Search

In x-ray computed tomography (CT), materials with different elemental compositions can have identical CT number values, depending on the mass density of each material and the energy of the detected x-ray beam. Differentiating and classifying different tissue types and contrast agents can thus be extremely challenging. In multienergy CT, one or more additional attenuation measurements are obtained at a second, third or more energy. This allows the differentiation of at least two materials. Commercial dual-energy CT systems (only two energy measurements) are now available either using sequential acquisitions of low- and high-tube potential scans, fast tube-potential switching, beam filtration combined with spiral scanning, dual-source, or dual-layer detector approaches. The use of energy-resolving, photon-counting detectors is now being evaluated on research systems. Irrespective of the technological approach to data acquisition, all commercial multienergy CT systems circa 2020 provide dual-energy data. Material decomposition algorithms are then used to identify specific materials according to their effective atomic number and/or to quantitate mass density. These algorithms are applied to either projection or image data. Since 2006, a number of clinical applications have been developed for commercial release, including those that automatically (a) remove the calcium signal from bony anatomy and/or calcified plaque; (b) create iodine concentration maps from contrast-enhanced CT data and/or quantify absolute iodine concentration; (c) create virtual non-contrast-enhanced images from contrast-enhanced scans; (d) identify perfused blood volume in lung parenchyma or the myocardium; and (e) characterize materials according to their elemental compositions, which can allow in vivo differentiation between uric acid and non-uric acid urinary stones or uric acid (gout) or non-uric acid (calcium pyrophosphate) deposits in articulating joints and surrounding tissues. In this report, the underlying physical principles of multienergy CT are reviewed and each of the current technical approaches are described. In addition, current and evolving clinical applications are introduced. Finally, the impact of multienergy CT technology on patient radiation dose is summarized.

Purpose When the scan field of view (SFOV) of a CT system is not large enough to enclose the entire cross-section of the patient, or the patient needs to be positioned partially outside the SFOV for certain clinical applications, truncation artifacts often appear in the reconstructed CT images. Many truncation artifact correction methods perform extrapolations of the truncated projection data based on certain a priori assumptions. The purpose of this work was to develop a novel CT truncation artifact reduction method that directly operates on DICOM images. Materials and Methods The blooming of pixel values associated with truncation was modeled using exponential decay functions, and based on this model, a discriminative dictionary was constructed to represent truncation artifacts and non-artifact image information in a mutually exclusive way. The discriminative dictionary consists of a truncation artifact sub-dictionary and a non-artifact sub-dictionary. The truncation artifact sub-dictionary contains 1000 atoms with different decay parameters, while the non-artifact sub-dictionary contains 1000 independent realizations of Gaussian white noise that are exclusive with the artifact features. By sparsely representing an artifact-contaminated CT image with this discriminative dictionary, the image was separated into a truncation artifact-dominated image and a complementary image with reduced truncation artifacts. The artifact-dominated image was then subtracted from the original image with an appropriate weighting coefficient to generate the final image with reduced artifacts. This proposed method was validated via physical phantom studies and retrospective human subject studies. Quantitative image evaluation metrics including the relative root mean square error (rRMSE) and the universal image quality index (UQI) were used to quantify the performance of the algorithm. Results For both phantom and human subject studies, truncation artifacts at the peripheral region of the SFOV were effectively reduced, revealing soft tissue and bony structure once buried in the truncation artifacts. For the phantom study, the proposed method reduced the relative RMSE from 15% (original images) to 11%, and improved the UQI from 0.34 to 0.80. Conclusion A discriminative dictionary representation method was developed to mitigate CT truncation artifacts directly in the DICOM image domain. Both phantom and human subject studies demonstrated that the proposed method can effectively reduce truncation artifacts without access to projection data. This article is protected by copyright. All rights reserved.

Purpose: The authors investigated the performance of a recently introduced 160-mm/256-row CT system for low dose quantitative myocardial perfusion (MP) imaging of the whole heart. This platform is equipped with a gantry capable of rotating at 280 ms per full cycle, a second generation of adaptive statistical iterative reconstruction (ASiR-V) to correct for image noise arising from low tube voltage potential/tube current dynamic scanning, and image reconstruction algorithms to tackle beam-hardening, cone-beam, and partial-scan effects. Methods: Phantom studies were performed to investigate the effectiveness of image noise and artifact reduction with a GE Healthcare Revolution CT system for three acquisition protocols used in quantitative CT MP imaging: 100, 120, and 140 kVp/25 mAs. The heart chambers of an anthropomorphic chest phantom were filled with iodinated contrast solution at different concentrations (contrast levels) to simulate the circulation of contrast through the heart in quantitative CT MP imaging. To evaluate beam-hardening correction, the phantom was scanned at each contrast level to measure the changes in CT number (in Hounsfield unit or HU) in the water-filled region surrounding the heart chambers with respect to baseline. To evaluate cone-beam artifact correction, differences in mean water HU between the central and peripheral slices were compared. Partial-scan artifact correction was evaluated from the fluctuation of mean water HU in successive partial scans. To evaluate image noise reduction, a small hollow region adjacent to the heart chambers was filled with diluted contrast, and contrast-to-noise ratio in the region before and after noise correction with ASiR-V was compared. The quality of MP maps acquired with the CT system was also evaluated in porcine CT MP studies. Myocardial infarct was induced in a farm pig from a transient occlusion of the distal left anterior descending (LAD) artery with a catheter-based interventional procedure. MP maps were generated from the dynamic contrast-enhanced (DCE) heart images taken at baseline and three weeks after the ischemic insult. Results: Their results showed that the phantom and animal images acquired with the CT platform were minimally affected by image noise and artifacts. For the beam-hardening phantom study, changes in water HU in the wall surrounding the heart chambers greatly reduced from >±30 to ≤ ± 5 HU at all kVp settings except one region at 100 kVp (7 HU). For the cone-beam phantom study, differences in mean water HU from the central slice were less than 5 HU at two peripheral slices with each 4 cm away from the central slice. These findings were reproducible in the pig DCE images at two peripheral slices that were 6 cm away from the central slice. For the partial-scan phantom study, standard deviations of the mean water HU in 10 successive partial scans were less than 5 HU at the central slice. Similar observations were made in the pig DCE images at two peripheral slices with each 6 cm away from the central slice. For the image noise phantom study, CNRs in the ASiR-V images were statistically higher (p < 0.05) than the non-ASiR-V images at all kVp settings. MP maps generated from the porcine DCE images were in excellent quality, with the ischemia in the LAD territory clearly seen in the three orthogonal views. Conclusions: The study demonstrates that this CT system can provide accurate and reproducible CT numbers during cardiac gated acquisitions across a wide axial field of view. This CT number fidelity will enable this imaging tool to assess contrast enhancement, potentially providing valuable added information beyond anatomic evaluation of coronary stenoses. Furthermore, their results collectively suggested that the 100 kVp/25 mAs protocol run on this CT system provides sufficient image accuracy at a low radiation dose (

Purpose: Noise characteristics of clinical multidetector CT (MDCT) systems can be quantified by the noise power spectrum (NPS). Although the NPS of CT has been extensively studied in the past few decades, the joint impact of the bowtie filter and object position on the NPS has not been systematically investigated. This work studies the interplay of these two factors on the two dimensional (2D) local NPS of a clinical CT system that uses the filtered backprojection algorithm for image reconstruction. Methods: A generalized NPS model was developed to account for the impact of the bowtie filter and image object location in the scan field-of-view (SFOV). For a given bowtie filter, image object, and its location in the SFOV, the shape and rotational symmetries of the 2D local NPS were directly computed from the NPS model without going through the image reconstruction process. The obtained NPS was then compared with the measured NPSs from the reconstructed noise-only CT images in both numerical phantom simulation studies and experimental phantom studies using a clinical MDCT scanner. The shape and the associated symmetry of the 2D NPS were classified by borrowing the well-known atomic spectral symbols s, p, and d, which correspond to circular, dumbbell, and cloverleaf symmetries, respectively, of the wave function of electrons in an atom. Finally, simulated bar patterns were embedded into experimentally acquired noise backgrounds to demonstrate the impact of different NPS symmetries on the visual perception of the object. Results: (1) For a central region in a centered cylindrical object, an s-wave symmetry was always present in the NPS, no matter whether the bowtie filter was present or not. In contrast, for a peripheral region in a centered object, the symmetry of its NPS was highly dependent on the bowtie filter, and both p-wave symmetry and d-wave symmetry were observed in the NPS. (2) For a centered region-ofinterest (ROI) in an off-centered object, the symmetry of its NPS was found to be different from that of a peripheral ROI in the centered object, even when the physical positions of the two ROIs relative to the isocenter were the same. (3) The potential clinical impact of the highly anisotropic NPS, caused by the interplay of the bowtie filter and position of the image object, was highlighted in images of specific bar patterns oriented at different angles. The visual perception of the bar patterns was found to be strongly dependent on their orientation. Conclusions: The NPS of CT depends strongly on the bowtie filter and object position. Even if the location of the ROI with respect to the isocenter is fixed, there can be different symmetries in the NPS, which depend on the object position and the size of the bowtie filter. For an isolated off-centered object, the NPS of its CT images cannot be represented by the NPS measured from a centered object.

Purpose: The introduction of a High-Resolution (Hi-Res) scan mode and another associated option that combines Hi-Res mode with the so-called High Definition (HD) reconstruction kernels (referred to as a Hi-Res/HD mode in this paper) in some multi-detector CT (MDCT) systems offers new opportunities to increase spatial resolution for some clinical applications that demand high spatial resolution. The purpose of this work was to quantify the in-plane spatial resolution along both the radial direction and tangential direction for the Hi-Res and Hi-Res/HD scan modes at different off-center positions. Methods: A technique was introduced and validated to address the signal saturation problem encountered in the attempt to quantify spatial resolution for the Hi-Res and Hi-Res/HD scan modes. Using the proposed method, the modulation transfer functions(MTFs) of a 64-slice MDCT system (Discovery CT750 HD, GE Healthcare) equipped with both Hi-Res and Hi-Res/HD modes were measured using a metal bead at nine different off-centered positions (0–16 cm with a step size of 2 cm); at each position, both conventional scans and Hi-Res scans were performed. For each type of scan and position, 80 repeated acquisitions were performed to reduce noise induced uncertainties in the MTF measurements. A total of 15 reconstruction kernels, including eight conventional kernels and seven HD kernels, were used to reconstructCTimages of the bead. An ex vivo animal study consisting of a bone fracture model was performed to corroborate the MTF results, as the detection of this high-contrast and high frequency task is predominantly determined by spatial resolution.Images of this animal model generated by different scan modes and reconstruction kernels were qualitatively compared with the MTF results. Results: At the centered position, the use of Hi-Res mode resulted in a slight improvement in the MTF; each HD kernel generated higher spatial resolution than its counterpart conventional kernel. However, the MTF along the tangential direction of the scan field of view (SFOV) was significantly degraded at off-centered positions, yet the combined Hi-Res/HD mode reduced this azimuthal MTF degradation. Images of the animal bone fracture model confirmed the improved spatial resolution at the off-centered positions through the use of the Hi-Res mode and HD kernels. Conclusions: The Hi-Res/HD scan improve spatial resolution of MDCT systems at both centered and off-centered positions.

Purpose: Phantom-based objective image quality assessment methods are widely used in the medical physics community. For a filtered backprojection (FBP) reconstruction-based linear or quasilinear imaging system, the use of this methodology is well justified. Many key image quality metrics acquired with phantom studies can be directly applied to in vivo human subject studies. Recently, a variety of image quality metrics have been investigated for model-based iterative image reconstruction (MBIR) methods and several novel characteristics have been discovered in phantom studies. However, the following question remains unanswered: can certain results obtained from phantom studies be generalized to in vivo animal studies and human subject studies? The purpose of this paper is to address this question. Methods: One of the most striking results obtained from phantom studies is a novel power-law relationship between noise variance of MBIR (σ2) and tube current-rotation time product (mAs): σ2 ∝ (mAs)−0.4 [K. Li et al., “Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance,” Med. Phys. 41, 041906 (15pp.) (2014)]. To examine whether the same power-law works for in vivo cases, experimental data from two types of in vivo studies were analyzed in this paper. All scans were performed with a 64-slice diagnostic CT scanner (Discovery CT750 HD, GE Healthcare) and reconstructed with both FBP and a MBIR method (Veo, GE Healthcare). An Institutional Animal Care and Use Committee-approved in vivo animal study was performed with an adult swine at six mAs levels (10–290). Additionally, human subject data (a total of 110 subjects) acquired from an IRB-approved clinical trial were analyzed. In this clinical trial, a reduced-mAs scan was performed immediately following the standard mAs scan; the specific mAs used for the two scans varied across human subjects and were determined based on patient size and clinical indications. The measurements of σ2 were performed at different mAs by drawing regions-of-interest (ROIs) in the liver and the subcutaneous fat. By applying a linear least-squares regression, the β values in the power-law relationship σ2 ∝ (mAs)−β were measured for the in vivo data and compared with the value found in phantom experiments. Results: For the in vivo swine study, an exponent of β = 0.43 was found for MBIR, and the coefficient of determination (R2) for the corresponding least-squares power-law regression was 0.971. As a reference, the β and R2 values for FBP were found to be 0.98 and 0.997, respectively, from the same study, which are consistent with the well-known σ2 ∝ (mAs)−1.0 relationship for linear CT systems. For the human subject study, the measured β values for the MBIR images were 0.41 ± 0.12 in the liver and 0.37 ± 0.12 in subcutaneous fat. In comparison, the β values for the FBP images were 1.04 ± 0.10 in the liver and 0.97 ± 0.12 in subcutaneous fat. The β values of MBIR and FBP obtained from the in vivo studies were found to be statistically equivalent to the corresponding β values from the phantom study within an equivalency interval of [− 0.1, 0.1] (p < 0.05); across MBIR and FBP, the difference in β was statistically significant (p < 0.05). Conclusions: Despite the nonlinear nature of the MBIR method, the power-law relationship, σ2 ∝ (mAs)−0.4, found from phantom studies can be applied to in vivo animal and human subject studies.

Purpose: For a given imaging task and patient size, the optimal selection of x-ray tube potential (kV) and tube current-rotation time product (mAs) is pivotal in achieving the maximal radiation dose reduction while maintaining the needed diagnostic performance. Although contrast-to-noise (CNR)-based strategies can be used to optimize kV/mAs for computed tomography (CT) imaging systems employing the linear filtered backprojection (FBP) reconstruction method, a more general framework needs to be developed for systems using the nonlinear statistical model-based iterative reconstruction (MBIR) method. The purpose of this paper is to present such a unified framework for the optimization of kV/mAs selection for both FBP- and MBIR-based CT systems. Methods: The optimal selection of kV and mAs was formulated as a constrained optimization problem to minimize the objective function, Dose(kV,mAs), under the constraint that the achievable detectability index d′(kV,mAs) is not lower than the prescribed value of d ℞ ′ for a given imaging task. Since it is difficult to analytically model the dependence of d′ on kV and mAs for the highly nonlinear MBIR method, this constrained optimization problem is solved with comprehensive measurements of Dose(kV,mAs) and d′(kV,mAs) at a variety of kV–mAs combinations, after which the overlay of the dose contours and d′ contours is used to graphically determine the optimal kV–mAs combination to achieve the lowest dose while maintaining the needed detectability for the given imaging task. As an example, d′ for a 17 mm hypoattenuating liver lesion detection task was experimentally measured with an anthropomorphic abdominal phantom at four tube potentials (80, 100, 120, and 140 kV) and fifteen mA levels (25 and 50–700) with a sampling interval of 50 mA at a fixed rotation time of 0.5 s, which corresponded to a dose (CTDI vol) range of [0.6, 70] mGy. Using the proposed method, the optimal kV and mA that minimized dose for the prescribed detectability level of d ℞ ′ = 16 were determined. As another example, the optimal kV and mA for an 8 mm hyperattenuating liver lesion detection task were also measured using the developed framework. Both an in vivo animal and human subject study were used as demonstrations of how the developed framework can be applied to the clinical work flow. Results: For the first task, the optimal kV and mAs were measured to be 100 and 500, respectively, for FBP, which corresponded to a dose level of 24 mGy. In comparison, the optimal kV and mAs for MBIR were 80 and 150, respectively, which corresponded to a dose level of 4 mGy. The topographies of the iso-d′ map and the iso-CNR map were the same for FBP; thus, the use of d′- and CNR-based optimization methods generated the same results for FBP. However, the topographies of the iso-d′ and iso-CNR map were significantly different in MBIR; the CNR-based method overestimated the performance of MBIR, predicting an overly aggressive dose reduction factor. For the second task, the developed framework generated the following optimization results: for FBP, kV = 140, mA = 350, dose = 37.5 mGy; for MBIR, kV = 120, mA = 250, dose = 18.8 mGy. Again, the CNR-based method overestimated the performance of MBIR. Results of the preliminary in vivo studies were consistent with those of the phantom experiments. Conclusions: A unified and task-driven kV/mAs optimization framework has been developed in this work. The framework is applicable to both linear and nonlinear CT systems such as those using the MBIR method. As expected, the developed framework can be reduced to the conventional CNR-based kV/mAs optimization frameworks if the system is linear. For MBIR-based nonlinear CT systems, however, the developed task-based kV/mAs optimization framework is needed to achieve the maximal dose reduction while maintaining the desired diagnostic performance.

Purpose: Organ dose estimation for a patient undergoing computed tomography (CT) scanning is very important. Although Monte Carlo methods are considered gold-standard in patient dose estimation, the computation time required is formidable for routine clinical calculations. Here, the authors instigate a deterministic method for estimating an absorbed dose more efficiently. Methods: Compared with current Monte Carlo methods, a more efficient approach to estimating the absorbed dose is to solve the linear Boltzmann equation numerically. In this study, an axial CT scan was modeled with a software package, Denovo, which solved the linear Boltzmann equation using the discrete ordinates method. The CT scanning configuration included 16 x-ray source positions, beam collimators, flat filters, and bowtie filters. The phantom was the standard 32 cm CT dose index (CTDI) phantom. Four different Denovo simulations were performed with different simulation parameters, including the number of quadrature sets and the order of Legendre polynomial expansions. A Monte Carlo simulation was also performed for benchmarking the Denovo simulations. A quantitative comparison was made of the simulation results obtained by the Denovo and the Monte Carlo methods. Results: The difference in the simulation results of the discrete ordinates method and those of the Monte Carlo methods was found to be small, with a root-mean-square difference of around 2.4%. It was found that the discrete ordinates method, with a higher order of Legendre polynomial expansions, underestimated the absorbed dose near the center of the phantom (i.e., low dose region). Simulations of the quadrature set 8 and the first order of the Legendre polynomial expansions proved to be the most efficient computation method in the authors’ study. The single-thread computation time of the deterministic simulation of the quadrature set 8 and the first order of the Legendre polynomial expansions was 21 min on a personal computer. Conclusions: The simulation results showed that the deterministic method can be effectively used to estimate the absorbed dose in a CTDI phantom. The accuracy of the discrete ordinates method was close to that of a Monte Carlo simulation, and the primary benefit of the discrete ordinates method lies in its rapid computation speed. It is expected that further optimization of this method in routine clinical CT dose estimation will improve its accuracy and speed.

Purpose: To further improve the image quality, in particularly, to suppress the boundary artifacts, in the extended scan field-of-view (SFOV) reconstruction. Methods: To combat projection truncation artifacts and to restore truncated objects outside the SFOV, an algorithm has previously been proposed based on fitting a partial water cylinder at the site of the truncation. Previous studies have shown this algorithm can simultaneously eliminate the truncation artifacts inside the SFOV and preserve the total amount of attenuation, owing to its emphasis on consistency conditions of the total attenuation in the parallel sampling geometry. Unfortunately, the water cylinder fitting parameters of this 2D algorithm are inclined to high noise fluctuation in the projection samples from image to image, causing anatomy boundaries artifacts, especially during helical scans with higher pitch (≥1.0). To suppress the boundary artifacts and further improve the image quality, the authors propose to use a roughness penalty function, based on the Huber regularization function, to reinforce the z-dimensional boundary consistency. Extensive phantom and clinical tests have been conducted to test the accuracy and robustness of the enhanced algorithm. Results: Significant reduction in the boundary artifacts is observed in both phantom and clinical cases with the enhanced algorithm. The proposed algorithm also reduces the percent difference error between the horizontal and vertical diameters to well below 1%. It is also noticeable that the algorithm has improved CT number uniformity outside the SFOV compared to the original algorithm. Conclusions: The proposed algorithm is capable of suppressing boundary artifacts and improving the CT number uniformity outside the SFOV.

Purpose: Recently, a fast-kVp switching (FKS) dual-energy method has been presented with clinical and phantom results to demonstrate its efficacy. Patient dose concern has been raised on FKS dual-energy since it involves higher energy acquisition at 140 kVp and slower gantry rotation time (e.g., 0.9–1 s) as opposed to 0.5 s as used in routine single-energy exams. The purpose of our study was to quantitatively compare the CTDIVOL of FKS and routine CT exams under the body and head conditions. Methods: For a fair comparison, we have to overcome the difficulty of unmatched protocols between FKS and routine CT exams. In this paper, we propose to match the low contrast detectability (LCD), a critical image quality metric impacting diagnostic quality, before measuring CTDIVOL. The kVp pair, flux ratio, and optimal monochromatic energy have been carefully optimized for FKS protocols prior to the comparison. Our baseline single-energy protocols were per IEC-61223-3-5 under head and body conditions except for mA, which was iteratively adjusted to match the LCD of FKS. CTDIVOL was measured using either a 16 cm (for head scanning) or a 32 cm (for body scanning) PMMA phantom of at least 14 cm in length. The LCD was measured using the uniform section of Catphan 600. To make the study repeatable, the automated statistical LCD measurement tool available on GE Discovery CT750 scanner was used in this work. A visual LCD phantom and a Gammex tissue characterization phantom were also employed to verify the statistical LCD measurements and to introduce various patient sizes and contrast levels. Results: The mean CTDIVOL for the head and body single-energy acquisitions was 57.5 and 29.2 mGy, respectively. The LCD was measured at 0.45% and 0.42%, respectively. The average CTDIVOL for FKS head and body scans was 70.4 and 33.4 mGy, respectively. The corresponding LCD was measured at 0.45% and 0.43%, respectively. The results from the visual LCD phantom and Gammex phantom supported the statistical LCD measurements. Conclusions: For equal image quality as measured by low contrast detectability, the CTDIVOL of a FKS head and body exam is roughly 22% and 14% higher than that of a routine single-energy head and body exam, respectively, for the phantom measured.

Purpose: The recently proposed prior image constrained compressed sensing (PICCS) method has been applied in cardiac MDCT to improve the temporal resolution by approximately a factor of 2, by using projection data acquired from half of the standard short-scan angular range to reconstructimages with improved temporal resolution. The method was referred to as temporal resolution improvement using PICCS (TRI-PICCS). The primary purpose of this article is to study (1) the relationship between the performance of the TRI-PICCS algorithm and the angular range of projection data used in image reconstruction; (2) the relationship between the performance of the TRI-PICCS algorithm and the motion orientations and motion patterns of moving objects; and (3) the relationship between the performance of the TRI-PICCS algorithm and various heart rates. Methods: A hybrid phantom consisting of realistic cardiac anatomy and eight moving objects with known motion profiles to simulate coronary arteries was constructed by superimposing the analytical projection data of eight simulated moving vessels to thein vivo projection data from a cardiac MDCT scan. The motion profiles of the moving objects may independently change orientations, period, and amplitude. A prior image was reconstructed using a short-scan filtered backprojection method from a gated short-scan data set for each given motion profile. The TRI-PICCS method was applied to improve temporal resolution for each configuration of given motion profiles of moving objects and given active angular range specified by the target temporal resolution. To quantitatively study the performance, figures of merit were introduced to quantify signal intensity deficit, image distortion, and residual motion artifacts, respectively. Results: The performance of the TRI-PICCS method is the same when the projection data are taken from 100° to 120°. The performance of the TRI-PICCS method is independent of location and motion orientations. The performance of the TRI-PICCS method does not significantly degrade for heart rates up to 100 bpm with a gantry rotation speed of 350 ms per rotation. Conclusions: The TRI-PICCS method can be used to systematically improve temporal resolution for MDCT cardiacimaging by a factor of 2–2.3 and the performance of the TRI-PICCS method is insensitive to motion locations and motion orientations. The TRI-PICCS method enables a single-source MDCT scanner with 350 ms or faster gantry speed to scan patients with heart rates as high as 100 bpm.

The current paradigm for temporal resolution improvement is to add more source-detector units and/or increase the gantry rotation speed. The purpose of this article is to present an innovative alternative method to potentially improve temporal resolution by approximately a factor of 2 for all MDCT scanners without requiring hardware modification. The central enabling technology is a most recently developed image reconstruction method: Prior image constrained compressed sensing (PICCS). Using the method, cardiac CT images can be accurately reconstructed using the projection data acquired in an angular range of about 120 degrees, which is roughly 50% of the standard short-scan angular range (approximately 240 degrees for an MDCT scanner). As a result, the temporal resolution of MDCT cardiac imaging can be universally improved by approximately a factor of 2. In order to validate the proposed method, two in vivo animal experiments were conducted using a state-of-the-art 64-slice CT scanner (GE Healthcare, Waukesha, WI) at different gantry rotation times and different heart rates. One animal was scanned at heart rate of 83 beats per minute (bpm) using 400 ms gantry rotation time and the second animal was scanned at 94 bpm using 350 ms gantry rotation time, respectively. Cardiac coronary CT imaging can be successfully performed at high heart rates using a single-source MDCT scanner and projection data from a single heart beat with gantry rotation times of 400 and 350 ms. Using the proposed PICCS method, the temporal resolution of cardiac CT imaging can be effectively improved by approximately a factor of 2 without modifying any scanner hardware. This potentially provides a new method for single-source MDCT scanners to achieve reliable coronary CT imaging for patients at higher heart rates than the current heart rate limit of 70 bpm without using the well-known multisegment FBP reconstruction algorithm. This method also enables dual-source MDCT scanner to achieve higher temporal resolution without further hardware modifications.

Diagnostic computed tomography (CT) images are usually acquired in both helical and axial scans in the clinical applications using cone beam volumetric CT. In addition to faster patient throughput, a helical scan in volumetric CT can provide better image quality because of the satisfaction of data sufficiency condition, and thus has been performed far more frequently so far in the clinic. However, the first and last images in a helical scan are usually prescribed at the locations that are half helical turn indented from the starting and ending points of the scan. Due to such an indention, the dose efficiency of helical scan deteriorates with increasing detector dimension along z direction. To improve the dose efficiency of helical scan in volumetric CT, a hybrid helical cone beam filtered backprojection (CB-FBP) algorithm is presented here to reconstruct helical images beyond the conventional indented image zone. The hybrid algorithm is a combination of the ray-wise three-dimensional (3D) weighted CB-FBP algorithms that are recently proposed for helical and axial CB image reconstructions. Through the hybridization, the ray-wise 3D weighting becomes dependent on both helical pitch and image slice location. Phantom study shows that the conventional indented image zone in helical scan can be extended substantially by using the hybrid algorithm. Consequently, the dose efficiency of volumetric CT in helical scan can be improved significantly. It is believed that, with increasing detector dimension along z direction in cone beam volumetric CT, the hybrid algorithm will become more attractive in clinical applications.

Multislice helical computed tomography scanning offers the advantages of faster acquisition and wide organ coverage for routine clinical diagnostic purposes. However, image reconstruction is faced with the challenges of three-dimensional cone-beam geometry, data completeness issues, and low dosage. Of all available reconstruction methods, statistical iterative reconstruction (IR) techniques appear particularly promising since they provide the flexibility of accurate physical noise modeling and geometric system description. In this paper, we present the application of Bayesian iterative algorithms to real 3D multislice helical data to demonstrate significant image quality improvement over conventional techniques. We also introduce a novel prior distribution designed to provide flexibility in its parameters to fine-tune image quality. Specifically, enhanced image resolution and lower noise have been achieved, concurrently with the reduction of helical cone-beam artifacts, as demonstrated by phantom studies. Clinical results also illustrate the capabilities of the algorithm on real patient data. Although computational load remains a significant challenge for practical development, superior image quality combined with advancements in computing technology make IR techniques a legitimate candidate for future clinical applications.

Until recently, most studies addressing the trade-off between spatial resolution and quantum noise were performed in the context of single-slice CT. In this study, we extend the theoretical framework of previous works to volumetric CT and further extend it by taking into account the actual shapes of the preferred reconstruction kernels. In the experimental study, we also attempt to explore a three-dimensional approach for spatial resolution measurement, as opposed to the conventional two-dimensional approaches that were widely adopted in previously published studies. By scanning a finite-sized sphere phantom, the MTF was measured from the edge profile along the spherical surface. Cases of different resolutions (and noise levels) were generated by adjusting the reconstruction kernel. To reduce bias, the total photon fluxes were matched: 120 kVp, 200 mA, and 1 s per gantry rotation. All data sets were reconstructed using a modified FDK algorithm under the same condition: Scan field-of-view (SFOV)=10 cm, and slice thickness=0.625 mm. The theoretical analysis indicated that the variance of noise is proportional to >4th power of the spatial resolution. Our experimental results supported this conclusion by showing the relationship is 4.6th (helical) or 5th (axial) power.

A cone-angle-based window function is defined in this manuscript for image reconstruction using helical cone beam filtered backprojection (CB-FBP) algorithms. Rather than defining the window boundaries in a two-dimensional detector acquiring projection data for computed tomographic imaging, the cone-angle-based window function deals with data redundancy by selecting rays with the smallest cone angle relative to the reconstruction plane. To be computationally efficient, an asymptotic approximation of the cone-angle-based window function is also given and analyzed in this paper. The benefit of using such an asymptotic approximation also includes the avoidance of functional discontinuities that cause artifacts in reconstructed tomographic images. The cone-angle-based window function and its asymptotic approximation provide a way, equivalent to the Tam-Danielsson-window, for helical CB-FBP reconstruction algorithms to deal with data redundancy, regardless of where the helical pitch is constant or dynamically variable during a scan. By taking the cone-parallel geometry as an example, a computer simulation study is conducted to evaluate the proposed window function and its asymptotic approximation for helical CB-FBP reconstruction algorithm to handle data redundancy. The computer simulated Forbild head and thorax phantoms are utilized in the performance evaluation, showing that the proposed cone-angle-based window function and its asymptotic approximation can deal with data redundancy very well in cone beam image reconstruction from projection data acquired along helical source trajectories. Moreover, a numerical study carried out in this paper reveals that the proposed cone-angle-based window function is actually equivalent to the Tam-Danielsson-window, and rigorous mathematical proofs are being investigated.

Coronary artery imaging with x-ray computed tomography (CT) is one of the most recent advancements in CT clinical applications. Although existing ''state-of-the-art'' clinical protocols today utilize helical data acquisition, it suffers from the lack of ability to handle irregular heart rate and relatively high x-ray dose to patients. In this paper, we propose a step-and-shoot data acquisition protocol that significantly overcomes these shortcomings. The key to the proposed protocol is the large volume coverage (40 mm) enabled by the cone beam CT scanner, which allows the coverage of the entire heart in 3 to 4 steps. In addition, we propose a gated complementary reconstruction algorithm that overcomes the longitudinal truncation problem resulting from the cone beam geometry. Computer simulations, phantom experiments, and clinical studies were conducted to validate our approach.

A novel exact fan-beam image reconstruction formula is presented and validated using both phantom data and clinical data. This algorithm takes the form of the standard ramp filtered backprojection (FBP) algorithm plus local compensation terms. This algorithm will be referred to as a locally compensated filtered backprojection (LCFBP). An equal weighting scheme is utilized in this algorithm in order to properly account for redundantly measured projection data. The algorithm has the desirable property of maintaining a mathematically exact result for: the full scan mode ( 2 π ) , the short scan mode ( π + full fan angle), and the supershort scan mode [less than ( π + full fan angle)]. Another desirable feature of this algorithm is that it is derivative-free. This feature is beneficial in preserving the spatial resolution of the reconstructed images. The third feature is that an equal weighting scheme has been utilized in the algorithm, thus the new algorithm has better noise properties than the standard filtered backprojection image reconstruction with a smooth weighting function. Both phantom data and clinical data were utilized to validate the algorithm and demonstrate the superior noise properties of the new algorithm.

With the evolution from multi-detector-row CT to cone beam (CB) volumetric CT, maintaining reconstruction accuracy becomes more challenging. To combat the severe artifacts caused by a large cone angle in CB volumetric CT, three-dimensional reconstruction algorithms have to be utilized. In practice, filtered backprojection (FBP) reconstruction algorithms are more desirable due to their computational structure and image generation efficiency. One of the CB-FBP reconstruction algorithms is the well-known FDK algorithm that was originally derived for a circular x-ray source trajectory by heuristically extending its two-dimensional (2-D) counterpart. Later on, a general CB-FBP reconstruction algorithm was derived for noncircular, such as helical, source trajectories. It has been recognized that a filtering operation in the projection data along the tangential direction of a helical x-ray source trajectory can significantly improve the reconstruction accuracy of helical CB volumetric CT. However, the tangential filtering encounters latitudinal data truncation, resulting in degraded noise characteristics or data manipulation inefficiency. A CB-FBP reconstruction algorithm using one-dimensional rotational filtering across detector rows (namely CB-RFBP) is proposed in this paper. Although the proposed CB-RFBP reconstruction algorithm is approximate, it approaches the reconstruction accuracy that can be achieved by exact helical CB-FBP reconstruction algorithms for moderate cone angles. Unlike most exact CB-FBP reconstruction algorithms in which the redundant data are usually discarded, the proposed CB-RFBP reconstruction algorithm make use of all available projection data, resulting in significantly improved noise characteristics and dose efficiency. Moreover, the rotational filtering across detector rows not only survives the so-called long object problem, but also avoids latitudinal data truncation existing in other helical CB-FBP reconstruction algorithm in which a tangential filtering is carried out, providing better noise characteristics, dose efficiency and data manipulation efficiency.

For various reasons, a projection dataset acquired on a computed tomography (CT) scanner can be truncated. That is, a portion of the scanned object is positioned outside the scan field-of-view (SFOV) and the line integrals corresponding to those regions are not measured. A projection truncation problem causes imaging artifacts that lead to suboptimal image quality. In this paper, we propose a reconstruction algorithm that enables an adequate estimation of the projection outside the SFOV. We make use of the fact that the total attenuation of each ideal projection in a parallel sampling geometry remains constant over views. We use the magnitudes and slopes of the projection samples at the location of truncation to estimate water cylinders that can best fit to the projection data outside the SFOV. To improve the robustness of the algorithm, continuity constraints are placed on the fitting parameters. Extensive phantom and patient experiments were conducted to test the robustness and accuracy of the proposed algorithm.

One of the key considerations in CT perfusion is the X-ray dose received by the patient, since cine acquisition mode is typically used in which repeated x-ray exposure occurs at the same anatomical location. In this technical note, we propose a new approach for dose reduction in which the X-ray tube current is maintained and the number of projection views is reduced per gantry rotation. A projection interpolation algorithm and an image prediction algorithm are developed to address the incompleteness of such projection data. Both algorithms utilize a priori knowledge that the contrast-uptake in perfusion images is gradual and predictable. As a result, excellent perfusion images can be reconstructed at a fraction of the nominal radiation dose.

Practicing medical physicists are often time charged with the tasks of evaluating and troubleshooting complex image quality issues related to CT scanners. This course will equip them with a solid and practical understanding of common CT imaging chain and its major components with emphasis on acquisition physics and hardware, reconstruction, artifacts, image quality, dose, and advanced clinical applications. The core objective is to explain the effects of these major system components on the image quality. This course will not focus on the rapid-changing advanced technologies given the two-hour time limit, but the fundamental principles discussed in this course may facilitate better understanding of those more complicated technologies. The course will begin with an overview of CT acquisition physics and geometry. X-ray tube and CT detector are important acquisition hardware critical to the overall image quality. Each of these two subsystems consists of several major components. An in-depth description of the function and failure modes of these components will be provided. Examples of artifacts related to these failure modes will be presented: off-focal radiation, tube arcing, heel effect, oil bubble, offset drift effect, cross-talk effect, and bad pixels. The fundamentals of CT image reconstruction will first be discussed on an intuitive level. Approaches that do not require rigorous derivation of mathematical formulations will be presented. This is followed by a detailed derivation of the Fourier slice theorem: the foundation of the FBP algorithm. FBP for parallel-beam, fan-beam, and cone-beam geometries will be discussed. To address the issue of radiation dose related to x-ray CT, recent advances in iterative reconstruction, their advantages, and clinical applications will also be described. Because of the nature of fundamental physics and mathematics, limitations in data acquisition, and non-ideal conditions of major system components, image artifact often arise in the reconstructed images. Because of the limited scope of this course, only major imaging artifacts, their appearance, and possible mitigation and corrections will be discussed. Assessment of the performance of a CT scanner is a complicated subject. Procedures to measure common image quality metrics such as high contrast spatial resolution, low contrast detectability, and slice profile will be described. The reason why these metrics used for FBP may not be sufficient for statistical iterative reconstruction will be explained. Optimizing radiation dose requires comprehension of CT dose metrics. This course will briefly describe various dose metrics, and interaction with acquisition parameters and patient habitus. CT is among the most frequently used imaging tools due to its superior image quality, easy to operate, and a broad range of applications. This course will present several interesting CT applications such as a mobile CT unit on an ambulance for stroke patients, low dose lung cancer screening, and single heartbeat cardiac CT. Learning Objectives: 1.Understand the function and impact of major components of X-ray tube on the image quality. 2.Understand the function and impact of major components of CT detector on the image quality. 3.Be familiar with the basic procedure of CT image reconstruction. 4.Understand the effect of image reconstruction on CT image quality and artifacts. 5.Understand the root causes of common CT image artifacts. 6.Be familiar with image quality metrics especially high and low contrast resolution, noise power spectrum, slice sensitivity profile, etc. 7.Understand why basic image quality metrics used for FBP may not be sufficient to characterize the performance of advanced iterative reconstruction. 8.Be familiar with various CT dose metrics and their interaction with acquisition parameters. 9.New development in advanced CT clinical applications. JH: Employee of GE Healthcare. FD: No disclosure.; J. Hsieh, Jiang Hsieh is an employee of GE Healthcare.

Purpose: Coronary CT angiography is a challenging task currently limited by the achievable temporal resolution of modern MDCT scanners. In this work, a highly innovative method has been developed and validated to improve temporal resolution of the MDCT by a factor of four with the newly developed SMART-RECON method to enable high quality coronary CTA exams. The primary purpose of this paper is to investigate the relationships between: (1) SMART-RECON and the motion pattern; (2) SMART-RECON and the average speed of moving vessels; (3) SMART-RECON and the position and direction of moving vessels. Methods: Using data acquired from a short scan angular range, the entire cardiac window is divided into 4–5 narrower cardiac windows, each corresponding to a 60-degree angular sector. These 4–5 sub-cardiac phase images can be jointly reconstructed with SMART-RECON to globally improve temporal resolution and noise properties. A hybrid phantom consisting of realistic cardiac anatomy and eight moving objects was constructed to validate the method under a wide variety of conditions and studied quantitatively. Additionally, in vivo data from twenty human subjects were used to demonstrate that SMART-RECON can significantly improve the quality of CTA using a Discovery CT 750 HD (GE Healthcare, WI, USA) with 350 ms gantry rotation time. Results: The performance of the proposed SMART-RECON cardiac CT imaging method is independent of motion speed, orientation, and location as long as there is a motionless phase that corresponds to 60° angular range. In contrast, the currently available FBP cardiac reconstruction with Parker weights demonstrates significant motion artifacts. The human subject results also demonstrate the significant improvement of coronary CTA quality cross all subjects. Conclusion: With a single short-scan acquisition, SMART-RECON can be used to systematically improve the temporal resolution for MDCT cardiac CT imaging by a factor of 4 with no prior knowledge of motion. Funding support: This work was support in part by GE Healthcare. Disclosures: Y. Li: None. X. Cao, Z. Xing, X. Sun and H. Jiang: GE employee. G. Chen: Research contract with GE Healthcare; Research contract with Siemens AX; Royalty received from GE Healthcare

The quality of a computed tomography (CT) image is often degraded by streaking artifacts resulting from excessive x-ray quantum noise. Often, a patient has to be rescanned at a higher technique or at a larger slice thickness in order to obtain an acceptable image for diagnosis. This results in a higher dose to the patient, a degraded cross plane resolution, or a reduced patient throughput. In this paper, we propose an adaptive filtering approach in Radon space based on the local statistical properties of the CT projections. We first model the noise characteristics of a projection sample undergoing important preprocessing steps. A filter is then designed such that its parameters are dynamically adjusted to adapt to the local noise characteristics. Because of the adaptive nature of the filter, a proper balance between streak artifact suppression and spatial resolution preservation is achieved. Phantom and clinical studies have been conducted to evaluate the robustness of our approach. Results demonstrate that the adaptive filtering approach is effective in reducing or eliminating quantum noise induced artifacts in CT. At the same time, the impact on the spatial resolution is kept at a low level.

Computed tomography fluoroscopy (CTF) has found many applications in interventional procedures. The advantage of CTF is its ability to remove overlapping structures in the human anatomy and, thereby, provide accurate spatial information. Another advantage is its ability to reconstruct images in a short period of time so that "real-time" information can be provided. In this paper, we perform theoretical analysis and computer simulations to evaluate the temporal response of the CTF. We investigate the impact of various reconstruction algorithms on CTF and demonstrate the inherent limitations of the CTF in terms of the time lag and delay. The analysis provides a useful guidance to the CTF operators to avoid potential pitfalls.

Helical Computed Tomography (HCT) has become the method of choice for many routine clinical studies. The advantages of HCT include the capability of scanning a complete anatomical volume in a single breath hold, the capability of generating images at any desired location, and the improved patient throughput. However, these advantages come at the expense of some image quality compromises. This is mainly caused by the fact that the projection set is inherently incomplete and inconsistent, due to the constant patient translation during the data acquisition process. In this paper, we will briefly review the research work performed in this area and present a more general approach to the problem. We give two specific examples of the general approach and compare the performance of one of the examples with one of the best methods available today.

Purpose: In modern CT scanners, a quantitative metric to assess temporal response, namely, to quantify the temporal resolution (TR), remains elusive. Rough surrogate metrics, such as half of the gantry rotation time for single source CT, a quarter of the gantry rotation time for dual source CT, or measurements of motion artifact's size, shape, or intensity have previously been used. In this work, a rigorous framework which quantifies TR and a practical measurement method are developed. Methods: A motion phantom was simulated which consisted of a single rod that is in motion except during a static period at the temporal center of the scan, termed the TR window. If the image of the motion scan has negligible motion artifacts compared to an image from a totally static scan, then the system has a TR no worse than the TR window used. By repeating this comparison with varying TR windows, the TR of the system can be accurately determined. Motion artifacts were also visually assessed and the TR was measured across varying rod motion speeds, directions, and locations. Noiseless fan beam acquisitions were simulated and images were reconstructed with a short-scan image reconstruction algorithm. Results: The size, shape, and intensity of motion artifacts varied when the rod speed, direction, or location changed. TR measured using the proposed method, however, was consistent across rod speeds, directions, and locations. Conclusion: Since motion artifacts vary depending upon the motion speed, direction, and location, they are not suitable for measuring TR. In this work, a CT system with a specified TR is defined as having the ability to produce a static image with negligible motion artifacts, no matter what motion occurs outside of a static window of width TR. This framework allows for practical measurement of temporal resolution in clinical CT imaging systems. Funding support: GE Healthcare; Conflict of Interest: Employee, GE Healthcare.

Purpose: Although the anatomy of interest should be positioned as close as possible to the isocenter of CT scanners, off-centering may be inevitable during certain exams in clinical practice such as lumbar spine and elbow imaging. Off-centering degrades image sharpness, generates streak artifacts, and sometimes creates blooming artifacts due to truncation. The purpose of this work was to investigate whether the use of model-based image reconstruction (MBIR) can alleviate the negative impacts of off-centering to achieve high quality CT bone imaging. Methods: Both an anthropomorphic phantom and an ex vivo swine elbow sample were scanned at centered and off-centered positions using clinical CT bone scan protocols. The magnitude of off-centering was determined from localizer radiographs. Both FBP and MBIR reconstructions were performed. For FBP, both standard and Bone Plus kernels commonly used in bone imaging were used. Objective assessment of image sharpness, noise standard deviation, and noise nonuniformity were performed. Additionally, we retrospectively analyzed human subject data acquired under off-centered conditions as a validation study. Results: In FBP images of the phantom, off-centering by 10 cm led to a 14% increase in noise (p

Purpose: A number of different techniques have been developed to reduce radiation dose in x-ray computed tomography (CT) imaging. In this paper, the authors will compare task-based measures of image quality of CT images reconstructed by two algorithms: conventional filtered back projection (FBP), and a new iterative reconstruction algorithm (IR). Methods: To assess image quality, the authors used the performance of a channelized Hotelling observer acting on reconstructed image slices. The selected channels are dense difference Gaussian channels (DDOG).A body phantom and a head phantom were imaged 50 times at different dose levels to obtain the data needed to assess image quality. The phantoms consisted of uniform backgrounds with low contrast signals embedded at various locations. The tasks the observer model performed included (1) detection of a signal of known location and shape, and (2) detection and localization of a signal of known shape. The employed DDOG channels are based on the response of the human visual system. Performance was assessed using the areas under ROC curves and areas under localization ROC curves. Results: For signal known exactly (SKE) and location unknown/signal shape known tasks with circular signals of different sizes and contrasts, the authors’ task-based measures showed that a FBP equivalent image quality can be achieved at lower dose levels using the IR algorithm. For the SKE case, the range of dose reduction is 50%–67% (head phantom) and 68%–82% (body phantom). For the study of location unknown/signal shape known, the dose reduction range can be reached at 67%–75% for head phantom and 67%–77% for body phantom case. These results suggest that the IR images at lower dose settings can reach the same image quality when compared to full dose conventional FBP images. Conclusions: The work presented provides an objective way to quantitatively assess the image quality of a newly introduced CT IR algorithm. The performance of the model observers using the IR images was always higher than that seen using the FBP images in the authors’ SKE and SKE location unknown detection tasks. To achieve a FBP-equivalent image quality in CT systems, the authors can lower the radiation dose by using this IR image reconstruction algorithm. Further studies are warranted using clinical data and human observer to validate these results for more complicated and realistic tasks.

Purpose: Quantitative accuracy of Iodine Hounsfield Unit (HU) in conventional single-kVp scanning is susceptible to beam-hardening effect. Dual-energy CT has unique capabilities of quantification using monochromatic CT images, but this scanning mode requires the availability of the state-of-the-art CT scanner and, therefore, is limited in routine clinical practice. Purpose of this work was to develop a beam-hardening-correction (BHC) for single-kVp CT that can linearize Iodine projections at any nominal energy, apply this approach to study Iodine response with respect to keV, and compare with dual-energy based monochromatic images obtained from material-decomposition using 80kVp and 140kVp. Methods: Tissue characterization phantoms (Gammex Inc.), containing solid-Iodine inserts of different concentrations, were scanned using GE multi-slice CT scanner at 80, 100, 120, and 140 kVp. A model-based BHC algorithm was developed where Iodine was estimated using re-projection of image volume and corrected through an iterative process. In the correction, the re-projected Iodine was linearized using a polynomial mapping between monochromatic path-lengths at various nominal energies (40 to 140 keV) and physically modeled polychromatic path-lengths. The beam-hardening-corrected 80kVp and 140kVp images (linearized approximately at effective energy of the beam) were used for dual-energy material-decomposition in Water-Iodine basis-pair followed by generation of monochromatic images. Characterization of Iodine HU and noise in the images obtained from singlekVp with BHC at various nominal keV, and corresponding dual-energy monochromatic images, was carried out. Results: Iodine HU vs. keV response from single-kVp with BHC and dual-energy monochromatic images were found to be very similar, indicating that single-kVp data may be used to create material specific monochromatic equivalent using modelbased projection linearization. Conclusion: This approach may enable quantification of Iodine contrast enhancement and potential reduction in injected contrast without using dual-energy scanning. However, in general, dual-energy scanning has unique value in material characterization and quantification, and its value cannot be discounted. GE Healthcare Employee

Purpose: Dual‐energy CT has attracted much attention in recent years. Most recently, a fast‐kVp switching (FKS) dual‐energy method has been presented with clinical and phantom results to demonstrate its efficacy. The purpose of our study was to quantitatively compare the CTDIw of FKS and routine CT exams under the body and head conditions. Material and Method: For a fair comparison, the low contrast detectability (LCD) was matched before measuring dose. In FKS protocols, an x‐ray generator switch rapidly between 140kVp and 80kVp in adjacent views, and the effective tube current is around 600mA. In addition to the tube voltage and current, the flux ratio between high and low kVp is optimized by asymmetric sampling of 35%–65%. The head and body protocols further differ by the gantry speed and type of bowtie filter. For baseline single‐energy, we followed the IEC standard head and body protocols but iteratively adjusted the tube current (mA) in order to match the LCD.CTDIw was measured using either a 16 cm or a 32 cm PMMA phantom of at least 14 cm in length. The LCD was measured using the water section of Catphan 600. To make the study repeatable, the automated statistical LCD measurement tool available on GE Discovery CT750 scanner was used in this work. Result: The mean CTDIw for the head and body single‐energy acquisitions were 57.5mGy and 29.2mGy, respectively. The LCD was measured at 0.45% and 0.42% (slice thickness=5mm, object size=3mm, central 4 images), respectively. The average CTDIw for FKS head and body scans was 70.4mGy and 33.4mGy, respectively, at the optimal monochromatic energy of 65 keV. The corresponding LCD was measured at 0.45% and 0.43%, respectively. Conclusion: This demonstrates that, with matching LCD,CTDIw of FKS is comparable to that of routine CT exams under head and body conditions.

Purpose: To identify the root causes of artifacts in axial cone beam reconstruction, propose and evaluate the solutions of suppressing artifacts for image quality optimization. Method and Materials: With increasing cone angle in volumetric CT, suppression of artifacts in axial cone beam reconstruction becomes more challenging. In the past, data insufficiency and longitudinal truncation were identified as the major causes of the artifacts. In this study, insufficient longitudinal sampling is identified as the third major cause. Based on a detailed artifact analysis, it has been experimentally verified that, (a) the artifacts caused by data insufficiency is quite acceptable at small cone angle up to 4.23°, and barely acceptable at moderate cone angle equal to 8.46°; (b) the artifacts caused by longitudinal truncation can be efficiently reduced by ray‐wise 3D weighting. A straightforward way to reduce the artifacts caused by insufficient longitudinal sampling is to increase detector's longitudinal sampling rate, but such a way degrades noise characteristics and dose efficiency. An anisotropic adaptive filtering approach is proposed to suppress the artifact caused by insufficient longitudinal sampling. An oblique wire phantom, humanoid head phantom, modified Defrise phantom and helical body phantom, are employed to analyze artifacts and evaluate the efficacy of the proposed solutions. Results: Experimental evaluation based on the phantom study shows that, the artifacts caused by longitudinal truncation and insufficient longitudinal sampling in axial cone beam reconstruction can be substantially suppressed by ray‐wise 3D weighting and anisotropic adaptive filtering, especially while the image plane is approaching the detector's longitudinal boundaries. Conclusion: It has been evaluated and verified that the combination of ray‐wise 3D weighting and anisotropic adaptive filtering can significantly improve the image quality of axial cone beam reconstruction at cone angle up to 4.23°. Moreover, it is expected that such a combination can work well at larger cone angles.

Purpose: To evaluate the impact on image quality of a new iterative reconstruction (IR) algorithm for CT systems and quantitate the amount of dose reduction by using mathematical model observers. Methods: Two phantoms with low‐contrast inserts (head mode and body mode) were used to evaluate task performance for both location known signal detection and location unknown signal detection tasks. The phantom consisted of low contrast cylindrical signals with contrasts ranging from −2 Hounsfield units (HU) to ‐ 10 HU and sizes ranging from 5mm to 7mm. The phantoms were scanned by multi row CT scanner using a range of tube currents 30&– 400mAs, and energy 120 kVp. The performance of a traditional filtered backprojection (FBP) algorithm and the new IR were evaluated using the channelized Hotelling observer. Seven channels designed to match human performance were selected to evaluate the image quality. Area under ROC curves and LROC curves were used to determine the image quality. Results: Evaluation of model observer performances indicates that a 3x dose reduction can be reached using the new IR algorithm in two modes (head and body) while maintaining image quality for location known and location unknown detection tasks. Conclusion: Overall, image quality as measured by task performance is greatly improved by using the IR compared to traditional FBP at equal mAs and kVp. Thus, this study indicates that a significant dose reduction in CT systems can be achieved by using this new IR algorithm. This new IR and the phantoms presented in this study will be used in future investigations of more complicated imaging tasks such as size and contrast estimation. GE Healthcare, Waukesha, WI

Purpose: With advancement in computed tomography(CT)reconstruction and dose reduction technologies, e.g., Model‐Based‐Iterative‐Reconstruction (MBIR) and Adaptive‐Statistical‐Iterative‐Reconstruction (ASiR), there is potential for significant dose reduction in clinical practice; therefore, it is immensely desirable to have a benchmarking of dose reduction steps to ensure un‐compromised diagnostic image‐quality at optimally reduced dose levels. Purpose of this work was to develop and evaluate a new projection domain noise insertion tool that can emulate lower dose scans using routine dose scans, and can provide a benchmarking guide for clinicians and physicists to achieve optimal dose levels without multiple scans of the patient. Methods: In order to emulate lower dose CT projections at reduced signal‐to‐noise‐ratio (SNR), a normally distributed random noise (quantum and electronic) was added to the transmission data obtained from initial scan. The estimate of variance was obtained using initial projections with appropriate scaling to represent true x‐ray photon‐flux for desired dose reduction factor. For validation of the method, a GE multi‐slice CT system was used to acquire a set of multi‐dose data for cylindrical and anthropomorphic phantoms. A comparison of emulated vs. acquired scans was made at different dose levels (upto 1/56th) relative to a baseline higher dose. Imagenoise,Modulation Transfer Function(MTF), Noise‐Power‐ Spectrum (NPS), and artifacts were compared between the emulated low dose scans and. the corresponding acquired scans. In addition, few clinical case studies were also used to compare the imaging performance in clinical data. Results: Initial results for the presented noise emulation method showed very good agreement with noise,MTF and NPS from actual acquired scans at significantly reduced dose levels, demonstrating immense potential in dose reduction studies and clinical protocol optimizations. Conclusions: The noise emulation tool has potential to provide a benchmarking guide to explore optimal dose levels without having multiple scans of the patient.

Purpose: This study is a comparative evaluation between Veo, GE Healthcare's model based iterative reconstruction engine, and contemporary filtered backprojection (FBP) techniques. The purpose is to estimate Veo's ability to produce diagnostic image quality at reduced dose levels. Methods: Standard image quality metrics were measured at different dose levels using physics phantoms commonly found in clinical settings. A GE multi‐slice CT system was used to scan a CATPHAN600® phantom in order to compare the noise and signal properties of FBP and Veo; tungsten wire phantoms were used to characterize high contrastspatial resolution between the two reconstruction algorithms. Three routine clinical protocols were tested: head, adult abdomen, and pediatric. Baseline FBP dose levels for each protocol were determined by the mean noise index from a large international database of scan histories. The metrics used in this study include MTF, noise power, contrast to noise ratio, and statistical low contrast detectability. Results: All of the tested metrics showed improved performance for the Veo at equal dose. Measurement differences between full dose FBP and 1/4th dose Veo were found to be statistically insignificant, indicating similar image quality. Conclusions: Veo reconstruction produces higher image quality than FBP at all measured dose levels and has the ability to greatly reduce the dose of routine CTimaging, as observed from standard physics phantom evaluation.

Purpose: To reduce the over‐beaming dose in conventional helical scans by acquiring and reconstructing the same image volume using a reduced scan range through an axial‐like reconstruction algorithm. Methods: In the proposed framework, the reconstruction volume is split into two types of regions along the z‐direction when the helical scan range is reduced: one central region where conventional reconstruction methods are applied and two boundary regions that have historically not been recoverable. In the boundary regions an axial‐like reconstruction algorithm which combines 3D view‐weighting and modified back‐projection is introduced. The 3D view‐weighting satisfies consistency condition for a ray and its conjugate ray while taking into account the view‐angle, cone‐angle and the distance of the image slice from the center view in a unified framework. The same view range as the edge slice of the middle region is used for reconstructing the boundary region, which makes the reconstruction similar to axial reconstruction.Results: Extensive experiments have been performed using both phantom and clinical scan data on volumetric CT scanners with various detector configurations and helical pitches. Experimental results demonstrated for the same prescribed image volume the xray scan range can be reduced by up to ¼ of the x‐ray beam width in z on each end of the helix compared to conventional scans. This means we may save an additional 8% and 5% dose in routine chest and abdomen scans, respectively, on top of the dose saving achieved with the dynamic collimation method. The proposed method has also been applied to multi‐energy CT scans with similar results. Conclusions: A new axial‐like helical reconstruction method is proposed that reconstructs the prescribed image volume with a reduced xray scan range. Experimental results indicate the new method can reduce the over‐beaming dose significantly. The method can be easily applied to multi‐energy scans. The authors are with GE Healthcare, Waukesha, WI.

Objectives: CT HU accuracy is influenced by the fundamental properties of x‐ray physics, CT system calibration processes, data acquisitionhardware and protocols, image reconstruction techniques, and patient preparation and handling. With a renewed and increased importance of quantitative imaging, this talk will provide an overview on this issue and focus on a few specific areas: scatter, beam‐hardening effect, CT components and system impact, and data acquisition protocols. Various techniques to reduce, correct, or avoid the pitfalls are presented. Current system limitations and new technologies to overcome the shortcomings will also be discussed.

Purpose: To determine whether a dose penalty exists when scanning patients in axial scan mode on General Electric (GE)Computed Tomography(CT)scanners. A 10‐millisecond‐long rise of the x‐ray tube output occurs immediately before image acquisition and is suspected to contribute additional dose near the start angle of the x‐ray tube. This dose penalty may exist for axial scanning because the rise time occurs for every 360° rotation of the x‐ray tube, whereas rise time only occurs once in helical scan mode. Method and Materials: 10‐, 15‐, and 32‐cm CTDI phantoms were scanned on a GE VCT scanner for a single axial rotation in service mode. Exposure was measured at a constant peripheral location (12:00) and recorded for various x‐ray tube start angles. These methods were repeated on the 32‐cm phantom, changing its vertical position in 2‐cm increments from 6‐cm below to 12‐cm above iso‐center. Results: Exposure, measured at the 12:00 peripheral chamber position, was 5.5%, 1.8%, and 1.0% higher in the 32‐, 15‐, and 10‐cm phantom, respectively, when a start angle of 0° was used versus a start angle of 270° (this start angle was used for comparison to avoid attenuation from the patient table). The exposure penalty ranged from 2.9% to 12.7% when the 32‐cm phantom was 6‐cm below and 12‐cm above iso‐center, respectively. Conclusion: In light of the dose penalty observed in this study, axial acquisitions should feature a start angle of 180° to avoid imparting this penalty on superficial radiosensitive organs (i.e. breast, testes, and thyroid), which are near the anterior side of patients. Also, dose is not consistent around the periphery of a phantom scanned in axial mode and contiguous helical scanning (pitch = 1.0) provides a dose advantage over axial scanning (all other technique factors being equal).

Purpose: To demonstrate the image‐quality benefits and potential for significant dose reduction with Model‐Based Iterative Reconstruction (MBIR) technique incorporating physical model of computed tomography(CT) systems. Method and Materials: A model based iterative reconstruction (MBIR), a maximum a posteriori (MAP) estimate with edge‐preserving prior, has been developed for x‐ray CTimage reconstruction. It utilizes a more accurate physical model of the imaging chain accounting for system‐optics, noise and non‐idealities in the data, hence improves image quality compared to conventional filtered backprojection (FBP) at significantly reduced dose levels. In this work, a GE multi‐slice CT system was used to acquire a set of multi‐dose data and standard FBP reconstruction. For resolution assessment, a Catphan600® phantom was scanned at three dose levels (40, 20, and 10 mGy with 120kVp spectrum), and images were reconstructed using two methods: FBP with ASiR, and the MBIR. For artifact and image‐quality evaluations, an anthropomorphic CT abdomen phantom (Kyoto Kagaku Co., Ltd) was scanned at four dose levels (120kVp spectrum with 225, 112, 54, and 27 mAs), and a comparative image‐quality study between standard FBP and MBIR in slice and multi‐planar reformat (MPR) modes was made. In addition, few clinical case studies were also used to compare the imaging performance in actual clinical data. Results: From the resolution study, we found that even at 1/4th dose, MBIR images have improved resolution at significantly reduced noise compared to standard state‐of‐the‐art FBP with ASiR. Use of ASIR provides up to 50% dose reduction with equivalent FBP image‐quality. For anthropomorphic phantom, even below 1/8th dose, MBIR images outperformed the corresponding FBP images in both, slice and MPR modes, demonstrating immense potential for dose reduction, yet improved image quality, in clinical CT.Conclusion: Results of the MBIR method demonstrated significant potential for dose reduction and image‐quality improvements in clinical CT.

Purpose: Dual‐energy (DE) CT has received much attention in recent years. There are various approaches to the data acquisition, differing in terms of the simultaneity, geometric alignment, data collection efficiency and completeness, and flexibility. We present a fast‐kVp switching (FKS) method in combination with advanced imagegeneration process, and demonstrate the efficacy of our approach with phantom and clinical results. Methods and Materials: In FKS, the input to the x‐ray tube is rapidly changed between two kVp‐settings in adjacent views. To ensure the signal fidelity, x‐ray generator was redesigned to minimize its input impedance, new scintillating material was developed to reduce the primary speed to a small fraction of a millisecond, and the data acquisition system was designed to sample up to 7Hz frequency. To take full advantage of the co‐registered dual‐energy projections, advanced algorithms were developed to enable projection‐space pre‐processing, calibration,reconstruction, and spectral image displays. These techniques allow the production of mono‐energetic CTimages, as well as different material decomposed images.Results: Phantom experiments and computer simulations show that because of the near simultaneous data acquisition in terms of timing and orientation, mis‐registration due to patient motion is kept to a minimized. FKS also allows the projection‐space processing of the dual‐energy signals and results in a significant improvement in terms of beam‐hardening artifacts. Advanced algorithms allow superb noise suppression in the mono‐energetic images as well as material‐decomposed images. Clinical studies demonstrate the importance of beam‐hardening reduction, metal artifact reduction, and the accuracy of material decomposition. Conclusion: We present a fast‐kVp switching approach to the dual‐energy data acquisition and advanced algorithms to the dual‐energy reconstruction. Phantom and clinical experiments have demonstrated that such approach provides superior image quality and clinical utility.

Purpose: The current paradigm for temporal resolution improvement is to add more source‐detector units and/or increase the gantry rotation speed. The purpose of this letter is to present an innovative alternative method to improve temporal resolution by at least a factor of 2 for all MDCT scanners, without requiring hardware modification. Methods: The central enabling technology is a most recently developed image reconstruction method: Prior Image Constrained Compressed Sensing (PICCS). Using the method, cardiac CTimages can be accurately reconstructed using projection data acquired in an angular range of about 120 degrees, which is roughly 50% of the standard short‐scan angular range (∼240 degrees for an MDCT scanner). As a result, the temporal resolution of MDCT cardiac imaging can be universally improved by approximately a factor of 2. In order to validate the proposed method, two in vivo animal experiments were conducted using a state‐of‐the‐art 64‐slice CTscanner(GE Healthcare, Waukesha, WI) at different gantry rotation times and different heart rates. One animal was scanned at heart rate of 83 beat per minute (bpm) using 400ms gantry rotation time and the second animal was scanned at 94bpm using 350ms gantry rotation time respectively. Results: Cardiac coronary CTimaging can be successfully performed at high heart rates using a single source MDCT scanner with gantry rotation time of 400ms and 350ms. Conclusions: Using the proposed PICCS method, temporal resolution of cardiac CTimaging can be effectively improved by approximately a factor of two without modifying any scanner hardware. This potentially provides a new method for single source MDCT scanners to achieve motion artifact‐free coronary CTimaging for most patients without prescription of beta blocker. This method also enables dual source MDCT scanner to achieve higher temporal resolution without further hardware modifications.

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.

The introduction of helical/spiral CT nearly 20 years ago enables, for the first time in CT history, the coverage of an entire human organ in a single breath‐hold. It offers a more uniform sampling along the patient long axis and allows clinicians to follow the contrast uptake in an organ. Nearly ten years later, the introduction of multi‐slice CT offers a truly isotropic spatial resolution any time and anywhere. Operator is no longer forced to make a choice between coverage and spatial resolution along the z‐axis. Its debut has changed the way radiologists scan patients and visualize images. With a significantly improved coverage, CTimaging has moved beyond the three‐dimensional spatial domain and included the fourth dimension of temporal domain. Multi‐slice helical/spiral CT also found its way into the cross‐modality imaging devices such as PET/CT or SPECT/CT. CT has become such an integral part of these devices that nearly all of the PET scanners built today include CT. These advancements inspired many new clinical applications such as cardiacimaging, perfusion, and more recently dual energy acquisitions. If the past ten years of CT history can be characterized by the “slice war”, new technological advancements nowadays are no longer constrained to the simple slice count. Many new frontiers, such as functional or physiological imaging, are now appearing on the horizon and are actively pursued by researcher around the world. In this talk, we will briefly review technological advances, technical challenges, and clinical impact associated with the helical/spiral scanning, multi‐slice CT, and PET/CT. We will discuss recent advances in the areas of cardiacimaging, dual energy imaging, 4DCT, and perfusion. We will conclude with a futuristic look at the CT.

Low‐contrast‐detectability (LCD) is one of the important performance parameters for computed tomography(CT). Often LCD is determined by visual inspection of low‐contrast phantom images. The testing process is gated not only by limitations of existing LCD phantoms, but also by the subjective nature of the evaluation methodology. Although statistical LCD methods were proposed, these methods often unfairly favor post‐processed images, since they measure mainly the noisecharacteristics in uniform portion of the phantom and do not consider the impact on LCD objects. In this paper, we present a measurement methodology that incorporates the LCD objects as part of the testing process. To overcome limited availability of low‐contrast phantoms in terms of object size and contrast level, computer simulated objects are inserted into the reconstructed uniform phantom images prior to the post‐process filtering steps. These test objects are obtained by convolving the ideal disc shaped objects with the point‐spread‐function (PSF) of the system. We also propose a LCD index that incorporates the object contrasts and noise levels of the LCDimages. The index is defined as the ratio of the measured object contrast over the standard deviation of means measured over a region equal to the LCD object size. This index overcomes the shortcomings of the previously proposed statistical method in which the visibility of post‐processed low‐contrast objects are over‐estimated. Extensive phantom tests were conducted. Existing statistical‐based LCD measure was compared with the proposed LCD index, and both were judged against visual inspection of experts. Phantoms vary over different contrast, object size, scan techniques, and reconstruction kernels. Test results have shown that the proposed LCD method outperforms the existing method and correlates well with human observers. Future extension of the algorithm includes the refinement of the LCD object shape and the non‐stationary characteristics of the PSF and noise in CT systems.

Cone Beam CT(CBCT) is one of the most recent technical advancements in x‐ray computed tomography. The state‐of‐the‐art 64‐slice scanners provide isotropic sub‐millimeter spatial resolution, significantly improved dose efficiency, large volumetric coverage, and markedly improved temporal resolution. These capabilities open doors to new clinical applications. This presentation provides an overview of the recent technical advancements in CBCT. The discussion first covers technical challenges that face CBCT, such as detector complexity, electrical and mechanical design, image reconstruction algorithms, dose, and information management. The second part discusses some of the recent developments in CBCT. These include the advanced dose‐reduction techniques, the dual‐source CTscanner, more advanced reconstruction algorithms that break the traditional noise vs. dose tradeoffs, larger volume coverage, and dual‐energy CT for material decomposition and presentation. If the past 10 years of CT development can be characterized by the “slice‐war”, new technology developments are pointing to different directions. Learning Objective: 1. Overview of the recent technology developments in CBCT. 2. Understand major technical challenges in CBCT development. 3. Explore future directions in CBCT technology.

Purpose: To extend the 3D weighted cone beam filtered backprojection (CB‐FBP) algorithm for diagnosticCTimaging to image‐guidedradiation therapy(IGRT) applications. Method and Materials: 3D isotropic spatial resolution is one of the most attracting features of state‐of‐the‐art volumetric CT for diagnosticsimaging. However, in IGRT treatment planning, the CTimage slice thickness is usually larger than what is determined by detector row width (namely thin image). A straightforward way to generate thicker image is the combination of weighted adjacent thin images in image domain, which is computationally expensive because each thin image has to go through a computation expensive 3D backprojection. Another way is to carry out cross‐row filtering in projection domain, which may cause shading/glaring artifacts and uneven slice thickness as isotropic 3D geometry is distorted. To optimize both image quality (IQ) and computational efficiency, a virtual reconstruction plane (RP) based algorithm is proposed and implemented. By using the 3D weighted CB‐FBP algorithm, a thick image is still a weighted combination of adjacent thin images, but the combination is implemented in projection domain using virtual RPs. To maintain the IQ of thick image, the 3D weighted CB‐FBP algorithm is applied by tracking re‐sampled projection data. The tracking process is to improve computational efficiency further by making use of the projection data corresponding to involved virtual RPs only, while the re‐sampling process is to improve IQ by increasing the in‐plane sampling‐rate in virtual RPs. Results: By using a helical body phantom, spatial resolution phantom and 20 cm water phantom, the performance of the proposed algorithm, such as suppression of artifacts, uniformity of slice thickness and noise characteristics, are experimentally evaluated and verified. Conclusion: The experimental evaluation shows the proposed algorithm is indeed an optimized image reconstruction solution for IGRT applications in terms of both image quality and computational efficiency.

Purpose: To reduce by a factor of ten the patient dose in contrast enhanced CT Neuro Perfusion protocols while maintaining SNR and physiologic information relative to standard full dose CT Neuro Perfusion protocols. Method and Materials: Our group's newly developed undersampling algorithm for contrast enhanced MRI, HighlY constrained back Projection (HYPR), is applied to a contrast enhanced CT Neuro Perfusion protocol. By using temporally redundant information in the time series, a reduction in the number of required projection angles for each time frame is possible. The time series data is acquired using interleaved and equally spaced projections. A composite image consisting of projection information from either the entire time series or a limited number of time frames is first constructed by the standard filtered back projection technique. Next, a HYPR time frame is reconstructed by multiplying the composite image by backprojections for each projection angle in the time frame after normalizing them by the corresponding projection from the composite image.Results: HYPR time frames with similar SNR to fully sampled images and containing equivalent physiologic information for the creation of perfusion parameter maps have been obtained. The simulated reduction in the number of projection angles for the studies completed would result in a reduction in dose by a factor of 10. Computed parametric maps of CBV, CBF, and MTT are qualitatively similar to that of full dose maps, and arterial and venous input functions show excellent agreement with full dose input functions. Conclusion: The application of HighlY constrained back Projection (HYPR) to contrast enhanced CT Neuro Perfusion protocols allows a potential reduction by an order of magnitude to the delivered patient dose while maintaining SNR and physiologic information in the form of CBV, CBF, and MTT maps and arterial, venous and tissue input functions.

Over the past decade, x‐ray computed tomography has experienced tremendously technological advancements: the introduction of helical/spiral and multi‐slice/volumetric acquisition. These advancements not only allow improved image quality and enable new clinical applications, but also significantly increase the technical challenges associated with image reconstruction. The first part of this lecture will cover the fundamentals of image reconstruction. For the ease of understanding, we start with an explanation of the central slice theorem (Fourier slice theorem). Both theoretical and intuitive approaches are used to illustrate the concept. The reconstruction algorithm is then extended to fan beam geometry by mathematical derivation and graphic description. Using the central slice theorem as the foundation, reconstruction algorithms for helical acquisition are discussed in the second part of the lecture. We analyze, for single slice, the major difference between helical and step‐andshoot acquisitions. Implications of different reconstruction approaches on image quality and computational complexity are also discussed. Cone beam reconstruction discussion will start with one of the most popular algorithms: FDK algorithm. The derivation of the algorithm from the fan‐beam case is first described and its extension to helical/spiral acquisition is then presented. The lecture ends with a discussion on some of the most recent advances in cone beam reconstruction, including both approximate and exact methods. Jiang Hsieh is an employee of GE Healthcare Technologies. Educational Objectives: 1. Learn the fundamentals of x‐ray CTreconstruction. 2. Understand recent advancements in reconstruction algorithms.

Over the past decade, x-ray computed tomography has experienced tremendously technological advancements: the introduction of helical/spiral and multi-slice/volumetric acquisition. These advancements not only allow improved image quality and enable new clinical applications, but also significantly increase the technical challenges associated with image reconstruction. The first part of this lecture will cover the fundamentals of image reconstruction. For the ease of understanding, we start with an explanation of the central slice theorem (Fourier slice theorem) for a 2D parallel beam geometry. Both theoretical and intuitive approaches are used to illustrate the concept. The reconstruction algorithm is then extended to fan beam geometry by mathematical derivation and graphic description. Using the central slice theorem as the foundation, reconstruction algorithms for helical acquisition are discussed in the second part of the lecture. We analyze, for single slice, the major difference between helical and step-and-shoot acquisitions. Implications of different reconstruction approaches on image quality and computational complexity are also discussed. Cone beam reconstruction discussion will start with one of the most popular algorithms: FDK algorithm. The derivation of the algorithm from the fan-beam case is first described and its extension to helical/spiral acquisition is then presented. The lecture ends with a discussion on some of the most recent advances in cone beam reconstruction, including both approximate and exact methods. Jiang Hsieh is an employee of GE Healthcare Technologies. Educational Objectives: 1. Learn the fundamentals of x-ray CT reconstruction. 2. Understand recent advancements in reconstruction algorithms.