Low-dose CT image and projection dataset.

PURPOSE: To describe a large, publicly available dataset comprising computed tomography (CT) projection data from patient exams, both at routine clinical doses and simulated lower doses. ACQUISITION AND VALIDATION METHODS: The library was developed under local ethics committee approval. Projection and image data from 299 clinically performed patient CT exams were archived for three types of clinical exams: noncontrast head CT scans acquired for acute cognitive or motor deficit, low-dose noncontrast chest scans acquired to screen high-risk patients for pulmonary nodules, and contrast-enhanced CT scans of the abdomen acquired to look for metastatic liver lesions. Scans were performed on CT systems from two different CT manufacturers using routine clinical protocols. Projection data were validated by reconstructing the data using several different reconstruction algorithms and through use of the data in the 2016 Low Dose CT Grand Challenge. Reduced dose projection data were simulated for each scan using a validated noise-insertion method. Radiologists marked location and diagnosis for detected pathologies. Reference truth was obtained from the patient medical record, either from histology or subsequent imaging. DATA FORMAT AND USAGE NOTES: Projection datasets were converted into the previously developed DICOM-CT-PD format, which is an extended DICOM format created to store CT projections and acquisition geometry in a nonproprietary format. Image data are stored in the standard DICOM image format and clinical data in a spreadsheet. Materials are provided to help investigators use the DICOM-CT-PD files, including a dictionary file, data reader, and user manual. The library is publicly available from The Cancer Imaging Archive (https://doi.org/10.7937/9npb-2637). POTENTIAL APPLICATIONS: This CT data library will facilitate the development and validation of new CT reconstruction and/or denoising algorithms, including those associated with machine learning or artificial intelligence. The provided clinical information allows evaluation of task-based diagnostic performance.

Overcoming calcium blooming and improving the quantification accuracy of percent area luminal stenosis by material decomposition of multi-energy computed tomography datasets.

Purpose: Conventional stenosis quantification from single-energy computed tomography (SECT) images relies on segmentation of lumen boundaries, which suffers from partial volume averaging and calcium blooming effects. We present and evaluate a method for quantifying percent area stenosis using multienergy CT (MECT) images. Approach: We utilize material decomposition of MECT images to measure stenosis based on the ratio of iodine mass between vessel locations with and without a stenosis, thereby eliminating the requirement for segmentation of iodinated lumen. The method was first assessed using simulated MECT images created with different spatial resolutions. To experimentally assess this method, four phantoms with different stenosis severity (30% to 51%), vessel diameters (5.5 to 14 mm), and calcification densities (700 to 1100 mgHA / cc ) were fabricated. Conventional SECT images were acquired using a commercial CT system and were analyzed with commercial software. MECT images were acquired using a commercial dual-energy CT (DECT) system and also from a research photon-counting detector CT (PCD-CT) system. Three-material-decomposition was performed on MECT data, and iodine density maps were used to quantify stenosis. Clinical radiation doses were used for all data acquisitions. Results: Computer simulation verified that this method reduced partial volume and blooming effects, resulting in consistent stenosis measurements. Phantom experiments showed accurate and reproducible stenosis measurements from MECT images. For DECT and two-threshold PCD-CT images, the estimation errors were 4.0% to 7.0%, 2.0% to 9.0%, 10.0% to 18.0%, and - 1.0 % to - 5.0 % (ground truth: 51%, 51%, 51%, and 30%). For four-threshold PCD-CT images, the errors were 1.0% to 3.0%, 4.0% to 6.0%, - 1.0 % to 9.0%, and 0.0% to 6.0%. Errors using SECT were much larger, ranging from 4.4% to 46%, and were especially worse in the presence of dense calcifications. Conclusions: The proposed approach was shown to be insensitive to acquisition parameters, demonstrating the potential to improve the accuracy and precision of stenosis measurements in clinical practice.

Targeted Imaging of Renal Fibrosis Using Antibody-Conjugated Gold Nanoparticles in Renal Artery Stenosis.

OBJECTIVES: The ability to determine the severity of renal fibrosis, which is involved in most chronic kidney diseases, may be beneficial for monitoring disease progression and management. The aim of this study was to assess a new method involving gold nanoparticles conjugated to an anti-collagen-I antibody (Co-I-AuNPs) as a computed tomography (CT) imaging contrast for the evaluation of renal fibrosis in situ. MATERIALS AND METHODS: Gold nanoparticles conjugated to an anti-collagen-I antibody were prepared using gold chloride reduction with sodium citrate and coated with polyethylene glycol (PEG), and their size was determined by electron microscopy and nanoparticle tracking analysis. Anti-collagen-I antibody was then conjugated to PEG-SH/COOH on the AuNP surface. The success of antibody conjugation was tested in vitro using collagen-coated plate and mouse stenotic kidney sections and in vivo using micro-CT and multidetector CT imaging. RESULTS: Bare AuNPs were 18.7 ± 0.6 nm and PEG-coated AuNPs were 45.3 ± 0.1 nm in size. In vitro, Co-I-AuNPs specifically bound to both a collagen-coated plate and mouse fibrotic kidneys. Furthermore, the stenotic mouse kidney showed increased Co-I-AuNPs retention compared with the contralateral kidney (59.3 ± 5.1 vs 45.1 ± 1.7 HU, P = 0.05), which correlated with its collagen deposition. Micro-CT also detected gold signals in situ in the Co-I-AuNP-injected kidney, which colocalized with histological trichrome staining. CONCLUSION: Gold nanoparticles conjugated to an anti-collagen-I antibody are able to visualize kidney fibrosis in vitro and in situ and may be useful for nondestructive quantification of tissue fibrosis.

Spectral performance of a whole-body research photon counting detector CT: quantitative accuracy in derived image sets.

Photon-counting computed tomography (PCCT) uses a photon counting detector to count individual photons and allocate them to specific energy bins by comparing photon energy to preset thresholds. This enables simultaneous multi-energy CT with a single source and detector. Phantom studies were performed to assess the spectral performance of a research PCCT scanner by assessing the accuracy of derived images sets. Specifically, we assessed the accuracy of iodine quantification in iodine map images and of CT number accuracy in virtual monoenergetic images (VMI). Vials containing iodine with five known concentrations were scanned on the PCCT scanner after being placed in phantoms representing the attenuation of different size patients. For comparison, the same vials and phantoms were also scanned on 2nd and 3rd generation dual-source, dual-energy scanners. After material decomposition, iodine maps were generated, from which iodine concentration was measured for each vial and phantom size and compared with the known concentration. Additionally, VMIs were generated and CT number accuracy was compared to the reference standard, which was calculated based on known iodine concentration and attenuation coefficients at each keV obtained from the U.S. National Institute of Standards and Technology (NIST). Results showed accurate iodine quantification (root mean square error of 0.5 mgI/cc) and accurate CT number of VMIs (percentage error of 8.9%) using the PCCT scanner. The overall performance of the PCCT scanner, in terms of iodine quantification and VMI CT number accuracy, was comparable to that of EID-based dual-source, dual-energy scanners.

Estimation of signal and noise for a whole-body research photon-counting CT system.

Photon-counting detector CT has a large number of acquisition parameters that require optimization, particularly the energy threshold configurations. Fast and accurate estimation of both signal and noise in photon-counting CT (PCCT) images can facilitate such optimization. Using the detector response function of a research PCCT system, we derived mathematical models for both signal and noise estimation, taking into account beam spectrum and filtration, object attenuation, water beam hardening, detector response, radiation dose, energy thresholds, and the propagation of noise. To determine the absolute noise value, a noise lookup table (LUT) for all available energy thresholds was acquired using a number of calibration scans. The noise estimation algorithm then used the noise LUT to estimate noise for scans with a variety of combination of energy thresholds, dose levels, and object attenuations. Validation of the estimation algorithms was performed on a whole-body research PCCT system using semianthropomorphic water phantoms and solutions of calcium and iodine. Clinical feasibility of noise estimation was assessed with scans of a cadaver head and a living swine. The algorithms achieved accurate estimation of both signal and noise for a variety of scanning parameter combinations. Maximum discrepancies were below 15%, while most errors were below 5%.

Noise performance of low-dose CT: comparison between an energy integrating detector and a photon counting detector using a whole-body research photon counting CT scanner.

Photon counting detector (PCD)-based computed tomography (CT) is an emerging imaging technique. Compared to conventional energy integrating detector (EID)-based CT, PCD-CT is able to exclude electronic noise that may severely impair image quality at low photon counts. This work focused on comparing the noise performance at low doses between the PCD and EID subsystems of a whole-body research PCD-CT scanner, both qualitatively and quantitatively. An anthropomorphic thorax phantom was scanned, and images of the shoulder portion were reconstructed. The images were visually and quantitatively compared between the two subsystems in terms of streak artifacts, an indicator of the impact of electronic noise. Furthermore, a torso-shaped water phantom was scanned using a range of tube currents. The product of the noise and the square root of the tube current was calculated, normalized, and compared between the EID and PCD subsystems. Visual assessment of the thorax phantom showed that electronic noise had a noticeably stronger degrading impact in the EID images than in the PCD images. The quantitative results indicated that in low-dose situations, electronic noise had a noticeable impact (up to a 5.8% increase in magnitude relative to quantum noise) on the EID images, but negligible impact on the PCD images.

Spectral prior image constrained compressed sensing (spectral PICCS) for photon-counting computed tomography.

Photon-counting computed tomography (PCCT) is an emerging imaging technique that enables multi-energy imaging with only a single scan acquisition. To enable multi-energy imaging, the detected photons corresponding to the full x-ray spectrum are divided into several subgroups of bin data that correspond to narrower energy windows. Consequently, noise in each energy bin increases compared to the full-spectrum data. This work proposes an iterative reconstruction algorithm for noise suppression in the narrower energy bins used in PCCT imaging. The algorithm is based on the framework of prior image constrained compressed sensing (PICCS) and is called spectral PICCS; it uses the full-spectrum image reconstructed using conventional filtered back-projection as the prior image. The spectral PICCS algorithm is implemented using a constrained optimization scheme with adaptive iterative step sizes such that only two tuning parameters are required in most cases. The algorithm was first evaluated using computer simulations, and then validated by both physical phantoms and in vivo swine studies using a research PCCT system. Results from both computer-simulation and experimental studies showed substantial image noise reduction in narrow energy bins (43-73%) without sacrificing CT number accuracy or spatial resolution.

Estimation of signal and noise for a whole-body photon counting research CT system.

Photon-counting CT (PCCT) may yield potential value for many clinical applications due to its relative immunity to electronic noise, increased geometric efficiency relative to current scintillating detectors, and the ability to resolve energy information about the detected photons. However, there are a large number of parameters that require optimization, particularly the energy thresholds configurations. Fast and accurate estimation of signal and noise in PCCT can benefit the optimization of acquisition parameters for specific diagnostic tasks. Based on the acquisition parameters and detector response of our research PCCT system, we derived mathematical models for both signal and noise. The signal model took the tube spectrum, beam filtration, object attenuation, water beam hardening, and detector response into account. The noise model considered the relationship between noise and radiation dose, as well as the propagation of noise as threshold data are subtracted to yield energy bin data. To determine the absolute noise value, a noise look-up table (LUT) was acquired using a limited number of calibration scans. The noise estimation algorithm then used the noise LUT to estimate noise for scans with a variety of combination of energy thresholds, dose levels, and object attenuation. Validation of the estimation algorithms was performed on our whole-body research PCCT system using semi-anthropomorphic water phantoms and solutions of calcium and iodine. The algorithms achieved accurate estimation of signal and noise for a variety of scanning parameter combinations. The proposed method can be used to optimize energy thresholds configuration for many clinical applications of PCCT.

How Low Can We Go in Radiation Dose for the Data-Completion Scan on a Research Whole-Body Photon-Counting Computed Tomography System.

PURPOSE: A research photon-counting computed tomography (CT) system that consists of an energy-integrating detector (EID) and a photon-counting detector (PCD) was installed in our laboratory. The scanning fields of view of the EID and PCD at the isocenter are 500 and 275 mm, respectively. When objects are larger than the PCD scanning field of view, a data-completion scan (DCS) using the EID subsystem is needed to avoid truncation artifacts in PCD images. The goals of this work were to (1) find the impact of a DCS on noise of PCD images and (2) determine the lowest possible dose for a DCS such that truncation artifacts are negligible in PCD images. METHODS: First, 2 semianthropomorphic abdomen phantoms were scanned on the PCD subsystem. For each PCD scan, we acquired 1 DCS with the maximum effective mAs and 5 with lower effective mAs values. The PCD image reconstructed using the maximum effective mAs was considered as the reference image, and those using the lower effective mAs as the test images. The PCD image reconstructed without a DCS was considered the baseline image. Each PCD image was assessed in terms of noise and CT number uniformity; the results were compared among the baseline, test, and reference images. Finally, the impact of a DCS on PCD image quality was qualitatively assessed for other body regions using an anthropomorphic torso phantom. RESULTS: The DCS had a negligible impact on the noise magnitude in the PCD images. The PCD images with the minimum available dose (CTDIvol < 2 mGy) showed greatly enhanced CT number uniformity compared with the baseline images without noticeable truncation artifacts. Further increasing the effective mAs of a DCS did not yield noticeable improvement in CT number uniformity. CONCLUSIONS: A DCS using the minimum available dose had negligible effect on image noise and was sufficient to maintain satisfactory CT number uniformity for the PCD scans.

Evaluation of conventional imaging performance in a research whole-body CT system with a photon-counting detector array.

This study evaluated the conventional imaging performance of a research whole-body photon-counting CT system and investigated its feasibility for imaging using clinically realistic levels of x-ray photon flux. This research system was built on the platform of a 2nd generation dual-source CT system: one source coupled to an energy integrating detector (EID) and the other coupled to a photon-counting detector (PCD). Phantom studies were conducted to measure CT number accuracy and uniformity for water, CT number energy dependency for high-Z materials, spatial resolution, noise, and contrast-to-noise ratio. The results from the EID and PCD subsystems were compared. The impact of high photon flux, such as pulse pile-up, was assessed by studying the noise-to-tube-current relationship using a neonate water phantom and high x-ray photon flux. Finally, clinical feasibility of the PCD subsystem was investigated using anthropomorphic phantoms, a cadaveric head, and a whole-body cadaver, which were scanned at dose levels equivalent to or higher than those used clinically. Phantom measurements demonstrated that the PCD subsystem provided comparable image quality to the EID subsystem, except that the PCD subsystem provided slightly better longitudinal spatial resolution and about 25% improvement in contrast-to-noise ratio for iodine. The impact of high photon flux was found to be negligible for the PCD subsystem: only subtle high-flux effects were noticed for tube currents higher than 300 mA in images of the neonate water phantom. Results of the anthropomorphic phantom and cadaver scans demonstrated comparable image quality between the EID and PCD subsystems. There were no noticeable ring, streaking, or cupping/capping artifacts in the PCD images. In addition, the PCD subsystem provided spectral information. Our experiments demonstrated that the research whole-body photon-counting CT system is capable of providing clinical image quality at clinically realistic levels of x-ray photon flux.

Extended ellipse-line-ellipse trajectory for long-object cone-beam imaging with a mounted C-arm system.

Recent reports show that three-dimensional cone-beam (CB) imaging with a floor-mounted (or ceiling-mounted) C-arm system has become a valuable tool in interventional radiology. Currently, a circular short scan is used for data acquisition, which inevitably yields CB artifacts and a short coverage in the direction of the patient table. To overcome these two limitations, a more sophisticated data acquisition geometry is needed. This geometry should be complete in terms of Tuy's condition and should allow continuous scanning, while being compatible with the mechanical constraints of mounted C-arm systems. Additionally, the geometry should allow accurate image reconstruction from truncated data. One way to ensure such a feature is to adopt a trajectory that provides full R-line coverage within the field-of-view (FOV). An R-line is any segment of line that connects two points on a source trajectory, and the R-line coverage is the set of points that belong to an R-line. In this work, we propose a novel geometry called the extended ellipse-line-ellipse (ELE) for long-object imaging with a mounted C-arm system. This trajectory is built from modules consisting of two elliptical arcs connected by a line. We demonstrate that the extended ELE can be configured in many ways so that full R-line coverage is guaranteed. Both tight and relaxed parametric settings are presented. All results are supported by extensive mathematical proofs provided in appendices. Our findings make the extended ELE trajectory attractive for axially-extended FOV imaging in interventional radiology.

Human Imaging With Photon Counting-Based Computed Tomography at Clinical Dose Levels: Contrast-to-Noise Ratio and Cadaver Studies.

OBJECTIVES: The purpose of this work was to measure and compare the iodine contrast-to-noise ratio (CNR) between a commercial energy-integrating detector (EID) computed tomography (CT) system and a photon-counting detector (PCD) CT scanner capable of human imaging at clinical dose rates, as well as to determine clinical feasibility using human cadavers. MATERIALS AND METHODS: A research dual-source PCD-CT scanner was used, where the "A" tube/detector subsystem used an EID and the "B" tube/detector subsystem used a PCD. Iodine CNR was measured in 4 anthropomorphic phantoms, simulating 4 patient sizes, at 4 tube potential settings. After biospecimen committee approval, PCD scans were performed on a fresh-frozen human head and a whole-body cadaver using clinical dose rates. Scans were repeated using the EID and identical parameters, and qualitative side-by-side comparisons were performed. RESULTS: For the same photon fluence, phantom measurements demonstrated a mean increase in CNR of 11%, 23%, 31%, 38% for the PCD system, relative to the EID system, at 80, 100, 120, and 140 kV, respectively. Photon-counting detector CT additionally provided energy-selective imaging, where low- and high-energy images reflected the energy dependence of the iodine signal. Photon-counting detector images of cadaveric anatomy demonstrated decreased beam hardening and calcium blooming in the high-energy bin images and increased contrast in the low-energy bins images relative to the EID images. Threshold-based PCD images were qualitatively deemed equivalent in other aspects. CONCLUSIONS: The evaluated research PCD-CT system was capable of clinical levels of image quality at clinical dose rates. It further provided improved CNR relative to state-of-the-art EID-CT. The energy-selective bin images provide further opportunity for dual-energy and multienergy analyses.

Dose-efficient ultrahigh-resolution scan mode using a photon counting detector computed tomography system.

An ultrahigh-resolution (UHR) data collection mode was enabled on a whole-body, research photon counting detector (PCD) computed tomography system. In this mode, 64 rows of [Formula: see text] detector pixels were used, which corresponded to a pixel size of [Formula: see text] at the isocenter. Spatial resolution and image noise were quantitatively assessed for the UHR PCD scan mode, as well as for a commercially available UHR scan mode that uses an energy-integrating detector (EID) and a set of comb filters to decrease the effective detector size. Images of an anthropomorphic lung phantom, cadaveric swine lung, swine heart specimen, and cadaveric human temporal bone were qualitatively assessed. Nearly equivalent spatial resolution was demonstrated by the modulation transfer function measurements: 15.3 and [Formula: see text] spatial frequencies were achieved at 10% and 2% modulation, respectively, for the PCD system and 14.2 and [Formula: see text] for the EID system. Noise was 29% lower in the PCD UHR images compared to the EID UHR images, representing a potential dose savings of 50% for equivalent image noise. PCD UHR images from the anthropomorphic phantom and cadaveric specimens showed clear delineation of small structures.

Technical Note: Development and validation of an open data format for CT projection data.

PURPOSE: Lack of access to projection data from patient CT scans is a major limitation for development and validation of new reconstruction algorithms. To meet this critical need, this work developed and validated a vendor-neutral format for CT projection data, which will further be employed to build a library of patient projection data for public access. METHODS: A digital imaging and communication in medicine (DICOM)-like format was created for CT projection data (CT-PD), named the DICOM-CT-PD format. The format stores attenuation information in the DICOM image data block and stores parameters necessary for reconstruction in the DICOM header under various tags (51 tags to store the geometry and scan parameters and 9 tags to store patient information). To validate the accuracy and completeness of the new format, CT projection data from helical scans of the ACR CT accreditation phantom were acquired from two clinical CT scanners (Somatom Definition Flash, Siemens Healthcare, Forchheim, Germany and Discovery CT750 HD, GE Healthcare, Waukesha, WI). After decoding (by the authors for Siemens, by the manufacturer for GE), the projection data were converted to the DICOM-CT-PD format. Off-line CT reconstructions were performed by internal and external reconstruction researchers using only the information stored in the DICOM-CT-PD files and the DICOM-CT-PD field definitions. RESULTS: Compared with the commercially reconstructed CT images, the off-line reconstructed images created using the DICOM-CT-PD format are similar in terms of CT numbers (differences of 5 HU for the bone insert and -9 HU for the air insert), image noise (±1 HU), and low contrast detectability (6 mm rods visible in both). Because of different reconstruction approaches, slightly different in-plane and cross-plane high contrast spatial resolution were obtained compared to those reconstructed on the scanners (axial plane: GE off-line, 7 lp/cm; GE commercial, 7 lp/cm; Siemens off-line, 8 lp/cm; Siemens commercial, 7 lp/cm. Coronal plane: Siemens off-line, 6 lp/cm; Siemens commercial, 8 lp/cm). CONCLUSIONS: A vendor-neutral extended DICOM format has been developed that enables open sharing of CT projection data from third-generation CT scanners. Validation of the format showed that the geometric parameters and attenuation information in the DICOM-CT-PD file were correctly stored, could be retrieved with use of the provided instructions, and contained sufficient data for reconstruction of CT images that approximated those from the commercial scanner.

Lesion insertion in the projection domain: Methods and initial results.

PURPOSE: To perform task-based image quality assessment in CT, it is desirable to have a large number of realistic patient images with known diagnostic truth. One effective way of achieving this objective is to create hybrid images that combine patient images with inserted lesions. Because conventional hybrid images generated in the image domain fails to reflect the impact of scan and reconstruction parameters on lesion appearance, this study explored a projection-domain approach. METHODS: Lesions were segmented from patient images and forward projected to acquire lesion projections. The forward-projection geometry was designed according to a commercial CT scanner and accommodated both axial and helical modes with various focal spot movement patterns. The energy employed by the commercial CT scanner for beam hardening correction was measured and used for the forward projection. The lesion projections were inserted into patient projections decoded from commercial CT projection data. The combined projections were formatted to match those of commercial CT raw data, loaded onto a commercial CT scanner, and reconstructed to create the hybrid images. Two validations were performed. First, to validate the accuracy of the forward-projection geometry, images were reconstructed from the forward projections of a virtual ACR phantom and compared to physically acquired ACR phantom images in terms of CT number accuracy and high-contrast resolution. Second, to validate the realism of the lesion in hybrid images, liver lesions were segmented from patient images and inserted back into the same patients, each at a new location specified by a radiologist. The inserted lesions were compared to the original lesions and visually assessed for realism by two experienced radiologists in a blinded fashion. RESULTS: For the validation of the forward-projection geometry, the images reconstructed from the forward projections of the virtual ACR phantom were consistent with the images physically acquired for the ACR phantom in terms of Hounsfield unit and high-contrast resolution. For the validation of the lesion realism, lesions of various types were successfully inserted, including well circumscribed and invasive lesions, homogeneous and heterogeneous lesions, high-contrast and low-contrast lesions, isolated and vessel-attached lesions, and small and large lesions. The two experienced radiologists who reviewed the original and inserted lesions could not identify the lesions that were inserted. The same lesion, when inserted into the projection domain and reconstructed with different parameters, demonstrated a parameter-dependent appearance. CONCLUSIONS: A framework has been developed for projection-domain insertion of lesions into commercial CT images, which can be potentially expanded to all geometries of CT scanners. Compared to conventional image-domain methods, the authors' method reflected the impact of scan and reconstruction parameters on lesion appearance. Compared to prior projection-domain methods, the authors' method has the potential to achieve higher anatomical complexity by employing clinical patient projections and real patient lesions.

Segmented slant hole collimator for stationary cardiac SPECT: Monte Carlo simulations.

PURPOSE: This work is a preliminary study of a stationary cardiac SPECT system. The goal of this research is to propose a stationary cardiac SPECT system using segmented slant-hole collimators and to perform computer simulations to test the feasibility. Compared to the rotational SPECT, a stationary system has a benefit of acquiring temporally consistent projections. The most challenging issue in building a stationary system is to provide sufficient projection view-angles. METHODS: A GATE (GEANT4 application for tomographic emission) Monte Carlo model was developed to simulate a two-detector stationary cardiac SPECT that uses segmented slant-hole collimators. Each detector contains seven segmented slant-hole sections that slant to a common volume at the rotation center. Consequently, 14 view-angles over 180° were acquired without any gantry rotation. The NCAT phantom was used for data generation and a tailored maximum-likelihood expectation-maximization algorithm was used for image reconstruction. Effects of limited number of view-angles and data truncation were carefully evaluated in the paper. RESULTS: Simulation results indicated that the proposed segmented slant-hole stationary cardiac SPECT system is able to acquire sufficient data for cardiac imaging without a loss of image quality, even when the uptakes in the liver and kidneys are high. Seven views are acquired simultaneously at each detector, leading to 5-fold sensitivity gain over the conventional dual-head system at the same total acquisition time, which in turn increases the signal-to-noise ratio by 19%. The segmented slant-hole SPECT system also showed a good performance in lesion detection. In our prototype system, a short hole-length was used to reduce the dead zone between neighboring collimator segments. The measured sensitivity gain is about 17-fold over the conventional dual-head system. CONCLUSIONS: The gate Monte Carlo simulations confirm the feasibility of the proposed stationary cardiac SPECT system with segmented slant-hole collimators. The proposed collimator consists of combined parallel and slant holes, and the image on the detector is not reduced in size.

Image-based Material Decomposition with a General Volume Constraint for Photon-Counting CT.

Photon-counting CT (PCCT) potentially offers both improved dose efficiency and material decomposition capabilities relative to CT systems using energy integrating detectors. With respect to material decomposition, both projection-based and image-based methods have been proposed, most of which require accurate a priori information regarding the shape of the x-ray spectra and the response of the detectors. Additionally, projection-based methods require access to projection data. These data can be difficult to obtain, since spectra, detector response, and projection data formats are proprietary information. Further, some published image-based, 3-material decomposition methods require a volume conservation assumption, which is often violated in solutions. We have developed an image-based material decomposition method that can overcome those limitations. We introduced a general condition on volume constraint that does not require the volume to be conserved in a mixture. An empirical calibration can be performed with various concentrations of basis materials. The material decomposition method was applied to images acquired from a prototype whole-body PCCT scanner. The results showed good agreement between the estimation and known mass concentration values. Factors affecting the performance of material decomposition, such as energy threshold configuration and volume conservation constraint, were also investigated. Changes in accuracy of the mass concentration estimates were demonstrated for four different energy configurations and when volume conservation was assumed.

Lesion Insertion in Projection Domain for Computed Tomography Image Quality Assessment.

To perform task-based image quality assessment in CT, it is desirable to have a large number of realistic patient images with known diagnostic truth. One effective way to achieve this objective is to create hybrid images that combine patient images with simulated lesions. Because conventional hybrid images generated in the image-domain fails to reflect the impact of scan and reconstruction parameters on lesion appearance, this study explored a projection-domain approach. Liver lesion models were forward projected according to the geometry of a commercial CT scanner to acquire lesion projections. The lesion projections were then inserted into patient projections (decoded from commercial CT raw data with the assistance of the vendor) and reconstructed to acquire hybrid images. To validate the accuracy of the forward projection geometry, simulated images reconstructed from the forward projections of a digital ACR phantom were compared to physically acquired ACR phantom images. To validate the hybrid images, lesion models were inserted into patient images and visually assessed. Results showed that the simulated phantom images and the physically acquired phantom images had great similarity in terms of HU accuracy and high-contrast resolution. The lesions in the hybrid image had a realistic appearance and merged naturally into the liver background. In addition, the inserted lesion demonstrated reconstruction-parameter-dependent appearance. Compared to conventional image-domain approach, our method enables more realistic hybrid images for image quality assessment.

Geometric Calibration and Image Reconstruction for a Segmented Slant-Hole Stationary Cardiac SPECT System.

UNLABELLED: A dedicated stationary cardiac single-photon emission computed tomography (SPECT) system with a novel segmented slant-hole collimator has been developed. The goal of this paper is to calibrate this new imaging geometry with a point source. METHODS: Unlike the commercially available dedicated cardiac SPECT systems, which are specialized and can be used only to image the heart, our proposed cardiac system is based on a conventional SPECT system but with a segmented slant-hole collimator replacing the collimator. For a dual-head SPECT system, 2 segmented collimators, each with 7 sections, are arranged in an L-shaped configuration such that they can produce a complete cardiac SPECT image with only one gantry position. A calibration method was developed to estimate the geometric parameters of each collimator section as well as the detector rotation radius, under the assumption that the point source location is calculated using the central-section data. With a point source located off the rotation axis, geometric parameters for each collimator section can be estimated independently. The parameters estimated individually are further improved by a joint objective function that uses all collimator sections simultaneously and incorporates the collimator symmetry information. RESULTS: Estimation results and images reconstructed from estimated parameters are presented for both simulated and real data acquired from a prototype collimator. The calibration accuracy was validated by computer simulations with an error of about 0.1° for the slant angles and about 1 mm for the rotation radius. Reconstructions of a heart-insert phantom did not show any image artifacts of inaccurate geometric parameters. CONCLUSION: Compared with the detector's intrinsic resolution, the estimation error is small and can be ignored. Therefore, the accuracy of the calibration is sufficient for cardiac SPECT imaging.

Axially extended-volume C-arm CT using a reverse helical trajectory in the interventional room.

C-arm computed tomography (CT) is an innovative technique that enables a C-arm system to generate 3-D images from a set of 2-D X-ray projections. This technique can reduce treatment-related complications and may improve interventional efficacy and safety. However, state-of-the-art C-arm systems rely on a circular short scan for data acquisition, which limits coverage in the axial direction. This limitation was reported as a problem in hepatic vascular interventions. To solve this problem, as well as to further extend the value of C-arm CT, axially extended-volume C-arm CT is needed. For example, such an extension would enable imaging the full aorta, the peripheral arteries or the spine in the interventional room, which is currently not feasible. In this paper, we demonstrate that performing long object imaging using a reverse helix is feasible in the interventional room. This demonstration involved developing a novel calibration method, assessing geometric repeatability, implementing a reconstruction method that applies to real reverse helical data, and quantitatively evaluating image quality. Our results show that: 1) the reverse helical trajectory can be implemented and reliably repeated on a multiaxis C-arm system; and 2) a long volume can be reconstructed with satisfactory image quality using reverse helical data.