Spectral Photon-Counting Computed Tomography: A Review on Technical Principles and Clinical Applications

Contrast-to-noise ratio comparison between X-ray fluorescence emission tomography and computed tomography

Purpose

We provide a comparison of X-ray fluorescence emission tomography (XFET) and computed tomography (CT) for detecting low concentrations of gold nanoparticles (GNPs) in soft tissue and characterize the conditions under which XFET outperforms energy-integrating CT (EICT) and photon-counting CT (PCCT).

Approach

We compared dose-matched Monte Carlo XFET simulations and analytical fan-beam EICT and PCCT simulations. Each modality was used to image a numerical mouse phantom and contrast-depth phantom containing GNPs ranging from 0.05% to 4% by weight in soft tissue. Contrast-to-noise ratios (CNRs) of gold regions were compared among the three modalities, and XFET's detection limit was quantified based on the Rose criterion. A partial field-of-view (FOV) image was acquired for the phantom region containing 0.05% GNPs.

Results

For the mouse phantom, XFET produced superior CNR values ( CNRs = 24.5 , 21.6, and 3.4) compared with CT images obtained with both energy-integrating ( CNR = 4.4 , 4.6, and 1.5) and photon-counting ( CNR = 6.5 , 7.7, and 2.0) detection systems. More generally, XFET outperformed CT for superficial imaging depths ( < 28.75    mm ) for gold concentrations at and above 0.5%. XFET's surface detection limit was quantified as 0.44% for an average phantom dose of 16 mGy compatible with in vivo imaging. XFET's ability to image partial FOVs was demonstrated, and 0.05% gold was easily detected with an estimated dose of ∼ 81.6    cGy to a localized region of interest.

Conclusions

We demonstrate a proof of XFET's benefit for imaging low concentrations of gold at superficial depths and the feasibility of XFET for in vivo metal mapping in preclinical imaging tasks.

Photon-Counting Computed Tomography Angiography of Carotid Arteries: A Topical Narrative Review with Case Examples

Photon counting computed tomography (PCCT) represents a paradigm shift from conventional CT imaging, propelled by a new generation of X-ray detectors capable of counting individual photons and measuring their energy. The first part of this narrative review is focused on the technical aspects of PCCT and describes its key advancements and benefits compared to conventional CT but also its limitations. By synthesizing the existing literature, the second part of the review seeks to elucidate the potential of PCCT as a valuable tool for assessing carotid artery disease. Thanks to the enhanced spatial resolution and image quality, PCCT allows for an accurate evaluation of carotid luminal stenosis. With its ability to finely discriminate between different tissue types, PCCT allows for detailed characterization of plaque morphology and composition, which is crucial for assessing plaque vulnerability and the risk of cerebrovascular events.

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.

Photon-counting computed tomography versus energy-integrating computed tomography for detection of small liver lesions: comparison using a virtual framework imaging

Purpose

Photon-counting computed tomography (PCCT) has the potential to provide superior image quality to energy-integrating CT (EICT). We objectively compare PCCT to EICT for liver lesion detection.

Approach

Fifty anthropomorphic, computational phantoms with inserted liver lesions were generated. Contrast-enhanced scans of each phantom were simulated at the portal venous phase. The acquisitions were done using DukeSim, a validated CT simulation platform. Scans were simulated at two dose levels (CTDI vol 1.5 to 6.0 mGy) modeling PCCT (NAEOTOM Alpha, Siemens, Erlangen, Germany) and EICT (SOMATOM Flash, Siemens). Images were reconstructed with varying levels of kernel sharpness (soft, medium, sharp). To provide a quantitative estimate of image quality, the modulation transfer function (MTF), frequency at 50% of the MTF (f 50 ), noise magnitude, contrast-to-noise ratio (CNR, per lesion), and detectability index (d ' , per lesion) were measured.

Results

Across all studied conditions, the best detection performance, measured byd ' , was for PCCT images with the highest dose level and softest kernel. With soft kernel reconstruction, PCCT demonstrated improved lesion CNR andd ' compared with EICT, with a mean increase in CNR of 35.0% ( p < 0.001 ) and 21% ( p < 0.001 ) and a mean increase ind ' of 41.0% ( p < 0.001 ) and 23.3% ( p = 0.007 ) for the 1.5 and 6.0 mGy acquisitions, respectively. The improvements were greatest for larger phantoms, low-contrast lesions, and low-dose scans.

Conclusions

PCCT demonstrated objective improvement in liver lesion detection and image quality metrics compared with EICT. These advances may lead to earlier and more accurate liver lesion detection, thus improving patient care.

Artificial Intelligence-Driven Radiomics in Head and Neck Cancer: Current Status and Future Prospects

BACKGROUND

Radiomics is a rapidly growing field used to leverage medical radiological images by extracting quantitative features. These are supposed to characterize a patient's phenotype, and when combined with artificial intelligence techniques, to improve the accuracy of diagnostic models and clinical outcome prediction.

OBJECTIVES

This review aims at examining the application areas of artificial intelligence-based radiomics (AI-based radiomics) for the management of head and neck cancer (HNC). It further explores the workflow of AI-based radiomics for personalized and precision oncology in HNC. Finally, it examines the current challenges of AI-based radiomics in daily clinical oncology and offers possible solutions to these challenges.

METHODS

Comprehensive electronic databases (PubMed, Medline via Ovid, Scopus, Web of Science, CINAHL, and Cochrane Library) were searched following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. The quality of included studies and their risk of biases were evaluated using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD)and Prediction Model Risk of Bias Assessment Tool (PROBAST).

RESULTS

Out of the 659 search hits retrieved, 45 fulfilled the inclusion criteria. Our review revealed that the application of AI-based radiomics model as an ancillary tool for improved decision-making in HNC management includes radiomics-based cancer diagnosis and radiomics-based cancer prognosis. The radiomics-based cancer diagnosis includes tumor staging, tumor grading, and classification of malignant and benign tumors. Similarly, radiomics-based cancer prognosis includes prediction for treatment response, recurrence, metastasis, and survival. In addition, the challenges in the implementation of these models for clinical evaluations include data imbalance, feature engineering (extraction and selection), model generalizability, multi-modal fusion, and model interpretability.

CONCLUSION

Considering the highly subjective and interobserver variability that is peculiar to the interpretation of medical images by expert clinicians, AI-based radiomics seeks to offer potentially useful quantitative information, which is not visible to the human eye or unintentionally often remain ignored during clinical imaging practice. By enabling the extraction of this type of information, AI-based radiomics has the potential to revolutionize HNC oncology, providing a platform for more personalized, higher quality, and cost-effective care for HNC patients.

Photon-Counting Detector CT Angiography Versus Digital Subtraction Angiography in Patients with Peripheral Arterial Disease

RATIONALE AND OBJECTIVES

This study aims to compare the diagnostic confidence of photon-counting detector CT angiography (PCD-CTA) depending on the used vascular reformatting kernels with digital subtraction angiography (DSA) as diagnostic reference standard in peripheral arterial occlusive disease (PAOD).

MATERIAL AND METHODS

In 39 patients, 45 lower extremity PCD-CTA with subsequent DSA were analyzed. Advanced PAOD (Fontaine stage 4) was ascertained in 77.8% of patients. CTA post-processing comprised three vascular kernels (Bv36/48/56). Objective image quality assessment included vessel attenuation, image noise, contrast-to-noise (CNR) and signal-to-noise ratios (SNR). Subjective evaluation of calcium blooming, vessel sharpness, luminal attenuation and image noise was performed by three radiologists. Diagnostic performance and concordance to DSA were assessed.

RESULTS

The luminal attenuation remained kernel-independent constant. With sharper kernels, image noise increased substantially, while SNR and CNR decreased. Subjective reduction of calcium blooming and increased vessel sharpness were noted for the sharp Bv56 kernel. While sensitivity in stenosis quantification was comparable between kernels (81.6% vs. 81.5% vs. 81.0%, p = 0.797), specificity increased slightly higher sharpness (71.1% vs. 76.9% vs. 79.6%, p = 0.067). Diagnostic concordance of stenosis ratings compared to DSA increased likewise (Bv36 vs. Bv56, p = 0.002). Severe crural vessel calcifications had no influence on sensitivity, regardless of kernel selection. Contrarily, specificity was substantially worse in severely calcified tibial vessels but could be improved by using the sharp Bv56 kernel (Bv36 vs. Bv56 p = 0.024). Diagnostic confidence was highest for Bv56.

CONCLUSION

In lower leg PCD-CTA, sharp convolution kernels increase diagnostic confidence compared to DSA by improved vessel delineation and reduced calcium blooming with acceptable image noise.

Photon-Counting Computed Tomography: Experience in Musculoskeletal Imaging

Since the emergence of the first photon-counting computed tomography (PCCT) system in late 2021, its advantages and a wide range of applications in all fields of radiology have been demonstrated. Compared to standard energy-integrating detector-CT, PCCT allows for superior geometric dose efficiency in every examination. While this aspect by itself is groundbreaking, the advantages do not stop there. PCCT facilitates an unprecedented combination of ultra-high-resolution imaging without dose penalty or field-of-view restrictions, detector-based elimination of electronic noise, and ubiquitous multi-energy spectral information. Considering the high demands of orthopedic imaging for the visualization of minuscule details while simultaneously covering large portions of skeletal and soft tissue anatomy, no subspecialty may benefit more from this novel detector technology than musculoskeletal radiology. Deeply rooted in experimental and clinical research, this review article aims to provide an introduction to the cosmos of PCCT, explain its technical basics, and highlight the most promising applications for patient care, while also mentioning current limitations that need to be overcome.

Imaging Assessment of Radiation Therapy-Related Normal Tissue Injury in Children: A PENTEC Visionary Statement

The Pediatric Normal Tissue Effects in the Clinic (PENTEC) consortium has made significant contributions to understanding and mitigating the adverse effects of childhood cancer therapy. This review addresses the role of diagnostic imaging in detecting, screening, and comprehending radiation therapy-related late effects in children, drawing insights from individual organ-specific PENTEC reports. We further explore how the development of imaging biomarkers for key organ systems, alongside technical advancements and translational imaging approaches, may enhance the systematic application of imaging evaluations in childhood cancer survivors. Moreover, the review critically examines knowledge gaps and identifies technical and practical limitations of existing imaging modalities in the pediatric population. Addressing these challenges may expand access to, minimize the risk of, and optimize the real-world application of, new imaging techniques. The PENTEC team envisions this document as a roadmap for the future development of imaging strategies in childhood cancer survivors, with the overarching goal of improving long-term health outcomes and quality of life for this vulnerable population.

Coronary calcium scoring on virtual non-contrast and virtual non-iodine reconstructions compared to true non-contrast images using photon-counting computed tomography

OBJECTIVES

To compare coronary artery calcification (CAC) scores measured on virtual non-contrast (VNC) and virtual non-iodine (VNI) reconstructions computed from coronary computed tomography angiography (CCTA) using photon-counting computed tomography (PCCT) to true non-contrast (TNC) images.

METHODS

We included 88 patients (mean age = 59 years ± 13.5, 69% male) who underwent a TNC coronary calcium scan followed by CCTA on PCCT. VNC images were reconstructed in 87 patients and VNI in 88 patients by virtually removing iodine from the CCTA images. For all reconstructions, CAC scores were determined, and patients were classified into risk categories. The overall agreement of the reconstructions was analyzed by Bland-Altman plots and the level of matching classifications.

RESULTS

The median CAC score on TNC was 27.8 [0-360.4] compared to 8.5 [0.2-101.6] (p < 0.001) on VNC and 72.2 [1.3-398.8] (p < 0.001) on VNI. Bland-Altman plots depicted a bias of 148.8 (ICC = 0.82, p < 0.001) and - 57.7 (ICC = 0.95, p < 0.001) for VNC and VNI, respectively. Of all patients with CACTNC = 0, VNC reconstructions scored 63% of the patients correctly, while VNI scored 54% correctly. Of the patients with CACTNC > 0, VNC and VNI reconstructions detected the presence of coronary calcium in 90% and 92% of the patients. CACVNC tended to underestimate CAC score, whereas CACVNI overestimated, especially in the lower risk categories. According to the risk categories, VNC misclassified 55% of the patients, while VNI misclassified only 32%.

CONCLUSION

Compared to TNC images, VNC underestimated and VNI overestimated the actual CAC scores. VNI reconstructions quantify and classify coronary calcification scores more accurately than VNC reconstructions.

CLINICAL RELEVANCE STATEMENT

Photon-counting CT enables spectral imaging, which might obviate the need for non-contrast enhanced coronary calcium scoring, but optimization is necessary for the clinical implementation of the algorithms.

KEY POINTS

• Photon-counting computed tomography uses spectral information to virtually remove the signal of contrast agents from contrast-enhanced scans. • Virtual non-contrast reconstructions tend to underestimate coronary artery calcium scores compared to true non-contrast images, while virtual non-iodine reconstructions tend to overestimate the calcium scores. • Virtual non-iodine reconstructions might obviate the need for non-contrast enhanced calcium scoring, but optimization is necessary for the clinical implementation of the algorithms.

Photon-Counting Computed Tomography in Atherosclerotic Plaque Characterization

Atherosclerotic plaque buildup in the coronary and carotid arteries is pivotal in the onset of acute myocardial infarctions or cerebrovascular events, leading to heightened levels of illness and death. Atherosclerosis is a complex and multistep disease, beginning with the deposition of low-density lipoproteins in the arterial intima and culminating in plaque rupture. Modern technology favors non-invasive imaging techniques to assess atherosclerotic plaque and offer insights beyond mere artery stenosis. Among these, computed tomography stands out for its widespread clinical adoption and is prized for its speed and accessibility. Nonetheless, some limitations persist. The introduction of photon-counting computed tomography (PCCT), with its multi-energy capabilities, enhanced spatial resolution, and superior soft tissue contrast with minimal electronic noise, brings significant advantages to carotid and coronary artery imaging, enabling a more comprehensive examination of atherosclerotic plaque composition. This narrative review aims to provide a comprehensive overview of the main concepts related to PCCT. Additionally, we aim to explore the existing literature on the clinical application of PCCT in assessing atherosclerotic plaque. Finally, we will examine the advantages and limitations of this recently introduced technology.

Advanced Imaging of Shunt Valves in Cranial CT Scans with Photon-Counting Scanner

This brief report aimed to show the utility of photon-counting technology alongside standard cranial imaging protocols for visualizing shunt valves in a patient's cranial computed tomography scan. Photon-counting CT scans with cranial protocols were retrospectively surveyed and four types of shunt valves were encountered: proGAV 2.0®, M.blue®, Codman Certas®, and proSA®. These scans were compared with those obtained from non-photon-counting scanners at different time points for the same patients. The analysis of these findings demonstrated the usefulness of photon-counting technology for the clear and precise visualization of shunt valves without any additional radiation or special reconstruction patterns. The enhanced utility of photon-counting is highlighted by providing superior spatial resolution compared to other CT detectors. This technology facilitates a more accurate characterization of shunt valves and may support the detection of subtle abnormalities and a precise assessment of shunt valves.

Photon-Counting Detector Computed Tomography (PCD-CT): A New Era for Cardiovascular Imaging? Current Status and Future Outlooks

Photon-counting detector computed tomography (PCD-CT) represents a revolutionary new generation of computed tomography (CT) for the imaging of patients with cardiovascular diseases. Since its commercial market introduction in 2021, numerous studies have identified advantages of this new technology in the field of cardiovascular imaging, including improved image quality due to an enhanced contrast-to-noise ratio, superior spatial resolution, reduced artifacts, and a reduced radiation dose. The aim of this narrative review was to discuss the current scientific literature, and to find answers to the question of whether PCD-CT has yet led to a true step-change and significant progress in cardiovascular imaging.

Three-Dimensional Visualization of Shunt Valves with Photon Counting CT and Comparison to Traditional X-ray in a Simple Phantom Model

This study introduces an application of innovative medical technology, Photon Counting Computer Tomography (PC CT) with novel detectors, for the assessment of shunt valves. PC CT technology offers enhanced visualization capabilities, especially for small structures, and opens up new possibilities for detailed three-dimensional imaging. Shunt valves are implanted under the skin and redirect excess cerebrospinal fluid, for example, to the abdominal cavity through a catheter. They play a vital role in regulating cerebrospinal fluid drainage in various pathologies, which can lead to hydrocephalus. Accurate imaging of shunt valves is essential to assess the rate of drainage, as their precise adjustment is a requirement for optimal patient care. This study focused on two adjustable shunt valves, the proGAV 2.0® and M. blue® (manufactured by Miethke, Potsdam, Germany). A comprehensive comparative analysis of PC CT and traditional X-ray techniques was conducted to explore this cutting-edge technology and it demonstrated that routine PC CT can efficiently assess shunt valves' adjustments. This technology shows promise in enhancing the accurate management of shunt valves used in settings where head scans are already frequently required, such as in the treatment of hydrocephalus.

New developments in the imaging of lung cancer

Radiological and nuclear medicine methods play a fundamental role in the diagnosis and staging of patients with lung cancer. Imaging is essential in the detection, characterisation, staging and follow-up of lung cancer. Due to the increasing evidence, low-dose chest computed tomography (CT) screening for the early detection of lung cancer is being introduced to the clinical routine in several countries. Radiomics and radiogenomics are emerging fields reliant on artificial intelligence to improve diagnosis and personalised risk stratification. Ultrasound- and CT-guided interventions are minimally invasive methods for the diagnosis and treatment of pulmonary malignancies. In this review, we put more emphasis on the new developments in the imaging of lung cancer.

A CT deep learning reconstruction algorithm: Image quality evaluation for brain protocol at decreasing dose indexes in comparison with FBP and statistical iterative reconstruction algorithms

PURPOSE

To characterise the impact of Precise Image (PI) deep learning reconstruction algorithm on image quality, compared to filtered back-projection (FBP) and iDose4 iterative reconstruction for brain computed tomography (CT) phantom images.

METHODS

Catphan-600 phantom was acquired with an Incisive CT scanner using a dedicated brain protocol, at six different dose levels (volume computed tomography dose index (CTDIvol): 7/14/29/49/56/67 mGy). Images were reconstructed using FBP, levels 2/5 of iDose4, and PI algorithm (Sharper/Sharp/Standard/Smooth/Smoother). Image quality was assessed by evaluating CT numbers, image histograms, noise, image non-uniformity (NU), noise power spectrum, target transfer function, and detectability index.

RESULTS

The five PI levels did not significantly affect the mean CT number. For a given CTDIvol using Sharper-to-Smoother levels, the spatial resolution for all the investigated materials and the detectability index increased while the noise magnitude decreased, slightly affecting noise texture. For a fixed PI level increasing the CTDIvol the detectability index increased, the noise magnitude decreased. From 29 mGy, NU values converged within 1 Hounsfield Unit from each other without a substantial improvement at higher CTDIvol values.

CONCLUSIONS

The improved performances of intermediate PI levels in brain protocols compared to conventional algorithms seem to suggest a potential reduction of CTDIvol.

Synergizing photon-counting CT with deep learning: potential enhancements in medical imaging

This review article highlights the potential of integrating photon-counting computed tomography (CT) and deep learning algorithms in medical imaging to enhance diagnostic accuracy, improve image quality, and reduce radiation exposure. The use of photon-counting CT provides superior image quality, reduced radiation dose, and material decomposition capabilities, while deep learning algorithms excel in automating image analysis and improving diagnostic accuracy. The integration of these technologies can lead to enhanced material decomposition and classification, spectral image analysis, predictive modeling for individualized medicine, workflow optimization, and radiation dose management. However, data requirements, computational resources, and regulatory and ethical concerns remain challenges that need to be addressed to fully realize the potential of this technology. The fusion of photon-counting CT and deep learning algorithms is poised to revolutionize medical imaging and transform patient care.

Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment

Cardiovascular CT is being widely used in the diagnosis of cardiovascular disease due to the rapid technological advancements in CT scanning techniques. These advancements include the development of multi-slice CT, from early generation to the latest models, which has the capability of acquiring images with high spatial and temporal resolution. The recent emergence of photon-counting CT has further enhanced CT performance in clinical applications, providing improved spatial and contrast resolution. CT-derived fractional flow reserve is superior to standard CT-based anatomical assessment for the detection of lesion-specific myocardial ischemia. CT-derived 3D-printed patient-specific models are also superior to standard CT, offering advantages in terms of educational value, surgical planning, and the simulation of cardiovascular disease treatment, as well as enhancing doctor-patient communication. Three-dimensional visualization tools including virtual reality, augmented reality, and mixed reality are further advancing the clinical value of cardiovascular CT in cardiovascular disease. With the widespread use of artificial intelligence, machine learning, and deep learning in cardiovascular disease, the diagnostic performance of cardiovascular CT has significantly improved, with promising results being presented in terms of both disease diagnosis and prediction. This review article provides an overview of the applications of cardiovascular CT, covering its performance from the perspective of its diagnostic value based on traditional lumen assessment to the identification of vulnerable lesions for the prediction of disease outcomes with the use of these advanced technologies. The limitations and future prospects of these technologies are also discussed.

Photon-counting computed tomography - clinical application in oncological, cardiovascular, and pediatric radiology

BACKGROUND

 Photon-counting detector computed tomography (PCD-CT) is a promising new technology with the potential to fundamentally change workflows in the daily routine and provide new quantitative imaging information to improve clinical decision-making and patient management.

METHOD

 The contents of this review are based on an unrestricted literature search of PubMed and Google Scholar using the search terms "photon-counting CT", "photon-counting detector", "spectral CT", "computed tomography" as well as on the authors' own experience.

RESULTS

 The fundamental difference with respect to the currently established energy-integrating CT detectors is that PCD-CT allows for the counting of every single photon at the detector level. Based on the identified literature, PCD-CT phantom measurements and initial clinical studies have demonstrated that the new technology allows for improved spatial resolution, reduced image noise, and new possibilities for advanced quantitative image postprocessing.

CONCLUSION

 For clinical practice, the potential benefits include fewer beam hardening artifacts, a radiation dose reduction, and the use of new or combinations of contrast agents. In particular, critical patient groups such as oncological, cardiovascular, lung, and head & neck as well as pediatric patient collectives benefit from the clinical advantages.

KEY POINTS

  · Photon-counting computed tomography (PCD-CT) is being used for the first time in routine clinical practice, enabling a significant dose reduction in critical patient populations such as oncology, cardiology, and pediatrics.. · Compared to conventional CT, PCD-CT enables a reduction in electronic image noise.. · Due to the spectral data sets, PCD-CT enables fully comprehensive post-processing applications..

CITATION FORMAT

· Hagen F, Soschynski M, Weis M et al. Photon-counting computed tomography - clinical application in oncological, cardiovascular, and pediatric radiology. Fortschr Röntgenstr 2024; 196: 25 - 34.

Advantages of Photon-Counting Detector CT in Aortic Imaging

Photon-counting Computed Tomography (PCCT) is a promising imaging technique. Using detectors that count the number and energy of photons in multiple bins, PCCT offers several advantages over conventional CT, including a higher image quality, reduced contrast agent volume, radiation doses, and artifacts. Although PCCT is well established for cardiac imaging in assessing coronary artery disease, its application in aortic imaging remains limited. This review summarizes the available literature and provides an overview of the current use of PCCT for the diagnosis of aortic imaging, focusing mainly on endoleaks detection and characterization after endovascular aneurysm repair (EVAR), contrast dose volume, and radiation exposure reduction, particularly in patients with chronic kidney disease and in those requiring follow-up CT.

Imaging in Third Molar Surgery: A Clinical Update

Third molar surgery is one of the most common surgical procedures performed in oral and maxillofacial surgery. Considering the patient's young age and the often-elective nature of the procedure, a comprehensive preoperative evaluation of the surgical site, relying heavily on preoperative imaging, is key to providing accurate diagnostic work-up, evidence-based clinical decision making, and, when appropriate, indication-specific surgical planning. Given the rapid developments of dental imaging in the field, the aim of this article is to provide a comprehensive, up-to-date clinical overview of various imaging techniques related to perioperative imaging in third molar surgery, ranging from panoramic radiography to emerging technologies, such as photon-counting computed tomography and magnetic resonance imaging. Each modality's advantages, limitations, and recent improvements are evaluated, highlighting their role in treatment planning, complication prevention, and postoperative follow-ups. The integration of recent technological advances, including artificial intelligence and machine learning in biomedical imaging, coupled with a thorough preoperative clinical evaluation, marks another step towards personalized dentistry in high-risk third molar surgery. This approach enables minimally invasive surgical approaches while reducing inefficiencies and risks by incorporating additional imaging modality- and patient-specific parameters, potentially facilitating and improving patient management.

Detectability and Volumetric Accuracy of Pulmonary Nodules in Low-Dose Photon-Counting Detector Computed Tomography: An Anthropomorphic Phantom Study

The aim of this phantom study was to assess the detectability and volumetric accuracy of pulmonary nodules on photon-counting detector CT (PCD-CT) at different low-dose levels compared to conventional energy-integrating detector CT (EID-CT). In-house fabricated artificial nodules of different shapes (spherical, lobulated, spiculated), sizes (2.5-10 mm and 5-1222 mm3), and densities (-330 HU and 100 HU) were randomly inserted into an anthropomorphic thorax phantom. The phantom was scanned with a low-dose chest protocol with PCD-CT and EID-CT, in which the dose with PCD-CT was lowered from 100% to 10% with respect to the EID-CT reference dose. Two blinded observers independently assessed the CT examinations of the nodules. A third observer measured the nodule volumes using commercial software. The influence of the scanner type, dose, observer, physical nodule volume, shape, and density on the detectability and volumetric accuracy was assessed by a multivariable regression analysis. In 120 CT examinations, 642 nodules were present. Observer 1 and 2 detected 367 (57%) and 289 nodules (45%), respectively. With PCD-CT and EID-CT, the nodule detectability was similar. The physical nodule volumes were underestimated by 20% (range 8-52%) with PCD-CT and 24% (range 9-52%) with EID-CT. With PCD-CT, no significant decrease in the detectability and volumetric accuracy was found at dose reductions down to 10% of the reference dose (p > 0.05). The detectability and volumetric accuracy were significantly influenced by the observer, nodule volume, and a spiculated nodule shape (p < 0.05), but not by dose, CT scanner type, and nodule density (p > 0.05). Low-dose PCD-CT demonstrates potential to detect and assess the volumes of pulmonary nodules, even with a radiation dose reduction of up to 90%.

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.

Photon-Counting Versus Energy-Integrating Detector CT Angiography of the Lower Extremity in a Human Cadaveric Model With Continuous Extracorporeal Perfusion

OBJECTIVES

Detailed visualization of the arterial runoff is mandatory for the assessment of peripheral arterial occlusive disease. This study aims to compare the performance of a first-generation photon-counting detector computed tomography (PCD-CT) to a third-generation energy-integrating detector CT (EID-CT).

MATERIALS AND METHODS

Computed tomography angiographies of 8 upper leg arterial runoffs were performed on human cadaveric models with continuous extracorporeal perfusion. For both PCD-CT and EID-CT, radiation dose-equivalent 120 kVp acquisition protocols (low-/medium-/high-dose: CTDI Vol = 3/5/10 mGy) were used. All scans were performed with standard collimation (PCD-CT: 144 × 0.4 mm; EID-CT: 96 × 0.6 mm), a pitch factor of 0.4, and a gantry rotation time of 1.0 second. Reformatting of data included the use of comparable vascular kernels (Bv 48/49), a slice thickness and increment of 1.0 mm, and a field of view of 150 × 150 mm. Eight radiologists evaluated image quality independently using a browser-based pairwise forced-choice comparison setup. Kendall concordance coefficient ( W ) was calculated to estimate interrater agreement. Signal-to-noise ratio and contrast-to-noise ratio (CNR) were compared based on 1-way analyses of variance and linear regression analysis.

RESULTS

Low-dose PCD-CT achieved superior signal-to-noise ratio/CNR values compared with high-dose EID-CT ( P < 0.001). Linear regression analysis suggested that an EID-CT scan with a CTDI Vol of at least 15.5 mGy was required to match the CNR value of low-dose PCD-CT. Intraluminal contrast attenuation was higher in PCD-CT than EID-CT, irrespective of dose level (415.0 ± 31.9 HU vs 329.2 ± 29.4 HU; P < 0.001). Subjective image quality of low-dose PCD-CT was considered superior to high-dose EID-CT ( P < 0.001). Interrater agreement was high ( W = 0.989).

CONCLUSIONS

Using cadaveric models with continuous extracorporeal perfusion allows for intraindividual image quality comparisons between PCD-CT and EID-CT on variable dose levels. With superior luminal contrast attenuation and denoising in angiographies of the peripheral arterial runoff, PCD-CT displayed potential for radiation saving of up to 83% compared with EID-CT.

Usefulness of Three-Dimensional Iodine Mapping Quantified by Dual-Energy CT for Differentiating Thymic Epithelial Tumors

Background: Dual-energy CT has been reported to be useful for differentiating thymic epithelial tumors. The purpose is to evaluate thymic epithelial tumors by using three-dimensional (3D) iodine density histogram texture analysis on dual-energy CT and to investigate the association of extracellular volume fraction (ECV) with the fibrosis of thymic carcinoma. Methods: 42 patients with low-risk thymoma (n = 20), high-risk thymoma (n = 16), and thymic carcinoma (n = 6) were scanned by dual-energy CT. 3D iodine density histogram texture analysis was performed for each nodule on iodine density mapping: Seven texture features (max, min, median, average, standard deviation [SD], skewness, and kurtosis) were obtained. The iodine effect (average on DECT180s-average on unenhanced DECT) and ECV on DECT180s were measured. Tissue fibrosis was subjectively rated by one pathologist on a three-point grade. These quantitative data obtained by examining associations with thymic carcinoma and high-risk thymoma were analyzed with univariate and multivariate logistic regression models (LRMs). The area under the curve (AUC) was calculated by the receiver operating characteristic curves. p values < 0.05 were significant. Results: The multivariate LRM showed that ECV > 21.47% in DECT180s could predict thymic carcinoma (odds ratio [OR], 11.4; 95% confidence interval [CI], 1.18-109; p = 0.035). Diagnostic performance was as follows: Sensitivity, 83.3%; specificity, 69.4%; AUC, 0.76. In high-risk thymoma vs. low-risk thymoma, the multivariate LRM showed that the iodine effect ≤1.31 mg/cc could predict high-risk thymoma (OR, 7; 95% CI, 1.02-39.1; p = 0.027). Diagnostic performance was as follows: Sensitivity, 87.5%; specificity, 50%; AUC, 0.69. Tissue fibrosis significantly correlated with thymic carcinoma (p = 0.026). Conclusions: ECV on DECT180s related to fibrosis may predict thymic carcinoma from thymic epithelial tumors, and the iodine effect on DECT180s may predict high-risk thymoma from thymoma.

Cardiovascular Applications of Photon-Counting CT Technology: A Revolutionary New Diagnostic Step

Photon-counting computed tomography (PCCT) is an emerging technology that can potentially transform clinical CT imaging. After a brief description of the PCCT technology, this review summarizes its main advantages over conventional CT: improved spatial resolution, improved signal and contrast behavior, reduced electronic noise and artifacts, decreased radiation dose, and multi-energy capability with improved material discrimination. Moreover, by providing an overview of the existing literature, this review highlights how the PCCT benefits have been harnessed to enhance and broaden the diagnostic capabilities of CT for cardiovascular applications, including the detection of coronary artery calcifications, evaluation of coronary plaque extent and composition, evaluation of coronary stents, and assessment of myocardial tissue characteristics and perfusion.

Advanced Cardiac Imaging and Women's Chest Pain: A Question of Gender

Awareness of gender differences in cardiovascular disease (CVD) has increased: both the different impact of traditional cardiovascular risk factors on women and the existence of sex-specific risk factors have been demonstrated. Therefore, it is essential to recognize typical aspects of ischemic heart disease (IHD) in women, who usually show a lower prevalence of obstructive coronary artery disease (CAD) as a cause of acute coronary syndrome (ACS). It is also important to know how to recognize pathologies that can cause acute chest pain with a higher incidence in women, such as spontaneous coronary artery dissection (SCAD) and myocardial infarction with non-obstructive coronary arteries (MINOCA). Coronary computed tomography angiography (CCTA) and cardiac magnetic resonance imaging (CMR) gained a pivotal role in the context of cardiac emergencies. Thus, the aim of our review is to investigate the most frequent scenarios in women with acute chest pain and how advanced cardiac imaging can help in the management and diagnosis of ACS.

Standardized assessment of vascular reconstruction kernels in photon-counting CT angiographies of the leg using a continuous extracorporeal perfusion model

This study evaluated the influence of different vascular reconstruction kernels on the image quality of CT angiographies of the lower extremity runoff using a 1st-generation photon-counting-detector CT (PCD-CT) compared with dose-matched examinations on a 3rd-generation energy-integrating-detector CT (EID-CT). Inducing continuous extracorporeal perfusion in a human cadaveric model, we performed CT angiographies of eight upper leg arterial runoffs with radiation dose-equivalent 120 kVp acquisition protocols (CTDI_vol 5 mGy). Reconstructions were executed with different vascular kernels, matching the individual modulation transfer functions between scanners. Signal-to-noise-ratios (SNR) and contrast-to-noise-ratios (CNR) were computed to assess objective image quality. Six radiologists evaluated image quality subjectively using a forced-choice pairwise comparison tool. Interrater agreement was determined by calculating Kendall's concordance coefficient (W). The intraluminal attenuation of PCD-CT images was significantly higher than of EID-CT (414.7 ± 27.3 HU vs. 329.3 ± 24.5 HU; p < 0.001). Using comparable kernels, image noise with PCD-CT was significantly lower than with EID-CT (p ≤ 0.044). Correspondingly, SNR and CNR were approximately twofold higher for PCD-CT (p < 0.001). Increasing the spatial frequency for PCD-CT reconstructions by one level resulted in similar metrics compared to EID-CT (CNR_fat; EID-CT Bv49: 21.7 ± 3.7 versus PCD-CT Bv60: 21.4 ± 3.5). Overall image quality of PCD-CTA achieved ratings superior to EID-CTA irrespective of the used reconstruction kernels (best: PCD-CT Bv60; worst: EID-CT Bv40; p < 0.001). Interrater agreement was good (W = 0.78). Concluding, PCD-CT offers superior intraluminal attenuation, SNR, and CNR compared to EID-CT in angiographies of the upper leg arterial runoff. Combined with improved subjective image quality, PCD-CT facilitates the use of sharper convolution kernels and ultimately bears the potential of improved vascular structure assessability.

Technical Basics and Clinical Benefits of Photon-Counting CT

ABSTRACT

Novel photon-counting detector CT (PCD-CT) has the potential to address the limitations of previous CT systems, such as insufficient spatial resolution, limited accuracy in detecting small low-contrast structures, or missing routine availability of spectral information. In this review article, we explain the basic principles and potential clinical benefits of PCD-CT, with a focus on recent literature that has grown rapidly since the commercial introduction of a clinically approved PCD-CT.

The Non-Invasive Diagnosis of Chronic Coronary Syndrome: A Focus on Stress Computed Tomography Perfusion and Stress Cardiac Magnetic Resonance

Coronary artery disease is still a major cause of death and morbidity worldwide. In the setting of chronic coronary disease, demonstration of inducible ischemia is mandatory to address treatment. Consequently, scientific and technological efforts were made in response to the request for non-invasive diagnostic tools with better sensitivity and specificity. To date, clinicians have at their disposal a wide range of stress-imaging techniques. Among others, stress cardiac magnetic resonance (S-CMR) and computed tomography perfusion (CTP) techniques both demonstrated their diagnostic efficacy and prognostic value in clinical trials when compared to other non-invasive ischemia-assessing techniques and invasive fractional flow reserve measurement techniques. Standardized protocols for both S-CMR and CTP usually imply the administration of vasodilator agents to induce hyperemia and contrast agents to depict perfusion defects. However, both methods have their own limitations, meaning that optimizing their performance still requires a patient-tailored approach. This review focuses on the characteristics, drawbacks, and future perspectives of these two techniques.

Dual-Source Photon-Counting Computed Tomography-Part I: Clinical Overview of Cardiac CT and Coronary CT Angiography Applications

The photon-counting detector (PCD) is a new computed tomography detector technology (photon-counting computed tomography, PCCT) that provides substantial benefits for cardiac and coronary artery imaging. Compared with conventional CT, PCCT has multi-energy capability, increased spatial resolution and soft tissue contrast with near-null electronic noise, reduced radiation exposure, and optimization of the use of contrast agents. This new technology promises to overcome several limitations of traditional cardiac and coronary CT angiography (CCT/CCTA) including reduction in blooming artifacts in heavy calcified coronary plaques or beam-hardening artifacts in patients with coronary stents, and a more precise assessment of the degree of stenosis and plaque characteristic thanks to its better spatial resolution. Another potential application of PCCT is the use of a double-contrast agent to characterize myocardial tissue. In this current overview of the existing PCCT literature, we describe the strengths, limitations, recent applications, and promising developments of employing PCCT technology in CCT.

Quantitative and qualitative image quality assessment in shoulder examinations with a first-generation photon-counting detector CT

Photon-counting detector (PCD) CT allows for ultra-high-resolution (UHR) examinations of the shoulder without requiring an additional post-patient comb filter to narrow the detector aperture. This study was designed to compare the PCD performance with a high-end energy-integrating detector (EID) CT. Sixteen cadaveric shoulders were examined with both scanners using dose-matched 120 kVp acquisition protocols (low-dose/full-dose: CTDI_vol = 5.0/10.0 mGy). Specimens were scanned in UHR mode with the PCD-CT, whereas EID-CT examinations were conducted in accordance with the clinical standard as "non-UHR". Reconstruction of EID data employed the sharpest kernel available for standard-resolution scans (ρ₅₀ = 12.3 lp/cm), while PCD data were reconstructed with both a comparable kernel (11.8 lp/cm) and a sharper dedicated bone kernel (16.5 lp/cm). Six radiologists with 2-9 years of experience in musculoskeletal imaging rated image quality subjectively. Interrater agreement was analyzed by calculation of the intraclass correlation coefficient in a two-way random effects model. Quantitative analyses comprised noise recording and calculating signal-to-noise ratios based on attenuation measurements in bone and soft tissue. Subjective image quality was higher in UHR-PCD-CT than in EID-CT and non-UHR-PCD-CT datasets (all p < 0.001). While low-dose UHR-PCD-CT was considered superior to full-dose non-UHR studies on either scanner (all p < 0.001), ratings of low-dose non-UHR-PCD-CT and full-dose EID-CT examinations did not differ (p > 0.99). Interrater reliability was moderate, indicated by a single measures intraclass correlation coefficient of 0.66 (95% confidence interval: 0.58-0.73; p < 0.001). Image noise was lowest and signal-to-noise ratios were highest in non-UHR-PCD-CT reconstructions at either dose level (p < 0.001). This investigation demonstrates that superior depiction of trabecular microstructure and considerable denoising can be realized without additional radiation dose by employing a PCD for shoulder CT imaging. Allowing for UHR scans without dose penalty, PCD-CT appears as a promising alternative to EID-CT for shoulder trauma assessment in clinical routine.

Ultrahigh-Resolution Photon-Counting CT in Cadaveric Fracture Models: Spatial Frequency Is Not Everything

In this study, the impact of reconstruction sharpness on the visualization of the appendicular skeleton in ultrahigh-resolution (UHR) photon-counting detector (PCD) CT was investigated. Sixteen cadaveric extremities (eight fractured) were examined with a standardized 120 kVp scan protocol (CTDI_vol 10 mGy). Images were reconstructed with the sharpest non-UHR kernel (Br76) and all available UHR kernels (Br80 to Br96). Seven radiologists evaluated image quality and fracture assessability. Interrater agreement was assessed with the intraclass correlation coefficient. For quantitative comparisons, signal-to-noise-ratios (SNRs) were calculated. Subjective image quality was best for Br84 (median 1, interquartile range 1-3; p ≤ 0.003). Regarding fracture assessability, no significant difference was ascertained between Br76, Br80 and Br84 (p > 0.999), with inferior ratings for all sharper kernels (p < 0.001). Interrater agreement for image quality (0.795, 0.732-0.848; p < 0.001) and fracture assessability (0.880; 0.842-0.911; p < 0.001) was good. SNR was highest for Br76 (3.4, 3.0-3.9) with no significant difference to Br80 and Br84 (p > 0.999). Br76 and Br80 produced higher SNRs than all kernels sharper than Br84 (p ≤ 0.026). In conclusion, PCD-CT reconstructions with a moderate UHR kernel offer superior image quality for visualizing the appendicular skeleton. Fracture assessability benefits from sharp non-UHR and moderate UHR kernels, while ultra-sharp reconstructions incur augmented image noise.

Laser Scribing for Electrode Patterning of Perovskite Spectrometer-Grade CsPbBr3 Gamma-ray Detectors

Making semiconductor radiation detectors that work at room temperature relies heavily on the deposition and pixelation of electrodes. Electrode patterning of perovskite solar cells widely implements laser scribing techniques, which is a convenient, scalable, and inexpensive technique. However, this method has not found its application in radiation detector patterning yet, and the question whether laser scribing can achieve high-quality patterns with minimum damage to a detector crystal and low interpixel cross-talk remains largely unanswered. To prove that laser scribing is a practical method for electrode patterning on perovskite CsPbBr₃ detectors, we use the material to create a variety of patterns. A very low lateral leakage current (60 nA at 10 V) and high mobility-lifetime product (9.7(3) × 10^-4 cm²/V) were observed between the pixel and the guard ring in tests of single-pixel devices with a separation of 200 or 100 μm between the central electrode and the guard ring. The 122 and 136 keV photopeaks in ⁵⁷Co gamma-ray spectra were very well resolved with an energy resolution of up to 6.1% at 122 keV. A further reduction in gap size to 50 μm is conceivable, but more process optimization is needed.

Image Quality Analysis of Photon-Counting CT Compared with Dual-Source CT: A Phantom Study for Chest CT Examinations

A comparison was made between the image quality of a photon-counting CT (PCCT) and a dual-source CT (DSCT). The evaluation of image quality was performed using a Catphan CT phantom, and the physical metrics, such as the noise power spectrum and task transfer function, were measured for both PCCT and DSCT at three CT dose indices (1, 5 and 10 mGy). Polyenergetic and virtual monoenergetic reconstructions were used to evaluate the performance differences by simulating a Gaussian spot with a radius of 5 mm and calculating the detectability index. The highest iterative reconstruction level was able to decrease the noise by about 70% compared with the filtered back projection using a parenchyma reconstruction kernel. The PCCT task transfer functions remained constant, while those of the DSCT increased with the reconstruction strength level. At monoenergetic 70 keV, a 50% decrease in noise was observed for DSCT with image smoothing, while PCCT had the same 50% decrease in noise without any smoothing. The PCCT detectability index at a reconstruction strength level of two was equivalent to the highest level of ADMIRE 5 for DSCT. The PCCT showed its superiority over the DSCT, especially for lung nodule detection.

Radiomics Applications in Head and Neck Tumor Imaging: A Narrative Review

Recent advances in machine learning and artificial intelligence technology have ensured automated evaluation of medical images. As a result, quantifiable diagnostic and prognostic biomarkers have been created. We discuss radiomics applications for the head and neck region in this paper. Molecular characterization, categorization, prognosis and therapy recommendation are given special consideration. In a narrative manner, we outline the fundamental technological principles, the overall idea and usual workflow of radiomic analysis and what seem to be the present and potential challenges in normal clinical practice. Clinical oncology intends for all of this to ensure informed decision support for personalized and useful cancer treatment. Head and neck cancers present a unique set of diagnostic and therapeutic challenges. These challenges are brought on by the complicated anatomy and heterogeneity of the area under investigation. Radiomics has the potential to address these barriers. Future research must be interdisciplinary and focus on the study of certain oncologic functions and outcomes, with external validation and multi-institutional cooperation in order to achieve this.

Photon-Counting Computed Tomography (PCCT): Technical Background and Cardio-Vascular Applications

Photon-counting computed tomography (PCCT) is a new advanced imaging technique that is going to transform the standard clinical use of computed tomography (CT) imaging. Photon-counting detectors resolve the number of photons and the incident X-ray energy spectrum into multiple energy bins. Compared with conventional CT technology, PCCT offers the advantages of improved spatial and contrast resolution, reduction of image noise and artifacts, reduced radiation exposure, and multi-energy/multi-parametric imaging based on the atomic properties of tissues, with the consequent possibility to use different contrast agents and improve quantitative imaging. This narrative review first briefly describes the technical principles and the benefits of photon-counting CT and then provides a synthetic outline of the current literature on its use for vascular imaging.

Imaging in translational cancer research

This review is aimed at presenting some of the recent developments in translational cancer imaging research, with a focus on novel, recently established, or soon to be established cross-sectional imaging techniques for computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET) imaging, including computational investigations based on machine-learning techniques.

Neurological manifestations of COVID-19: a retrospective observational study based on 1060 patients with a narrative review

Background

In the past two decades, three coronavirus epidemics have been reported. Coronavirus disease 2019 (COVID-19) is caused by a severe acute respiratory syndrome (SARS)-like coronavirus (SARS-CoV-2). In most patients, the disease is characterized by interstitial pneumonia, but features can affect other organs.

Purpose

To document the radiological features of the patients and to perform a narrative review of the literature.

Material and Methods

We conducted a retrospective, single-center study on 1060 consecutive hospitalized patients with COVID-19 at our institution. According to the inclusion criteria, we selected patients to be studied in more radiological detail. All images were obtained as per standard of care protocols. We performed a statistic analysis to describe radiological features. We then presented a systematic review of the main and conventional neuroimaging findings in COVID-19.

Results

Of 1060 patients hospitalized for COVID-19 disease, 15% (159) met the eligibility criteria. Of these, 16 (10%) did not undergo radiological examinations for various reasons, while 143 (90%) were examined. Of these 143 patients, 48 (33.6%) had positive neuroimaging. We found that the most frequent pathology was acute ischemic stroke (n=16, 33.3%). Much less frequent were Guillain–Barre syndrome (n=9, 18.8%), cerebral venous thrombosis (n=7, 14.6%), encephalitis or myelitis (n=6, 12.5%), intracranial hemorrhage and posterior hemorrhagic encephalopathy syndrome (n=4, 8.3%), exacerbation of multiple sclerosis (n=4, 8.3%), and Miller–Fisher syndrome (n=2, 4.2%).

Conclusion

Our data are coherent with the published literature. Knowledge of these patterns will make clinicians consider COVID-19 infection when unexplained neurological findings are encountered.

Virtual Monochromatic Images from Dual-Energy Computed Tomography Do Not Improve the Detection of Synovitis in Hand Arthritis

The objective of this study was to investigate subtraction images from different polychromatic and virtual monochromatic reconstructions of dual-energy computed tomography (CT) for the detection of inflammation (synovitis/tenosynovitis or peritendonitis) in patients with hand arthritis. In this IRB-approved prospective study, 35 patients with acute hand arthritis underwent contrast-enhanced dual-energy CT and musculoskeletal ultrasound (MSUS) of the clinically dominant hand. CT subtractions (CT-S) were calculated from 80 and 135 kVp source data and monochromatic 50 and 70 keV images. CT-S and MSUS were scored for synovitis and tenosynovitis/peritendonitis. Specificity, sensitivity and diagnostic accuracy were assessed by using MSUS as a reference. Parameters of objective image quality were measured. Thirty-three patients were analyzed. MSUS was positive for synovitis and/or tenosynovitis/peritendonitis in 28 patients. The 70 keV images had the highest diagnostic accuracy, with 88% (vs. 50 keV, 82%; 80 kVp, 85%; and 135 kVp, 82%), and superior sensitivity, with 96% (vs. 50 keV: 86%, 80 kVp: 93% and 135 kVp: 79%). The 80 kVp images showed the highest signal- and contrast-to-noise ratio, while the 50 keV images provided the lowest image quality. While all subtraction methods of contrast-enhanced dual-energy CT proved to be able to detect inflammation with sufficient diagnostic accuracy, virtual monochromatic images with low keV showed no significant improvement over conventional subtraction techniques and lead to a loss of image quality.