Initial Clinical Images From a Second-Generation Prototype Silicon-Based Photon-Counting Computed Tomography System.

RATIONALE AND OBJECTIVES: To demonstrate the feasibility and potential of using a second-generation prototype photon-counting computed tomography (CT) system to provide simultaneous high spatial resolution images and high spectral resolution material information across a range of routine imaging tasks using clinical patient exposure levels. MATERIALS AND METHODS: The photon-counting system employs an innovative silicon-based photon-counting detector to provide a balanced approach to ultra-high-resolution spectral CT imaging. An initial cohort of volunteer subjects was imaged using the prototype photon-counting system. Acquisition technique parameters and radiation dose exposures were guided by routine clinical exposure levels used at the institution. Images were reconstructed in native slice thickness using an early version of a spectral CT reconstruction algorithm Samples of images across a range of clinical tasks were selected and presented for review. RESULTS: Clinical cases are presented across inner ear, carotid angiography, chest, and musculoskeletal imaging tasks. Initial reconstructed images illustrate ultra-high spatial resolution imaging. The fine detail of small structures and pathologies is clearly visualized, and structural boundaries are well delineated. The prototype system additionally provides concomitant spectral information with high spatial resolution. CONCLUSION: This initial study demonstrates that routine imaging at clinically appropriate patient exposure levels is feasible using a novel deep-silicon photon-counting detector CT system. Furthermore, a deep-silicon detector may provide a balanced approach to photon-counting CT, providing high spatial resolution imaging with simultaneous high-fidelity spectral information.

Stent appearance in a novel silicon-based photon-counting CT prototype: ex vivo phantom study in head-to-head comparison with conventional energy-integrating CT.

BACKGROUND: In this study, stent appearance in a novel silicon-based photon-counting computed tomography (Si-PCCT) prototype was compared with a conventional energy-integrating detector CT (EIDCT) system. METHODS: An ex vivo phantom was created, consisting of a 2% agar-water mixture, in which human-resected and stented arteries were individually embedded. Using similar technique parameters, helical scan data was acquired using a novel prototype Si-PCCT and a conventional EIDCT system at a volumetric CT dose index (CTDIvol) of 9 mGy. Reconstructions were made at 502 and 1502 mm2 field-of-views (FOVs) using a bone kernel and adaptive statistical iterative reconstruction with 0% blending. Using a 5-point Likert scale, reader evaluations were performed on stent appearance, blooming and inter-stent visibility. Quantitative image analysis was performed on stent diameter accuracy, blooming and inter-stent distinction. Qualitative and quantitative differences between Si-PCCT and EIDCT systems were tested with a Wilcoxon signed-rank test and a paired samples t-test, respectively. Inter- and intra-reader agreement was assessed using the intraclass correlation coefficient (ICC). RESULTS: Qualitatively, Si-PCCT images were rated higher than EIDCT images at 150-mm FOV, based on stent appearance (p = 0.026) and blooming (p = 0.015), with a moderate inter- (ICC = 0.50) and intra-reader (ICC = 0.60) agreement. Quantitatively, Si-PCCT yielded more accurate diameter measurements (p = 0.001), reduced blooming (p < 0.001) and improved inter-stent distinction (p < 0.001). Similar trends were observed for the images reconstructed at 50-mm FOV. CONCLUSIONS: When compared to EIDCT, the improved spatial resolution of Si-PCCT yields enhanced stent appearance, more accurate diameter measurements, reduced blooming and improved inter-stent distinction. KEY POINTS: • This study evaluated stent appearance in a novel silicon-based photon-counting computed tomography (Si-PCCT) prototype. • Compared to standard CT, Si-PCCT resulted in more accurate stent diameter measurements. • Si-PCCT also reduced blooming artefacts and improved inter-stent visibility.

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 gen ' ) 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 gen ' ). The proposed method leverages existing AEC methods that are based on a prescribed noise level. The generalized d gen ' 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 gen ' and noise standard deviation. The performance of the proposed d gen ' -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 gen ' predicted by the lookup table and d ' 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 gen ' -AEC method were 3.3 (reference image), 3.5 (IR1), 3.6 (IR2), 3.5 (IR3), and 2.2 (IR4). When using the d gen ' -AEC method, the observers' IQ scores for the reference reconstruction were statistical equivalent to the scores for IR1, IR2, and IR3 iterative reconstructions (P > 0.35). The d gen ' -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 gen ' -AEC can produce similar IQ across different iterative reconstruction approaches at different dose levels.

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 < 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.

Technical Note: Phantom study to evaluate the dose and image quality effects of a computed tomography organ-based tube current modulation technique.

PURPOSE: This technical note quantifies the dose and image quality performance of a clinically available organ-dose-based tube current modulation (ODM) technique, using experimental and simulation phantom studies. The investigated ODM implementation reduces the tube current for the anterior source positions, without increasing current for posterior positions, although such an approach was also evaluated for comparison. METHODS: Axial CT scans at 120 kV were performed on head and chest phantoms on an ODM-equipped scanner (Optima CT660, GE Healthcare, Chalfont St. Giles, England). Dosimeters quantified dose to breast, lung, heart, spine, eye lens, and brain regions for ODM and 3D-modulation (SmartmA) settings. Monte Carlo simulations, validated with experimental data, were performed on 28 voxelized head phantoms and 10 chest phantoms to quantify organ dose and noise standard deviation. The dose and noise effects of increasing the posterior tube current were also investigated. RESULTS: ODM reduced the dose for all experimental dosimeters with respect to SmartmA, with average dose reductions across dosimeters of 31% (breast), 21% (lung), 24% (heart), 6% (spine), 19% (eye lens), and 11% (brain), with similar results for the simulation validation study. In the phantom library study, the average dose reduction across all phantoms was 34% (breast), 20% (lung), 8% (spine), 20% (eye lens), and 8% (brain). ODM increased the noise standard deviation in reconstructed images by 6%-20%, with generally greater noise increases in anterior regions. Increasing the posterior tube current provided similar dose reduction as ODM for breast and eye lens, increased dose to the spine, with noise effects ranging from 2% noise reduction to 16% noise increase. At noise equal to SmartmA, ODM increased the estimated effective dose by 4% and 8% for chest and head scans, respectively. Increasing the posterior tube current further increased the effective dose by 15% (chest) and 18% (head) relative to SmartmA. CONCLUSIONS: ODM reduced dose in all experimental and simulation studies over a range of phantoms, while increasing noise. The results suggest a net dose/noise benefit for breast and eye lens for all studied phantoms, negligible lung dose effects for two phantoms, increased lung dose and/or noise for eight phantoms, and increased dose and/or noise for brain and spine for all studied phantoms compared to the reference protocol.

Evaluation of the absorbed dose to the breast using radiochromic film in a dedicated CT mammotomography system employing a quasi-monochromatic x-ray beam.

PURPOSE: A dual modality SPECT-CT prototype system dedicated to uncompressed breast imaging (mammotomography) has been developed. The computed tomography subsystem incorporates an ultrathick K-edge filtration technique producing a quasi-monochromatic x-ray cone beam that optimizes the dose efficiency of the system for lesion imaging in an uncompressed breast. Here, the absorbed dose in various geometric phantoms and in an uncompressed and pendant cadaveric breast using a normal tomographic cone beam imaging protocol is characterized using both thermoluminescent dosimeter (TLD) measurements and ionization chamber-calibrated radiochromic film. METHODS: Initially, two geometric phantoms and an anthropomorphic breast phantom are filled in turn with oil and water to simulate the dose to objects that mimic various breast shapes having effective density bounds of 100% fatty and glandular breast compositions, respectively. Ultimately, an excised human cadaver breast is tomographically scanned using the normal tomographic imaging protocol, and the dose to the breast tissue is evaluated and compared to the earlier phantom-based measurements. RESULTS: Measured trends in dose distribution across all breast geometric and anthropomorphic phantom volumes indicate lower doses in the medial breast and more proximal to the chest wall, with consequently higher doses near the lateral peripheries and nipple regions. Measured doses to the oil-filled phantoms are consistently lower across all volume shapes due to the reduced mass energy-absorption coefficient of oil relative to water. The mean measured dose to the breast cadaver, composed of adipose and glandular tissues, was measured to be 4.2 mGy compared to a mean whole-breast dose of 3.8 and 4.5 mGy for the oil- and water-filled anthropomorphic breast phantoms, respectively. CONCLUSIONS: Assuming rotational symmetry due to the tomographic acquisition exposures, these results characterize the 3D dose distributions in an uncompressed human breast tissue volume for this dedicated breast imaging device and illustrate advantages of using the novel ultrathick K-edge filtered beam to minimize the dose to the breast during fully-3D imaging.