Dual-source photon-counting CT: impact of residual cross-scatter on quantitative spectral results

Dual-source photon-counting CT combines the high temporal resolution and high pitch of dual-source CT with the material quantification capabilities of photon-counting CT. It, however, results in cross-scatter that increases in severity with increased patient size and collimation. This cross-scatter must be corrected to ensure the removal of scatter artifacts and improve quantitative accuracy. To evaluate residual cross-scatter of a first-generation dual-source photon-counting CT and the effect of phantom size, collimation, and radiation dose, a phantom was scanned in single- and dual-source modes with and without its extension ring at three collimations and three radiation doses. Virtual monoenergetic images (VMI) at 50 keV, VMI 150 keV, and iodine density maps were reconstructed to determine variation between acquisition parameters in single- and dual-source modes. Additionally, differences relative to single-source acquisitions and to single-source and small collimation acquisitions were calculated to reflect residual cross-scatter with and without matched collimation. At VMI 50 keV, inserts exhibited accuracy and similar variation between single- and dual-source modes, averaging 5.4 ± 2.6 and 6.2 ± 2.5 HU, respectively, across phantom size, collimation, and radiation dose. Differences relative to single-source measured 5.1 ± 8.5 and 0.4 ± 4.2 HU while differences relative to single-source and small collimation acquisitions were 6.4 ± 10.8 HU and -0.5 ± 3.9 HU for VMI 50 and 150 keV, respectively. This minimal residual cross-scatter increases confidence in the quantitative accuracy of spectral results necessary for clinical applications of dual-source photon-counting CT with motion, such as cardiac imaging.

Quantitative Dual-Energy X-ray Imaging Based on K-Edge Absorption Difference

Conventional flat panel X-ray imaging (FPXI) employs a single scintillator for X-ray conversion, which lacks energy spectrum information. The recent innovation of employing multilayer scintillators offers a route for multispectral X-ray imaging. However, the principles guiding optimal multilayer scintillator configuration selection and quantitative analysis models remain largely unexplored. Here, we propose to adopt the K-edge absorption coefficient as a key parameter for selecting tandem scintillator combinations and to utilize the coefficient matrix to calculate the absorption efficiency spectrum of the sample. Through a dual scintillator example comprising C4H12NMnCl3 and Cs3Cu2I5, we establish a streamlined quantitative framework for deducing X-ray spectra from scintillation spectra, with an average relative error of 6.28% between the calculated and measured sample absorption spectrum. This insight forms the foundation for our quantitative method to distinguish the material densities. Leveraging this tandem scintillator configuration, in conjunction with our analytical tools, we successfully demonstrate the inherent merits of dual-energy X-ray imaging for discerning materials with varied densities and thicknesses.

Evaluation of the quantitative performance of non-enhanced dual-energy CT X-map in detecting acute ischemic brain stroke: A model observer study using computer simulation

PURPOSE

A simulation study was performed to evaluate the quantitative performance of X-map images-derived from non-enhanced (NE) dual-energy computed tomography (DECT)-in detecting acute ischemic stroke (AIS) compared with that of NE-DECT mixed images.

METHODS

A virtual phantom, 150 mm in diameter, filled with tissues comprising various gray- and white-matter proportions was used to generate pairs of NE-head images at 80 kV and Sn150 kV at three dose levels (20, 40, and 60 mGy). The phantom included an inserted low-contrast object, 15 mm in diameter, with four densities (0%, 5%, 10%, and 15%) mimicking ischemic edema. Mixed and X-map images were generated from these sets of images and compared in terms of detectability of ischemic edema using a channelized Hotelling observer (CHO). The area under the curve (AUC) of the receiver operating characteristic that generated CHO for each condition was used as a figure of merit.

RESULTS

The AUCs of X-map images were always significantly higher than those of mixed images (P < 0.001). The improvement in AUC for X-map images compared with that for mixed images at edema densities was 9.2%-12.6% at 20 mGy, 10.1%-17.7% at 40 mGy, and 14.0%-19.4% at 60 mGy. At any edema density, X-map images at 20 mGy resulted in higher AUCs than mixed images acquired at any other dose level (P < 0.001), which corresponded to a 66% dose reduction on X-map images.

CONCLUSIONS

The simulation study confirmed that NE-DECT X-map images have superior capability of detecting AIS than NE-DECT mixed images.

Learning-based synthetic dual energy CT imaging from single energy CT for stopping power ratio calculation in proton radiation therapy

OBJECTIVE

Dual energy CT (DECT) has been shown to estimate stopping power ratio (SPR) map with a higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. This work presents a learning-based method to synthesize DECT images from SECT image for proton radiotherapy.

METHODS

The proposed method uses a residual attention generative adversarial network. Residual blocks with attention gates were used to force the model to focus on the difference between DECT images and SECT images. To evaluate the accuracy of the method, we retrospectively investigated 70 head-and-neck cancer patients whose DECT and SECT scans were acquired simultaneously. The model was trained to generate both a high and low energy DECT image based on a SECT image. The generated synthetic low and high DECT images were evaluated against the true DECT images using leave-one-out cross-validation. To evaluate our method in the context of a practical application, we generated SPR maps from synthetic DECT (sDECT) using a dual-energy based stoichiometric method and compared the SPR maps to those generated from DECT. A dosimetric comparison for dose obtained from DECT was performed against that derived from sDECT.

RESULTS

The mean of mean absolute error, peak signal-to-noise ratio and normalized cross-correlation for the synthetic high and low energy CT images was 36.9 HU, 29.3 dB, 0.96 and 35.8 HU, 29.2 dB, and 0.96, respectively. The corresponding SPR maps generated from synthetic DECT showed an average normalized mean square deviation of about 1% with reduced noise level and artifacts than those from original DECT. Dose-volume histogram (DVH) metrics for the clinical target volume agree within 1% between the DECT and sDECT calculated dose.

CONCLUSION

Our method synthesized accurate DECT images and showed a potential feasibility for proton SPR map generation.

ADVANCES IN KNOWLEDGE

This study investigated a learning-based method to synthesize DECT images from SECT image for proton radiotherapy.

The ultrafast, high-pitch turbo FLASH mode of third-generation dual-source CT: Effect of different pitch and corresponding SFOV on image quality in a phantom study

PURPOSE

To investigate the effect of different pitches and corresponding scan fields of view (SFOVs) on the image quality in the ultrafast, high-pitch turbo FLASH mode of the third-generation dual-source CT using an anthropomorphic phantom.

METHODS

The phantom was scanned using the ultrafast, high-pitch turbo FLASH protocols of the third-generation dual-source CT with the different pitches and corresponding SFOVs (pitches: 1.55 to 3.2 with increments of 0.1, SFOVs: 50 cm to 35.4 cm). The objective parameters such as the CT number, image noises, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and artifacts index (AI), and image features from the head, chest, and abdomen were compared between the CT images with a pitch of 1.55 and SFOV of Ø 50 cm and a pitch of 3.2 and SFOV of Ø 35.4 cm. Then, the 18 series of CT images of the head, chest, and abdomen were evaluated by three radiologists independently.

RESULTS

The differences in the CT numbers were not statically significant between the CT images with a pitch of 1.55 and SFOV of Ø 50 cm and a pitch of 3.2 and SFOV of Ø 35.4 cm from most body parts and potential combinations (p > 0.05), Most of the image noises and the AI from the images with the pitch of 1.55 were significantly lower than those with the pitch of 3.2 (p < 0.05), and the SNR and CNR from the images with the pitch of 1.55 were higher than those with the pitch of 3.2. There were significant differences in the first-order features and texture features of the head (59.3%, 28.3%), chest (66%, 35.7%), and abdomen (71.6%, 64.7%) (p < 0.05). The subjective image quality was excellent when the pitch was less than 2.0 and gradually decreased with the increasing pitch. In addition, the image quality decreased significantly when the pitch was higher than 3.0 (all k≥0.69), especially in the head and chest.

CONCLUSIONS

In the ultrafast, high-pitch turbo FLASH mode of the third-generation DSCT, increasing the pitch and lowering the corresponding SFOV will change the image features and cause more artifacts degrading the image quality. Specific to the clinical needs, decreasing the pitch not only can expand the SFOV but also can improve the image quality.

Principles and Applications of Dual Energy Computed Tomography in Neuroradiology

Dual-energy computed tomography (DE CT) is a promising tool with many current and evolving applications. Available DE CT scanners usually consist of one or two tubes, or use layered detectors for spectral separation. Most DE CT scanners can be used in single energy or dual-energy mode, except for the layered detector scanners that always acquire data in dual-energy mode. However, the layered detector scanners can retrospectively integrate the data from two layers to obtain conventional single energy images. DE CT mode enables generation of virtual monochromatic images, blended images, iodine quantification, improving conspicuity of iodinated contrast enhancement, and material decomposition maps or more sophisticated quantitative analysis not possible with conventional SE CT acquisition with an acceptable or even lower dose than the SE CT. This article reviews the basic principles of dual-energy CT and highlights many of its clinical applications in the evaluation of neurological conditions.

Computed tomography recent history and future perspectives

Purpose: We provide a review of the key computed tomography (CT) technologies developed since the late 1980s and offer an overview of one of the future technologies under development. The focus of this review is mainly on the hardware and system development. The topics on the historical event linked to the early days of CT development and other innovations that contributed to the CT development, such as advanced image reconstruction techniques, are covered by companion papers in this special issue. Approach: The review is divided into five major sections, each linked to a key innovation in CT: helical spiral data acquisition, multi-slice CT, wide-cone CT, dual-source CT, and spectral CT. Given the limited scope of this review, only one of the future technologies, photon-counting CT, is discussed in detail. Whenever possible, both theory of operation and clinical examples are provided. Results: Theoretical analyses, phantom results, and clinical examples clearly demonstrate the efficacy and clinical relevancy of five historical technology developments and one future technology in CT. These technologies have improved and will continue to improve CT performance in terms of isotropic volume coverage, improved temporal resolution, and material differentiation and characterization capabilities. Conclusions: Over the past 30 years, technological developments of CT have contributed to the success of CT in many clinical applications such as trauma, oncology, cardiac imaging, and stroke. Advanced clinical applications have and will continue to demand more advanced technology development.

Energy-integrating-detector multi-energy CT: Implementation and a phantom study

PURPOSE

Multi-energy computed tomography (MECT) has a great potential to enable many novel clinical applications such as simultaneous multi-contrast imaging. The purpose of this study was to implement triple-beam MECT on a traditional energy-integrating-detector (EID) CT platform (EID-MECT).

METHODS

This was accomplished by mounting a z-axis split-filter (0.05 mm Au, 0.6 mm Sn) on Tube A of a dual-source EID CT scanner. With the two split x-ray beams from Tube A and the third beam from Tube B, three beams with different x-ray spectra can be simultaneously acquired. With Tube B operated at 70 or 80 kV and Tube A at 120 or 140 kV, four different triple-beam configurations were calibrated for MECT measurements: 70/Au120/Sn120, 80/Au120/Sn120, 70/Au140/Sn140, and 80/Au140/Sn140 kV. Iodine (I), gadolinium (Gd), bismuth (Bi) samples, and their mixtures were prepared for 2 three-material-decomposition tasks and 1 four-material-decomposition task. For each task, samples were placed in a water phantom and scanned using each of the four triple-beam configurations. For comparison, the same phantom was also scanned using three other dual-energy CT (DECT) or MECT technologies: twin-beam DECT (TB-DECT), dual-source DECT (DS-DECT), and photon-counting-detector CT (PCD-CT), all with optimal x-ray spectrum settings and at equal volume CT dose index (CTDIvol). The phantom for four-material decomposition (I/Gd/Bi/Water imaging) was scanned using the PCD-CT only (140 kV with 25, 50, 75, and 90 keV). Image-based material decomposition was performed to acquire material-specific images, on which the mean basis material concentrations and noise levels were measured and compared across all triple-beam configurations in EID-MECT and various DECT/MECT systems.

RESULTS

The optimal triple-beam configuration was task-dependent with 70/Au120/Sn120, 70/Au140/Sn140, and 70/Au120/Sn120 kV for I/Gd/Water, I/Bi/Water, and I/Gd/Bi/Water material decomposition tasks, respectively. At equal radiation dose level, EID-MECT provided comparable or better quantification accuracy in material-specific images for all three material decomposition tasks, compared to EID-based DECT and PCD-CT systems. In terms of noise level comparison, EID-MECT-derived material-specific images showed lower noise levels than TB-DECT and DS-DECT, but slightly higher than that from PCD-CT in I/Gd/Water imaging. For I/Bi/Water imaging, EID-MECT showed a comparable noise level to DS-DECT, and a much lower noise level than TB-DECT and PCD-CT in all material-specific images. For the four-material decomposition task involving I/Gd/Bi/Water, the bismuth-specific image derived from EID-MECT was slightly noisier, but both iodine- and gadolinium-specific images showed much lower noise levels in comparison to PCD-CT.

CONCLUSIONS

For the first time, an EID-based MECT system that can simultaneously acquire three x-ray spectra measurements was implemented on a clinical scanner, which demonstrated comparable or better imaging performance than existing DECT and MECT systems.

Deep learning-based forward and cross-scatter correction in dual-source CT

PURPOSE

Dual-source computed tomography (DSCT) uses two source-detector pairs offset by about 90°. In addition to the well-known forward scatter, a special issue in DSCT is cross-scattered radiation from X-ray tube A detected in the detector of system B and vice versa. This effect can lead to artifacts and reduction of the contrast-to-noise ratio of the images. The purpose of this work is to present and evaluate different deep learning-based methods for scatter correction in DSCT.

METHODS

We present different neural network-based methods for forward and cross-scatter correction in DSCT. These deep scatter estimation (DSE) methods mainly differ in the input and output information that is provided for training and inference and in whether they operate on two-dimensional (2D) or on three-dimensional (3D) data. The networks are trained and validated with scatter distributions obtained by our in-house Monte Carlo simulation. The simulated geometry is adapted to a realistic clinical setup.

RESULTS

All DSE approaches reduce scatter-induced artifacts and lead to superior results than the measurement-based scatter correction. Forward scatter, under the presence of cross-scatter, is best estimated either by our network that uses the current projection and a couple of neighboring views (fDSE 2D few views) or by our 3D network that processes all projections simultaneously (fDSE 3D). Cross-scatter, under the presence of forward scatter, is best estimated using xSSE XDSE 2D, with xSSE referring to a quick single scatter estimate of cross scatter, or by xDSE 3D that uses all projections simultaneously. By using our proposed networks, the total scatter error in dual could be reduced from about 18 HU to approximately 3 HU.

CONCLUSIONS

Deep learning-based scatter correction can reduce scatter artifacts in DSCT. To achieve more accurate cross-scatter estimations, the use of a cross-scatter approximation improves the results. Also, the ability to leverage across different projection angles improves the precision of the algorithm.

Nonlinear reconstruction of coded spectral X-ray CT based on material decomposition

Coded spectral X-ray computed tomography (CT) based on K-edge filtered illumination is a cost-effective approach to acquire both 3-dimensional structure of objects and their material composition. This approach allows sets of incomplete rays from sparse views or sparse rays with both spatial and spectral encoding to effectively reduce the inspection duration or radiation dose, which is of significance in biological imaging and medical diagnostics. However, reconstruction of spectral CT images from compressed measurements is a nonlinear and ill-posed problem. This paper proposes a material-decomposition-based approach to directly solve the reconstruction problem, without estimating the energy-binned sinograms. This approach assumes that the linear attenuation coefficient map of objects can be decomposed into a few basis materials that are separable in the spectral and space domains. The nonlinear problem is then converted to the reconstruction of the mass density maps of the basis materials. The dimensionality of the optimization variables is thus effectively reduced to overcome the ill-posedness. An alternating minimization scheme is used to solve the reconstruction with regularizations of weighted nuclear norm and total variation. Compared to the state-of-the-art reconstruction method for coded spectral CT, the proposed method can significantly improve the reconstruction quality. It is also capable of reconstructing the spectral CT images at two additional energy bins from the same set of measurements, thus providing more spectral information of the object.

Learning-Based Stopping Power Mapping on Dual-Energy CT for Proton Radiation Therapy

Purpose

Dual-energy computed tomography (DECT) has been used to derive relative stopping power (RSP) maps by obtaining the energy dependence of photon interactions. The DECT-derived RSP maps could potentially be compromised by image noise levels and the severity of artifacts when using physics-based mapping techniques. This work presents a noise-robust learning-based method to predict RSP maps from DECT for proton radiation therapy.

Materials and Methods

The proposed method uses a residual attention cycle-consistent generative adversarial network to bring DECT-to-RSP mapping close to a 1-to-1 mapping by introducing an inverse RSP-to-DECT mapping. To evaluate the proposed method, we retrospectively investigated 20 head-and-neck cancer patients with DECT scans in proton radiation therapy simulation. Ground truth RSP values were assigned by calculation based on chemical compositions and acted as learning targets in the training process for DECT datasets; they were evaluated against results from the proposed method using a leave-one-out cross-validation strategy.

Results

The predicted RSP maps showed an average normalized mean square error of 2.83% across the whole body volume and an average mean error less than 3% in all volumes of interest. With additional simulated noise added in DECT datasets, the proposed method still maintained a comparable performance, while the physics-based stoichiometric method suffered degraded inaccuracy from increased noise level. The average differences from ground truth in dose volume histogram metrics for clinical target volumes were less than 0.2 Gy for D_95% and D_max with no statistical significance. Maximum difference in dose volume histogram metrics of organs at risk was around 1 Gy on average.

Conclusion

These results strongly indicate the high accuracy of RSP maps predicted by our machine-learning–based method and show its potential feasibility for proton treatment planning and dose calculation.

Principles and applications of dual source CT

This article describes the technical principles and clinical applications of dual source CT. A dual source CT (DSCT) is a CT system with two x-ray tubes and two detectors at an angle of approximately 90°. Both measurement systems acquire CT scan data simultaneously at the same anatomical level of the patient (same z-position). DSCT provides temporal resolution of approximately a quarter of the gantry rotation time for cardiac, cardio-thoracic and pediatric imaging. Successful imaging of the heart and the coronary arteries at high and variable heart rates has been demonstrated. DSCT systems can be operated at twice the spiral pitch of single source CT systems (up to pitch 3.2). The resulting high table speed is beneficial for pediatric applications and fast CT angiographic scans, e. g. of the aorta or the extremities. Operating both X-ray tubes at different tube potential (kV) enables the acquisition of dual energy data and the corresponding applications such as monoenergetic imaging and computation of material maps. Spectral separation can be improved by different filtration of the X-ray beams of both X-ray tubes. As a downside, DSCT systems have to cope with some challenges, among them the limited size of the second measurement system, and cross-scattered radiation.

Spectral Computed Tomography: Fundamental Principles and Recent Developments

CT is a diagnostic tool with many clinical applications. The CT voxel intensity is related to the magnitude of X-ray attenuation, which is not unique to a given material. Substances with different chemical compositions can be represented by similar voxel intensities, making the classification of different tissue types challenging. Compared to the conventional single-energy CT, spectral CT is an emerging technology offering superior material differentiation, which is achieved using the energy dependence of X-ray attenuation in any material. A specific form of spectral CT is dual-energy imaging, in which an additional X-ray attenuation measurement is obtained at a second X-ray energy. Dual-energy CT has been implemented in clinical settings with great success. This paper reviews the theoretical basis and practical implementation of spectral/dual-energy CT.

Ventilation/Perfusion Relationships and Gas Exchange: Measurement Approaches

Ventilation-perfusion ( V ˙ A / Q ˙ ) matching, the regional matching of the flow of fresh gas to flow of deoxygenated capillary blood, is the most important mechanism affecting the efficiency of pulmonary gas exchange. This article discusses the measurement of V ˙ A / Q ˙ matching with three broad classes of techniques: (i) those based in gas exchange, such as the multiple inert gas elimination technique (MIGET); (ii) those derived from imaging techniques such as single-photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance imaging (MRI), computed tomography (CT), and electrical impedance tomography (EIT); and (iii) fluorescent and radiolabeled microspheres. The focus is on the physiological basis of these techniques that provide quantitative information for research purposes rather than qualitative measurements that are used clinically. The fundamental equations of pulmonary gas exchange are first reviewed to lay the foundation for the gas exchange techniques and some of the imaging applications. The physiological considerations for each of the techniques along with advantages and disadvantages are briefly discussed. © 2020 American Physiological Society. Compr Physiol 10:1155-1205, 2020.

Dose and blending fraction quantification for adaptive statistical iterative reconstruction based on low-contrast detectability in abdomen CT

Purpose

The utilization of iterative reconstruction makes it difficult to identify the dose‐noise relationship, resulting in empirical design of scan protocols and inconsistent conclusions on dose reduction for consistent image quality. This study was to quantitatively determine the dose and the blending fraction of adaptive statistical iterative reconstruction (ASIR) based on the specified low‐contrast detectability (LCD).

Methods

A tissue equivalent abdomen phantom and a GE discovery 750 HD computed tomography (CT) were utilized. The normality of the noise distribution was tested at various spatial scales (2.1–9.8 mm) in the presence of ASIR (10–100%) with a wide range of doses (2.24–38 mGy). The statically defined minimum detectable contrast (MDC) was used as the image quality metric. The parametric model decomposed the MDC into two terms: one with and the other without ASIR, each was related to the dose in the form of power law with factors and indices dependent on spatial scales. The parameters were identified by least‐square fitting to the experimental data. By considering the constraint of the blending fraction in the range of [0, 1], the dose and ASIR blending fraction were determined for any specified low‐contrast detectability (LCD), quantified by the MDC at the concerned lesion size.

Results

It was verified that noise distribution is normal in the presence of ASIR. It was also found that the noises obtained from the subtractions of adjacent slices had an underestimate of 20% as compared to the ground truth noises, regardless of the spatial scale, pitch, or ASIR blending fraction. The least‐square fitting for the parametric model resulted in correlation coefficients from 0.905 to 0.996. The root‐mean‐square errors ranged from 1.27% to 7.15%.

Conclusion

The parametric model can be used to form a look‐up‐table for dose and ASIR blending fraction. The dose choices may be substantially limited in some cases depending on the required LCD.

Technical Principles of Dual-Energy Cone Beam Computed Tomography and Clinical Applications for Radiation Therapy

PURPOSE

Medical imaging is an indispensable tool in radiotherapy for dose planning, image guidance and treatment monitoring. Cone beam CT (CBCT) is a low dose imaging technique with high spatial resolution capability as a direct by-product of using flat-panel detectors. However, certain issues such as x-ray scatter, beam hardening and other artifacts limit its utility to the verification of patient positioning using image-guided radiotherapy.

METHODS AND MATERIALS

Dual-energy (DE)-CBCT has recently demonstrated promise as an improved tool for tumor visualization in benchtop applications. It has the potential to improve soft-tissue contrast and reduce artifacts caused by beam hardening and metal. In this review, the practical aspects of developing a DE-CBCT based clinical and technical workflow are presented based on existing DE-CBCT literature and concepts adapted from the well-established library of work in DE-CT. Furthermore, the potential applications of DE-CBCT on its future role in radiotherapy are discussed.

RESULTS AND CONCLUSIONS

Based on current literature and an investigation of future applications, there is a clear potential for DE-CBCT technologies to be incorporated into radiotherapy. The applications of DE-CBCT include (but are not limited to): adaptive radiotherapy, brachytherapy, proton therapy, radiomics and theranostics.

Development of a scanner-specific simulation framework for photon-counting computed tomography

The aim of this study was to develop and validate a simulation platform that generates photon-counting CT images of voxelized phantoms with detailed modeling of manufacturer-specific components including the geometry and physics of the x-ray source, source filtrations, anti-scatter grids, and photon-counting detectors. The simulator generates projection images accounting for both primary and scattered photons using a computational phantom, scanner configuration, and imaging settings. Beam hardening artifacts are corrected using a spectrum and threshold dependent water correction algorithm. Physical and computational versions of a clinical phantom (ACR) were used for validation purposes. The physical phantom was imaged using a research prototype photon-counting CT (Siemens Healthcare) with standard (macro) mode, at four dose levels and with two energy thresholds. The computational phantom was imaged with the developed simulator with the same parameters and settings used in the actual acquisition. Images from both the real and simulated acquisitions were reconstructed using a reconstruction software (FreeCT). Primary image quality metrics such as noise magnitude, noise ratio, noise correlation coefficients, noise power spectrum, CT number, in-plane modulation transfer function, and slice sensitivity profiles were extracted from both real and simulated data and compared. The simulator was further evaluated for imaging contrast materials (bismuth, iodine, and gadolinium) at three concentration levels and six energy thresholds. Qualitatively, the simulated images showed similar appearance to the real ones. Quantitatively, the average relative error in image quality measurements were all less than 4% across all the measurements. The developed simulator will enable systematic optimization and evaluation of the emerging photon-counting computed tomography technology.

Feasibility of multi-contrast imaging on dual-source photon counting detector (PCD) CT: An initial phantom study

PURPOSE

Photon-counting-detector-computed tomography (PCD-CT) allows separation of multiple, simultaneously imaged contrast agents, such as iodine (I), gadolinium (Gd), and bismuth (Bi). However, PCDs suffer from several technical limitations such as charge sharing, K-edge escape, and pulse pile-up, which compromise spectral separation of multi-energy data and degrade multi-contrast imaging performance. The purpose of this work was to determine the performance of a dual-source (DS) PCD-CT relative to a single-source (SS) PCD-CT for the separation of simultaneously imaged I, Gd, and Bi contrast agents.

METHODS

Phantom experiments were performed using a research whole-body PCD-CT and head/abdomen-sized phantoms containing vials of different I, Gd, Bi concentrations. To emulate a DS-PCD-CT, the phantoms were scanned twice on the SS-PCD-CT using different tube potentials for each scan. A tube potential of 80 kV (energy thresholds = 25/50 keV) was used for low-energy tube, while the high-energy tube used Sn140 kV (Sn indicates tin filter) and thresholds of 25/90 keV. The same phantoms were scanned also on the SS-PCD-CT using the chess acquisition mode. In chess mode, the 4 × 4 subpixels within a macro detector pixel are split into two sets based on a chess-board pattern. With each subpixel set having two energy thresholds, chess mode allows four energy-bin data sets, which permits simultaneous multi-contrast imaging. Because of this design, only 50% area of each detector pixel is configured to receive photons of a pre-defined threshold, leading to 50% dose utilization efficiency. To compensate for this dose inefficiency, the radiation dose for this scan was doubled compared to DS-PCD-CT. A 140 kV tube potential and thresholds = 25/50/75/90 keV were used. These settings were determined based on the K-edges of Gd, and Bi, and were found to yield good differentiation of I/Gd/Bi based on phantom experiments and other literature. The energy-bin images obtained from each scan (scan pair) were used to generate I-, Gd-, Bi-specific image via material decomposition. Root-mean-square-error (RMSE) between the known and measured concentrations was calculated for each scenario. A 20-cm water cylinder phantom was scanned on both systems, which was used for evaluating the magnitude of noise, and noise power spectra (NPS) of I/Gd/Bi-specific images.

RESULTS

Phantom results showed that DS-PCD-CT reduced noise in material-specific images for both head and body phantoms compared to SS-PCD-CT. The noise level of SS-PCD was reduced from 2.55 to 0.90 mg/mL (I), 1.97 to 0.78 mg/mL (Gd), and 0.85 to 0.74 mg/mL (Bi) using DS-PCD. NPS analysis showed that the noise texture of images acquired on both systems is similar. For the body phantom, the RMSE for SS-PCD-CT was reduced relative to DS-PCD-CT from 10.52 to 2.76 mg/mL (I), 7.90 to 2.01 mg/mL (Gd), and 1.91 to 1.16 mg/mL (Bi). A similar trend was observed for the head phantom: RMSE reduced from 2.59 (SS-PCD) to 0.72 (DS-PCD) mg/mL (I), 2.02 to 0.58 mg/mL (Gd), and 0.85 to 0.57 mg/mL (Bi).

CONCLUSION

We demonstrate the feasibility of performing simultaneous imaging of I, Gd, and Bi materials on DS-PCD-CT. Under the condition without cross scattering, DS-PCD reduced the RMSE for quantification of material concentration in relative to a SS-PCD-CT system using chess mode.

Physics Model-Based Scatter Correction in Multi-Source Interior Computed Tomography

Multi-source interior computed tomography (CT) has a great potential to provide ultra-fast and organ-oriented imaging at low radiation dose. However, X-ray cross scattering from multiple simultaneously activated X-ray imaging chains compromises imaging quality. Previously, we published two hardware-based scatter correction methods for multi-source interior CT. Here, we propose a software-based scatter correction method, with the benefit of no need for hardware modifications. The new method is based on a physics model and an iterative framework. The physics model was derived analytically, and was used to calculate X-ray scattering signals in both forward direction and cross directions in multi-source interior CT. The physics model was integrated to an iterative scatter correction framework to reduce scatter artifacts. The method was applied to phantom data from both Monte Carlo simulations and physical experimentation that were designed to emulate the image acquisition in a multi-source interior CT architecture recently proposed by our team. The proposed scatter correction method reduced scatter artifacts significantly, even with only one iteration. Within a few iterations, the reconstructed images fast converged toward the "scatter-free" reference images. After applying the scatter correction method, the maximum CT number error at the region-of-interests (ROIs) was reduced to 46 HU in numerical phantom dataset and 48 HU in physical phantom dataset respectively, and the contrast-noise-ratio at those ROIs increased by up to 44.3% and up to 19.7%, respectively. The proposed physics model-based iterative scatter correction method could be useful for scatter correction in dual-source or multi-source CT.

Bone mineral density measurements in vertebral specimens and phantoms using dual-layer spectral computed tomography

To assess whether phantomless calcium-hydroxyapatite (HA) specific bone mineral density (BMD) measurements with dual-layer spectral computed tomography are accurate in phantoms and vertebral specimens. Ex-vivo human vertebrae (n = 13) and a phantom containing different known HA concentrations were placed in a semi-anthropomorphic abdomen phantom with different extension rings simulating different degrees of obesity. Phantomless dual-layer spectral CT was performed at different tube current settings (500, 250, 125 and 50 mAs). HA-specific BMD was derived from spectral-based virtual monoenergetic images at 50 keV and 200 keV. Values were compared to the HA concentrations of the phantoms and conventional qCT measurements using a reference phantom, respectively. Above 125 mAs, errors for phantom measurements ranged between -1.3% to 4.8%, based on spectral information. In vertebral specimens, high correlations were found between BMD values assessed with spectral CT and conventional qCT (r ranging between 0.96 and 0.99; p < 0.001 for all) with different extension rings, and a high agreement was found in Bland Altman plots. Different degrees of obesity did not have a significant influence on measurements (P > 0.05 for all). These results suggest a high validity of HA-specific BMD measurements based on dual-layer spectral CT examinations in setups simulating different degrees of obesity without the need for a reference phantom, thus demonstrating their feasibility in clinical routine.

Quantifying potential reduction in contrast dose with monoenergetic images synthesized from dual-layer detector spectral CT

OBJECTIVE

To estimate the potential dose reduction in iodinated contrast when interpreting monoenergetic images from spectral CT.

METHODS

51 paediatric patients received contrast-enhanced CT simulation for radiation therapy using a single-source, dual-layer detector spectral CT. The contrast-to-noise ratios (CNRs) of blood vessels were measured relative to surrounding soft tissue. CNRs on monoenergetic 40-70 keV images were compared with polychromatic 120 kVp images. To compare with in vivo results, a phantom with iodine inserts (2-20 mg ml-1 concentration) was scanned and CNRs were calculated relative to water background.

RESULTS

Monoenergetic keV and body site had significant effects on CNR ratio (p < 0.0001). Across all body sites, the mean CNR ratio (monoenergetic/polychromatic CNR) was 3.3 (20th percentile [%20] 2.6), 2.4 (%20 2.1), 1.7 (%20 1.5), 1.2 (%20 1.0) for 40, 50, 60 and 70 keV images, respectively. Image noise was highest at 40 keV and lowest at 70 keV. Phantom measurements indicated that the same CNR as 120 kVp images can be achieved with a 4.0-fold lower iodine concentration on 40 keV images and 2.5-fold lower on 50 keV images.

CONCLUSION

50 keV monoenergetic images provided the best balance of improved CNR on all studies (mean 2.4-fold increase in vivo) for enhancing vessels vs image noise. A 50% reduction in contrast dose on a 50 keV image should maintain comparable or better CNR as compared with polychromatic CT in over 80% of CT studies. Advances in knowledge: Use of a novel, single-source, dual-layer detector spectral CT scanner to improve visualization of contrast-enhanced blood vessels will reduce the amount of iodinated contrast required for radiation oncology treatment planning.

X-ray scatter correction for multi-source interior computed tomography

PURPOSE

The schemes of multi-source interior computed tomography (CT) have shown promise for ultra-fast, organ-oriented, and low-dose dynamic imaging. Besides forward scattering, x-ray cross scattering from multiple x-ray sources activated simultaneously can further degrade image quality. Here, we investigate the overall x-ray scattering artifact in a recently proposed multi-source interior CT architecture, and present two methods for scatter correction.

METHODS

Compared to single-source global CT, scattering in multi-source interior CT architecture is affected by two new factors: cross scattering from simultaneously activated multiple x-ray sources and region-of-interest (ROI) oriented interior CT mode. The scatter artifact in the multi-source interior CT architecture was evaluated through both numerical simulation and physical experimentation, and compared to that from conventional single-source global CT. Monte Carlo simulation was conducted with a modified numerical CATphan^® 600 phantom. Physical experiments were performed in an in-house developed CT imaging platform with a custom-built phantom. The simulation and experiments were carried out on the single-source CT architecture and the multi-source CT architecture, respectively in the global CT mode and the interior CT mode for comparison. To correct the scattering artifact, two new methods were presented. The first is a beam-stopper-array (BSA)-based method, which enables an online correction of forward scattering and cross scattering simultaneously. The second is a source-trigger-sequence (STS)-based method dedicated to cross-scatter correction. It enables on-the-fly measurements of the cross scattering signals at a few pre-selected views. The CT image quality was quantitatively evaluated in terms of contrast-to-noise ratio (CNR) and CT number deviation before and after the scatter correction.

RESULTS

X-ray cross scattering degraded image quality in both the simulation and experiments. Before the scatter correction, the multi-source interior CT mode yielded a reduction of CNR at the ROIs by up to 68.5% and 50.7% in the simulation and experiments, respectively. The stationary BSA-based method significantly improved CNR and CT number accuracy in the images from multi-source interior CT mode, by reducing the negative effects from both forward scattering and cross scattering. The STS-based method enabled multi-source interior CT mode to provide comparable image quality to that with the single-source interior CT mode, by correcting the artifact from cross scattering. The remaining forward scattering artifact can be corrected with the fast adaptive scatter kernel superposition (FASKS) technique. With the proposed scatter correction methods, the CT number error at the ROIs was reduced to less than 37 HU in both simulation and experiments, respectively.

CONCLUSIONS

Cross scattering, in addition to forward scattering, can cause significant image quality degradation in the multi-source interior CT architecture. However, image quality can be significantly improved with the proposed scatter correction methods.

The role of dual-energy computed tomography in the assessment of pulmonary function

The assessment of pulmonary function, including ventilation and perfusion status, is important in addition to the evaluation of structural changes of the lung parenchyma in various pulmonary diseases. The dual-energy computed tomography (DECT) technique can provide the pulmonary functional information and high resolution anatomic information simultaneously. The application of DECT for the evaluation of pulmonary function has been investigated in various pulmonary diseases, such as pulmonary embolism, asthma and chronic obstructive lung disease and so on. In this review article, we will present principles and technical aspects of DECT, along with clinical applications for the assessment pulmonary function in various lung diseases.

A model-based scatter artifacts correction for cone beam CT

PURPOSE

Due to the increased axial coverage of multislice computed tomography (CT) and the introduction of flat detectors, the size of x-ray illumination fields has grown dramatically, causing an increase in scatter radiation. For CT imaging, scatter is a significant issue that introduces shading artifact, streaks, as well as reduced contrast and Hounsfield Units (HU) accuracy. The purpose of this work is to provide a fast and accurate scatter artifacts correction algorithm for cone beam CT (CBCT) imaging.

METHODS

The method starts with an estimation of coarse scatter profiles for a set of CBCT data in either image domain or projection domain. A denoising algorithm designed specifically for Poisson signals is then applied to derive the final scatter distribution. Qualitative and quantitative evaluations using thorax and abdomen phantoms with Monte Carlo (MC) simulations, experimental Catphan phantom data, and in vivo human data acquired for a clinical image guided radiation therapy were performed. Scatter correction in both projection domain and image domain was conducted and the influences of segmentation method, mismatched attenuation coefficients, and spectrum model as well as parameter selection were also investigated.

RESULTS

Results show that the proposed algorithm can significantly reduce scatter artifacts and recover the correct HU in either projection domain or image domain. For the MC thorax phantom study, four-components segmentation yields the best results, while the results of three-components segmentation are still acceptable. The parameters (iteration number K and weight β) affect the accuracy of the scatter correction and the results get improved as K and β increase. It was found that variations in attenuation coefficient accuracies only slightly impact the performance of the proposed processing. For the Catphan phantom data, the mean value over all pixels in the residual image is reduced from -21.8 to -0.2 HU and 0.7 HU for projection domain and image domain, respectively. The contrast of the in vivo human images is greatly improved after correction.

CONCLUSIONS

The software-based technique has a number of advantages, such as high computational efficiency and accuracy, and the capability of performing scatter correction without modifying the clinical workflow (i.e., no extra scan/measurement data are needed) or modifying the imaging hardware. When implemented practically, this should improve the accuracy of CBCT image quantitation and significantly impact CBCT-based interventional procedures and adaptive radiation therapy.

Dual- and Multi-Energy CT: Principles, Technical Approaches, and Clinical Applications

In x-ray computed tomography (CT), materials having different elemental compositions can be represented by identical pixel values on a CT image (ie, CT numbers), depending on the mass density of the material. Thus, the differentiation and classification of different tissue types and contrast agents can be extremely challenging. In dual-energy CT, an additional attenuation measurement is obtained with a second x-ray spectrum (ie, a second "energy"), allowing the differentiation of multiple materials. Alternatively, this allows quantification of the mass density of two or three materials in a mixture with known elemental composition. Recent advances in the use of energy-resolving, photon-counting detectors for CT imaging suggest the ability to acquire data in multiple energy bins, which is expected to further improve the signal-to-noise ratio for material-specific imaging. In this review, the underlying motivation and physical principles of dual- or multi-energy CT are reviewed and each of the current technical approaches is described. In addition, current and evolving clinical applications are introduced.

Technical limitations of dual-energy CT in neuroradiology: 30-month institutional experience and review of literature

BACKGROUND

Dual-energy CT (DECT) has been shown to be a useful modality in neuroradiology.

OBJECTIVE

To assess failure modes and limitations of DECT in different neuroimaging applications.

PATIENTS AND METHODS

Dual-source DECT scans were performed in 72 patients over 30 months to differentiate contrast agent staining or extravasation from intracranial hemorrhage (ICH) (n=40); to differentiate calcium from ICH (n=2); for metal-artifact reduction (n=5); and for angiographic assessment (n=25). A three-material decomposition algorithm was used to obtain virtual non-contrast (VNC) and iodine (or calcium) overlay images. Images were analyzed in consensus by two board-certified radiologists to determine the success of the algorithm and to assess confounding factors. Furthermore, a dilution experiment using cylinders containing defined heparinized swine blood, normal saline, and selected iodine concentrations was conducted to assess other possible confounding factors.

RESULTS

Dual-energy analysis was successful in 65 (90.2%) patients. However, the algorithm failed when images were affected by beam hardening (n=3, 4.2%), the presence of a fourth material (parenchymal calcification) (n=3, 4.2%), or motion (n=1, 1.4%). In the dilution experiment, a saturation effect was seen at high iodine concentrations (≥37 mg/ml). VNC and iodine overlay images were not reliable above this concentration, and beam-hardening artifacts were noted.

CONCLUSIONS

DECT material decomposition is usually successful in neuroradiology. However, it can only distinguish up to three preselected materials. A fourth material such as parenchymal calcium may confound the analysis. Artifacts such as beam hardening, metallic streak, or saturation effect can also impair material decomposition.

Scatter correction associated with dedicated dual-source CT hardware improves accuracy of lung air measures

RATIONALE AND OBJECTIVES

Accurate assessment of air density used to quantitatively characterize amount and distribution of emphysema in chronic obstructive pulmonary disease (COPD) subjects has remained challenging. Hounsfield units (HU) within tracheal air can be considerably less negative than -1000 HU. This study has sought to characterize the effects of improved scatter correction used in dual-source pulmonary computed tomography (CT).

MATERIALS AND METHODS

Dual-source dual-energy (DSDE) and single-source (SS) scans taken at multiple energy levels and scan settings were acquired for quantitative comparison using anesthetized ovine (n = 6), swine (n = 13), and a lung phantom. Data were evaluated for the lung, inferior vena cava, and tracheal segments. To minimize the effect of cross-scatter, the phantom scans in the DSDE mode were obtained by reducing the current of one of the tubes to near zero.

RESULTS

A significant shift in mean HU values in the tracheal regions of animals and the phantom is observed, with values consistently closer to -1000 HU in DSDE mode. HU values associated with SS mode demonstrated a positive shift of up to 32 HU. In vivo tracheal air measurements demonstrated considerable variability with SS scanning, whereas these values were more consistent with DSDE imaging. Scatter effects in the lung parenchyma differed from adjacent tracheal measures.

CONCLUSION

Data suggest that the scatter correction introduced into the dual-energy mode of imaging has served to provide more accurate CT lung density measures sought to quantitatively assess the presence and distribution of emphysema in COPD subjects. Data further suggest that CT images, acquired without adequate scatter correction, cannot be corrected by linear algorithms given the variability in tracheal air HU values and the independent scatter effects on lung parenchyma.

Detection of ischaemic myocardial lesions with coronary CT angiography and adenosine-stress dynamic perfusion imaging using a 128-slice dual-source CT: diagnostic performance in comparison with cardiac MRI

OBJECTIVE

We assessed the diagnostic performance of adenosine-stress dynamic CT perfusion (ASDCTP) imaging and coronary CT angiography (CCTA) for the detection of ischaemic myocardial lesions using 128-slice dual-source CT compared with that of 1.5 T cardiac MRI.

METHODS

This prospective study included 33 patients (61±8 years, 82% male) with suspected coronary artery diseases who underwent ASDCTP imaging and adenosine-stress cardiac MRI. Two investigators independently evaluated ASDCTP images in correlation with significant coronary stenosis on CCTA using two different thresholds of 50% and 70% diameter stenosis. Hypoattenuated myocardial lesions on ASDCTP associated with significant coronary stenoses on CCTA were regarded as true perfusion defects. All estimates of diagnostic performance were calculated and compared with those of cardiac MRI.

RESULTS

With use of a threshold of 50% diameter stenosis on CCTA, the diagnostic estimates per-myocardial segment were as follows: sensitivity, 81% [95% confidence interval (CI): 70-92%]; specificity, 94% (95% CI: 92-96%); and accuracy 93% (95% CI: 91-95%). With use of a threshold of 70%, the diagnostic estimates were as follows: sensitivity, 48% (95% CI: 34-62%); specificity, 99% (95% CI: 98-100%); and accuracy, 94% (95% CI: 92-96%).

CONCLUSION

Dynamic CTP using 128-slice dual-source CT enables the assessment of the physiological significance of coronary artery lesions with high diagnostic accuracy in patients with clinically suspected coronary artery disease.

ADVANCES IN KNOWLEDGE

Combined CCTA and ASDCTP yielded high accuracy in the detection of perfusion defects regardless of the threshold of significant coronary stenosis.

Interleaved acquisition for cross scatter avoidance in dual cone-beam CT

PURPOSE

Cone-beam x-ray imaging with flat panel detectors is used for target localization in image guided radiation therapy. This imaging includes cone-beam computed tomography (CBCT) and planar imaging. Use of two orthogonal x-ray systems could reduce imaging time for CBCT, provide simultaneous orthogonal views in planar imaging, facilitate dual-energy methods, and be useful in alleviating cone-beam artifacts by providing two axially offset focal-spot trajectories. However, the potential advantages of a second cone-beam system come at the cost of cross scatter, i.e., scatter of photons originating from one tube into the noncorresponding detector. Herein, cross scatter is characterized for dual cone-beam imaging, and a method for avoiding cross scatter is proposed and evaluated.

METHODS

A prototype dual-source CBCT system has been developed that models the geometry of a gantry-mounted kV imaging device used in radiation therapy. Cross scatter was characterized from 70 to 145 kVp in projections and reconstructed images using this system and three cylindrical phantoms (15, 20, and 30 cm) with a common Catphan core. A novel strategy for avoiding cross scatter in dual CBCT was developed that utilized interleaved data acquisition on each imaging chain. Interleaving, while maintaining similar angular sampling, can be achieved by either doubling the data acquisition rate or, as presented herein, halving the rotation speed.

RESULTS

The ratio of cross scatter to the total detected signal was found to be as high as 0.59 in a 30 cm diameter phantom. The measured scatter-to-primary ratio in some cases exceeded 4. In the 30 cm phantom, reconstructed contrast was reduced across all ROIs by an average of 48.7% when cross scatter was present. These cross-scatter degradations were almost entirely avoided by the method of interleaved exposures.

CONCLUSIONS

Cross scatter is substantial in dual cone-beam imaging, but its effects can be largely removed by interleaved acquisition, which can be achieved at the same angular sampling rate either by doubling the data acquisition rate or halving the rotation speed.

Attenuation-based estimation of patient size for the purpose of size specific dose estimation in CT. Part I. Development and validation of methods using the CT image

PURPOSE

For the purpose of size-specific dose estimation, information regarding patient attenuation is required. The purpose of this work is to describe a method for measuring patient attenuation and expressing the results in terms of a water cylinder, with cross sectional area A(w), which would absorb the same average dose as the irradiated patient. The ability to calculate A(w) directly from the CT image was validated with Monte Carlo simulations and an analytical model.

METHODS

A series of virtual cylinders were created with diameters ranging from 10 to 40 cm and lengths of 40 cm. The cylinders were given an atomic number equal to that of water; the density of the cylinders was varied from 0.26 to 1.2 g∕cm(3). The average dose to the cylinders from an axial scan at the longitudinal center position was calculated using Monte Carlo simulation and an analytical model. The relationship between phantom cross sectional area and calculated dose was determined for each density value to determine the dependence of A(w) on object attenuation. In addition, A(w) was estimated from the virtual CT images based on two derived models expressing the potential dependence of A(w) on object attenuation, one model assuming a linear dependence and the other assuming a quadratic dependence. Model results were compared with those from the Monte Carlo simulation and the analytical dose calculation approach. Virtual thorax and abdomen phantoms of adult and pediatric sizes were created, and A(w) was estimated using geometrical size parameters or the derived models. The accuracy of each approach for estimating A(w) was determined by comparing the average dose to the virtual phantom calculated using Monte Carlo simulation to the average dose to a water equivalent phantom of cross sectional area A(w).

RESULTS

In the absence of a bowtie filter, both the Monte Carlo simulation and analytical model showed that (A(w)∕A) had a quadratic dependence on (μ∕μ(w)). However, including a bowtie filter in the Monte Carlo simulation altered the relationship, such that A(w)∕A was linearly dependent on μ∕μ(w). Using this relationship, the dose absorbed by a water cylinder of area A(w) agreed with the dose absorbed by adult and pediatric, thorax and abdomen phantoms to within 6% (mean difference = 0.5 ± 4.8%). Estimates of A(w) (or the water equivalent diameter D(w)) using only anterior-posterior and lateral phantom dimensions led to dose estimates that agreed with Monte Carlo-derived dose values within 3% and 6% for the abdomen adult and pediatric phantoms, respectively. However, because of density differences between lung and tissue, larger differences in dose relative to Monte Carlo-derived values were observed in the thorax adult and pediatric phantoms (15% and 11%, respectively) when only geometrical parameters were used to estimate D(w).

CONCLUSIONS

Patient attenuation can be quantified in terms of the diameter of a water cylinder that absorbs same average dose as the irradiated cross section of the patient. The linear dependence of A(w) on object attenuation makes it straightforward to calculate A(w) from a CT image on most operator consoles or clinical workstations.

Dual-energy CT and its potential use for quantitative myocardial CT perfusion

Application of quantitative myocardial CT perfusion (CTP) for the assessment of coronary artery disease may have a significant effect on patient care as the functional significance of a coronary stenosis can be evaluated through absolute measurement of the downstream myocardial perfusion (MP) both at rest and under exercise or pharmacologic stress. A main challenge of myocardial CTP is beam hardening (BH), arising from the polychromatic nature of x-rays used in CT scanning and the presence of highly attenuating contrast agent in the heart chambers during the CT acquisition. The BH effect induces significant nonuniform shifts in CT numbers which, if uncorrected, can lead to inaccurate assessment of MP. With the recent developments of dual-energy CT (DECT) scanning on clinical scanners, the BH effect on MP measurement could be reduced with the generation of monochromatic images relatively free of BH artifacts from the acquired dual-energy data. Here, we review the different techniques of acquiring dual-energy scans and generating monochromatic images, followed by discussion on the progress of developing a DECT technique with reduced radiation dose for quantitative myocardial CTP.

Variability of CT contrast enhancement in the pancreas: a cause for concern?

BACKGROUND

Multidetector CT is a valuable technique for diagnosis/staging in several pancreatic pathologies. Diagnosis is usually based on tissue density measurements. Recently, newer functional CT techniques have been introduced. The aim of this study was to assess variability in perfusion and dual-energy CT data, and to compare these data with density measurements in the pancreas of a healthy population.

METHODS

Two groups were included: 20 patients underwent perfusion CT imaging, and 10 patients were scanned using a dual-energy protocol. In both groups, tissue density [Hounsfield units (HU)] was measured in the pancreatic head, body and tail. Functional data were calculated (blood flow/blood volume in the perfusion CT group, iodine concentration in the dual-energy group), and variability was assessed.

RESULTS

Density measurements were comparable for the perfusion and dual-energy CT groups, and ranged from 14 to 60 HU. Maximal enhancement differences between the head/body/tail of the pancreas ranged between 2 and 21 HU. Considerable variability was observed, both in density measurements (ranging from 3 to 34%) and in functional parameters (mean variability in perfusion CT parameters blood flow and blood volume was 21.3 and 10% respectively; mean variability in dual-energy iodine-mapping results was 24.4%).

CONCLUSION

This study demonstrated the presence of important intraindividual variability in pancreatic tissue contrast enhancement, regardless of the CT technique used. Considering the variability observed in this study, the use of cut-off values to characterize pancreatic pathologies seems troublesome, and morphologic primary and secondary changes will remain important, even when using novel functional imaging techniques. and IAP.

A general framework and review of scatter correction methods in x-ray cone-beam computerized tomography. Part 1: Scatter compensation approaches

Since scattered radiation in cone-beam volume CT implies severe degradation of CT images by quantification errors, artifacts, and noise increase, scatter suppression is one of the main issues related to image quality in CBCT imaging. The aim of this review is to structurize the variety of scatter suppression methods, to analyze the common structure, and to develop a general framework for scatter correction procedures. In general, scatter suppression combines hardware techniques of scatter rejection and software methods of scatter correction. The authors emphasize that scatter correction procedures consist of the main components scatter estimation (by measurement or mathematical modeling) and scatter compensation (deterministic or statistical methods). The framework comprises most scatter correction approaches and its validity also goes beyond transmission CT. Before the advent of cone-beam CT, a lot of papers on scatter correction approaches in x-ray radiography, mammography, emission tomography, and in Megavolt CT had been published. The opportunity to avail from research in those other fields of medical imaging has not yet been sufficiently exploited. Therefore additional references are included when ever it seems pertinent. Scatter estimation and scatter compensation are typically intertwined in iterative procedures. It makes sense to recognize iterative approaches in the light of the concept of self-consistency. The importance of incorporating scatter compensation approaches into a statistical framework for noise minimization has to be underscored. Signal and noise propagation analysis is presented. A main result is the preservation of differential-signal-to-noise-ratio (dSNR) in CT projection data by ideal scatter correction. The objective of scatter compensation methods is the restoration of quantitative accuracy and a balance between low-contrast restoration and noise reduction. In a synopsis section, the different deterministic and statistical methods are discussed with respect to their properties and applications. The current paper is focused on scatter compensation algorithms. The multitude of scatter estimation models will be dealt with in a separate paper.

[Challenges for computed tomography of overweight patients]

In morbidly obese patients, computed tomography frequently represents the only viable option for non-invasive imaging diagnostics. The aim of this study was to analyze the weight limits, dose and image quality with standard CT scanners and to determine the diagnostic value and dose with a dual source XXL mode.A total of 15 patients (average body weight 189.6 ± 42 kg) were retrospectively identified who had been examined with the XXL mode. Of these patients 7 (average body weight 176.4 ± 56 kg) had been examined using both the XXL and standard protocols allowing for an intraindividual comparison in this subcollective. Additionally 14 patients weighing between 90 and 150 kg (average 106.1 ± 19 kg) examined with standard protocols were included as references. Dose, image noise and subjectively assessed image quality (rating scale 1-4) were determined. Additionally, a large abdomen phantom of 48 cm diameter was examined with both protocols at equivalent tube current-time product in order to compare the dose efficiency.The patient groups differed significantly in dose (CTDI(vol) XXL 72.9 ± 23 versus standard 16.7 ± 11 mGy; intraindividual 64.1 ± 20 versus 27.0 ± 15 mGy). The image noise was generally somewhat higher in the XXL group but significantly lower in the intraindividual comparison (liver 24.2 ± 14 HU versus 36.3 ± 20 HU; p = 0.03; fat 15.5 ± 8 HU versus 26.2 ± 12 HU; p=0.02). With ratings of 1.9 ± 0.7 and 1.8 ± 0.7 image quality did not differ significantly in general, whereas there was a clear difference in the intraindividual comparison (1.8 ± 0.8 versus 3.0 ± 1.2) and only the XXL protocol achieved diagnostic quality in all cases, while 43% of the examinations with the standard protocol were rated as non-diagnostic. The quantification of dose efficiency in the phantom scans yielded no significant difference between the protocols.Up to 150 kg body weight, CT can be performed with the standard technique at 120 kVp with tube current modulation. In larger patients diagnostic image quality can only be achieved reliably with the dual source XXL mode, although at considerably increased calculated dose. However, standard conversion factors yield false high values so that the estimation of the biologically relevant equivalent dose is very difficult.