Clinical Applications of Photon-counting CT: A Review of Pioneer Studies and a Glimpse into the Future

Photon-counting CT: technical features and clinical impact on abdominal imaging

Photon-counting CT has a completely different detector mechanism than conventional energy-integrating CT. In the photon-counting detector, X-rays are directly converted into electrons and received as electrical signals. Photon-counting CT provides virtual monochromatic images with a high contrast-to-noise ratio for abdominal CT imaging and may improve the ability to visualize small or low-contrast lesions. In addition, photon-counting CT may offer the possibility of reducing radiation dose. This review provides an overview of the actual clinical operation of photon-counting CT and its diagnostic utility in abdominal imaging. We also describe the clinical implications of photon-counting CT including imaging of hepatocellular carcinoma, liver metastases, hepatic steatosis, pancreatic cancer, intraductal mucinous neoplasm of the pancreas, and thrombus.

Diagnostic performance of high and ultra-high-resolution photon counting CT for detection of coronary artery disease in patients evaluated for transcatheter aortic valve implantation

We assessed the diagnostic performance of both ultra-high-resolution (UHR) and high-resolution (HR) modes of photon-counting detector (PCD)-CT within the confines of standard pre-TAVI CT scans, as well as the performance of UHR mode adjusted specifically for coronary imaging, using quantitative coronary angiography (QCA) as the reference. We included 60 patients undergoing pre-TAVI planning CT scans. Patients were divided into 3 groups: 20 scanned in HR mode, 20 in UHR mode, and 20 in adjusted UHR mode, on a dual-source PCD-CT. The adjusted UHR mode employed a lower tube voltage (90 kV vs. 120 kV) and a higher image quality level (65 vs. 34) to enhance coronary artery visualization. Patients underwent invasive coronary angiography as part of clinical routine. CCTA and QCA were reviewed to assess CAD presence defined as stenosis ≥ 50% in proximal and middle coronary segments. We included 60 patients (mean age 79 ± 7 years; 39(65%) men). Mean heart rate during scanning was 72 ± 13 bpm. Median coronary calcium score was 973 [379-2007]. QCA identified significant CAD in 24 patients (40%): 9 patients scanned with HR mode, 10 patients with the UHR mode, and 5 patients with the UHR adjusted mode. Per-patient area under the curves were 0.57 for HR, 0.80 for UHR, and 0.80 for adjusted UHR, with no significant differences between the scan modes, and per-vessel the area under the curves were 0.73 for HR, 0.69 for UHR, and 0.87 for adjusted UHR, with significant differences between UHR and adjusted UHR (p = 0.04). UHR and adjusted UHR modes of dual source PCD-CT show potential for improved sensitivity and negative predictive value for detecting CAD in patients undergoing pre-TAVI scans, however, no statistically significant difference from HR mode was observed.

An exploration of radiological signs in post-intervention liver complications

The advent and progression of radiological techniques in the past few decades have revolutionized the diagnostic and therapeutic landscape for liver diseases. These minimally invasive interventions, ranging from biopsies to complex therapeutic procedures like transjugular intrahepatic portosystemic shunt placement and transarterial embolization, offer substantial benefits for the treatment of patients with liver diseases. They provide accurate tissue diagnosis, allow real-time visualization, and render targeted treatment for hepatic lesions with enhanced precision. Despite their advantages, these procedures are not without risks, with the potential for complications that can significantly impact patient outcomes. It is imperative for radiologists to recognize the signs of these complications promptly to mitigate further health deterioration. Ultrasound, CT, and MRI are widely utilized examinations for monitoring the complications. This article presents an overarching review of the most commonly encountered hepatobiliary complications post-radiological interventions, emphasizing their imaging characteristics to improve patient post-procedure management.

Photon-counting detector computed tomography in cardiac imaging

Photon-counting detector computed tomography (PCD-CT) has emerged as a revolutionary technology in CT imaging. PCD-CT offers significant advancements over conventional energy-integrating detector CT, including increased spatial resolution, artefact reduction and inherent spectral imaging capabilities. In cardiac imaging, PCD-CT can offer a more accurate assessment of coronary artery disease, plaque characterisation and the in-stent lumen. Additionally, it might improve the visualisation of myocardial fibrosis through qualitative late enhancement imaging and quantitative extracellular volume measurements. The use of PCD-CT in cardiac imaging holds significant potential, positioning itself as a valuable modality that could serve as a one-stop-shop by integrating both angiography and tissue characterisation into a single examination. Despite its potential, large-scale clinical trials, standardisation of protocols and cost-effectiveness considerations are required for its broader integration into clinical practice. This narrative review provides an overview of the current literature on PCD-CT regarding the possibilities and limitations of cardiac imaging.

Imaging in France: 2024 Update

Radiology in France has made major advances in recent years through innovations in research and clinical practice. French institutions have developed innovative imaging techniques and artificial intelligence applications in the field of diagnostic imaging and interventional radiology. These include, but are not limited to, a more precise diagnosis of cancer and other diseases, research in dual-energy and photon-counting computed tomography, new applications of artificial intelligence, and advanced treatments in the field of interventional radiology. This article aims to explore the major research initiatives and technological advances that are shaping the landscape of radiology in France. By highlighting key contributions in diagnostic imaging, artificial intelligence, and interventional radiology, we provide a comprehensive overview of how these innovations are improving patient outcomes, enhancing diagnostic accuracy, and expanding the possibilities for minimally invasive therapies. As the field continues to evolve, France's position at the forefront of radiological research ensures that these innovations will play a central role in addressing current healthcare challenges and improving patient care on a global scale.

Ultra-high resolution spectral photon-counting CT outperforms dual layer CT for lung imaging: Results of a phantom study

PURPOSE

The purpose of this study was to compare lung image quality obtained with ultra-high resolution (UHR) spectral photon-counting CT (SPCCT) with that of dual-layer CT (DLCT), at standard and low dose levels using an image quality phantom and an anthropomorphic lung phantom.

METHODS

An image quality phantom was scanned using a clinical SPCCT prototype and an 8 cm collimation DLCT from the same manufacturer at 10 mGy. Additional acquisitions at 6 mGy were performed with SPCCT only. Images were reconstructed with dedicated high-frequency reconstruction kernels, slice thickness between 0.58 and 0.67 mm, and matrix between 5122 and 10242 mm, using a hybrid iterative algorithm at level 6. Noise power spectrum (NPS), task-based transfer function (TTF) for iodine and air inserts, and detectability index (d') were assessed for ground-glass and solid nodules of 2 mm to simulate highly detailed lung lesions. Subjective analysis of an anthropomorphic lung phantom was performed by two radiologists using a five-point quality score.

RESULTS

At 10 mGy, noise magnitude was reduced by 29.1 % with SPCCT images compared to DLCT images for all parameters (27.1 ± 11.0 [standard deviation (SD)] HU vs. 38.2 ± 1.0 [SD] HU, respectively). At 6 mGy with SPCCT images, noise magnitude was reduced by 8.9 % compared to DLCT images at 10 mGy (34.8 ± 14.1 [SD] HU vs. 38.2 ± 1.0 [SD] HU, respectively). At 10 mGy and 6 mGy, average NPS spatial frequency (fav) was greater for SPCCT images (0.75 ± 0.17 [SD] mm-1) compared to DLCT images at 10 mGy (0.55 ± 0.04 [SD] mm-1) while remaining constant from 10 to 6 mGy. At 10 mGy, TTF at 50 % (f50) was greater for SPCCT images (0.92 ± 0.08 [SD] mm-1) compared to DLCT images (0.67 ± 0.06 [SD] mm-1) for both inserts. At 6 mGy, f50 decreased by 1.1 % for SPCCT images, while remaining greater compared to DLCT images at 10 mGy (0.91 ± 0.06 [SD] mm-1 vs. 0.67 ± 0.06 [SD] mm-1, respectively). At both dose levels, d' were greater for SPCCT images compared to DLCT for all clinical tasks. Subjective analysis performed by two radiologists revealed a greater median image quality for SPCCT (5; Q1, 4; Q3, 5) compared to DLCT images (3; Q1, 3; Q3, 3).

CONCLUSION

UHR SPCCT outperforms DLCT in terms of image quality for lung imaging. In addition, UHR SPCCT contributes to a 40 % reduction in radiation dose compared to DLCT.

Photon-counting CT systems: A technical review of current clinical possibilities

In recent years, computed tomography (CT) has undergone a number of developments to improve radiological care. The most recent major innovation has been the development of photon-counting detectors. By comparison with the energy-integrating detectors traditionally used in CT, these detectors offer better dose efficiency, eliminate electronic noise, improve spatial resolution and have intrinsic spectral sensitivity. These detectors also allow the energy of each photon to be counted, thus improving the sampling of the X-ray spectrum in multiple energy bins, to better distinguish between photoelectric and Compton attenuation coefficients, resulting in better spectral images and specific color K-edge images. The purpose of this article was to make the reader more familiar with the basic principles and techniques of new photon-counting CT systems equipped with photon-counting detectors and also to describe the currently available devices that could be used in clinical practice.

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.

Accuracy of Ultralow-Dose Photon-counting CT in the Detection of Lung Changes after Lung Transplant

Background Data on the diagnostic accuracy of ultralow-dose (ULD) CT protocols for periodic surveillance in recipients of lung transplant are lacking. Purpose To assess the potential for radiation dose reduction using ULD photon-counting CT (PCT) to detect lung abnormalities in recipients of lung transplant during repeat CT follow-up. Materials and Methods Consecutive adult recipients of lung transplant undergoing same-day standard-of-care low-dose (LD) and ULD PCT from March 2023 to May 2023 were prospectively included. The ULD protocols were performed with two target effective doses comprising 20% (hereafter, ULD1) and 10% (hereafter, ULD2) of the standard LD protocol. The 1-mm reconstructions were reviewed by three readers. Subjective image quality, the visibility of certain anatomic structures (using a five-point Likert scale), and the presence of lung abnormalities were independently assessed. The χ2 or t tests were used to evaluate differences between the ULD1 and ULD2 protocols. Results A total of 82 participants (median age, 64 years [IQR, 54-69 years]; 47 male) were included (41 participants for each ULD protocol). The mean effective doses per protocol were 1.41 mSv ± 0.44 (SD) for LD, 0.26 mSv ± 0.08 for ULD1, and 0.17 mSv ± 0.04 for ULD2. According to three readers, the subjective image quality of the ULD images was deemed diagnostic (Likert score ≥3) in 39-40 (ULD1) and 40-41 (ULD2) participants, and anatomic structures could be adequately visualized (Likert score ≥3) in 33-41 (ULD1) and 34-41 (ULD2) participants. The detection accuracy for individual lung anomalies exceeded 70% for both ULD protocols, except for readers 1 and 3 detecting proximal bronchiectasis and reader 3 detecting bronchial wall thickening and air trapping. No evidence of a statistically significant difference in noise (P = .96), signal-to-noise ratio (P = .77), or reader accuracy (all P ≥ .05) was noted between the ULD protocols. Conclusion ULD PCT was feasible for detecting lung abnormalities following lung transplant, with a tenfold radiation dose reduction. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ciet in this issue.

Standardizing technical parameters and terms for abdominopelvic photon-counting CT: laying the groundwork for innovation and evidence sharing

Photon-counting detector CT (PCD-CT) is a new technology that has multiple diagnostic benefits including increased spatial resolution, iodine signal, and radiation dose efficiency, as well as multi-energy imaging capability, but which also has unique challenges in abdominal imaging. The purpose of this work is to summarize key features, technical parameters, and terms, which are common amongst current abdominopelvic PCD-CT systems and to propose standardized terminology (where none exists). In addition, user-selectable protocol parameters are highlighted to facilitate both scientific evaluation and early clinical adoption. Unique features of PCD-CT systems include photon-counting detectors themselves, energy thresholds and bins, and tube potential considerations for preserved spectral separation. Key parameters for describing different PCD-CT systems are reviewed and explained. While PCD-CT can generate multi-energy images like dual-energy CT, there are new types of images such as threshold images, energy bin images, and special spectral images. The standardized terms and concepts herein build upon prior interdisciplinary consensus and have been endorsed by the newly created Society of Abdominal Radiology Photon-counting CT Emerging Technology Commission.

Optimal Spectral Performance on Pediatric Photon-Counting CT: Investigating Phantom-Based Size-Dependent kV Selection for Spectral Body Imaging

PURPOSE

The comprehensive evaluation of kV selection on photon-counting computed tomography (PCCT) has yet to be performed. The aim of the study is to evaluate and determine the optimal kV options for variable pediatric body sizes on the PCCT unit.

MATERIALS AND METHODS

In this study, 4 phantoms of variable sizes were utilized to represent abdomens of newborn, 5-year-old, 10-year-old, and adult-sized pediatric patients. One solid water and 4 solid iodine inserts with known concentrations (2, 5, 10, and 15 mg I/mL) were inserted into phantoms. Each phantom setting was scanned on a PCCT system (Siemens Alpha) with 4 kV options (70 and 90 kV under Quantum Mode, 120 and 140 kV under QuantumPlus Mode) and clinical dual-source (3.0 pitch) protocol. For each phantom setting, radiation dose (CTDIvol) was determined by clinical dose settings and matched for all kV acquisitions. Sixty percent clinical dose images were also acquired. Reconstruction was matched across all acquisitions using Qr40 kernel and QIR level 3. Virtual monoenergetic images (VMIs) between 40 and 80 keV with 10 keV interval were generated on the scanner. Low-energy and high-energy images were reconstructed from each scan and subsequently used to generate an iodine map (IM) using an image-based 2-material decomposition method. Image noise of VMIs from each kV acquisition was calculated and compared between kV options. Absolute percent error (APE) of iodine CT number accuracy in VMIs was calculated and compared. Root mean square error (RMSE) and bias of iodine quantification from IMs were compared across kV options.

RESULTS

At the newborn size and 50 keV VMI, noise is lower at low kV acquisitions (70 kV: 10.5 HU, 90 kV: 10.4 HU), compared with high kV acquisitions (120 kV: 13.8 HU, 140 kV: 13.9 HU). At the newborn size and 70 keV VMI, the image noise from different kV options is comparable (9.4 HU for 70 kV, 8.9 HU for 90 kV, 9.7 HU for 120 kV, 10.2 HU for 140 kV). For APE of VMI, high kV (120 or 140 kV) performed overall better than low kV (70 or 90 kV). At the 5-year-old size, APE of 90 kV (median: 3.6%) is significantly higher (P < 0.001, Kruskal-Wallis rank sum test with Bonferroni correction) than 140 kV (median: 1.6%). At adult size, APE of 70 kV (median: 18.0%) is significantly higher (P < 0.0001, Kruskal-Wallis rank sum test with Bonferroni correction) than 120 kV (median: 1.4%) or 140 kV (median: 0.8%). The high kV also demonstrated lower RMSE and bias than the low kV across all controlled conditions. At 10-year-old size, RMSE and bias of 120 kV are 1.4 and 0.2 mg I/mL, whereas those from 70 kV are 1.9 and 0.8 mg I/mL.

CONCLUSIONS

The high kV options (120 or 140 kV) on the PCCT unit demonstrated overall better performance than the low kV options (70 or 90 kV), in terms of image quality of VMIs and IMs. Our results recommend the use of high kV for general body imaging on the PCCT.

Review: The Role of Dual-Energy Computed Tomography in Detecting Monosodium Urate Deposits in Vascular Tissues

PURPOSE OF REVIEW

To highlight novel findings in the detection of monosodium urate deposits in vessels using dual energy computed tomography, and to discuss the potential clinical implications for gout and hyperuricemia patients.

RECENT FINDINGS

Gout is an independent risk factor for cardiovascular disease. However, classical risk calculators do not take into account these hazards, and parameters to identify patients at risk are lacking. Monosodium urate measured by dual energy computed tomography is a well-established technology for the detection and quantification of monosodium urate deposits in peripheral joints and tendons. Recent findings also suggest its applicability to identify vascular urate deposits. Dual energy computed tomography is a promising tool for detection of cardiovascular monosodium urate deposits in gout patients, to better delineate individuals at increased risk for cardiovascular disease.

Ultra-High-Resolution and K-Edge Imaging of Prosthetic Heart Valves With Spectral Photon-Counting CT: A Phantom Study

BACKGROUND AND PURPOSE

The contribution of cardiac computed tomography (CT) for the detection and characterization of prosthetic heart valve (PHV) complications is still limited due mainly to artifacts. Computed tomography systems equipped with photon-counting detectors (PCDs) have the potential to overcome these limitations. Therefore, the aim of the study was to compare image quality of PHV with PCD-CT and dual-energy dual-layer CT (DEDL-CT).

MATERIALS AND METHODS

Two metallic and 3 biological PHVs were placed in a tube containing diluted iodinated contrast inside a thoracic phantom and scanned repeatedly at different angles on a DEDL-CT and PCD-CT. Two small lesions (~2 mm thickness; containing muscle and fat, respectively) were attached to the structure of 4 valves, placed inside the thoracic phantom, with and without an extension ring, and scanned again. Acquisition parameters were matched for the 2 CT systems and used for all scans. Metallic valves were scanned again with parameters adapted for tungsten K-edge imaging. For all valves, different metallic parts were measured on conventional images to assess their thickness and blooming artifacts. In addition, 6 parallelepipeds per metallic valve were drawn, and all voxels with density <3 times the standard deviation of the contrast media were recorded as an estimate of streak artifacts. For subjective analysis, 3 expert readers assessed conventional images of the valves, with and without lesions, and tungsten K-edge images. Conspicuity and sharpness of the different parts of the valve, the lesions, metallic, and blooming artifacts were scored on a 4-point scale. Measurements and scores were compared with the paired t test or Wilcoxon test.

RESULTS

The objective analysis showed that, with PCD-CT, valvular metallic structures were thinner and presented less blooming artifacts. Metallic artifacts were also reduced with PCD-CT (11 [interquartile (IQ) = 6] vs 40 [IQ = 13] % of voxels). Subjective analysis allowed noticing that some structures were visible or clearly visible only with PCD-CT. In addition, PCD-CT yielded better scores for the conspicuity and for the sharpness of all structures (all P s < 0.006), except for the conspicuity of the leaflets of the mechanical valves, which were well visible with either technique (4 [IQ = 3] for both). Both blooming and streak artifacts were reduced with PCD-CT ( P ≤ 0.01). Overall, the use of PCD-CT resulted in better conspicuity and sharpness of the lesions compared with DEDL-CT (both P s < 0.02). In addition, only with PCD-CT some differences between the 2 lesions were detectable. Adding the extension ring resulted in reduced conspicuity and sharpness with DEDL-CT ( P = 0.04 and P = 0.02, respectively) and only in reduced sharpness with PCD-CT ( P = 0.04). Tungsten K-edge imaging allowed for the visualization of the only dense structure containing it, the leaflets, and it resulted in images judged having less blooming and metallic artifacts as compared with conventional PCD-CT images ( P < 0.01).

CONCLUSIONS

With PCD-CT, objective and subjective image quality of metallic and biological PHVs is improved compared with DEDL-CT. Notwithstanding the improvements in image quality, millimetric lesions attached to the structure of the valves remain a challenge for PCD-CT. Tungsten K-edge imaging allows for even further reduction of artifacts.

What to Expect (and What Not) from Dual-Energy CT Imaging Now and in the Future?

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual-energy imaging remains relatively untapped, possibly due to its intricate workflow and the intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is necessary for an appropriate clinical use. The aims of this paper are to review the physical and technical bases of DECT acquisition and analysis, to discuss the advantages and limitations of DECT in different clinical scenarios, to review the technical constraints in material labeling and quantification, and to evaluate the cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radiogenomics.

Imbalanced spectral data analysis using data augmentation based on the generative adversarial network

Spectroscopic techniques generate one-dimensional spectra with distinct peaks and specific widths in the frequency domain. These features act as unique identities for material characteristics. Deep neural networks (DNNs) has recently been considered a powerful tool for automatically categorizing experimental spectra data by supervised classification to evaluate material characteristics. However, most existing work assumes balanced spectral data among various classes in the training data, contrary to actual experiments, where the spectral data is usually imbalanced. The imbalanced training data deteriorates the supervised classification performance, hindering understanding of the phase behavior, specifically, sol-gel transition (gelation) of soft materials and glycomaterials. To address this issue, this paper applies a novel data augmentation method based on a generative adversarial network (GAN) proposed by the authors in their prior work. To demonstrate the effectiveness of the proposed method, the actual imbalanced spectral data from Pluronic F-127 hydrogel and Alpha-Cyclodextrin hydrogel are used to classify the phases of data. Specifically, our approach improves 8.8%, 6.4%, and 6.2% of the performance of the existing data augmentation methods regarding the classifier's F-score, Precision, and Recall on average, respectively. Specifically, our method consists of three DNNs: the generator, discriminator, and classifier. The method generates samples that are not only authentic but emphasize the differentiation between material characteristics to provide balanced training data, improving the classification results. Based on these validated results, we expect the method's broader applications in addressing imbalanced measurement data across diverse domains in materials science and chemical engineering.

Assessing the Stability of Photon-Counting CT: Insights from a Two-Year Longitudinal Study

Background

Among the advancements in computed tomography (CT) technology, photon-counting computed tomography (PCCT) stands out as a significant innovation, providing superior spectral imaging capabilities while simultaneously reducing radiation exposure. Its long-term stability is important for clinical care, especially longitudinal studies, but is currently unknown.

Purpose

This study sets out to comprehensively analyze the long-term stability of a first-generation clinical PCCT scanner.

Materials and Methods

Over a two-year period, from November 2021 to November 2023, we conducted weekly identical experiments utilizing the same multi-energy CT protocol. These experiments included various tissue-mimicking inserts to rigorously assess the stability of Hounsfield Units (HU) and image noise in Virtual Monochromatic Images (VMIs) and iodine density maps. Throughout this period, notable software and hardware modifications were meticulously recorded. Each week, VMIs and iodine density maps were reconstructed and analyzed to evaluate quantitative stability over time.

Results

Spectral results consistently demonstrated the quantitative stability of PCCT. VMIs exhibited stable HU values, such as variation in relative error for VMI 70 keV measuring 0.11% and 0.30% for single-source and dual-source modes, respectively. Similarly, noise levels remained stable with slight fluctuations linked to software changes for VMI 40 and 70 keV that corresponded to changes of 8 and 1 HU, respectively. Furthermore, iodine density quantification maintained stability and showed significant improvement with software and hardware changes, especially in dual-source mode with nominal errors decreasing from 1.44 to 0.03 mg/mL.

Conclusion

This study provides the first long-term reproducibility assessment of quantitative PCCT imaging, highlighting its potential for the clinical arena. This study indicates its long-term utility in diagnostic radiology, especially for longitudinal studies.

Ultrahigh-Resolution K-Edge Imaging of Coronary Arteries With Prototype Deep-Silicon Photon-Counting CT: Initial Results in Phantoms

Background Photon-counting CT (PCCT) represents a recent advancement in CT, offering improved spatial resolution and spectral separability. By using multiple adjustable energy bins, PCCT enables K-edge imaging, allowing mixed contrast agent distinction. Deep-silicon is a new type of photon-counting detector with different characteristics compared with cadmium photon-counting detectors. Purpose To evaluate the performance of a prototype deep-Si PCCT scanner and compare it with that of a state-of-the-art dual-energy energy-integrating detector (EID) scanner in imaging coronary artery plaques enhanced with iodine and K-edge contrast agents. Materials and Methods A series of 10 three-dimensional-printed inserts (diameter, 3.5 mm) was prepared, and materials mimicking soft and calcified plaques were added to simulate stenosed coronary arteries. Inserts filled with an iodine- or gadolinium-based contrast agent (GBCA) were scanned. Virtual monoenergetic images (VMIs) and iodine maps were generated using two- and eight-energy bin data from EID CT and PCCT, respectively. Gadolinium maps were calculated for PCCT. The CT numbers of VMIs and iodine maps were compared. Spatial resolution and blooming artifacts were compared on the 70-keV VMIs in plaque-free and calcified coronary arteries. Results No evidence of a significant difference in the CT number of 70-keV images was found except in inserts containing GBCAs. In the absence of a GBCA, excellent (r > 0.99) agreement for iodine was found. PCCT could quantify the GBCA within 0.2 mg Gd/mL ± 0.8 accuracy of the ground truth, whereas EID CT failed to detect the GBCA. Lumen measurements were more accurate for PCCT than for EID CT, with mean errors of 167 versus 442 µm (P < .001) compared with the 3.5-mm ground truth. Conclusion Deep-Si PCCT demonstrated good accuracy in iodine quantification and could accurately decompose mixtures of two contrast agents. Its improved spatial resolution resulted in sharper images with blooming artifacts reduced by 50% compared with a state-of-the-art dual-energy EID CT scanner. © RSNA, 2024.

Update on Renal Cell Carcinoma Diagnosis with Novel Imaging Approaches

This review highlights recent advances in renal cell carcinoma (RCC) imaging. It begins with dual-energy computed tomography (DECT), which has demonstrated a high diagnostic accuracy in the evaluation of renal masses. Several studies have suggested the potential benefits of iodine quantification, particularly for distinguishing low-attenuation, true enhancing solid masses from hyperdense cysts. By determining whether or not a renal mass is present, DECT could avoid the need for additional imaging studies, thereby reducing healthcare costs. DECT can also provide virtual unenhanced images, helping to reduce radiation exposure. The review then provides an update focusing on the advantages of multiparametric magnetic resonance (MR) imaging performance in the histological subtyping of RCC and in the differentiation of benign from malignant renal masses. A proposed standardized stepwise reading of images helps to identify clear cell RCC and papillary RCC with a high accuracy. Contrast-enhanced ultrasound may represent a promising diagnostic tool for the characterization of solid and cystic renal masses. Several combined pharmaceutical imaging strategies using both sestamibi and PSMA offer new opportunities in the diagnosis and staging of RCC, but their role in risk stratification needs to be evaluated. Although radiomics and tumor texture analysis are hampered by poor reproducibility and need standardization, they show promise in identifying new biomarkers for predicting tumor histology, clinical outcomes, overall survival, and the response to therapy. They have a wide range of potential applications but are still in the research phase. Artificial intelligence (AI) has shown encouraging results in tumor classification, grade, and prognosis. It is expected to play an important role in assessing the treatment response and advancing personalized medicine. The review then focuses on recently updated algorithms and guidelines. The Bosniak classification version 2019 incorporates MRI, precisely defines previously vague imaging terms, and allows a greater proportion of masses to be placed in lower-risk classes. Recent studies have reported an improved specificity of the higher-risk categories and better inter-reader agreement. The clear cell likelihood score, which adds standardization to the characterization of solid renal masses on MRI, has been validated in recent studies with high interobserver agreement. Finally, the review discusses the key imaging implications of the 2017 AUA guidelines for renal masses and localized renal cancer.

Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes

Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as one of the most robust approaches for atherosclerotic cardiovascular disease risk stratification in primary prevention and a powerful tool to guide therapeutic choices. Groundbreaking advances in computational models and computer power translated into a surge of artificial intelligence (AI)-based approaches directly or indirectly linked to CACS analysis. This review aims to provide essential knowledge on the AI-based techniques currently applied to CACS, setting the stage for a holistic analysis of the use of these techniques in coronary artery calcium imaging. While the focus of the review will be detailing the evidence, strengths, and limitations of end-to-end CACS algorithms in electrocardiography-gated and non-gated scans, the current role of deep-learning image reconstructions, segmentation techniques, and combined applications such as simultaneous coronary artery calcium and pulmonary nodule segmentation, will also be discussed.

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.

Computed Tomography in Infectious Endocarditis

Imaging is one of the cornerstones in diagnosis and management of infective endocarditis, underlined by recent guidelines. Echocardiography is the first-line imaging technique, however, computed tomography (CT) has a class I recommendation in native and prosthetic valve endocarditis to detect valvular lesions in case of possible endocarditis and to detect paravalvular and periprosthetic complications in case of inconclusive echocardiography. Echocardiography has a higher diagnostic accuracy than CT in detecting valvular lesions, but not for diagnosing paravalvular lesions where CT is superior. Additionally, CT is useful and recommended by guidelines to detect extracardiac manifestations of endocarditis and in planning surgical treatment including assessment of the coronary arteries. The advent of photon-counting CT and its improved spatial resolution and spectral imaging is expected to expand the role of CT in the diagnosis of infective endocarditis. In this review, we provide an overview of the current role of CT in infective endocarditis focusing on image acquisition, image reconstruction, interpretation, and diagnostic accuracy.

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.