Experimental study of optimal energy weighting in energy-resolved CT using a CZT detector

Recent advances in energy-resolved CT can potentially improve contrast-to-noise ratio (CNR), which could subsequently reduce dose in conventional and dedicated breast CT. Two methods have been proposed for optimal energy weighting: weighting the energy-bin data prior to log normalization (projection-based weighting) and weighting the energy-bin data after log normalization (image-based weighting). Previous studies suggested that optimal projection-based and image-based energy weighting provide similar CNR improvements for energy-resolved CT compared to photon-counting or conventional energy-integrating CT. This study experimentally investigated the improvement in CNR of projection-based and image-based weighted images relative to photon-counting for six different energy-bin combinations using a bench top system with a CZT detector. The results showed CNR values ranged between 0.85 and 1.01 for the projection-based weighted images and between 0.91 and 1.43 for the image-based weighted images, relative to the CNR for the photon-counting image. The range of CNR values demonstrates the effects of energy-bin selection on CNR for a particular energy weighting scheme. The non-ideal spectral response of the CZT detector caused spectral tailing, which appears to generally reduce the CNR for the projection-based weighted images. Image-based weighting increased CNR in five of the six bin combinations despite the non-ideal spectral effects

Reducing Radiation Dose to the Female Breast During Conventional and Dedicated Breast Computed Tomography

The purpose of this study was to quantify the effectiveness of techniques intended to reduce dose to the breast during CT coronary angiography (CTCA) scans with respect to task-based image quality, and to evaluate the effectiveness of optimal energy weighting in improving contrast-to-noise ratio (CNR), and thus the potential for reducing breast dose, during energy-resolved dedicated breast CT. A database quantifying organ dose for several radiosensitive organs irradiated during CTCA, including the breast, was generated using Monte Carlo simulations. This database facilitates estimation of organ-specific dose deposited during CTCA protocols using arbitrary x-ray spectra or tube-current modulation schemes without the need to run Monte Carlo simulations. The database was used to estimate breast dose for simulated CT images acquired for a reference protocol and five protocols intended to reduce breast dose. For each protocol, the performance of two tasks (detection of signals with unknown locations) was compared over a range of breast dose levels using a task-based, signal-detectability metric: the estimator of the area under the exponential free-response relative operating characteristic curve, AFE. For large-diameter/medium-contrast signals, when maintaining equivalent AFE, the 80 kV partial, 80 kV, 120 kV partial, and 120 kV tube-current modulated protocols reduced breast dose by 85%, 81%, 18%, and 6%, respectively, while the shielded protocol increased breast dose by 68%. Results for the small-diameter/high-contrast signal followed similar trends, but with smaller magnitude of the percent changes in dose. The 80 kV protocols demonstrated the greatest reduction to breast dose, however, the subsequent increase in noise may be clinically unacceptable. Tube output for these protocols can be adjusted to achieve more desirable noise levels with lesser dose reduction. The improvement in CNR of optimally projection-based and image-based weighted images relative to photon-counting was investigated for six different energy bin combinations using a bench-top energy-resolving CT system with a cadmium zinc telluride (CZT) detector. The non-ideal spectral response reduced the CNR for the projection-based weighted images, while image-based weighting improved CNR for five out of the six investigated bin combinations, despite this non-ideal response, indicating potential for image-based weighting to reduce breast dose during dedicated breast CT

A Database for Estimating Organ Dose for Chest and Head CT Scans for Arbitrary Spectra and Angular Tube Current Modulation

Purpose: The purpose of this study was to develop a database for estimating organ dose in a voxelized patient model for coronary angiography and brain perfusion CT acquisitions with any spectra and angular tube current modulation setting. The database enables organ dose estimation for existing and novel acquisition techniques without requiring Monte Carlo simulations. Methods: The study simulated transport of monoenergetic photons between 5 and 150 keV for 1000 projections over 360◦ through anthropomorphic voxelized female chest and head (0◦ and 30◦ tilt) phantoms and standard head and body CTDI dosimetry cylinders. The simulations resulted in tables of normalized dose deposition for several radiosensitive organs quantifying the organ dose per emitted photon for each incident photon energy and projection angle for coronary angiography and brain perfusion acquisitions. The values in a table can be multiplied by an incident spectrum and number of photons at each projection angle and then summed across all energies and angles to estimate total organ dose. Scanner-specific organ dose may be approximated by normalizing the database-estimated organ dose by the database-estimated CTDIvol and multiplying by a physical CTDIvol measurement. Two examples are provided demonstrating how to use the tables to estimate relative organ dose. In the first, the change in breast and lung dose during coronary angiography CT scans is calculated for reduced kVp, angular tube current modulation, and partial angle scanning protocols relative to a reference protocol. In the second example, the change in dose to the eye lens is calculated for a brain perfusion CT acquisition in which the gantry is tilted 30◦ relative to a nontilted scan. Results: Our database provides tables of normalized dose deposition for several radiosensitive organs irradiated during coronary angiography and brain perfusion CT scans. Validation results indicate total organ doses calculated using our database are within 1% of those calculated using Monte Carlo simulations with the same geometry and scan parameters for all organs except red bone marrow (within 6%), and within 23% of published estimates for different voxelized phantoms. Results from the example of using the database to estimate organ dose for coronary angiography CT acquisitions show 2.1%, 1.1%, and −32% change in breast dose and 2.1%, −0.74%, and 4.7% change in lung dose for reduced kVp, tube current modulated, and partial angle protocols, respectively, relative to the reference protocol. Results show −19.2% difference in dose to eye lens for a tilted scan relative to a nontilted scan. The reported relative changes in organ doses are presented without quantification of image quality and are for the sole purpose of demonstrating the use of the proposed database. Conclusions: The proposed database and calculation method enable the estimation of organ dose for coronary angiography and brain perfusion CT scans utilizing any spectral shape and angular tube current modulation scheme by taking advantage of the precalculated Monte Carlo simulation results. The database can be used in conjunction with image quality studies to develop optimized acquisition techniques and may be particularly beneficial for optimizing dual kVp acquisitions for which numerous kV, mA, and filtration combinations may be investigated. © 2012 American Association of Physicists in Medicine

Energy Deposition in the Breast During CT Scanning: Quantification and Implications for Dose Reduction

Studies suggest that dose to the breast leads to a higher lifetime attributable cancer incidence risk from a chest CT scan for women compared to men. Numerous methods have been proposed for reducing dose to the breast during CT scanning, including bismuth shielding, tube current modulation, partial-angular scanning, and reduced kVp. These methods differ in how they alter the spectrum and fluence across projection angle. This study used Monte Carlo CT simulations of a voxelized female phantom to investigate the energy (dose) deposition in the breast as a function of both photon energy and projection angle. The resulting dose deposition matrix was then used to investigate several questions regarding dose reduction to the breast: (1) Which photon energies deposit the most dose in the breast, (2) How does increased filtration compare to tube current reduction in reducing breast dose, and (3) Do reduced kVp scans reduce dose to breast, and if so, by what mechanism? The results demonstrate that while high-energy photons deposit more dose per emitted photon, the low-energy photons deposit more dose to the breast for a 120 kVp acquisition. The results also demonstrate that decreasing the tube current for the AP views to match the fluence exiting a shield deposits nearly the same dose to the breast as when using a shield (within ~1%). Finally, results suggest that the dose reduction observed during lower kVp scans is caused by reduced photon fluence rather than the elimination of high-energy photons from the beam. Overall, understanding the mechanisms of dose deposition in the breast as a function of photon energy and projection angle enables comparisons of dose reduction methods and facilitates further development of optimized dose reduction schemes

Application of Fractal Dimension for Quantifying Noise Texture in Computed Tomography Images

Purpose Evaluation of noise texture information in CT images is important for assessing image quality. Noise texture is often quantified by the noise power spectrum (NPS), which requires numerous image realizations to estimate. This study evaluated fractal dimension for quantifying noise texture as a scalar metric that can potentially be estimated using one image realization. Methods The American College of Radiology CT accreditation phantom (ACR) was scanned on a clinical scanner (Discovery CT750, GE Healthcare) at 120 kV and 25 and 90 mAs. Images were reconstructed using filtered back projection (FBP/ASIR 0%) with varying reconstruction kernels: Soft, Standard, Detail, Chest, Lung, Bone, and Edge. For each kernel, images were also reconstructed using ASIR 50% and ASIR 100% iterative reconstruction (IR) methods. Fractal dimension was estimated using the differential box‐counting algorithm applied to images of the uniform section of ACR phantom. The two‐dimensional Noise Power Spectrum (NPS) and one‐dimensional‐radially averaged NPS were estimated using established techniques. By changing the radiation dose, the effect of noise magnitude on fractal dimension was evaluated. The Spearman correlation between the fractal dimension and the frequency of the NPS peak was calculated. The number of images required to reliably estimate fractal dimension was determined and compared to the number of images required to estimate the NPS‐peak frequency. The effect of Region of Interest (ROI) size on fractal dimension estimation was evaluated. Feasibility of estimating fractal dimension in an anthropomorphic phantom and clinical image was also investigated, with the resulting fractal dimension compared to that estimated within the uniform section of the ACR phantom. Results Fractal dimension was strongly correlated with the frequency of the peak of the radially averaged NPS curve, having a Spearman rank‐order coefficient of 0.98 (P‐value \u3c 0.01) for ASIR 0%. The mean fractal dimension at ASIR 0% was 2.49 (Soft), 2.51 (Standard), 2.52 (Detail), 2.57 (Chest), 2.61 (Lung), 2.66 (Bone), and 2.7 (Edge). A reduction in fractal dimension was observed with increasing ASIR levels for all investigated reconstruction kernels. Fractal dimension was found to be independent of noise magnitude. Fractal dimension was successfully estimated from four ROIs of size 64 × 64 pixels or one ROI of 128 × 128 pixels. Fractal dimension was found to be sensitive to non‐noise structures in the image, such as ring artifacts and anatomical structure. Fractal dimension estimated within a uniform region of an anthropomorphic phantom and clinical head image matched that estimated within the ACR phantom for filtered back projection reconstruction. Conclusions Fractal dimension correlated with the NPS‐peak frequency and was independent of noise magnitude, suggesting that the scalar metric of fractal dimension can be used to quantify the change in noise texture across reconstruction approaches. Results demonstrated that fractal dimension can be estimated from four, 64 × 64‐pixel ROIs or one 128 × 128 ROI within a head CT image, which may make it amenable for quantifying noise texture within clinical images

Reducing Radiation Dose to the Female Breast during CT Coronary Angiography: A Simulation Study Comparing Breast Shielding, Angular Tube Current Modulation, Reduced kV, and Partial Angle Protocols Using an Unknown-location Signal-detectability Metric

Purpose: The authors compared the performance of five protocols intended to reduce dose to the breast during computed tomography (CT) coronary angiography scans using a model observer unknown-location signal-detectability metric. Methods: The authors simulated CT images of an anthropomorphic female thorax phantom for a 120 kV reference protocol and five “dose reduction” protocols intended to reduce dose to the breast: 120 kV partial angle (posteriorly centered), 120 kV tube-current modulated (TCM), 120 kV with shielded breasts, 80 kV, and 80 kV partial angle (posteriorly centered). Two image quality tasks were investigated: the detection and localization of 4-mm, 3.25 mg/ml and 1-mm, 6.0 mg/ml iodine contrast signals randomly located in the heart region. For each protocol, the authors plotted the signal detectability, as quantified by the area under the exponentially transformed free response characteristic curve estimator (AˆFE), as well as noise and contrast-to-noise ratio (CNR) versus breast and lung dose. In addition, the authors quantified each protocol\u27s dose performance as the percent difference in dose relative to the reference protocol achieved while maintaining equivalentAˆFE. Results: For the 4-mm signal-size task, the 80 kV full scan and 80 kV partial angle protocols decreased dose to the breast (80.5% and 85.3%, respectively) and lung (80.5% and 76.7%, respectively) withAˆFE= 0.96, but also resulted in an approximate three-fold increase in image noise. The 120 kV partial protocol reduced dose to the breast (17.6%) at the expense of increased lung dose (25.3%). The TCM algorithm decreased dose to the breast (6.0%) and lung (10.4%). Breast shielding increased breast dose (67.8%) and lung dose (103.4%). The 80 kV and 80 kV partial protocols demonstrated greater dose reductions for the 4-mm task than for the 1-mm task, and the shielded protocol showed a larger increase in dose for the 4-mm task than for the 1-mm task. In general, the CNR curves indicate a similar relative ranking of protocol performance as the correspondingAˆFEcurves, however, the CNR metric overestimated the performance of the shielded protocol for both tasks, leading to corresponding underestimates in the relative dose increases compared to those obtained when using theAˆFEmetric. Conclusions: The 80 kV and 80 kV partial angle protocols demonstrated the greatest reduction to breast and lung dose, however, the subsequent increase in image noise may be deemed clinically unacceptable. Tube output for these protocols can be adjusted to achieve a more desirable noise level with lesser breast dose savings. Breast shielding increased breast and lung dose when maintaining equivalentAˆFE. The results demonstrated that comparisons of dose performance depend on both the image quality metric and the specific task, and that CNR may not be a reliable metric of signal detectability

CT Automated Exposure Control Using A Generalized Detectability Index

Purpose Identifying an appropriate tube current setting can be challenging when using iterative reconstruction due to the varying relationship between spatial resolution, contrast, noise, and dose across different algorithms. This study developed and investigated the application of a generalized detectability index (d\u27gen) to determine the noise parameter to input to existing automated exposure control (AEC) systems to provide consistent image quality (IQ) across different reconstruction approaches. Methods This study proposes a task‐based automated exposure control (AEC) method using a generalized detectability index (d\u27gen). The proposed method leverages existing AEC methods that are based on a prescribed noise level. The generalized d\u27gen metric is calculated using lookup tables of task‐based modulation transfer function (MTF) and noise power spectrum (NPS). To generate the lookup tables, the American College of Radiology CT accreditation phantom was scanned on a multidetector CT scanner (Revolution CT, GE Healthcare) at 120 kV and tube current varied manually from 20 to 240 mAs. Images were reconstructed using a reference reconstruction algorithm and four levels of an in‐house iterative reconstruction algorithm with different regularization strengths (IR1–IR4). The task‐based MTF and NPS were estimated from the measured images to create lookup tables of scaling factors that convert between d\u27gen and noise standard deviation. The performance of the proposed d\u27gen‐AEC method in providing a desired IQ level over a range of iterative reconstruction algorithms was evaluated using the American College of Radiology (ACR) phantom with elliptical shell and using a human reader evaluation on anthropomorphic phantom images. Results The study of the ACR phantom with elliptical shell demonstrated reasonable agreement between the d\u27gen predicted by the lookup table and d\u27 measured in the images, with a mean absolute error of 15% across all dose levels and maximum error of 45% at the lowest dose level with the elliptical shell. For the anthropomorphic phantom study, the mean reader scores for images resulting from the d\u27gen‐AEC method were 3.3 (reference image), 3.5 (IR1), 3.6 (IR2), 3.5 (IR3), and 2.2 (IR4). When using the d\u27gen‐AEC method, the observers’ IQ scores for the reference reconstruction were statistical equivalent to the scores for IR1, IR2, and IR3 iterative reconstructions (P \u3e 0.35). The d\u27gen‐AEC method achieved this equivalent IQ at lower dose for the IR scans compared to the reference scans. Conclusions A novel AEC method, based on a generalized detectability index, was investigated. The proposed method can be used with some existing AEC systems to derive the tube current profile for iterative reconstruction algorithms. The results provide preliminary evidence that the proposed d\u27gen‐AEC can produce similar IQ across different iterative reconstruction approaches at different dose levels