weighs the incident x-ray photons in direct proportion to the energy (contradicting the information content) which is not an optimal approach. PCD do not inherently weigh the incident photons. By choosing optimal energy weights, higher SNR can be achieved for microcalcifications and hence better detectability. In this simulation study, forward projection data of a numerical breast phantom with microcalcifications inserted were acquired using CsI-EID and PCD. The PCD projections were optimally weighed, and reconstructed using filtered back-projection. We compared observer performance in identifying microcalcifications in the reconstructed images using ROC analysis. ROC based results show that the average area(s) under curve(s) (AUC) for AUC_PCD based methods are higher than the average AUC_CsI-EID method.

Mammography is currently the most widely accepted tool for detection and diagnosis of breast cancer. However, the sensitivity of mammography is reduced in women with dense breast tissue due to tissue overlap, which may obscure lesions. Digital breast tomosynthesis with contrast enhancement reduces tissue overlap and provides additional functional information about lesions (i.e. morphology and kinetics), which in turn may improve lesion characterization. The performance of such techniques is highly dependent on the structural composition of the breast, which varies significantly across patients. Therefore, optimization of breast imaging systems should be done with respect to this patient versatility. Furthermore, imaging techniques that employ contrast require the inclusion of a temporally varying breast composition with respect to the contrast agent kinetics to enable the optimization of the system. To these ends, we have developed a dynamic 4D anthropomorphic breast phantom, which can be used for optimizing a breast imaging system by incorporating material characteristics. The presented dynamic phantom is based on two recently developed anthropomorphic breast phantoms, which can be representative of a whole population through their randomized anatomical feature generation and various compression levels. The 4D dynamic phantom is incorporated with the kinetics of contrast agent uptake in different tissues and can realistically model benign and malignant lesions. To demonstrate the utility of the proposed dynamic phantom, contrast-enhanced digital mammography and breast tomosynthesis were simulated where a ray-tracing algorithm emulated the projections, a filtered back projection algorithm was used for reconstruction, and dual-energy and temporal subtractions were performed and compared.

This paper proposes a new method to improve contrast of a mammogram using multi-energy x-ray (MEX) images. The x-ray attenuation differences among breast tissues increase as incident photons have lower energy. Thus an image obtained by a narrow low energy spectrum has higher contrast than a full (wide) energy spectrum image. The proposed mammogram enhancement utilizes this fact using MEX images. Lowpass data of a low energy spectrum image and high frequency components of a wide energy spectrum image are combined to have high contrast and low noise. Nonsubsampled contourlet transform (NSCT) is employed to decompose image data into multi-scale and multidirectional information. The NSCT overcomes the shortage of directions of wavelet transform by expressing smoothness along contours sufficiently. The outcome of the transform is a lowpass subband and multiple bandpass directional subbands. First, the lowpass subband coefficients of a wide energy spectrum image are substituted by those of a low energy spectrum image. Before the coefficient modification, the low energy spectrum image is processed to have high contrast and sharp details. Next, for the bandpass directional subbands, the locally adaptive bivariate shrinkage of contourlet coefficients is applied to suppress noise. The bivariate shrinkage function exploits interscale dependency of coefficients. Local contrast of the resultant mammogram is considerably enhanced and shows clear fibroglandular tissue structures. Experimental results illustrate that the proposed method produces a high contrast and low noise level image, as compared to the conventional mammography based on a single energy spectrum image.

X-ray scatter leads to erroneous calculations of dual-energy digital mammography (DEDM). The purpose of this work is to design an algorithmic method for scatter correction in DEDM without extra exposures or lead sheet. The method was developed based on the knowledge that scatter radiation in mammograms varies slowly spatially and most pixels in mammograms are non-calcification pixels, and implemented on a commercial full-field digital mammography system with a phantom of breast tissue equivalent material. The pinhole-array interpolation scatter correction method was also implemented on the system. We compared the background dual-energy (DE) calcification signals in the DE calcification images. Results show that the background signal in the DE calcification image can be reduced. The rms of background DE calcification image signal of 1105μm with scatter-uncorrected data was reduced to 187μm and 253μm after scatter correction, using our algorithmic method and pinhole-array interpolation method, respectively. The range of background DE calcification signals using scatter-uncorrected data was reduced by ~80% with scatter-corrected data using algorithmic method. The proposed algorithmic scatter correction method is effective; it has similar or even better performance than pinhole-array interpolation method in scatter correction for DEDM.

Phase-contrast imaging is an emerging technology that may increase the signal-difference-to-noise ratio in medical imaging. One of the most promising phase-contrast techniques is Talbot interferometry, which, combined with energy-sensitive photon-counting detectors, enables spectral differential phase-contrast mammography. We have evaluated a realistic system based on this technique by cascaded-systems analysis and with a task-dependent ideal-observer detectability index as a figure-of-merit. Beam-propagation simulations were used for validation and illustration of the analytical framework. Differential phase contrast improved detectability compared to absorption contrast, in particular for fine tumor structures. This result was supported by images of human mastectomy samples that were acquired with a conventional detector. The optimal incident energy was higher in differential phase contrast than in absorption contrast when disregarding the setup design energy. Further, optimal weighting of the transmitted spectrum was found to have a weaker energy dependence than for absorption contrast. Taking the design energy into account yielded a superimposed maximum on both detectability as a function of incident energy, and on optimal weighting. Spectral material decomposition was not facilitated by phase contrast, but phase information may be used instead of spectral information.

Active matrix flat-panel imagers (AMFPIs) have become ubiquitous across a wide variety of medical x-ray imaging applications. While AMFPIs based on both direct and indirect detection of the incident radiation offer many advantages, their performance is limited by relatively modest system gain compared to electronic additive noise. The effects of this limitation upon imaging performance become particularly apparent at lower exposures and/or at higher spatial frequencies. One potential strategy for overcoming this limitation involves the use of a high gain photoconductor such as mercuric iodide (HgI₂) which has the potential to improve system gain by up to an order of magnitude compared to that provided by a-Se, the only photoconductor material presently used in direct detection AMFPIs. In this paper, preliminary results from an investigation of the performance of a prototype direct detection AMFPI employing a relatively thin layer of polycrystalline HgI₂ created through a screen-printing method and operated under mammographic irradiation conditions are presented. The results encourage further examination of this strategy to improve the performance of AMFPIs designed for mammography.

Effective detective quantum efficiency (eDQE) and effective noise equivalent quanta (eNEQ) were recently introduced to broaden the notion of DQE and NEQ by including system parameters such as focus blurring and system scatter rejection methods. This work investigates eDQE and eNEQ normalized for mean glandular dose (eNEQ_MGD) as a means to characterize and select optimal exposure parameters for a digital mammographic system. The eDQE was measured for three anode/filter combinations, with and without anti-scatter grid and for four thicknesses of poly(methylmethacrylate) (PMMA). The modulation transfer function used to calculate eDQE and eNEQ was measured from an edge positioned at 20,40,60,70 mm above the table top without scattering material in the beam. The grid-in eDQE results for all A/F settings were generally larger than those for grid-out. Contrarily, the eNEQ_MGD results were higher for grid-out than gridin, with a maximum difference of 61% among all A/F combinations and PMMA thicknesses. The W/Rh combination gave the highest eNEQMGD for all PMMA thicknesses compared to the other A/F combinations (for grid-in and grid-out), supporting the results of alternative methods (e.g. the signal difference to noise ratio method). The eNEQ_MGD was then multiplied with the contrast obtained from a 0.2mm Al square, resulting in a normalized quantity that was higher for the W/Rh combination than for the other A/F combinations. In particular, the results for the W/Rh combination were greater for the grid-in case. Furthermore, these results showed close agreement with a non-prewhitened match filter with eye response model observer (d') normalized for MGD.

We present a novel method for characterizing mammographic findings using spectral imaging without the use of contrast agent. Within a statistical framework, suspicious findings are analyzed to determine if they are likely to be benign cystic lesions or malignant tissue. To evaluate the method, we have designed a phantom where combinations of different tissue types are realized by decomposition into the material bases aluminum and polyethylene. The results indicate that the lesion size limit for reliable characterization is below 10 mm diameter, when quantum noise is the only considered source of uncertainty. Furthermore, preliminary results using clinical images are encouraging, but allow no conclusions with significance.

European Guidelines for quality control in digital mammography specify acceptable and achievable standards of image quality (IQ) in terms of threshold gold thickness using the CDMAM test object. However, there is little evidence relating such measurements to cancer detection. This work investigated the relationship between calcification detection and threshold gold thickness. An observer study was performed using a set of 162 amorphous selenium direct digital (DR) detector images (81 no cancer and 81 with 1-3 inserted calcification clusters). From these images four additional IQs were simulated: different digital detectors (computed radiography (CR) and DR) and dose levels. Seven observers marked and rated the locations of suspicious regions. DBM analysis of variances was performed on the JAFROC figure of merit (FoM) yielding 95% confidence intervals for IQ pairs. Automated threshold gold thickness (T_g) analysis was performed for the 0.25mm gold disc diameter on CDMAM images at the same IQs (16 images per IQ). T_g was plotted against FoM and a power law fitted to the data. There was a significant reduction in FoM for calcification detection for CR images compared with DR; FoM decreased from 0.83 to 0.63 (p≤0.0001). Detection was also sensitive to dose. There was a good correlation between FoM and T_g (R²=0.80, p<0.05), consequently threshold gold thickness was a good predictor of calcification detection at the same IQ. Since the majority of threshold gold thicknesses for the various IQs were above the acceptable standard despite large variations in calcification detection by radiologists, current EU guidelines may need revising.

Breast percent density (PD%), as measured mammographically, is one of the strongest known risk factors for breast cancer. While the majority of studies to date have focused on PD% assessment from digitized film mammograms, digital mammography (DM) is becoming increasingly common, and allows for direct PD% assessment at the time of imaging. This work investigates the accuracy of a generalized linear model-based (GLM) estimation of PD% from raw and postprocessed digital mammograms, utilizing image acquisition physics, patient characteristics and gray-level intensity features of the specific image. The model is trained in a leave-one-woman-out fashion on a series of 81 cases for which bilateral, mediolateral-oblique DM images were available in both raw and post-processed format. Baseline continuous and categorical density estimates were provided by a trained breast-imaging radiologist. Regression analysis is performed and Pearson's correlation, r, and Cohen's kappa, κ, are computed. The GLM PD% estimation model performed well on both processed (r=0.89, p<0.001) and raw (r=0.75, p<0.001) images. Model agreement with radiologist assigned density categories was also high for processed (κ=0.79, p<0.001) and raw (κ=0.76, p<0.001) images. Model-based prediction of breast PD% could allow for a reproducible estimation of breast density, providing a rapid risk assessment tool for clinical practice.

The aim of the present work was to develop a method for simulating breast lesions in digital mammographic images. Based on the visual appearance of real masses, three dimensional masses were created using a 3D random walk method where the choice of parameters (number of walks and number of steps) enables one to control the appearance of the simulated structure. This work is the first occasion that the random walk results have been combined with a model of digital mammographic imaging systems. This model takes into account appropriate physical image acquisition processes representing a particular digital X-ray mammography system. The X-ray spectrum, local glandularity above the insertion site and scatter were all taken account during the insertion procedure. A preliminary observer study was used to validate the realism of the masses. Seven expert readers each viewed 60 full field mammograms and rated the realism of the masses they contained. Half of the images contained real, histologically-confirmed masses, and half contained simulated lesions. The ROC analysis of the study (average AUC of 0.58±0.06) suggests that, on the average, there is evidence that the radiologists could distinguish, somewhat, between real and simulated masses.

The diagnostic quality of phase-contrast computed tomography (PCCT) is one the unexplored areas in medical imaging; at the same time, it seems to offer the opportunity as a fast and highly sensitive diagnostic tool. Conventional computed tomography (CT) has had an enormous impact on medicine, while it is limited in soft-tissue contrast. One example that portrays this challenge is the differentiation between benign and malignant renal cysts. In this work we report on a feasibility study to determine the usefulness of PCCT in differentiation of renal cysts. A renal phantom was imaged with a grating-based PCCT system consisting of a standard rotating anode x-ray tube (40 kV, 70 mA) and a Pilatus II photoncounting detector (pixel size: 172 μm). The phantom is composed of a renal equivalent soft-tissue and cystic lesions grouped in non-enhancing cyst and hemorrhage series and an iodine enhancing series. The acquired projection images (absorption and phase-contrast) are reconstructed with a standard filtered backprojection algorithm. For evaluation both reconstructions are compared in respect to contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), and subjective image quality. We found that with PCCT a significantly improved differentiation between hemorrhage renal cysts from contrast enhancing malignant cysts is possible. If comparing PCCT and CT with respect to CNR and SNR, PCCT shows significant improvements. In conclusion, PCCT has the potential to improve the diagnostics and characterization of renal cysts without using any contrast agents. These results in combination with a non-synchrotron setup indicate a future paradigm shift in diagnostic computed tomography.

X-ray tomography of small animals is an important tool for medical research. For high-resolution x-ray imaging of few-cm-thick samples such as, e.g., mice, high-brightness x-ray sources with energies in the few-10-keV range are required. In this paper we perform the first small-animal imaging and tomography experiments using liquid-metal-jet-anode x-ray sources. This type of source shows promise to increase the brightness of microfocus x-ray systems, but present sources are typically optimized for an energy of 9 keV. Here we describe the details of a high-brightness 24-keV electron-impact laboratory microfocus x-ray source based on continuous operation of a heated liquid-In/Ga-jet anode. The source normally operates with 40 W of electron-beam power focused onto the metal jet, producing a 7×7 μm² FWHM x-ray spot. The peak spectral brightness is 4 × 10⁹ photons / ( s × mm² × mrad² × 0.1%BW) at the 24.2 keV In K_α line. We use the new In/Ga source and an existing Ga/In/Sn source for high-resolution imaging and tomography of mice.

Carbon nanotube (CNT) micro-focus x-ray tubes have been demonstrated as a novel technology for in-vivo small animal imaging. It enables simultaneous respiratory and cardiac gated prospective CT imaging of free breathing animals with high temporal resolution. Operating the micro-focus CNT x-ray source at high power is required to achieve high temporal resolution. The thermal loading of the anode focal spot is a limiting factor in determining the maximum power of an x-ray tube. In this paper, we developed a reliable simulation model to quantitatively analyze the anode heat load of the CNT x-ray source operating in both DC and pulse modes. The anode temperature distribution is simulated using finite element analysis. The model is validated by comparing simulation results for the micro-focus x- ray tube with reported experimental results. We investigated the relationship between the maximum power and the effective focal spot size for CNT micro-CT system running in both DC and pulse modes. Our results show that when operating in pulse mode, the maximum power of the CNT x-ray source can be significantly higher than when operating in DC mode. In DC mode, we found that the maximum power scales non-linearly with the effective focal spot size as P(in W) = (0.25/ sin θ+1.6)f^0.73 _s (in μm), where 1/sin θ is the projection factor for a given anode angle θ. However, in pulse mode the maximum power linearly increases with the effective focal spot size asP(in W) = (0.20/ sin θ+0.35)f_s(in μm), and is significantly higher than that in the DC mode. This implies that it is feasible to improve the micro-CT temporal resolution further without sacrificing the image quality. The simulation method developed here also enables us to analyze the thermal loading of the other CNT x-ray sources for other applications, such as the stationary digital breast tomosynthesis scanner and the CNT microbeam radiation therapy system.

Computerized phantoms are finding an increasingly important role in medical imaging research. With the ability to simulate various imaging conditions, they offer a practical means with which to quantitatively evaluate and improve imaging devices and techniques. This is especially true in CT due to the high radiation levels involved with it. Despite their utility, due to the time required to develop them, only a handful of computational models currently exist of varying detail. Most phantoms available are limited to 3D and not capable of modeling patient motion. We have previously developed a technique to rapidly create highly detailed 4D extended cardiac-torso (XCAT) phantoms based on patient CT data [1]. In this study, we utilize this technique to generate 58 new adult XCAT phantoms to be added to our growing library of virtual patients available for imaging research. These computerized patients provide a valuable tool for investigating imaging devices and the effects of anatomy and motion in imaging. They also provide the essential tools to investigate patient-specific dose estimation and optimization for adults undergoing CT procedures.

Phantom equivalents of different human anatomical parts are routinely used for imaging system evaluation or dose calculations. The various recommendations on the generic phantom structure given by organizations such as the AAPM, are not always accurate when evaluating a very specific task. When we compared the AAPM head phantom containing 3 mm of aluminum to actual neuro-endovascular image guided interventions (neuro-EIGI) occurring in the Circle of Willis, we found that the system automatic exposure rate control (AERC) significantly underestimated the x-ray parameter selection. To build a more accurate phantom for neuro-EIGI, we reevaluated the amount of aluminum which must be included in the phantom. Human skulls were imaged at different angles, using various angiographic exposures, at kV's relevant to neuro-angiography. An aluminum step wedge was also imaged under identical conditions, and a correlation between the gray values of the imaged skulls and those of the aluminum step thicknesses was established. The average equivalent aluminum thickness for the skull samples for frontal projections in the Circle of Willis region was found to be about 13 mm. The results showed no significant changes in the average equivalent aluminum thickness with kV or mAs variation. When a uniform phantom using 13 mm aluminum and 15 cm acrylic was compared with an anthropomorphic head phantom the x-ray parameters selected by the AERC system were practically identical. These new findings indicate that for this specific task, the amount of aluminum included in the head equivalent must be increased substantially from 3 mm to a value of 13 mm.

X-ray fluorescence molecular imaging (XFMI) can be a potential alternative to existing molecular imaging modalities providing high sensitivity and good spatial resolution. However, high sensitivity at a few tens of μg/mL can be reached only with monochromatic synchrotron x-rays; in typical laboratory setting using conventional x-ray sources XFMI has been reported to reach only about 10 mg/mL sensitivity. In this paper, we demonstrated the feasibility of simultaneously detecting x-ray fluorescence signals from a mouse-sized object containing iodine and indium solutions at 50 μg/mL concentration using a carbon nanotube (CNT) x-ray source. XFMI has the high potential to provide molecular imaging capability in small-animal models with high sensitivity, high spatial and temporal resolution, high multiplexing capacity, and at low radiation dose.

X-ray Luminescence CT (XLCT) is a hybrid imaging modality combining x-ray and optical imaging in which x-ray luminescent nanophosphors (NPs) are used as emissive imaging probes. NPs are easily excited using common CT energy x-ray beams, and the NP luminescence is efficiently collected using sensitive light-based detection systems. XLCT can be recognized as a close analog to fluorescence diffuse optical tomography (FDOT). However, XLCT has remarkable advantages over FDOT due to the substantial excitation penetration depths provided by x-rays relative to laser light sources, long-term photo-stability of NPs, and the ability to tune NP emission within the NIR spectral window. Since XCLT uses an x-ray pencil beam excitation, the emitted light can be measured and back-projected along the x-ray path during reconstruction, where the size of the x-ray pencil beam determines the resolution for XLCT. In addition, no background signal competes with NP luminescence (i.e., no auto fluorescence) in XLCT. Currently, no small animal XLCT system has been proposed or tested. This paper investigates an XLCT system built and integrated with a dual source micro-CT system. A novel sampling paradigms that results in more efficient scanning is proposed and tested via simulations. Our preliminary experimental results in phantoms indicate that a basic CT-like reconstruction is able to recover a map of the NP locations and differences in NP concentrations. With the proposed dual source system and faster scanning approaches, XLCT has the potential to revolutionize molecular imaging in preclinical studies.

Background: Micro-computed tomography offers numerous advantages for small animal imaging, including the ability to monitor the same animals throughout a longitudinal study. However, concerns are often raised regarding the effects of x-ray dose accumulated over the course of the experiment. In this study, we scan C57BL/6 mice multiple times per week for six weeks, to determine the effect of the cumulative dose on pulmonary tissue at the end of the study. Methods/Results: C57BL/6 male mice were split into two groups (irradiated group=10, control group=10). The irradiated group was scanned (80kVp/50mA) each week for 6 weeks; the weekly scan session had three scans. This resulted in a weekly dose of 0.84 Gy, and a total study dose of 5.04 Gy. The control group was scanned on the final week. Scans from weeks 1 and 6 were reconstructed and analyzed: overall, there was no significant difference in lung volume or lung density between the control group and the irradiated group. Similarly, there were no significant differences between the week 1 and week 6 scans in the irradiated group. Histological samples taken from excised lung tissue also showed no evidence of inflammation or fibrosis in the irradiated group. Conclusion: This study demonstrates that a 5 Gy x-ray dose accumulated over six weeks during a longitudinal micro-CT study has no significant effects on the pulmonary tissue of C57BL/6 mice. As a result, the many advantages of micro- CT imaging, including rapid acquisition of high-resolution, isotropic images in free-breathing mice, can be taken advantage of in longitudinal studies without concern for negative dose-related effects.

We are investigating a liquid xenon (LXe) gamma ray detector-based PET system for small animals. The proposed system consists of 12 modules arranged into a ring. Each detector module is a trapezoidal LXe time projection chamber (TPC) viewed by two arrays of large area avalanche photodiodes (LAAPD). We developed a Geant4-based Monte Carlo code to model the LXe PET system and study its imaging performance. Events depositing energy in multiple locations were reconstructed with a Compton reconstruction algorithm. The simulated data were stored in a list-mode file and reconstructed with the maximum likelihood expectation maximization iterative algorithm (MLEM). Simulation results indicate an absolute sensitivity at the center of the field of view (FOV) of 12.6% and a 3D position resolution ≤ 0.8 mm (FWHM) throughout the FOV. A simulated image of a micro-Derenzo phantom shows that rods of 0.6 mm diameter are visible.

Dual energy imaging enables material decomposition and requires attenuation measurements with at least two different energies. Today's clinically available implementations use two separate exposures, at a low and high tube voltage (dual kV). Photon counting x-ray detectors (PCXDs) are an alternative technology that takes advantage of an x-ray source's broad spectrum by counting the number of transmitted photons at each energy from a single exposure. The richness of the information contained in these measurements can depend heavily on the detector's energy response, itself dependent on count rate. We compare the material decomposition precision of dual kV with energy integrating detectors to that of realistic PCXDs. We model the three primary effects that degrade PCXD performance: count rate limitations, energy resolution, and spectrum tailing. For example, the high flux rates required for clinical imaging pose a serious challenge for PCXDs. The Cram´er-Rao Lower Bound is used to predict the best possible material decomposition variance as a function of these detector imperfections. For dual kV and photon counting, we determined the optimal kV, mAs, and filtration for a broad range of imaging tasks, subject to dose and tube power constraints. We found that a well-optimized dual kV protocol performs on par with the estimated performance of today's PCXDs. For dual kV protocols, it is helpful to increase the energy separation between the spectra by increasing the kV separation and adding filtration. For PCXDs, the detector's count rate capabilities must be increased and the spectrum tailing reduced for photon counting to become a competitive technology at the high intensities of clinical imaging.

μWe introduce a novel hybrid prototype scanner built to explore benefits of the quantum-counting technique in the context of clinical CT. The scanner is equipped with two measurement systems. One is a CdTe-based counting detector with 22cm field-of-view. Its revised ASIC architecture allows configuration of the counter thresholds of the 225m small sub-pixels in chess patterns, enabling data acquisition in four energy bins or studying high-flux scenarios with pile-up trigger. The other one is a conventional GOS-based energy-integrating detector from a clinical CT scanner. The integration of both detection technologies in one CT scanner provides two major advantages. It allows direct comparison of image quality and contrast reproduction as well as instantaneous quantification of the relative dose usage and material separation performance achievable with counting techniques. In addition, data from the conventional detector can be used as complementary information during reconstruction of the images from the counting device. In this paper we present CT images acquired with the hybrid prototype scanner, illustrate its underlying conceptual methods, and provide first experimental results quantifying clinical benefits of quantum-counting CT.

We have developed an ultra-fast photon-counting energy-resolved application specific integrated circuit (ASIC) for spectral computed tomography (CT). A comprehensive characterization has been carried out to investigate the performance of the ASIC in terms of energy resolution under different photon flux rates and the count rate linearity in photon-counting mode. An energy resolution of 4.7 % has been achieved for 59.5 keV low flux photons. The count rate performance of the ASIC was measured with 120 kVp polychromatic x-rays. The results indicate that the count rate linearity can be kept for a flux rate up to 150 Mphotons s^-1 mm^-2 with retained energy information, and this value is increased to be 250 Mphotons s^-1 mm^-2 in photon-counting mode.

Photon counting statistics with pulse pileup effects (PPE) have been investigated for detection schemes with two assumptions: a fixed deadtime (i.e., non-paralyable and paralyzable detection schemes) and a delta pulse shape. Analytical expressions have been developed which shed light on interesting findings: (1) the variance becomes smaller than mean with PPE; and (2) the variance-to-mean ratio (VMR) of narrow energy windows remains very close to 1. In this study, we experimentally investigate VMR with PPE with a variable deadtime (i.e., pulse height analysis) and bipolar and unipolar pulse shapes with a long tail in addition to the above cases. We will use Monte Carlo simulation for a systematic study and a physical photon counting detector to confirm the results.

The prospect of single-photon counting (SPC) detectors for x-ray image acquisition has identified a number of potential benefits over the usual approach in which the detector signal is proportional to total energy deposited during an image-acquisition interval. While a generalized approach to describing transfer of signal and noise through medical imaging systems has been developed over the past several years, in which image-forming processes are represented in terms in cascades of amplified point processes, theis approach describes conventional detectors. We extend cascaded systems analysis (CSA) to the description of signal and noise in SPC x-ray detectors. Expressions describing transfer of the mean value and noise power spectrum (NPS) through a signal thresholding stage are derived and used to describe the effects of conversion to secondary quanta, collection of secondary quanta, additive noise, and thresholding on the zero-frequency DQE of a hypothetical flat-panel SPC detector. We found that when the mean number of secondary quanta collected is 2 to 3 times greater than the threshold value, the zero-frequency DQE for an SPC detector was 5-10% greater than that of a conventionaldetector. We also found that when additive noise is not thresholded out, DQE(0) can be degraded 30-50 %. However, when thresholding techniques are implemented, in some situations this reduction can be largely recovered. It is concluded that in some situations SPC x-ray imaging has the potential to provide equal or better DQE values than conventional energy-integrating detectors.

The x-ray spectrum recorded by a photon-counting x-ray detector (PCXD) is distorted due to the following physical effects which are independent of the count rate: finite energy-resolution, Compton scattering, charge-sharing, and Kescape. If left uncompensated, the spectral response (SR) of a PCXD due to the above effects will result in image artifacts and inaccurate material decomposition. We propose a new SR compensation (SRC) algorithm using the sinogram restoration approach. The two main contributions of our proposed algorithm are: (1) our algorithm uses an efficient conjugate gradient method in which the first and second derivatives of the cost functions are directly calculated analytically, whereas a slower optimization method that requires numerous function evaluations was used in other work; (2) our algorithm guarantees convergence by combining the non-linear conjugate gradient method with line searches that satisfy Wolfe conditions, whereas the algorithm in other work is not backed by theorems from optimization theory to guarantee convergence. In this study, we validate the performance of the proposed algorithm using computer simulations. The bias was reduced to zero from 11%, and image artifacts were removed from the reconstructed images. Quantitative K-edge imaging in possible only when SR compensation is done.

Energy-resolving photon-counting detectors have the potential for improved material decomposition compared to dual-kVp approaches. However, material decomposition accuracy is limited by the nonideal spectral response of the detectors. This work proposes an empirical method for correcting the nonideal spectral response, including spectrum-tailing effects. Unlike previous correction methods which relied on synchrotron measurements, the proposed method can be performed on the scanner. The proposed method estimates a spectral-response matrix by performing x-ray projection measurements through a range of known thicknesses of two or more calibration materials. Once estimated, the spectral-response matrix is incorporated into conventional material decomposition algorithms. A simulation study investigated preliminary feasibility of the proposed method. The spectral-response matrix was estimated using simulated projection measurements through PMMA, aluminum, and gadolinium. An energy-resolved acquisition of a thorax phantom with gadolinium in the blood pool was simulated assuming a five-bin detector with realistic spectral response. Energy-bin data was decomposed into Compton, photoelectric, and gadolinium basis projections with and without the proposed correction method. Basis images were reconstructed by filtered backprojection. Results demonstrated that the nonideal spectral response reduced the ability to distinguish gadolinium from materials such as bone, while images reconstructed with the proposed correction method successfully depicted the contrast agent. The proposed correction method reduced errors from 9% to 0.6% in the Compton image, 90% to 0.6% in the photoelectric image and from 40% to 6% in the gadolinium image when using a three-material calibration. Overall, results support feasibility of the proposed spectral-response correction method.

Limitations to the spatial resolution of current digital x-ray systems are bounded by the physical characteristics of the xray detector. However, the need to image smaller structures provides motivation to develop high-resolution x-ray detector systems for use with computed radiographic, and tomographic x-ray systems. We report the implementation of a tilted detector technique (TDT) to attain near isotropic resolution enhancement by combining two orthogonal image views, acquired with existing detector hardware tilted at a fixed angle. Images were acquired using a ceiling-mounted x-ray unit (Proteus XR/a, GE Medical Systems, 50kVp, 250mAs). Images were digitized using a Fujifilm Capsula X CR system, from a 35×43cm detector cassette placed on an angulated stand, featuring a 3520×4280 image matrix with an in-plane pixel spacing of 0.1mm. Three images were acquired: two for use with our TDT; and one for comparison, with no detector tilt. Performance was determined by using two line-pair phantoms (Models 07-521 and 07-533, Nuclear Associates) placed orthogonally to each other in the field of view. Custom software corrected for perspective distortion, co-registered and combined the tilted-detector images into a single higher-resolution image. Following unwarping and co-registration, the limiting spatial resolution of an image obtained via the weighted combination of the two orthogonal views (8 lp/mm) is found to be superior to that of a single view acquired with no detector tilt (5 lp/mm). This novel technique shows significant improvement in the spatial resolution of x-ray image acquisitions, using existing x-ray components and detector hardware.

The detective quantum efficiency (DQE) is widely accepted as a primary measure of x-ray detector performance in the scientific community. A standard method for measuring the DQE, based on IEC 62220-1, requires the system to have a linear response meaning that the detector output signals are proportional to the incident x-ray exposure. However, many systems have a non-linear response due to characteristics of the detector, or post processing of the detector signals, that cannot be disabled and may involve unknown algorithms considered proprietary by the manufacturer. For these reasons, the DQE has not been considered as a practical candidate for routine quality assurance testing in a clinical setting. In this article we described a method that can be used to measure the DQE of both linear and non-linear systems that employ only linear image processing algorithms. The method was validated on a Cesium Iodide based flat panel system that simultaneously stores a raw (linear) and processed (non-linear) image for each exposure. It was found that the resulting DQE was equivalent to a conventional standards-compliant DQE with measurement precision, and the gray-scale inversion and linear edge enhancement did not affect the DQE result. While not IEC 62220-1 compliant, it may be adequate for QA programs.

Intracranial aneurysm (IA) embolization using Gugliemi Detachable Coils (GDC) under x-ray fluoroscopic guidance is one of the most important neuro-vascular interventions. Coil deposition accuracy is key and could benefit substantially from higher resolution imagers such as the micro-angiographic fluoroscope (MAF). The effect of MAF guidance improvement over the use of standard Flat Panels (FP) is challenging to assess for such a complex procedure. We propose and investigate a new metric, inter-frame cross-correlation sensitivity (CCS), to compare detector performance for such procedures. Pixel (P) and histogram (H) CCS's were calculated as one minus the cross-correlation coefficients between pixel values and histograms for the region of interest at successive procedure steps. IA treatment using GDC's was simulated using an anthropomorphic head phantom which includes an aneurysm. GDC's were deposited in steps of 3 cm and the procedure was imaged with a FP and the MAF. To measure sensitivity to detect progress of the procedure by change in images of successive steps, an ROI was selected over the aneurysm location and pixel-value and histogram changes were calculated after each step. For the FP, after 4 steps, the H and P CCSs between successive steps were practically zero, indicating that there were no significant changes in the observed images. For the MAF, H and P CCSs were greater than zero even after 10 steps (30 cm GDC), indicating observable changes. Further, the proposed quantification method was applied for evaluation of seven patients imaged using the MAF, yielding similar results (H and P CCSs greater than zero after the last GDC deposition). The proposed metric indicates that the MAF can offer better guidance during such procedures.

Due to the need for high-resolution angiographic and interventional vascular imaging, a Micro-Angiographic Fluoroscope (MAF) detector with a Control, Acquisition, Processing, and Image Display System (CAPIDS) was installed on a detector changer, which was attached to the C-arm of a clinical angiographic unit at a local hospital. The MAF detector provides high-resolution, high-sensitivity, and real-time imaging capabilities and consists of a 300 μm thick CsI phosphor, a dual stage micro-channel plate light image intensifier (LII) coupled to a fiber optic taper (FOT), and a scientific grade frame-transfer CCD camera, providing an image matrix of 1024×1024 35 μm effective square pixels with 12 bit depth. The changer allows the MAF region-of-interest (ROI) detector to be inserted in front of the Image Intensifier (II) when higher resolution is needed during angiographic or interventional vascular imaging procedures, e.g. endovascular stent deployment. The CAPIDS was developed and implemented using Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) software and provides a user-friendly interface that enables control of several clinical radiographic imaging modes of the MAF including: fluoroscopy, roadmapping, radiography, and digital-subtraction-angiography (DSA). The total system has been used for image guidance during endovascular image-guided interventions (EIGI) for diagnosing and treating artery stenoses and aneurysms using self-expanding endovascular stents and coils in fifteen patient cases, which have demonstrated benefits of using the ROI detector. The visualization of the fine detail of the endovascular devices and the vessels generally gave the clinicians confidence on performing neurovascular interventions and in some instances contributed to improved interventions.

A novel cone-beam CT (CBCT) system has been developed with promising capabilities for musculoskeletal imaging (e.g., weight-bearing extremities and combined radiographic / volumetric imaging). The prototype system demonstrates diagnostic-quality imaging performance, while the compact geometry and short scan orbit raise new considerations for scatter management and dose characterization that challenge conventional methods. The compact geometry leads to elevated, heterogeneous x-ray scatter distributions - even for small anatomical sites (e.g., knee or wrist), and the short scan orbit results in a non-uniform dose distribution. These complex dose and scatter distributions were investigated via experimental measurements and GPU-accelerated Monte Carlo (MC) simulation. The combination provided a powerful basis for characterizing dose distributions in patient-specific anatomy, investigating the benefits of an antiscatter grid, and examining distinct contributions of coherent and incoherent scatter in artifact correction. Measurements with a 16 cm CTDI phantom show that the dose from the short-scan orbit (0.09 mGy/mAs at isocenter) varies from 0.16 to 0.05 mGy/mAs at various locations on the periphery (all obtained at 80 kVp). MC estimation agreed with dose measurements within 10-15%. Dose distribution in patient-specific anatomy was computed with MC, confirming such heterogeneity and highlighting the elevated energy deposition in bone (factor of ~5-10) compared to soft-tissue. Scatter-to-primary ratio (SPR) up to ~1.5-2 was evident in some regions of the knee. A 10:1 antiscatter grid was found earlier to result in significant improvement in soft-tissue imaging performance without increase in dose. The results of MC simulations elucidated the mechanism behind scatter reduction in the presence of a grid. A ~3-fold reduction in average SPR was found in the MC simulations; however, a linear grid was found to impart additional heterogeneity in the scatter distribution, mainly due to the increase in the contribution of coherent scatter with increased spatial variation. Scatter correction using MC-generated scatter distributions demonstrated significant improvement in cupping and streaks. Physical experimentation combined with GPU-accelerated MC simulation provided a sophisticated, yet practical approach in identifying low-dose acquisition techniques, optimizing scatter correction methods, and evaluating patientspecific dose.

Clinical applications of CBCT imaging are still limited by excessive imaging dose from repeated scans and poor image quality mainly due to scatter contamination. Compressed sensing (CS) reconstruction algorithms have shown promises in recovering faithful signals from low-dose projection data, but do not serve well the needs of accurate CBCT imaging if effective scatter correction is not in place. Scatter can be accurately measured and removed using measurement-based methods. However, in conventional FDK reconstruction, these approaches are considered unpractical since they require multiple scans or moving the beam blocker during the data acquisition to compensate for the inevitable primary loss. In this work, we combine the measurement-based scatter correction and CS-based iterative reconstruction algorithm, such that scatter-free images can be obtained from low-dose data. We lower the CBCT dose by reducing the projection number and inserting lead strips between the x-ray source and the object. The insertion of lead strips also enables scatter measurement on the measured samples inside the strip shadows. CS-based iterative reconstruction is finally carried out to obtain scatter-free and low-dose CBCT images. Simulation studies are designed to optimize the lead strip geometry for a certain dose reduction ratio. After optimization, our approach reduces the CT number error from over 220HU to below 5HU on the Shepp-Logan phantom, with a dose reduction of ~80%. With the same dose reduction and the optimized method parameters, the CT number error is reduced from 242HU to 20HU in the selected region of interest on Catphan©600 phantom.

The multi-source inverse-geometry CT(MS-IGCT) system is composed of multiple sources and a small 2D detector array. An experimental MS-IGCT system was built and we report initial results with 2×4 x-ray sources, a 75 mm inplane field-of-view (FOV) and 160 mm z-coverage in a single gantry rotation. To evaluate the system performance, experimental data were acquired from several phantoms and a post-mortem rat. Before image reconstruction, geometric calibration, data normalization, beam hardening correction and detector spectral calibration were performed. For reconstruction, the projection data were rebinned into two full cone beam data sets, and the FDK algorithm was used. The reconstructed volumes from the upper and lower source rows shared an overlap volume which was combined in image space. The reconstructed images of the uniform cylinder phantom showed good uniformity of the reconstructed values without any artifacts. The rat data were also reconstructed reliably. The initial experimental results from this rotating-gantry MS-IGCT system demonstrated its ability to image a complex anatomical object without any significant image artifacts and to ultimately achieve large volumetric coverage in a single gantry rotation.

Between 2006 and 2008, the business volume of the top 20 orthopedic manufacturers increased by 30% to about $35 Billion. Similar growth rates could be observed in the market of neurological devices, which went up in 2009 by 10.9% to a volume of $2.2 Billion in the US and by 7.0% to 500 Million in Europe.* These remarkable increases are closely connected to the fact that nowadays, many medical procedures, such as implantations in osteosynthesis or the placement of stents in neuroradiology can be performed using minimally-invasive approaches. Such approaches require elaborate interoperative imaging technology. C-arm based tomographic X-ray region-of-interest (ROI) tomography can deliver suitable imaging guidance in these circumstances: it can offer 3D information in desired patient regions at reasonably low X-ray dose. Tomographic ROI reconstruction, however, is in general challenging since projection images might be severely truncated. Recently, a novel, truncation-robust algorithm (ATRACT) has been suggested for 3D C-arm ROI imaging. In this paper, we report for the first time on the performance of ATRACT for reconstruction from real, angiographic C-arm data. Our results indicate that the resulting ROI image quality is suitable for intraoperative imaging. We observe only little differences to the images from a non-truncated acquisition, which would necessarily require significantly more X-ray dose.

While the Medtronic O-arm was developed for image-guidance applications during orthopedic procedures, it has potential to assist in cardiac surgical and electrophysiological applications; the purpose of this study was to evaluate the feasibility of using a mobile conebeam imaging system (O-arm) for gated cardiac imaging. In an in vivo study (two pigs), projection data from four independently acquired breath-held scans were combined to obtain cardiac gated 3D images. Projection images were acquired during the infusion of contrast agent and while tracking the ECG. Both standard and high-definition modes of the O-arm were evaluated. Projection data were retrospectively combined to generate images corresponding to systole and diastole; different acceptance windows were investigated. The contrast to noise ratio (CNR) between blood and myocardium was compared for the different gating strategies. Gated cardiac images were successfully reconstructed with as few as two scans combined (CNR = 2.5) and a window of 200 ms. Improved image quality was achieved when selecting views based on the minimum time from the selected phase point in the cardiac cycle, rather than a fixed window; in this case the effective temporal window increased to 475 ms for two scans. The O-arm has the potential to be used as a mobile cardiac imaging system, capable of three-dimensional imaging.

C-arm based tomographic 3D imaging is applied in an increasing number of minimal invasive procedures. Due to the limited acquisition speed for a complete projection data set required for tomographic reconstruction, breathing motion is a potential source of artifacts. This is the case for patients who cannot comply breathing commands (e.g. due to anesthesia). Intra-scan motion estimation and compensation is required. Here, a scheme for projection based local breathing motion estimation is combined with an anatomy adapted interpolation strategy and subsequent motion compensated filtered back projection. The breathing motion vector is measured as a displacement vector on the projections of a tomographic short scan acquisition using the diaphragm as a landmark. Scaling of the displacement to the acquisition iso-center and anatomy adapted volumetric motion vector field interpolation delivers a 3D motion vector per voxel. Motion compensated filtered back projection incorporates this motion vector field in the image reconstruction process. This approach is applied in animal experiments on a flat panel C-arm system delivering improved image quality (lower artifact levels, improved tumor delineation) in 3D liver tumor imaging.

In recent years, iterative image reconstruction algorithms have received much interest in x-ray CT imaging. Images reconstructed by the conventional filtered backprojection algorithm are often used as seed images to start the iterations. This paper presents a new consistency property of the measured CT projection data and the forward projected data from a motion contaminated image reconstructed using an analytical image reconstruction algorithm. It is theoretically proven and numerically validated that, when the measured projection data is not redundant, the measured projection data is consistent with the forward projected data of a reconstructed image using analytical image reconstruction algorithms, no matter whether motion artifacts are present in the image or not. However, when there is redundancy in the measured projection data, the consistency depends on the choice of weighting function used for the redundant data. The forward projected data is always consistent with those measured projections with the weight 1.0, no matter what weighting schemes are used. For the measured projection data with a weight smaller than 1.0, the forward projected data is consistent with the weighted sum of redundantly measured projection data. With this new property, some potential issues of directly using FBP images as seed images for iterative algorithms are discussed.

The dose efficiency of dual energy imaging can be improved if the spectra are filtered to increase spectral separation. Our preliminary simulations showed that a fixed Gd filter can be efficacious in rapid kVp-switching systems. We conducted physical experiments on a table top x-ray system to verify the performance improvement before moving forward to a real CT scanner. We chose a commercial Gd₂O₂S screen as our filter and used an acrylic-copper step wedge phantom. Data were collected at 70 and 125 kVp, with and without the filter. The tube current was adjusted to make the exposure rate with and without the filter to be roughly the same. The data were decomposed into basis material images and the variance of the decomposition was measured for each acrylic-copper thickness pair. Simulations were done with the same experimental settings for comparison and validation. The experiments verified that a Gd filter can reduce the variance at fixed dose. The variance reduction is monotonically stronger as the object becomes more attenuating. This study demonstrates the potential of fixed Gd filtration to improve the dose efficiency and material decomposition precision for rapid kVp-switching dual energy systems.

While the imaging protocol determines radiation dose and image quality, it is difficult to find the lowest dose protocol (kVp, mAs, filtration) that provides appropriate diagnostic quality images. Recently, we developed a method for retrospectively synthesizing CT scans of arbitrary protocols using a previously acquired dual energy scan that relies on projection space data. Here, we propose a new variant of synthetic CT that only requires reconstructed dual energy images to simulate realistic images from arbitrary low dose protocols. Axial scans of a phantom were acquired on a GE CT750 HD system at 80 kVp and separately at 140 kVp, enabling material decomposition. Additional scans at 100 and 120 kVp and at different exposures were made to compare with synthesized results. Raw data for any spectrum can be estimated by forward transmission through the material decomposition images, but these have degraded spatial resolution. To avoid blurring, the synthesized image is represented as a linear combination (i.e., mixed or blended image) of the 80/140 kVp images. Noise with the correct statistics is then added so that the total noise matches the expected noise of the simulated protocol (estimated from forward transmission). For the studied object, the resulting synthesized images are indistinguishable from the actual images. Synthetic CT enables users to visualize the impact of protocol changes on the contrast and noise of CT scans, which can be used to develop lower dose protocols by demonstrating dose/noise/protocol trade-offs. Our new image domain implementation significantly increases the accessibility of synthetic CT to potential users.

Radiation dose from CT scans is an increasing health concern in the practice of radiology. Higher dose scans can produce clearer images with high diagnostic quality, but may increase the potential risk of radiation-induced cancer or other side effects. Lowering radiation dose alone generally produces a noisier image and may degrade diagnostic performance. Recently, CT dose reduction based on non-local means (NLM) filtering for noise reduction has yielded promising results. However, traditional NLM denoising operates under the assumption that image noise is spatially uniform noise, while in CT images the noise level varies significantly within and across slices. Therefore, applying NLM filtering to CT data using a global filtering strength cannot achieve optimal denoising performance. In this work, we have developed a technique for efficiently estimating the local noise level for CT images, and have modified the NLM algorithm to adapt to local variations in noise level. The local noise level estimation technique matches the true noise distribution determined from multiple repetitive scans of a phantom object very well. The modified NLM algorithm provides more effective denoising of CT data throughout a volume, and may allow significant lowering of radiation dose. Both the noise map calculation and the adaptive NLM filtering can be performed in times that allow integration with the clinical workflow.

The recent CT systems yield high spatial resolution in all directions of volumetric images in clinical routine. The quantitative characterization of the performance of CT systems is important for comparing the effects of different scan and reconstruction parameters, for comparing between different CT systems, and for evaluating the accuracy of size and density measurements of fine details in CT images. This paper presents a method to determine the modulation transfer function (MTF) in the scan plane obtained by CT system from profiles of human anatomical structures such as blood vessel measured by clinical measurement conditions without magnified reconstruction. MTF estimations are performed for cylindrical tube phantoms with three different diameters (1 mm, 2 mm, and 3 mm) injected by solution of contrast material and human blood vessels measured by the clinical measurement conditions. We demonstrate the potential usefulness of the method for estimating the MTF from blood vessel profiles measured in CT systems.

The optimization of dual-energy computed tomography (DE-CT) is challenged by the lack of a theoretical foundation for image quality. This work reports a cascaded systems analysis model that was used to derive signal and noise propagation in DE-CBCT in prevalent Fourier metrics such as the noise-power spectrum (NPS) and noise-equivalent quanta (NEQ). The model was validated in comparison to measurements of the 3D NPS and NEQ in DE-CBCT images acquired using an experimental imaging bench. Task-based detectability index was derived using DE-NPS and NEQ as an objective function in optimizing DE imaging parameters such as the dose allocation factor (D_A) and kVp pair. The resulting dose allocation optimization is in agreement with the practice of assigning more dose to the high-energy image (D_A < 0.5), and the model provides a quantitative basis for examining the optimal dose allocation as a function of total dose, kVp pair, the presence of electronics noise, and the imaging task. An example optimization is shown for a breast tumor detection task. Using DE decomposition to cancel fibroglandular tissue (rendering a DE-CBCT image of breast tumor against an adipose tissue background) and assuming a total dose of 15mGy, the optimal kVp pair is identified at [45, 105]kVp with DA=0.46. The model is sufficiently general for applications beyond this example, demonstrating utility in the optimization in a broad range of imaging parameters. The model provides a new, valuable framework for understanding the theoretical limits of DE-CBCT imaging performance and maximizing image quality while minimizing radiation dose.