Comparison of automated kidney stone size measurement and volumetry in photon counting CT compared to 3rd generation dual energy CT and physically measurements - an ex vivo study.

PURPOSE: This ex vivo study aimed to compare a newly developed dual-source photon-counting CT (PCCT) with a 3rd generation dual-source dual-energy CT (DECT) for the detection and measurement (stone lengths and volumetrics) of urinary stones. METHODS: 143 urinary stones with a known geometry were physically measured and defined as reference values. Next, urinary stones were placed in an anthropomorphic abdomen-model and were scanned with DECT and PCCT. Images were read by two experienced examiners and automatically evaluated using a specific software. RESULTS: DECT and PCCT showed a high sensitivity for manual stone detection of 97.9% and 94.4%, and for automatic detection of 93.0% and 87.4%, respectively. Compared to that uric acid and xanthine stones were recognized slightly worse by DECT and PCCT with manual stone detection (93.3% and 82.2%), and with automatic detection (77.8% and 60.0%). All other stone entities were completely recognized. By comparing the maximum diameter of the reference value and DECT, Pearson-correlation was 0.96 (p < 0.001) for manual and 0.97 (p < 0.001) for automatic measurement, and for PCCT it was 0.94 (p < 0.001) for manual and 0.97 (p < 0.001) for automatic measurements. DECT and PCCT can also reliably determine volume manually and automatically with a Pearson-correlation of 0.99 (p < 0.001), respectively. CONCLUSION: Both CTs showed comparable results in stone detection, length measurement and volumetry compared to the reference values. Automatic measurement tends to underestimate the maximum diameter. DECT proved to be slightly superior in the recognition of xanthine and uric acid stones.

Image quality of lung perfusion with photon-counting-detector CT: comparison with dual-source, dual-energy CT.

PURPOSE: To evaluate the quality of lung perfusion imaging obtained with photon-counting-detector CT (PCD-CT) in comparison with dual-source, dual-energy CT (DECT). METHODS: Seventy-one consecutive patients scanned with PCD-CT were compared to a paired population scanned with dual-energy on a 3rd-generation DS-CT scanner using (a) for DS-CT (Group 1): collimation: 64 × 0.6 × 2 mm; pitch: 0.55; (b) for PCD-CT (Group 2): collimation: 144 × 0.4 mm; pitch: 1.5; single-source acquisition. The injection protocol was similar in both groups with the reconstruction of perfusion images by subtraction of high- and low-energy virtual monoenergetic images. RESULTS: Compared to Group 1, Group 2 examinations showed: (a) a shorter duration of data acquisition (0.93 ± 0.1 s vs 3.98 ± 0.35 s; p < 0.0001); (b) a significantly lower dose-length-product (172.6 ± 55.14 vs 339.4 ± 75.64 mGy·cm; p < 0.0001); and (c) a higher level of objective noise (p < 0.0001) on mediastinal images. On perfusion images: (a) the mean level of attenuation did not differ (p = 0.05) with less subjective image noise in Group 2 (p = 0.049); (b) the distribution of scores of fissure visualization differed between the 2 groups (p < 0.0001) with a higher proportion of fissures sharply delineated in Group 2 (n = 60; 84.5% vs n = 26; 26.6%); (c) the rating of cardiac motion artifacts differed between the 2 groups (p < 0.0001) with a predominance of examinations rated with mild artifacts in Group 2 (n = 69; 97.2%) while the most Group 1 examinations showed moderate artifacts (n = 52; 73.2%). CONCLUSION: PCD-CT acquisitions provided similar morphologic image quality and superior perfusion imaging at lower radiation doses. CLINICAL RELEVANCE STATEMENT: The improvement in the overall quality of perfusion images at lower radiation doses opens the door for wider applications of lung perfusion imaging in clinical practice. KEY POINTS: The speed of data acquisition with PCD-CT accounts for mild motion artifacts. Sharply delineated fissures are depicted on PCD-CT perfusion images. High-quality perfusion imaging was obtained with a 52% dose reduction.

Photon-Counting Computed Tomography for Microstructural Imaging of Bone and Joints.

PURPOSE OF REVIEW: Recently, photon-counting computed tomography (PCCT) has been introduced in clinical research and diagnostics. This review describes the technological advances and provides an overview of recent applications with a focus on imaging of bone. RECENT FINDINGS: PCCT is a full-body scanner with short scanning times that provides better spatial and spectral resolution than conventional energy-integrating-detector CT (EID-CT), along with an up to 50% reduced radiation dose. It can be used to quantify bone mineral density, to perform bone microstructural analyses and to assess cartilage quality with adequate precision and accuracy. Using a virtual monoenergetic image reconstruction, metal artefacts can be greatly reduced when imaging bone-implant interfaces. Current PCCT systems do not allow spectral imaging in ultra-high-resolution (UHR) mode. Given its improved resolution, reduced noise and spectral imaging capabilities PCCT has diagnostic capacities in both qualitative and quantitative imaging that outperform those of conventional CT. Clinical use in monitoring bone health has already been demonstrated. The full potential of PCCT systems will be unlocked when UHR spectral imaging becomes available.

Chances and challenges of photon-counting CT in musculoskeletal imaging.

In musculoskeletal imaging, CT is used in a wide range of indications, either alone or in a synergistic approach with MRI. While MRI is the preferred modality for the assessment of soft tissues and bone marrow, CT excels in the imaging of high-contrast structures, such as mineralized tissue. Additionally, the introduction of dual-energy CT in clinical practice two decades ago opened the door for spectral imaging applications. Recently, the advent of photon-counting detectors (PCDs) has further advanced the potential of CT, at least in theory. Compared to conventional energy-integrating detectors (EIDs), PCDs provide superior spatial resolution, reduced noise, and intrinsic spectral imaging capabilities. This review briefly describes the technical advantages of PCDs. For each technical feature, the corresponding applications in musculoskeletal imaging will be discussed, including high-spatial resolution imaging for the assessment of bone and crystal deposits, low-dose applications such as whole-body CT, as well as spectral imaging applications including the characterization of crystal deposits and imaging of metal hardware. Finally, we will highlight the potential of PCD-CT in emerging applications, underscoring the need for further preclinical and clinical validation to unleash its full clinical potential.

CT in musculoskeletal imaging: still helpful and for what?

Computed tomography (CT) is a common modality employed for musculoskeletal imaging. Conventional CT techniques are useful for the assessment of trauma in detection, characterization and surgical planning of complex fractures. CT arthrography can depict internal derangement lesions and impact medical decision making of orthopedic providers. In oncology, CT can have a role in the characterization of bone tumors and may elucidate soft tissue mineralization patterns. Several advances in CT technology have led to a variety of acquisition techniques with distinct clinical applications. These include four-dimensional CT, which allows examination of joints during motion; cone-beam CT, which allows examination during physiological weight-bearing conditions; dual-energy CT, which allows material decomposition useful in musculoskeletal deposition disorders (e.g., gout) and bone marrow edema detection; and photon-counting CT, which provides increased spatial resolution, decreased radiation, and material decomposition compared to standard multi-detector CT systems due to its ability to directly translate X-ray photon energies into electrical signals. Advanced acquisition techniques provide higher spatial resolution scans capable of enhanced bony microarchitecture and bone mineral density assessment. Together, these CT acquisition techniques will continue to play a substantial role in the practices of orthopedics, rheumatology, metabolic bone, oncology, and interventional radiology.

Visual and Quantitative Evaluation of Low-Concentration Bismuth in Dual-Contrast Imaging of Iodine and Bismuth Using Clinical Photon-Counting CT.

Simultaneous dual-contrast imaging of iodine and bismuth has shown promise in prior phantom and animal studies utilizing spectral CT. However, it is noted that in previous studies, Pepto-Bismol has frequently been employed as the source of bismuth, exceeding the recommended levels for human subjects. This investigation sought to assess the feasibility of visually differentiating and precisely quantifying low-concentration bismuth using clinical dual-source photon-counting CT (PCCT) in a scenario involving both iodinated and bismuth-based contrast materials. Four bismuth samples (0.6, 1.3, 2.5, and 5.1 mg/mL) were prepared using Pepto-Bismol, alongside three iodine rods (1, 2, and 5 mg/mL), inserted into multi-energy CT phantoms with three different sizes, and scanned on a PCCT system at three tube potentials (120, 140, and Sn140 kV). A generic image-based three-material decomposition method generated iodine and bismuth maps, with mean mass concentrations and noise levels measured. The root-mean-square errors for iodine and bismuth determined the optimal tube potential. The tube potential of 140 kV demonstrated optimal quantification performance when both iodine and bismuth were considered. Distinct differentiation of iodine rods with all three concentrations and bismuth samples with mass concentrations ≥ 1.3 mg/mL was observed across all phantom sizes at the optimal kV setting.

Value of virtual non-contrast images to identify uncomplicated cystic renal lesions: photon-counting detector CT vs. dual-energy integrating detector CT.

PURPOSE: To investigate the value of photon-counting detector CT (PCD-CT) derived virtual non-contrast (VNC) reconstructions to identify renal cysts in comparison with conventional dual-energy integrating detector (DE EID) CT-derived VNC reconstructions. MATERIAL AND METHODS: We prospectively enrolled consecutive patients with simple renal cysts (Bosniak classification-Version 2019, density ≤ 20 HU and/or enhancement ≤ 20 HU) who underwent multiphase (non-contrast, arterial, portal venous phase) PCD-CT and for whom non-contrast and portal venous phase DE EID-CT was available. Subsequently, VNC reconstructions were calculated for all contrast phases and density as well as contrast enhancement within the cysts were measured and compared. MRI and/or ultrasound served as reference standards for lesion classification. RESULTS: 19 patients (1 cyst per patient; age 69.5 ± 10.7 years; 17 [89.5%] male) were included. Density measurements on PCD-CT non-contrast and VNC reconstructions (arterial and portal venous phase) revealed no significant effect on HU values (p = 0.301). In contrast, a significant difference between non-contrast vs. VNC images was found for DE EID-CT (p = 0.02). For PCD-CT, enhancement for VNC reconstructions was < 20 HU for all evaluated cysts. DE EID-CT measurements revealed an enhancement of > 20 HU in five lesions (26.3%) using the VNC reconstructions, which was not seen with the non-contrast images. CONCLUSION: PCD-CT-derived VNC images allow for reliable and accurate characterization of simple cystic renal lesions similar to non-contrast scans whereas VNC images calculated from DE EID-CT resulted in substantial false characterization. Thus, PCD-CT-derived VNC images may substitute for non-contrast images and reduce radiation dose and follow-up imaging.

Seeing Is Believing: Photon Counting Computed Tomography Clearly Images Directional Deep Brain Stimulation Lead Segments and Markers After Implantation.

BACKGROUND AND OBJECTIVES: Directional deep brain stimulation (DBS) electrodes are increasingly used, but conventional computed tomography (CT) is unable to directly image segmented contacts owing to physics-based resolution constraints. Postoperative electrode segment orientation assessment is necessary because of the possibility of significant deviation during or immediately after insertion. Photon-counting detector (PCD) CT is a relatively novel technology that enables high resolution imaging while addressing several limitations intrinsic to CT. We show how PCD CT can enable clear in vivo imaging of DBS electrodes, including segmented contacts and markers for all major lead manufacturers. MATERIALS AND METHODS: We describe postoperative imaging and reconstruction protocols we have developed to enable optimal lead visualization. PCD CT images were obtained of directional leads from the three major manufacturers and fused with preoperative 3T magnetic resonance imaging (MRI). Radiation dosimetry also was evaluated and compared with conventional imaging controls. Orientation estimates from directly imaged leads were compared with validated software-based reconstructions (derived from standard CT imaging artifact analysis) to quantify congruence in alignment and directional orientation. RESULTS: High-fidelity images were obtained for 15 patients, clearly indicating the segmented contacts and directional markers both on CT alone and when fused to MRI. Our routine imaging protocol is described. Ionizing radiation doses were significantly lower than with conventional CT. For most leads, the directly imaged lead orientations and depths corresponded closely to those predicted by CT artifact-based reconstructions. However, unlike direct imaging, the software reconstructions were susceptible to 180° error in orientation assessment. CONCLUSIONS: High-resolution photon-counting CT can very clearly image segmented DBS electrode contacts and directional markers and unambiguously determine lead orientation, with lower radiation than in conventional imaging. This obviates the need for further imaging and may facilitate anatomically tailored directional programming.

Deep-silicon photon-counting x-ray projection denoising through reinforcement learning.

BACKGROUND: In recent years, deep reinforcement learning (RL) has been applied to various medical tasks and produced encouraging results. OBJECTIVE: In this paper, we demonstrate the feasibility of deep RL for denoising simulated deep-silicon photon-counting CT (PCCT) data in both full and interior scan modes. PCCT offers higher spatial and spectral resolution than conventional CT, requiring advanced denoising methods to suppress noise increase. METHODS: In this work, we apply a dueling double deep Q network (DDDQN) to denoise PCCT data for maximum contrast-to-noise ratio (CNR) and a multi-agent approach to handle data non-stationarity. RESULTS: Using our method, we obtained significant image quality improvement for single-channel scans and consistent improvement for all three channels of multichannel scans. For the single-channel interior scans, the PSNR (dB) and SSIM increased from 33.4078 and 0.9165 to 37.4167 and 0.9790 respectively. For the multichannel interior scans, the channel-wise PSNR (dB) increased from 31.2348, 30.7114, and 30.4667 to 31.6182, 30.9783, and 30.8427 respectively. Similarly, the SSIM improved from 0.9415, 0.9445, and 0.9336 to 0.9504, 0.9493, and 0.0326 respectively. CONCLUSIONS: Our results show that the RL approach improves image quality effectively, efficiently, and consistently across multiple spectral channels and has great potential in clinical applications.

Feature shared multi-decoder network using complementary learning for Photon counting CT ring artifact suppression.

BACKGROUND: Photon-counting computed tomography (Photon counting CT) utilizes photon-counting detectors to precisely count incident photons and measure their energy. These detectors, compared to traditional energy integration detectors, provide better image contrast and material differentiation. However, Photon counting CT tends to show more noticeable ring artifacts due to limited photon counts and detector response variations, unlike conventional spiral CT. OBJECTIVE: To comprehensively address this issue, we propose a novel feature shared multi-decoder network (FSMDN) that utilizes complementary learning to suppress ring artifacts in Photon counting CT images. METHODS: Specifically, we employ a feature-sharing encoder to extract context and ring artifact features, facilitating effective feature sharing. These shared features are also independently processed by separate decoders dedicated to the context and ring artifact channels, working in parallel. Through complementary learning, this approach achieves superior performance in terms of artifact suppression while preserving tissue details. RESULTS: We conducted numerous experiments on Photon counting CT images with three-intensity ring artifacts. Both qualitative and quantitative results demonstrate that our network model performs exceptionally well in correcting ring artifacts at different levels while exhibiting superior stability and robustness compared to the comparison methods. CONCLUSIONS: In this paper, we have introduced a novel deep learning network designed to mitigate ring artifacts in Photon counting CT images. The results illustrate the viability and efficacy of our proposed network model as a new deep learning-based method for suppressing ring artifacts.

Metal artifacts and artifact reduction of neurovascular coils in photon-counting detector CT versus energy-integrating detector CT - in vitro comparison of a standard brain imaging protocol.

OBJECTIVES: Photon-counting detector computed tomography (PCD-CT) is a promising new technique for CT imaging. The aim of the present study was the in vitro comparison of coil-related artifacts in PCD-CT and conventional energy-integrating detector CT (EID-CT) using a comparable standard brain imaging protocol before and after metal artifact reduction (MAR). METHODS: A nidus-shaped rubber latex, resembling an aneurysm of the cerebral arteries, was filled with neurovascular platinum coils and inserted into a brain imaging phantom. Image acquisition and reconstruction were repeatedly performed for PCD-CT and EID-CT (n = 10, respectively) using a standard brain imaging protocol. Moreover, linear interpolation MAR was performed for PCD-CT and EID-CT images. The degree of artifacts was analyzed quantitatively (standard deviation in a donut-shaped region of interest) and qualitatively (5-point scale analysis). RESULTS: Quantitative and qualitative analysis demonstrated a lower degree of metal artifacts in the EID-CT images compared to the total-energy PCD-CT images (e.g., 82.99 ± 7.89 Hounsfield units (HU) versus 90.35 ± 6.28 HU; p < 0.001) with no qualitative difference between the high-energy bin PCD-CT images and the EID-CT images (4.18 ± 0.37 and 3.70 ± 0.64; p = 0.575). After MAR, artifacts were more profoundly reduced in the PCD-CT images compared to the EID-CT images in both analyses (e.g., 2.35 ± 0.43 and 3.18 ± 0.34; p < 0.001). CONCLUSION: PCD-CT in combination with MAR have the potential to provide an improved option for reduction of coil-related artifacts in cerebral imaging in this in vitro study. KEY POINTS: • Photon-counting detector CT produces more artifacts compared to energy-integrating detector CT without metal artifact reduction in cerebral in vitro imaging after neurovascular coil-embolization. • Spectral information of PCD-CT provides the potential for new post-processing techniques, since the coil-related artifacts were lower in PCD-CT images compared to EID-CT images after linear interpolation metal artifact reduction in this in vitro study.

Myeloma bone disease imaging on a 1st-generation clinical photon-counting detector CT vs. 2nd-generation dual-source dual-energy CT.

OBJECTIVE: Subjective and objective image quality comparison of bone microstructure and disease-related abnormalities in multiple myeloma patients using a 1st-generation dual-source photon-counting detector CT(DS-PCD-CT) and a 2nd-generation dual-source dual-energy (energy-integrating detector) CT (DS-EID-CT). METHODS: Fifty multiple myeloma patients (mean age 67.7 ± 10.9 years,16 females) were prospectively enrolled. Unenhanced whole-body CTs were clinically indicated and performed on DS-EID-CT and DS-PCD-CT (median time difference: 12 months). DS-PCD-CT was performed in Quantumplus UHR mode and DS-EID-CT was performed using dual-energy mode. DS-PCD-CT kernel was set at Br64 with Quantum iterative reconstruction strength Q1; for DS-EID-CT a comparable I70f kernel with SAFIRE iterative reconstruction strength 1 was used. Two independent radiologists assessed image quality subjectively using a 5-point Likert scale considering delineation and sharpness of trabecular bone and lytic bone lesions in the spine and pelvic bones. Additionally, ImageJ was used for quantification of bony septa inside the cancellous bone and through or the edges of osteolysis. RESULTS: Overall quality as well as detectability and sharpness in the delineation of lytic bone lesions were superior for DS-PCD-CT compared with DS-EID-CT (p < 0.0001). The inter-reader agreement for subjective image quality readings showed excellent consistency(α = 94.2-98.8). CTDI and DLP mean values for DS-PCD-CT and DS-EID-CT were 1107.4 ± 247.6 mGy*cm and 8.2 ± 1.8 mGy vs. 1344.3 ± 204.6 mGy*cm and 10.1 ± 1.9 mGy. The quantitative metric for bone microstructure in the femoral head showed significantly better visualization of trabeculae in DS-PCD-CT compared with DS-EID-CT (p < 0.0001). Quantitative analyses of edge sharpness of osteolysis showed significant steeper edges for DS-PCD-CT (p < 0.0001). CONCLUSION: DS-PCD-CT significantly improves spatial resolution of bony microstructure and lytic bone lesions compared to DS-EID-CT. KEY POINTS: • Application of photon-counting detector CT is superior to dual-source dual-energy integrating detector in clinical workup of multiple myeloma patients. • Compared to energy integrating detectors, photon-counting detectors significantly increase the spatial resolution of bone microstructure including disease-related lytic bone lesions in patients with multiple myeloma.

Pediatric Applications of Photon-Counting Detector CT.

Photon-counting detector (PCD) CT represents the most recent generational advance in CT technology. PCD CT has the potential to reduce image noise, improve spatial resolution and contrast resolution, and provide multispectral capability, all of which may be achieved with an overall decrease in the radiation dose. These effects may be used to reduce the iodinated contrast media dose and potentially obtain multiphase images through a single-acquisition technique. The benefits of PCD CT have previously been shown primarily in phantoms and adult patients. This article describes the application of PCD CT in children, as illustrated by clinical examples from a commercially available PCD CT system.

Comparison of Radiation Dose and Image Quality of Pediatric High-Resolution Chest CT Between Photon-Counting Detector CT and Energy-Integrated Detector CT: A Matched Study.

BACKGROUND. Photon-counting detector (PCD) CT has been shown to reduce radiation dose and improve image quality in adult chest CT examinations; its potential impact in pediatric CT is not well documented. OBJECTIVE. The purpose of our study was to compare radiation dose, objective image quality, and subjective image quality of PCD CT and energy-integrating detector (EID) CT in children undergoing high-resolution CT (HRCT) of the chest. METHODS. This retrospective study included 27 children (median age, 3.9 years; 10 girls, 17 boys) who underwent PCD CT between March 1, 2022, and August 31, 2022, and 27 children (median age, 4.0 years; 13 girls, 14 boys) who underwent EID CT between August 1, 2021, and January 31, 2022; all examinations comprised clinically indicated chest HRCT. The patients in the two groups were matched by age and water-equivalent diameter. Radiation dose parameters were recorded. One observer placed ROIs to measure objective parameters (lung attenuation, image noise, and SNR). Two radiologists independently assessed subjective measures (overall image quality and motion artifacts) using 5-point Likert scales (1 = highest quality). Groups were compared. RESULTS. PCD CT, in comparison with EID CT, showed lower median CTDIvol (0.41 vs 0.71 mGy, p < .001), DLP (10.2 vs 13.7 mGy × cm, p = .008), size-specific dose estimate (0.82 vs 1.34 mGy, p < .001), and tube current-exposure time product (48.0 vs 202.0 mAs, p < .001). PCD CT and EID CT showed no significant difference in right upper lobe (RUL) lung attenuation (mean, -793 vs -750 HU; p = .09), right lower lobe (RLL) lung attenuation (mean, -745 vs -716 HU; p = .23), RUL image noise (mean, 55 vs 51 HU; p = .27), RLL image noise (mean, 59 vs 57 HU; p = .48), RUL SNR (mean, -14.9 vs -15.8; p = .89), or RLL SNR (mean, -13.1 vs -13.6; p = .79). PCD CT and EID CT showed no significant difference in median overall image quality for reader 1 (1.0 vs 1.0, p = .28) or reader 2 (1.0 vs 1.0, p = .17) or median motion artifacts for reader 1 (1.0 vs 1.0, p = .07) or reader 2 (1.0 vs 1.0, p = .22). CONCLUSION. PCD CT showed significantly reduced dose levels without a significant difference in objective or subjective image quality compared with EID CT. CLINICAL IMPACT. These data expand understanding of the capabilities of PCD CT and support its routine use in children.

CT in osteoarthritis: its clinical role and recent advances.

Computed tomography (CT) is a widely available imaging method and considered as one of the most reliable techniques in bone assessment. Although CT has limited tissue contrast and needs radiation exposure, it has several advantages like fast scanning time and high spatial resolution. In this regard, CT has unique roles in osteoarthritis (OA) and its variable utilities have been reported. Hence, this review highlights the clinical role of CT in OA of representative joints. In addition, CT showed the several technical advancements recently, for example, acquiring the CT image with standing, obtaining the dual-energy data, and novel photon-counting detector development. Therefore, the recent studies and potential utility of these new CT systems in OA are also discussed.

Feasibility of photon-counting CT for femoroacetabular impingement syndrome evaluation: lower radiation dose and improved diagnostic confidence.

OBJECTIVE: The feasibility of low-dose photon-counting detector (PCD) CT to measure alpha and acetabular version angles of femoroacetabular impingement (FAI). MATERIAL AND METHODS: FAI patients undergoing an energy-integrating detector (EID) CT underwent an IRB-approved prospective ultra-high-resolution (UHR) PCD-CT between 5/2021 and 12/2021. PCD-CT was dose-matched to the EID-CT or acquired at 50% dose. Simulated 50% dose EID-CT images were generated. Two radiologists evaluated randomized EID-CT and PCD-CT images and measured alpha and acetabular version angles on axial image slices. Image quality (noise, artifacts, and visualization of cortex) and confidence in non-FAI pathology were rated on a 4-point scale (3 = adequate). Preference tests of standard dose PCD-CT, 50% dose PCD-CT, and 50% dose EID-CT relative to standard dose EID-CT were performed using Wilcoxon Rank test. RESULTS: 20 patients underwent standard dose EID-CT (~ CTDIvol, 4.5 mGy); 10 patients, standard dose PCD-CT (4.0 mGy); 10 patients, 50% PCD-CT (2.6 mGy). Standard dose EID-CT images were scored as adequate for diagnostic task in all categories (range 2.8-3.0). Standard dose PCD-CT images scored higher than the reference in all categories (range 3.5-4, p < 0.0033). Half-dose PCD-CT images also scored higher for noise and cortex visualization (p < 0.0033) and equivalent for artifacts and visualization of non-FAI pathology. Finally, simulated 50% EID-CT images scored lower in all categories (range 1.8-2.4, p < 0.0033). CONCLUSIONS: Dose-matched PCD-CT is superior to EID-CT for alpha angle and acetabular version measurement in the work up of FAI. UHR-PCD-CT enables 50% radiation dose reduction compared to EID while remaining adequate for the imaging task.

A methodology for incorporating a photon-counting CT system into routine clinical use.

Photon-counting computed tomography (PCCT) systems are increasingly available in the U.S. following Food and Drug Administration (FDA) approval of the first clinical PCCT system in Fall 2021. Consequently, there will be a need to incorporate PCCTs into existing fleets of traditional CT systems. The commissioning process of a PCCT was devised by evaluating the degree of agreement between the performance of the PCCT and that of established clinical CT systems. A PCCT system (Siemens NAEOTOM Alpha) was evaluated using the American College of Radiology(ACR) CT phantom (Gammex 464). The phantom was scanned on the system and on a 3rd Generation EID CT system (Siemens Force) at three clinical dose levels. Images were reconstructed across the range of available reconstruction kernels and Iterative Reconstruction (IR) strengths. Two image quality metrics-spatial resolution and noise texture-were calculated using AAPM TG233 software (imQuest), as well as a dose metric to achieve target image noise magnitude of 10 HU. For each pair of EID-PCCT kernel/IR strengths, the difference in metrics were calculated, weighted, and multiplied over all metrics to determine the concordance between systems. IR performance was characterized by comparing relative noise texture and reference dose as a function of IR strength for each system. In general, as kernel "sharpness" increased for each system, spatial resolution, noise spatial frequency, and reference dose increased. For a given kernel, EID reconstruction showed higher spatial resolution compared to PCCT in standard resolution mode. PCCT implementation of IR better preserved noise texture across all strengths compared to the EID, demonstrated by respective 20 and 7% shifts in noise texture from IR "Off" to IR "Max." Overall, the closest match for a given EID reconstruction kernel/IR strength was identified as a PCCT kernel with "sharpness" increased by 1 step and IR strength increased by 1-2 steps. Substantial dose reduction potential of up to 70% was found when targeting a constant noise magnitude.

Noise correlation and its impact on the performance of multi-material decomposition-based spectral imaging in photon-counting CT.

PURPOSE: It has been known that noise correlation plays an important role in the determination of the performance of spectral imaging based on two-material decomposition (2-MD). To further understand the basics of spectral imaging in photon-counting CT toward optimal design and implementation, we study the noise correlation in multi-MD (m-MD) and its impact on the performance of spectral imaging. METHOD: We derive the equations that characterize the noise and noise correlation in the material-specific (basis) images in m-MD, followed by a simulation study to verify the derived equations and study the noise correlation's impact on the performance of spectral imaging. Using a specially designed digital phantom, the study of noise correlation runs over the cases of two-, three-, and four-MD (2-MD, 3-MD, and 4-MD). Then, the noise correlation's impact on the performance of spectral imaging in photon-counting CT is investigated, using a modified Shepp-Logan phantom. RESULTS: The results in 2-MD show that, in-line with what has been reported in the literature, the noise correlation coefficient between the material-specific images corresponding to the basis materials approaches -1. The results in m-MD (m ≥ 3) are more complicated and interesting, as the noise correlation coefficients between a pair of the material-specific images alternate between ±1, and so do in the case of 4-MD. The m-MD data show that the noise in virtual monochromatic imaging (a form of spectral imaging) is moderate even though the noises in material-specific (basis) images vary drastically. CONCLUSIONS: The observation of noise correlation in 3-MD, 4-MD, and beyond (i.e., m-MD) is informative to the community. The relationship between noise correlation and the performance of spectral imaging revealed in this work may help clinical medical physicists understand the fundamentals of spectral imaging based on MD and optimize the performance of spectral imaging in photon-counting CT and other X-ray imaging modalities.

Calculation of Stopping-Power Ratio from Multiple CT Numbers Using Photon-Counting CT System: Two- and Three-Parameter-Fitting Method.

The two-parameter-fitting method (PFM) is commonly used to calculate the stopping-power ratio (SPR). This study proposes a new formalism: a three-PFM, which can be used in multiple spectral computed tomography (CT). Using a photon-counting CT system, seven rod-shaped samples of aluminium, graphite, and poly(methyl methacrylate) (PMMA), and four types of biological phantom materials were placed in a water-filled sample holder. The X-ray tube voltage and current were set at 150 kV and 40 µA, respectively, and four CT images were obtained at four threshold settings. A semi-empirical correction method that corrects the difference between the CT values from the photon-counting CT images and theoretical values in each spectral region was also introduced. Both the two- and three-PFMs were used to calculate the effective atomic number and electron density from multiple CT numbers. The mean excitation energy was calculated via parameterisation with the effective atomic number, and the SPR was then calculated from the calculated electron density and mean excitation energy. Then, the SPRs from both methods were compared with the theoretical values. To estimate the noise level of the CT numbers obtained from the photon-counting CT, CT numbers, including noise, were simulated to evaluate the robustness of the aforementioned PFMs. For the aluminium and graphite, the maximum relative errors for the SPRs calculated using the two-PFM and three-PFM were 17.1% and 7.1%, respectively. For the PMMA and biological phantom materials, the maximum relative errors for the SPRs calculated using the two-PFM and three-PFM were 5.5% and 2.0%, respectively. It was concluded that the three-PFM, compared with the two-PFM, can yield SPRs that are closer to the theoretical values and is less affected by noise.