Next-Generation Hardware Advances in CT: Cardiac Applications

An end-to-end neural network for 4D cardiac CT reconstruction using single-beat scans

Objective.Motion artifacts remain a significant challenge in cardiac CT imaging, often impairing the accurate detection and diagnosis of cardiac diseases. These artifacts result from involuntary cardiac motion, and traditional mitigation methods typically rely on retrospective rescans, which increase radiation exposure and are less effective for patients with irregular heart rhythms. In this study, we proposed a deep learning-based end-to-end reconstruction framework for dynamic cardiac imaging using single-beat rapid CT scanning.Approach.The method used common cardiac CT projections and applied a sliding-window approach to divide the projection data into overlapping short-scan intervals centered on specific cardiac phases. Each short-scan interval was first reconstructed and then processed through a denoising network, before being fed into the registration module to compute deformation vector fields (DVFs). These DVFs were then used to perform motion-compensated reconstruction. The denoising and registration networks were trained end-to-end by minimizing the difference between the reconstructed images and ground truth in a supervised manner. The model was trained using simulated projection data from 30 real patients and validated on simulated datasets from different institutions and XCAT-generated continuous phantoms.Main results.Experimental results showed that the proposed method effectively reduced motion artifacts and restored key anatomical structures such as coronary arteries. On high-resolution test cases, SSIM improved from 0.7234 to 0.7795, peak signal-to-noise ratio from 35.40 to 37.58, and root mean square error (HU) decreased from 63.98 to 49.28. Additional evaluations showed consistent improvements in segmentation accuracy, with Dice similarity coefficient scores for the left ventricle, coronary arteries, and calcified plaques increasing from 0.8025, 0.7347, and 0.5966 to 0.9614, 0.8811, and 0.7774, respectively.Significance.By relying solely on single-cycle scan data and placing no explicit restrictions on heart rate, the method demonstrated strong potential for generalizability and wider clinical applications.

Beam hardening of K-edge contrast agents: a phantom study comparing clinical energy-integrating detector and photon-counting detector CT systems

BACKGROUND

Beam hardening (BH) artifacts negatively influence computed tomography (CT) measurements, especially when due to dense materials or materials with high effective atomic numbers. Photon-counting detectors (PCD) are more susceptible to BH due to equal weighting of photons regardless of their energies. The problem is further confounded by the use of contrast agents (CAs) with K-edge in the diagnostic CT energy range. We quantified the BH effect of different materials comparing energy-integrating detector (EID)-CT and PCD-CT.

METHODS

Pairs of test tubes were filled with dense CA (iodine-, gadolinium-, and bismuth-based) and placed inside a water phantom. The phantoms were scanned on EID- and PCD-CT systems, at all available tube voltages for the PCD scanner. Images were reconstructed with standard water BH correction but without any iodine/bone BH corrections. Virtual monoenergetic images (VMI) were calculated from PCD-CT data.

RESULTS

PCD-CT had higher CT numbers in all x-ray spectra for all CAs (p < 0.001) and produced larger cupping artifacts in all test cases (p < 0.001). Bismuth-based CA artifacts were 3- to 5-fold smaller than those of iodine- or gadolinium-based CA. PCD-CT-based VMI completely removed iodine BH artifacts. Iodine BH artifacts decreased with increasing tube voltage. However, gadolinium-based BH artifacts had a different trend increasing at 120 kVp.

CONCLUSION

EID had fewer BH artifacts compared to PCD at x-ray tube voltages of 120 kVp and higher. The inherent spectral information of PCDs can be used to eliminate BH artifacts. Special care is needed to correct BH artifacts for gadolinium- and bismuth-based CAs.

RELEVANCE STATEMENT

With the increasing availability of clinical photon-counting CT systems offering the possibility of dual contrast imaging capabilities, addressing and comprehending the BH artifacts attributed to old and novel CT CAs grows in research and ultimately clinical relevance.

KEY POINTS

EID-CT provides fewer BH artifacts compared to PCD-CT at x-ray tube voltages of 120 kVp and higher. K-edge CAs, such as those based on gadolinium, further confound BH artifacts. The inherent spectral information of photon counting detector CT can be used to effectively eliminate BH artifacts.

Synchronous Regulation of Charge Transfer and Defects in Perovskite Nanocomposite Films for Enhanced Sensitivity and Stability in Monolithically Integrated X-Ray Imaging Arrays

Perovskites nanocrystals (PNCs) have garnered significant research interest in X-ray detection due to their strong X-ray absorption capability, and unique advantages in large area and thick film deposition that result from the decoupling of perovskite crystallization from film formation. However, traditional long-chain ligands used in PNCs, such as oleic acid and oleyl amine, suffer from poor conductivity and susceptibility to detachment, which limits the performance of X-ray detectors based on them. In this study, a strategy is proposed to partially replace long-chain ligands with short-chain counterparts like phenethylammoniumbromide (PEABr) and CF3PEABr, during the synthesis of CsPbBr3 PNCs. This approach leads to a lower defect density, enhanced carrier transport, and suppressed ion migration simultaneously in the resulting PNCs. These PNCs are then combined with organic bulk heterojunction to construct the nanocomposite X-ray detectors, which exhibit an impressive sensitivity of 10787 µC Gyair⁻¹ cm⁻2 and stable dark current baseline under a large electric field of ≈17 000 V cm-1. Finally, a flat panel X-ray imaging sensor is prepared by monolithically integrating the nanocomposite film with a thin-film transistor backplane, enabling high-resolution and real-time X-ray imaging. The image quality is further enhanced through a super-resolution reconstruction approach, effectively facilitating a wide range of practical applications in real-world scenarios.

Photon-Counting CT: Technology, Current and Potential Future Clinical Applications, and Overview of Approved Systems and Those in Various Stages of Research and Development

Photon-counting CT (PCCT) has emerged as a transformative technology, with the potential to herald a new era of clinical capabilities. This review provides an overview of the current status and potential future developments of PCCT, including basic physics principles and technical implementation by different vendors, with special attention to applications that have not, to date, been emphasized in the literature. The technologic underpinnings that distinguish PCCT scanners from traditional energy-integrating detector (EID) CT scanners with dual-energy capability are discussed. The inherent challenges of PCCT and the innovative breakthroughs that have enabled key PCCT features, such as enhanced image resolution, material discrimination, and radiation dose efficiency, are reviewed. Two categories of clinical applications are considered: (a) applications that are possible with current-generation EID CT but may be improved with the higher spatial, temporal, and contrast resolution of PCCT (eg, CT angiographic vasculitis imaging with high spatial, contrast, and temporal resolution and ultra-high-spatial-resolution "opportunistic" osseous imaging) and (b) potential future applications that are not currently feasible with EID CT but that may become possible and practical with PCCT (eg, reduced need for serial follow-up imaging with advanced CT or MRI because of more complete, definitive imaging evaluation with PCCT at first presentation).

Camera-on-tip endoscope for in vivo cardiovascular diagnostics and surgical guidance

Cardiovascular imaging with camera-on-tip endoscopes has the potential to provide physiologically relevant data on the tissue state and device placement that can improve clinical outcomes. In this work, we review the unmet clinical need for image-based in vivo cardiovascular diagnostics and guidance for minimally invasive procedures. We present a 7 Fr camera-on-tip endoscope with fibre-coupled multispectral illumination that includes methods for imaging in a blood-filled field of view (FOV). We demonstrate that the endoscope can be navigated from the femoral artery to cardiac regions such as the left atrium and left ventricle in a porcine model, where in vivo images of the cardiac walls are recorded. We further show that physiologically relevant parameters such as heart rate and respiration can be extracted from the images and that changes to tissue state can be inferred from the imaging data. Finally, a methodology for merging the imaging data with diffuse reflection spectroscopy (DRS) recorded through the optical fibre is outlined.

Clinical Advances in Cardiovascular Computed Tomography: From Present Applications to Promising Developments

PURPOSE OF THE REVIEW

This review aims to provide a profound overview on most recent studies on the clinical significance of Cardiovascular Computed Tomography (CCT) in diagnostic and therapeutic pathways. Herby, this review helps to pave the way for a more extended but yet purposefully use in modern day cardiovascular medicine.

RECENT FINDINGS

In recent years, new clinical applications of CCT have emerged. Major applications include the assessment of coronary artery disease and structural heart disease, with corresponding recommendations by major guidelines of international societies. While CCT already allows for a rapid and non-invasive diagnosis, technical improvements enable further in-depth assessments using novel imaging parameters with high temporal and spatial resolution. Those developments facilitate diagnostic and therapeutic decision-making as well as improved prognostication. This review determined that recent advancements in both hardware and software components of CCT allow for highly advanced examinations with little radiation exposure. This particularly strengthens its role in preventive care and coronary artery disease. The addition of functional analyses within and beyond coronary artery disease offers solutions in wide-ranging patient populations. Many techniques still require improvement and validation, however, CCT possesses potential to become a "one-stop-shop" examination.

Coronary artery calcification and cardiovascular outcome as assessed by intravascular OCT and artificial intelligence

Coronary artery calcification (CAC) is a marker of atherosclerosis and is thought to be associated with worse clinical outcomes. However, evidence from large-scale high-resolution imaging data is lacking. We proposed a novel deep learning method that can automatically identify and quantify CAC in massive intravascular OCT data trained using efficiently generated sparse labels. 1,106,291 OCT images from 1,048 patients were collected and utilized to train and evaluate the method. The Dice similarity coefficient for CAC segmentation and the accuracy for CAC classification are 0.693 and 0.932, respectively, close to human-level performance. Applying the method to 1259 ST-segment elevated myocardial infarction patients imaged with OCT, we found that patients with a greater extent and more severe calcification in the culprit vessels were significantly more likely to have major adverse cardiovascular and cerebrovascular events (MACCE) (p < 0.05), while the CAC in non-culprit vessels did not differ significantly between MACCE and non-MACCE groups.

Triple-source saddle-curve cone-beam photon counting CT image reconstruction: A simulation study

PURPOSE

The most common detector material in the PC CT system, cannot achieve the best performance at a relatively higher photon flux rate. In the reconstruction view, the most commonly used filtered back projection, is not able to provide sufficient reconstructed image quality in spectral computed tomography (CT). Developing a triple-source saddle-curve cone-beam photon counting CT image reconstruction method can improve the temporal resolution.

METHODS

Triple-source saddle-curve cone-beam trajectory was rearranged into four trajectory sets for simulation and reconstruction. Projection images in different energy bins were simulated by forward projection and photon counting CT respond model simulation. After simulation, the object was reconstructed using Katsevich's theory after photon counts correction using the pseudo inverse of photon counting CT response matrix. The material decomposition can be performed based on images in different energy bins.

RESULTS

Root mean square error (RMSE) and structural similarity index (SSIM) are calculated to quantify the image quality of reconstruction images. Compared with FDK images, the RMSE for the triple-source image was improved by 27%, 21%, 14%, 8%, and 6% for the reconstrued image of 20-33, 33-47, 47-58, 58-69, 69-80 keV energy bin. The SSIM was improved by 1.031%, 0.665%, 0.396%, 0.235%, 0.174% for corresponding energy bin. The decomposition image based on corrected images shows improved RMSE and SSIM, each by 33.861% and 0.345%. SSIM of corrected decomposition image of iodine reaches 99.415% of the original image.

CONCLUSIONS

A new Triple-source saddle-curve cone-beam PC CT image reconstruction method was developed in this work. The exact reconstruction of the triple-source saddle-curve improved both the image quality and temporal resolution.

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.

Coronary computed tomography angiography for clinical practice

Coronary artery disease (CAD) is a common condition caused by the accumulation of atherosclerotic plaques. It can be classified into stable CAD or acute coronary syndrome. Coronary computed tomography angiography (CCTA) has a high negative predictive value and is used as the first examination for diagnosing stable CAD, particularly in patients at intermediate-to-high risk. CCTA is also adopted for diagnosing acute coronary syndrome, particularly in patients at low-to-intermediate risk. Myocardial ischemia does not always co-exist with coronary artery stenosis, and the positive predictive value of CCTA for myocardial ischemia is limited. However, CCTA has overcome this limitation with recent technological advancements such as CT perfusion and CT-fractional flow reserve. In addition, CCTA can be used to assess coronary artery plaques. Thus, the indications for CCTA have expanded, leading to an increased demand for radiologists. The CAD reporting and data system (CAD-RADS) 2.0 was recently proposed for standardizing CCTA reporting. This RADS evaluates and categorizes patients based on coronary artery stenosis and the overall amount of coronary artery plaque and links this to patient management. In this review, we aimed to review the major trials and guidelines for CCTA to understand its clinical role. Furthermore, we aimed to introduce the CAD-RADS 2.0 including the assessment of coronary artery stenosis, plaque, and other key findings, and highlight the steps for CCTA reporting. Finally, we aimed to present recent research trends including the perivascular fat attenuation index, artificial intelligence, and the advancements in CT technology.

Cardiac-induced motion of the pancreas and its effect on image quality of ultrahigh-resolution CT

Recent advancements in diagnostic CT detector technology have made it possible to resolve anatomical features smaller than 20 LP/cm, referred to as ultra-high-resolution (UHR) CT. Subtle biological motions that did not affect standard-resolution (SR) CT may not be neglected in UHR. This study aimed to quantify the cardiac-induced motion of the pancreas and simulate its impact on the image quality of UHR-CT. We measured the displacement of the head of the pancreas in three healthy volunteers using Displacement Encoding with Stimulated Echoes (DENSE) MRI. The results were used to simulate SR- and UHR-CT acquisitions affected by pancreatic motion.We found pancreatic displacement in the 0.24-1.59 mm range during one cardiac cycle across the subjects. The greatest displacement was observed in the anterior-posterior direction. The time to peak displacement varied across subjects. Both SR and UHR images showed reduced image quality, as measured by radial modulation transfer function, due to cardiac-induced motion, but the motion artifacts caused more severe degradation in UHR acquisitions. Our investigation of cardiac-induced pancreatic displacement reveals its potential to degrade both standard and UHR-CT scans. To fully utilize the improvement in spatial resolution offered by UHR-CT, the effects of cardiac-induced motion in the abdomen need to be understood and corrected.Relevance statement Advancements in CT detector technology have enhanced CT scanner spatial resolution to approximately 100 µm. Consequently, previously ignored biological motions such as the cardiac-induced motion of the pancreas now demand attention to fully utilize this improved resolution.

Cardiac imaging with photon counting CT

CT of the heart, in particular ECG-controlled coronary CT angiography (cCTA), has become clinical routine due to rapid technical progress with ever new generations of CT equipment. Recently, CT scanners with photon-counting detectors (PCD) have been introduced which have the potential to address some of the remaining challenges for cardiac CT, such as limited spatial resolution and lack of high-quality spectral data. In this review article, we briefly discuss the technical principles of photon-counting detector CT, and we give an overview on how the improved spatial resolution of photon-counting detector CT and the routine availability of spectral data can benefit cardiac applications. We focus on coronary artery calcium scoring, cCTA, and on the evaluation of the myocardium.

Visualization of the lenticulostriate arteries, long insular arteries, and long medullary arteries on intra-arterial computed tomography angiography with ultrahigh resolution in patients with glioma

PURPOSE

The anatomical association between the lesion and the perforating arteries supplying the pyramidal tract in insulo-opercular glioma resection should be evaluated. This study reported a novel method combining the intra-arterial administration of contrast medium and ultrahigh-resolution computed tomography angiography (UHR-IA-CTA) for visualizing the lenticulostriate arteries (LSAs), long insular arteries (LIAs), and long medullary arteries (LMAs) that supply the pyramidal tract in two patients with insulo-opercular glioma.

METHODS

This method was performed by introducing a catheter to the cervical segment of the internal carotid artery. The infusion rate was set at 3 mL/s for 3 s, and the delay time from injection to scanning was determined based on the time-to-peak on angiography. On 2- and 20-mm-thick UHR-IA-CTA slab images and fusion with magnetic resonance images, the anatomical associations between the perforating arteries and the tumor and pyramidal tract were evaluated.

RESULTS

This novel method clearly showed the relationship between the perforators that supply the pyramidal tract and tumor. It showed that LIAs and LMAs were far from the lesion but that the proximal LSAs were involved in both cases. Based on these results, subtotal resection was achieved without complications caused by injury of perforators.

CONCLUSION

UHR-IA-CTA can be used to visualize the LSAs, LIAs, and LMAs clearly and provide useful preoperative information for insulo-opercular glioma resection.

[Benefits and drawbacks of CT scan as a triple rule-out exam in acute chest pain to exclude acute coronary syndrome, pulmonary embolism and aortic dissection]

Chest pain is one of the major causes for admission in the Emergency Room in most countries and one of the principal reasons for urgent consultation with a cardiologist or a general practitioner. After clinical examination and initial biological measurements, substantial patients require further explorations. CT scan allows the search for pulmonary embolism in the early stage of pulmonary arteries iodine contrast exploration. During the same exam at the systemic arterial phase, the search for aortic dissection or coronary artery disease is possible while exploring the later contrast in the aortic artery. This triple rule-out exam allows correct diagnosis in case of acute chest pain with suspected pulmonary embolism, aortic dissection and other acute aortic syndromes or acute coronary syndrome. But X-rays are substantially increased as well as iodine contrast agent quantity while exam quality is globally decreased. Artificial intelligence may play an important role in the development of this protocol.

Computed Tomography 2.0: New Detector Technology, AI, and Other Developments

ABSTRACT

Computed tomography (CT) dramatically improved the capabilities of diagnostic and interventional radiology. Starting in the early 1970s, this imaging modality is still evolving, although tremendous improvements in scan speed, volume coverage, spatial and soft tissue resolution, as well as dose reduction have been achieved. Tube current modulation, automated exposure control, anatomy-based tube voltage (kV) selection, advanced x-ray beam filtration, and iterative image reconstruction techniques improved image quality and decreased radiation exposure. Cardiac imaging triggered the demand for high temporal resolution, volume acquisition, and high pitch modes with electrocardiogram synchronization. Plaque imaging in cardiac CT as well as lung and bone imaging demand for high spatial resolution. Today, we see a transition of photon-counting detectors from experimental and research prototype setups into commercially available systems integrated in patient care. Moreover, with respect to CT technology and CT image formation, artificial intelligence is increasingly used in patient positioning, protocol adjustment, and image reconstruction, but also in image preprocessing or postprocessing. The aim of this article is to give an overview of the technical specifications of up-to-date available whole-body and dedicated CT systems, as well as hardware and software innovations for CT systems in the near future.

Dual-Energy CT in Cardiothoracic Imaging: Current Developments

This article describes the technical principles and clinical applications of dual-energy computed tomography (DECT) in the context of cardiothoracic imaging with a focus on current developments and techniques. Since the introduction of DECT, different vendors developed distinct hard and software approaches for generating multi-energy datasets and multiple DECT applications that were developed and clinically investigated for different fields of interest. Benefits for various clinical settings, such as oncology, trauma and emergency radiology, as well as musculoskeletal and cardiovascular imaging, were recently reported in the literature. State-of-the-art applications, such as virtual monoenergetic imaging (VMI), material decomposition, perfused blood volume imaging, virtual non-contrast imaging (VNC), plaque removal, and virtual non-calcium (VNCa) imaging, can significantly improve cardiothoracic CT image workflows and have a high potential for improvement of diagnostic accuracy and patient safety.

Artificial Intelligence in CT and MR Imaging for Oncological Applications

Cancer care increasingly relies on imaging for patient management. The two most common cross-sectional imaging modalities in oncology are computed tomography (CT) and magnetic resonance imaging (MRI), which provide high-resolution anatomic and physiological imaging. Herewith is a summary of recent applications of rapidly advancing artificial intelligence (AI) in CT and MRI oncological imaging that addresses the benefits and challenges of the resultant opportunities with examples. Major challenges remain, such as how best to integrate AI developments into clinical radiology practice, the vigorous assessment of quantitative CT and MR imaging data accuracy, and reliability for clinical utility and research integrity in oncology. Such challenges necessitate an evaluation of the robustness of imaging biomarkers to be included in AI developments, a culture of data sharing, and the cooperation of knowledgeable academics with vendor scientists and companies operating in radiology and oncology fields. Herein, we will illustrate a few challenges and solutions of these efforts using novel methods for synthesizing different contrast modality images, auto-segmentation, and image reconstruction with examples from lung CT as well as abdome, pelvis, and head and neck MRI. The imaging community must embrace the need for quantitative CT and MRI metrics beyond lesion size measurement. AI methods for the extraction and longitudinal tracking of imaging metrics from registered lesions and understanding the tumor environment will be invaluable for interpreting disease status and treatment efficacy. This is an exciting time to work together to move the imaging field forward with narrow AI-specific tasks. New AI developments using CT and MRI datasets will be used to improve the personalized management of cancer patients.

Computed tomographic angiography in coronary artery disease

Coronary computed tomographic angiography (CCTA) is becoming the first-line investigation for establishing the presence of coronary artery disease and, with fractional flow reserve (FFRCT), its haemodynamic significance. In patients without significant epicardial obstruction, its role is either to rule out atherosclerosis or to detect subclinical plaque that should be monitored for plaque progression/regression following prevention therapy and provide risk classification. Ischaemic non-obstructive coronary arteries are also expected to be assessed by non-invasive imaging, including CCTA. In patients with significant epicardial obstruction, CCTA can assist in planning revascularisation by determining the disease complexity, vessel size, lesion length and tissue composition of the atherosclerotic plaque, as well as the best fluoroscopic viewing angle; it may also help in selecting adjunctive percutaneous devices (e.g., rotational atherectomy) and in determining the best landing zone for stents or bypass grafts.

Recent technologies in cardiac imaging

Cardiac imaging allows physicians to view the structure and function of the heart to detect various heart abnormalities, ranging from inefficiencies in contraction, regulation of volumetric input and output of blood, deficits in valve function and structure, accumulation of plaque in arteries, and more. Commonly used cardiovascular imaging techniques include x-ray, computed tomography (CT), magnetic resonance imaging (MRI), echocardiogram, and positron emission tomography (PET)/single-photon emission computed tomography (SPECT). More recently, even more tools are at our disposal for investigating the heart's physiology, performance, structure, and function due to technological advancements. This review study summarizes cardiac imaging techniques with a particular interest in MRI and CT, noting each tool's origin, benefits, downfalls, clinical application, and advancement of cardiac imaging in the near future.

Regional left ventricular endocardial strains estimated from low-dose 4DCT: Comparison with cardiac magnetic resonance feature tracking

BACKGROUND

Estimates of regional left ventricular (LV) strains provide additional information to global function parameters such as ejection fraction (EF) and global longitudinal strain (GLS) and are more sensitive in detecting abnormal regional cardiac function. The accurate and reproducible assessment of regional cardiac function has implications in the management of various cardiac diseases such as heart failure, myocardial ischemia, and dyssynchrony.

PURPOSE

To develop a method that yields highly reproducible, high-resolution estimates of regional endocardial strains from 4DCT images.

METHODS

A method for estimating regional LV endocardial circumferential( ε c c ) $( {{\epsilon }_{cc}} )$ and longitudinal (ε l l ${\epsilon }_{ll}$ ) strains from 4DCT was developed. Point clouds representing the LV endocardial surface were extracted for each time frame of the cardiac cycle from 4DCT images. 3D deformation fields across the cardiac cycle were obtained by registering the end diastolic point cloud to each subsequent point cloud in time across the cardiac cycle using a 3D point-set registration technique. From these deformation fields,ε c c and ε l l ${\epsilon }_{cc}\ {\rm{and\ }}{\epsilon }_{ll}$ were estimated over the entire LV endocardial surface by fitting an affine transformation with maximum likelihood estimation. The 4DCT-derived strains were compared with strains estimated in the same subjects by cardiac magnetic resonance (CMR); twenty-four subjects had CMR scans followed by 4DCT scans acquired within a few hours. Regional LV circumferential and longitudinal strains were estimated from the CMR images using a commercially available feature tracking software (cvi42). Global circumferential strain (GCS) and global longitudinal strain (GLS) were calculated as the mean of the regional strains across the entire LV for both modalities. Pearson correlation coefficients and Bland-Altman analyses were used for comparisons. Intraclass correlation coefficients (ICC) were used to assess the inter- and intraobserver reproducibility of the 4DCT-derived strains.

RESULTS

The 4DCT-derived regional strains correlated well with the CMR-derived regional strains (ε c c ${\epsilon }_{cc}$ : r = 0.76, p < 0.001;ε l l ${\epsilon }_{ll}$ : r = 0.64, p < 0.001). A very strong correlation was found between 4DCT-derived GCS and 4DCT-derived EF (r = -0.96; p < 0.001). The 4DCT-derived strains were also highly reproducible, with very low inter- and intraobserver variability (intraclass correlation coefficients in the range of [0.92, 0.99]).

CONCLUSIONS

We have developed a novel method to estimate high-resolution regional LV endocardial circumferential and longitudinal strains from 4DCT images. Except for the definition of the mitral valve and LV outflow tract planes, the method is completely user independent, thus yielding highly reproducible estimates of endocardial strain. The 4DCT-derived strains correlated well with those estimated using a commercial CMR feature tracking software. The promising results reported in this study highlight the potential utility of 4DCT in the precise assessment of regional cardiac function for the management of cardiac disease.

Influence of CT Image Matrix Size and Kernel Type on the Assessment of HRCT in Patients with SSC-ILD

Background: Interstitial lung disease (ILD) is a frequent complication of systemic sclerosis (SSc), and its early detection and treatment may prevent deterioration of lung function. Different vendors have recently made larger image matrices available as a post-processing option for computed tomography (CT), which could facilitate the diagnosis of SSc-ILD. Therefore, the objective of this study was to assess the effect of matrix size on lung image quality in patients with SSc by comparing a 1024-pixel matrix to a standard 512-pixel matrix and applying different reconstruction kernels. Methods: Lung scans of 50 patients (mean age 54 years, range 23−85 years) with SSc were reconstructed with these two different matrix sizes, after determining the most appropriate kernel in a first step. Four observers scored the images on a five-point Likert scale regarding image quality and detectability of clinically relevant findings. Results: Among the eight tested kernels, the Br59-kernel (sharp) reached the highest score (19.48 ± 3.99), although differences did not reach statistical significance. The 1024-pixel matrix scored higher than the 512-pixel matrix HRCT overall (p = 0.01) and in the subcategories sharpness (p < 0.01), depiction of bronchiole (p < 0.01) and overall image impression (p < 0.01), and lower for the detection of ground-glass opacities (GGO) (p = 0.04). No significant differences were found for detection of extent of reticulations/bronchiectasis/fibrosis (p = 0.50) and image noise (p = 0.09). Conclusions: Our results show that with the use of a sharp kernel, the 1024-pixel matrix HRCT, provides a slightly better subjective image quality in terms of assessing interstitial lung changes, whereby GGO are more visible on the 512-pixel matrix. However, it remains to be answered to what extent this is related to the improved representation of the smallest structures.

Quantum Iterative Reconstruction for Abdominal Photon-counting Detector CT Improves Image Quality

Background An iterative reconstruction (IR) algorithm was introduced for clinical photon-counting detector (PCD) CT. Purpose To investigate the image quality and the optimal strength level of a quantum IR algorithm (QIR; Siemens Healthcare) for virtual monoenergetic images and polychromatic images (T3D) in a phantom and in patients undergoing portal venous abdominal PCD CT. Materials and Methods In this retrospective study, noise power spectrum (NPS) was measured in a water-filled phantom. Consecutive oncologic patients who underwent portal venous abdominal PCD CT between March and April 2021 were included. Virtual monoenergetic images at 60 keV and T3D were reconstructed without QIR (QIR-off; reference standard) and with QIR at four levels (QIR 1-4; index tests). Global noise index, contrast-to-noise ratio (CNR), and voxel-wise CT attenuation differences were measured. Noise and texture, artifacts, diagnostic confidence, and overall quality were assessed qualitatively. Conspicuity of hypodense liver lesions was rated by four readers. Parametric (analyses of variance, paired t tests) and nonparametric tests (Friedman, post hoc Wilcoxon signed-rank tests) were used to compare quantitative and qualitative image quality among reconstructions. Results In the phantom, NPS showed unchanged noise texture across reconstructions with maximum spatial frequency differences of 0.01 per millimeter. Fifty patients (mean age, 59 years ± 16 [standard deviation]; 31 women) were included. Global noise index was reduced from QIR-off to QIR-4 by 45% for 60 keV and by 44% for T3D (both, P < .001). CNR of the liver improved from QIR-off to QIR-4 by 74% for 60 keV and by 69% for T3D (both, P < .001). No evidence of difference was found in mean attenuation of fat and liver (P = .79-.84) and on a voxel-wise basis among reconstructions. Qualitatively, QIR-4 outperformed all reconstructions in every category for 60 keV and T3D (P value range, <.001 to .01). All four readers rated QIR-4 superior to other strengths for lesion conspicuity (P value range, <.001 to .04). Conclusion In portal venous abdominal photon-counting detector CT, an iterative reconstruction algorithm (QIR; Siemens Healthcare) at high strength levels improved image quality by reducing noise and improving contrast-to-noise ratio and lesion conspicuity without compromising image texture or CT attenuation values. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Sinitsyn in this issue.

Influence of Contrast Material Temperature on Patient Comfort and Image Quality in Computed Tomography of the Abdomen: A Randomized Controlled Trial

BACKGROUND

International guideline recommendations on safe use of contrast media (CM) are conflicting regarding the necessity to prewarm iodinated CM.

PURPOSE

Aim of the study was to evaluate the effects of room temperature CM compared with prewarmed CM on image quality, safety, and patient comfort in abdominal computed tomography (CT).

METHODS

CATCHY (Contrast Media Temperature and Patient Comfort in Computed Tomography of the Abdomen) is a double-blinded, randomized noninferiority trial. Between February and August 2020, 218 participants referred for portal venous abdominal CT were prospectively and randomly assigned to 1 of 2 groups. All patients received iopromide at 300 mg I/mL: group 1 at room temperature (~23°C [~73°F]) and group 2 prewarmed to body temperature (37°C [99°F]). A state-of-the-art individualized CM injection protocol was used, based on body weight and adapted to tube voltage. Primary outcome was absolute difference in mean liver attenuation between groups, calculated with a 2-sided 95% confidence interval. The noninferiority margin was set at -10 HU. Secondary outcomes were objective (signal-to-noise ratio and contrast-to-noise ratio) and subjective image quality; CM extravasations and other adverse events; and participant comfort (5-point scale questionnaire) and pain (numeric rating scale). This trial is registered with ClinicalTrials.gov (NCT04249479).

RESULTS

The absolute difference in mean attenuation between groups was + 4.23 HU (95% confidence interval, +0.35 to +8.11; mean attenuation, 122.2 ± 13.1 HU in group 1, 118.0 ± 15.9 HU in group 2; P = 0.03). Signal-to-noise ratio, contrast-to-noise ratio, and subjective image quality were not significantly different between groups (P = 0.53, 0.23, and 0.99 respectively). Contrast extravasation occurred in 1 patient (group 2), and no other adverse events occurred. Comfort scores were significantly higher in group 1 than in group 2 (P = 0.03); pain did not significantly differ (perceived P > 0.99; intensity P = 0.20).

CONCLUSIONS

Not prewarming iodinated CM was found noninferior in abdominal CT imaging. Prewarming conferred no beneficial effect on image quality, safety, and comfort, and might therefore no longer be considered a prerequisite in state-of-the art injection protocols for parenchymal imaging.

Advances in CT Techniques in Vascular Calcification

Vascular calcification, a common pathological phenomenon in atherosclerosis, diabetes, hypertension, and other diseases, increases the incidence and mortality of cardiovascular diseases. Therefore, the prevention and detection of vascular calcification play an important role. At present, various techniques have been applied to the analysis of vascular calcification, but clinical examination mainly depends on non-invasive and invasive imaging methods to detect and quantify. Computed tomography (CT), as a commonly used clinical examination method, can analyze vascular calcification. In recent years, with the development of technology, in addition to traditional CT, some emerging types of CT, such as dual-energy CT and micro CT, have emerged for vascular imaging and providing anatomical information for calcification. This review focuses on the latest application of various CT techniques in vascular calcification.

The accuracy of coronary CT angiography in patients with coronary calcium score above 1000 Agatston Units: Comparison with quantitative coronary angiography

BACKGROUND

High amounts of coronary artery calcium (CAC) pose challenges in interpretation of coronary CT angiography (CCTA). The accuracy of stenosis assessment by CCTA in patients with very extensive CAC is uncertain.

METHODS

Retrospective study was performed including patients who underwent clinically directed CCTA with CAC score >1000 and invasive coronary angiography within 90 days. Segmental stenosis on CCTA was graded by visual inspection with two-observer consensus using categories of 0%, 1-24%, 25-49%, 50-69%, 70-99%, 100% stenosis, or uninterpretable. Blinded quantitative coronary angiography (QCA) was performed on all segments with stenosis ≥25% by CCTA. The primary outcome was vessel-based agreement between CCTA and QCA, using significant stenosis defined by diameter stenosis ≥70%. Secondary analyses on a per-patient basis and inclusive of uninterpretable segments were performed.

RESULTS

726 segments with stenosis ≥25% in 346 vessels within 119 patients were analyzed. Median coronary calcium score was 1616 (1221-2118). CCTA identification of QCA-based stenosis resulted in a per-vessel sensitivity of 79%, specificity of 75%, positive predictive value (PPV) of 45%, negative predictive value (NPV) of 93%, and accuracy 76% (68 false positive and 15 false negative). Per-patient analysis had sensitivity 94%, specificity 55%, PPV 63%, NPV 92%, and accuracy 72% (30 false-positive and 3 false-negative). Inclusion of uninterpretable segments had variable effect on sensitivity and specificity, depending on whether they are considered as significant or non-significant stenosis.

CONCLUSIONS

In patients with very extensive CAC (>1000 Agatston units), CCTA retained a negative predictive value ​> ​90% to identify lack of significant stenosis on a per-vessel and per-patient level, but frequently overestimated stenosis.

The evolving role of coronary CT angiography in Acute Coronary Syndromes

In the United States, non-obstructive coronary disease has been on the rise, and each year, nearly one million adults suffer myocardial infarction, 70% of which are non-ST-segment elevation myocardial infarction (NSTEMI). In addition, approximately 15% of patients suffering NSTEMI will have subsequent readmission for a recurrent acute coronary syndrome (ACS). While invasive angiography remains the standard of care in the diagnostic and therapeutic approach to these patients, these methods have limitations that include procedural complications, uncertain specificity in diagnosis of the culprit lesion in patients with multi-vessel coronary artery disease (CAD), and challenges in following coronary disease over time. The role of coronary computed tomography angiography (CCTA) for evaluating patients with both stable and acute chest pain has seen a paramount upshift in the last decade. This paper reviews the established role of CCTA for the rapid exclusion of obstructive plaque in troponin negative acute chest pain, while exploring opportunities to address challenges in the current approach to evaluating NSTEMI.