Application Of Computed Tomography Research Articles

Syn2Real: synthesis of CT image ring artifacts for deep learning-based correction.

Objective.We strive to overcome the challenges posed by ring artifacts in X-ray computed tomography (CT) by developing a novel approach for generating training data for deep learning-based methods. Training such networks require large, high quality, datasets that are often generated in the data domain, time-consuming and expensive. Our objective is to develop a technique for synthesizing realistic ring artifacts directly in the image domain, enabling scalable production of training data without relying on specific imaging system physics.
Approach.We develop ''Syn2Real,'' a computationally efficient pipeline that generates realistic ring artifacts directly in the image domain. To demonstrate the effectiveness of our approach, we train two versions of UNet, vanilla and a high capacity version with self-attention layers that we call UNetpp, with ℓ2and perceptual losses, as well as a diffusion model, on energy-integrating CT images with and without these synthetic ring artifacts. 
Main Results.Despite being trained on conventional single-energy CT images, our models effectively correct ring artifacts across various monoenergetic images, at different energy levels and slice thicknesses, from a prototype photon-counting CT system. This generalizability validates the realism and versatility of our ring artifact generation process.
Significance.Ring artifacts in X-ray CT pose a unique challenge to image quality and clinical utility. By focusing on data generation, our work provides a foundation for developing more robust and adaptable ring artifact correction methods for pre-clinical, clinical and other CT applications.

Dual-energy computed tomography: pediatric considerations.

Multidetector computed tomography (CT) has revolutionized medicine and is now a fundamental aspect of modern radiology. Hardware and software advancements have significantly improved CT accessibility, image quality, and acquisition times. While considerable attention has been directed towards the potential risks of ionizing radiation from CT scans in children, recent concerns regarding the possible short- and long-term risks related to magnetic resonance imaging (MRI) conducted under general anesthesia have generated fresh interest in novel pediatric CT applications and techniques that allow imaging of awake patients at low radiation doses. Among these novel techniques, dual-energy CT (DECT) stands out for its ability to provide enhanced diagnostic information, reduce radiation doses further, and facilitate faster scans, making it a highly promising tool in pediatric radiology. This manuscript explores the current role of DECT in pediatric imaging, emphasizing its technical foundations, hardware configurations, and various reconstruction techniques. We discuss advanced post-processing techniques, such as material decomposition algorithms and virtual monoenergetic imaging, highlighting their clinical advantages in improving diagnostic accuracy and patient outcomes. Furthermore, the paper reviews the clinical applications of DECT in evaluating pulmonary perfusion, cardiovascular assessments, and oncologic imaging in pediatric patients.

The overview of imaging protocols for chest CT

Computed Tomography (CT) is a common method of choice in the diagnosis of thoracic diseases. Since CT operates on the principle of ionizing radiation and frequently involves the use of contrast agents, it is crucial to standardize CT protocols to reduce the need for repeat imaging and, consequently, minimize patient exposure to radiation. The selection of a CT protocol primarily depends on the patient’s clinical indications and needs. The main classification of CT protocols distinguishes between the use of contrast agents (CECT) and non-contrast protocols (NCCT). The LDCT protocol is characterized by a low radiation dose and high sensitivity for detecting pulmonary nodules, making it suitable for lung cancer screening. Ultra-LDCT yields satisfactory results in diagnosing pneumonia and pneumothorax. Cine CT enables the assessment of cardiac function throughout the entire cardiac cycle, though it involves a high radiation dose and low temporal resolution. The use of contrast agents is particularly beneficial for differentiating adjacent non-vascular structures, more accurately identifying vascular anatomy, and improving the detection and characterization of pathological lesions. For diagnosing vascular pathologies, CTA is used, while CTPA is essential for diagnosing pulmonary embolism (PE) with high sensitivity and specificity. TRO CT is useful in cases of acute chest pain to rule out emergencies. Dynamic changes in tissue perfusion are monitored with DCE-CT, which is also valuable in tumor diagnostics. In pediatric applications of CT for the chest, it is essential to emphasize the use of the lowest possible radiation dose and contrast agent to minimize risks.

Evolution in Spinal Fracture Diagnosis and Brain Tumor Detection in the Last two Decades: A Timeline-Based Study

Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are arguably the most prominent and most widely used healthcare diagnostic modalities for a wide range of applications. There are certain specific applications for which a particular modality is specifically used or has been adopted over a period of time because of reasons like good diagnostic accuracy, fast diagnosis, etc. One such application for CT has been “Spinal Fracture Diagnosis” and for MRI has been “Brain Tumor Detection”. This study presents case studies from different time periods to demonstrate the evolution of these respective applications and emphasizes the role of Artificial Intelligence (AI) based techniques like machine learning, deep learning, etc. for advancements in the diagnostic process. The case studies will enable the new researchers to understand the background and the work done in the respective time period. The time period of the studies referred to is between the years 2000 and 2023 (Present date). The purpose of this study is to enlighten the reader about the evolution of spinal fractures and brain tumor diagnosis which are understood to be primary applications of CT and MRI, respectively and, encourage further study into topics pertaining to AI-based tools used in diagnostic modalities for applications like automatic detection and prediction, smart decision making, early detection, etc.

Effect of experimental parameters on X-ray Micro-CT imaging for Spectral CT applications

Computed tomography (CT) is recognized as a reliable method for structural characterization of different materials. Recently, Spectral CT methods have emerged as a tool to describe the sample composition through assessment of mass density (ρ) and effective atomic number (Zeff) assessment from CT results. These techniques depend on measuring the linear attenuation of a set of standards samples. However, besides ρ and Zeff, these results are influenced by factors such as X-ray energy and may be affected by experimental factors not accounted for in the foundational equation. Thus, in this study, we propose to quantify the effects of two factors: uniaxial compression and image pixel size on measurements of linear attenuation assessed through the registered mean gray value and its standard deviation. Initially, a group of metallic oxides pellets were compressed under different pressures and scanned at various magnification factors. Subsequently, based on factorial design theory, Yates’ method was applied to evaluate the significant effects of the factors. In a second phase, using a group of known samples, a Dual-Energy CT (DECT) measurement of a validation sample was conducted to verify the quantified effects. As expected initially, we observed that uniaxial compression positively influences attenuation, as it directly affects mass density. However, we found that an increase in image pixel size leads to a decrease in registered attenuation as it reduces the relationship between radiation attenuation and detected photons. Indeed, for the leveraged variation, the linear effect of pixel size variation proved to be the most influential on the registered mean gray value. When considering these effects in DECT application, no statistical difference was observed between loose powder and pellet measurements. Furthermore, no trend was observed in the results regarding image pixel size. However, it is possible that more significant changes in these factors may yield different results, and therefore, operators applying Spectral CT methods must ensure that the same experimental conditions are applied to both the standard sample set and the sample under investigation.

Illustrated cross-sectional computed tomography of the cetacean abdomino-pelvic organs

Computed tomography (CT) is a non-invasive diagnostic imaging modality which can be used to study the anatomy and morphology of live or deceased animals in-situ. In cetaceans, existing CT anatomy studies mostly focused on the head and thoracic regions. Using postmortem CT (PMCT) scans of Indo-Pacific finless porpoises (Neophocaena phocaenoides), this study describes the cross-sectional imaging anatomy of the cetacean abdomino-pelvic organs for the first time. PMCT scans of finless porpoises stranded in Hong Kong waters were reviewed, of which two freshly dead cases, one male and one female, were selected for illustration. In addition, a contrast-enhanced PMCT scan was performed on the female subject as a trial for a PMCT-angiography study (PMCTA) in cetaceans. A total of 18 axial PMCT images were acquired at selected vertebral levels in the abdomen and supplemented with a series of corresponding labeled anatomical diagrams. By applying different image rendering techniques, most osseous and soft tissue structures in the finless porpoise abdomen were successfully depicted and annotated on PMCT, including the male and female reproductive organs in the pelvic region. The application of contrast medium in PMCT created artificial radiodensity differences which improved the ability to visualize and differentiate soft organs and vasculature. The merits and limitations of CT compared to other imaging modalities, as well as the future directions of PMCT in stranding investigation, were discussed. The findings from this study significantly enhance the applications of CT in cetaceans by assisting researchers and veterinarians in the interpretation of cetacean abdomino-pelvic CT for morphological and pathological assessment during clinical or postmortem examination.

State-of-the-Art Research on Loess Microstructure Based on X-ray Computer Tomography

Computer tomography (CT), combined with advanced image processing techniques, can be used to visualize the complex internal structures of living and non-living media in a non-destructive, intuitive, and precise manner in both two and three-dimensional spaces. Beyond its clinical uses, CT has been extensively employed within the field of geotechnical engineering to provide both qualitative and quantitative analyses of the microstructural properties of loess. This technology has been successfully applied in many fields. However, with the rapid development of CT technology and the expansion of its application scope, a reassessment is necessary. In recent years, only a few documents have attempted to organize and review the application cases of CT in the field of loess microstructure research. Therefore, the objectives of this work are as follows: (1) to briefly introduce the development process of CT equipment and the basic principles of CT and image processing; (2) to determine the current state and hotspots of CT technology research based on a bibliometric analysis of the literature from the past three decades in the Web of Science Core Collection and CNKI databases; and (3) to comprehensively review the application of CT to explore the microstructural characteristics (such as particle size, shape, arrangement, and the connectivity, orientation, and pore throats of pores, etc.) and the evolution of structural damage in loess within geotechnical science. In addition, the progress and deficiencies of CT applications in the field of loess microstructure are summarized, and future prospects are proposed.

Advanced Imaging of Total Knee Arthroplasty.

The prevalence of total knee arthroplasty (TKA) is increasing with the aging population. Although long-term results are satisfactory, suspected postoperative complications often require imaging with the implant in place. Advancements in computed tomography (CT), such as tin prefiltration, metal artifact reduction algorithms, dual-energy CT with virtual monoenergetic imaging postprocessing, and the application of cone-beam CT and photon-counting detector CT, allow a better depiction of the tissues adjacent to the metal. For magnetic resonance imaging (MRI), high bandwidth (BW) optimization, the combination of view angle tilting and high BW, as well as multispectral imaging techniques with multiacquisition variable-resonance image combination or slice encoding metal artifact correction, have significantly improved imaging around metal implants, turning MRI into a useful clinical tool for patients with suspected TKA complications.

Edge-illumination spectral phase-contrast tomography

Following the rapid, but independent, diffusion of x-ray spectral and phase-contrast systems, this work demonstrates the first combination of spectral and phase-contrast computed tomography (CT) obtained by using the edge-illumination technique and a CdTe small-pixel (62 μm) spectral detector. A theoretical model is introduced, starting from a standard attenuation-based spectral decomposition and leading to spectral phase-contrast material decomposition. Each step of the model is followed by quantification of accuracy and sensitivity on experimental data of a test phantom containing different solutions with known concentrations. An example of a micro CT application (20 μm voxel size) on an iodine-perfused ex vivo murine model is reported. The work demonstrates that spectral-phase contrast combines the advantages of spectral imaging, i.e. high-Z material discrimination capability, and phase-contrast imaging, i.e. soft tissue sensitivity, yielding simultaneously mass density maps of water, calcium, and iodine with an accuracy of 1.1%, 3.5%, and 1.9% (root mean square errors), respectively. Results also show a 9-fold increase in the signal-to-noise ratio of the water channel when compared to standard spectral decomposition. The application to the murine model revealed the potential of the technique in the simultaneous 3D visualization of soft tissue, bone, and vasculature. While being implemented by using a broad spectrum (pink beam) at a synchrotron radiation facility (Elettra, Trieste, Italy), the proposed experimental setup can be readily translated to compact laboratory systems including conventional x-ray tubes.

Age Estimation Based on Computed Tomography Analysis of the Scapula.

Background and Objectives: Age estimation from skeletal remains and in living individuals is an important issue for human identification, and also plays a critical role in judicial proceedings for migrants. Forensic analysis of ossification centers is the main evaluation method for age estimation, and ossification degree can be determined using computed tomography analysis. The purpose of this study is to investigate the applicability of CT (computed tomography) in the analysis of left scapula ossification centers, for forensic age estimation in Turkish society. Materials and Methods: We analyzed six ossification centers of the left scapula and these ossification centers are the coracoid, subcoracoid, coracoid apex, acromial, glenoid, and inferior angle ossification centers. A pediatric radiologist analyzed these six ossification centers of the scapula by using a staging method defined by Schmeling et al. in 2004. Two months after the first assessment, 20 randomly selected cases was reanalyzed by the first observer and by another pediatric radiologist. Correlation between the age and ossification stage was assessed using Spearman's nonparametric correlation test. Linear regression analysis was performed using a backwards model. Cohen's kappa coefficient was used for evaluating interobserver and intraobserver variability. Results: In this retrospective study, 397 (248 male and 149 female) cases were evaluated. Ages ranged between 7.1 and 30.9. The mean age was 19.83 ± 6.49. We determined a positive significant correlation between the age and the ossification stages of ossification centers analyzed in both sexes. In each ossification center, except inferior angle, all of the stage 1 and 2 cases in both sexes were under 18 years old. Intraobserver and interobserver evaluations showed that reproducibility and consistency of the method was relatively good. Conclusions: The present study indicated that CT analysis of scapula ossification centers might be helpful in forensic age assessment of living individuals and dry bones.

The Application of Dual-layer Spectral Detector CT in Abdominal Vascular Imaging.

As a convenient and non-invasive diagnostic method, computed tomography (CT) has been developing continuously, and dual-energy CT imaging is one of its current research hotspots. Dualenergy CT, using two different X-ray energies for imaging, can generate spectral image sets such as virtual monoenergetic images, virtual non-contrast images, iodine density images, uric acid images, calcium inhibition images, and effective atomic number images. These images could help to increase the contrast of vascular, improve the detection rate of lesions, reduce artifacts, reduce the dose of radiation, and characterize materials. Dual-layer spectral detector CT, a detector-based dual-energy scanning device, has an X-ray tube and a dual-layer X-ray detector that can simultaneously separate lowenergy and high-energy photons from a multi-energy X-ray beam, which means excellent time registration. This paper aims to introduce the applications of dual-layer spectral detector CT in abdominal angiography, including optimizing image quality, reducing the dose of contrast agent and radiation, providing richer diagnostic information, organ perfusion, and thrombus identification.

Application of CT and MRI images based on an artificial intelligence algorithm for predicting lymph node metastasis in breast cancer patients: a meta-analysis

BackgroundThis study aimed to comprehensively evaluate the accuracy and effect of computed tomography (CT) and magnetic resonance imaging (MRI) based on artificial intelligence (AI) algorithms for predicting lymph node metastasis in breast cancer patients.MethodsWe systematically searched the PubMed, Embase and Cochrane Library databases for literature from inception to June 2023 using keywords that included ‘artificial intelligence’, ‘CT,’ ‘MRI’, ‘breast cancer’ and ‘lymph nodes’. Studies that met the inclusion criteria were screened and their data were extracted for analysis. The main outcome measures included sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and area under the curve (AUC).ResultsA total of 16 studies were included in the final meta-analysis, covering 4,764 breast cancer patients. Among them, 11 studies used the manual algorithm MRI to calculate breast cancer risk, which had a sensitivity of 0.85 (95% confidence interval [CI] 0.79–0.90; p < 0.001; I2 = 75.3%), specificity of 0.81 (95% CI 0.66–0.83; p < 0.001; I2 = 0%), a positive likelihood ratio of 4.6 (95% CI 4.0–4.8), a negative likelihood ratio of 0.18 (95% CI 0.13–0.26) and a diagnostic odds ratio of 25 (95% CI 17–38). Five studies used manual algorithm CT to calculate breast cancer risk, which had a sensitivity of 0.88 (95% CI 0.79–0.94; p < 0.001; I2 = 87.0%), specificity of 0.80 (95% CI 0.69–0.88; p < 0.001; I2 = 91.8%), a positive likelihood ratio of 4.4 (95% CI 2.7–7.0), a negative likelihood ratio of 0.15 (95% CI 0.08–0.27) and a diagnostic odds ratio of 30 (95% CI 12–72). For MRI and CT, the AUC after study pooling was 0.85 (95% CI 0.82–0.88) and 0.91 (95% CI 0.88–0.93), respectively.ConclusionComputed tomography and MRI images based on an AI algorithm have good diagnostic accuracy in predicting lymph node metastasis in breast cancer patients and have the potential for clinical application.

Phase retrieval for X-ray differential phase contrast radiography with knowledge transfer learning from virtual differential absorption model

Grating-based X-ray phase contrast radiography and computed tomography (CT) are promising modalities for future medical applications. However, the ill-posed phase retrieval problem in X-ray phase contrast imaging has hindered its use for quantitative analysis in biomedical imaging. Deep learning has been proved as an effective tool for image retrieval. However, in practical grating-based X-ray phase contrast imaging system, acquiring the ground truth of phase to form image pairs is challenging, which poses a great obstacle for using deep leaning methods. Transfer learning is widely used to address the problem with knowledge inheritance from similar tasks. In the present research, we propose a virtual differential absorption model and generate a training dataset with differential absorption images and absorption images. The knowledge learned from the training is transferred to phase retrieval with transfer learning techniques. Numerical simulations and experiments both demonstrate its feasibility. Image quality of retrieved phase radiograph and phase CT slices is improved when compared with representative phase retrieval methods. We conclude that this method is helpful in both X-ray 2D and 3D imaging and may find its applications in X-ray phase contrast radiography and X-ray phase CT.

Application of spectral CT in diagnosis, classification and prognostic monitoring of gastrointestinal cancers: progress, limitations and prospects

Gastrointestinal (GI) cancer is the leading cause of cancer-related deaths worldwide. Computed tomography (CT) is an important auxiliary tool for the diagnosis, evaluation, and prognosis prediction of gastrointestinal tumors. Spectral CT is another major CT revolution after spiral CT and multidetector CT. Compared to traditional CT which only provides single-parameter anatomical diagnostic mode imaging, spectral CT can achieve multi-parameter imaging and provide a wealth of image information to optimize disease diagnosis. In recent years, with the rapid development and application of spectral CT, more and more studies on the application of spectral CT in the characterization of GI tumors have been published. For this review, we obtained a substantial volume of literature, focusing on spectral CT imaging of gastrointestinal cancers, including esophageal, stomach, colorectal, liver, and pancreatic cancers. We found that spectral CT can not only accurately stage gastrointestinal tumors before operation but also distinguish benign and malignant GI tumors with improved image quality, and effectively evaluate the therapeutic response and prognosis of the lesions. In addition, this paper also discusses the limitations and prospects of using spectral CT in GI cancer diagnosis and treatment.

Artificial intelligence applications in computed tomography in gastric cancer: a narrative review.

Artificial intelligence (AI) is a revolutionary technique which is deeply impacting and reshaping clinical practice in oncology. This review aims to summarize the current status of the clinical application of AI-based computed tomography (CT) for gastric cancer (GC), focusing on diagnosis, genetic status detection and risk prediction of metastasis, prognosis and treatment efficacy. The challenges and prospects for future research will also be discussed. We searched the PubMed/MEDLINE database to identify clinical studies published between 1990 and November 2022 that investigated AI applications in CT in GC. The major findings of the verified studies were summarized. AI applications in CT images have attracted considerable attention in various fields such as diagnosis, prediction of metastasis risk, survival, and treatment response. These emerging techniques have shown a high potential to outperform clinicians in diagnostic accuracy and time-saving. AI-powered tools showed great potential to increase diagnostic accuracy and reduce radiologists' workload. However, the goal of AI is not to replace human ability but to help oncologists make decisions in their practice. Therefore, radiologists should play a predominant role in AI applications and decide the best ways to integrate these complementary techniques within clinical practice.

Ultrasound Sonosensitizers for Tumor Sonodynamic Therapy and Imaging: A New Direction with Clinical Translation.

With the rapid development of sonodynamic therapy (SDT), sonosensitizers have evolved from traditional treatments to comprehensive diagnostics and therapies. Sonosensitizers play a crucial role in the integration of ultrasound imaging (USI), X-ray computed tomography (CT), and magnetic resonance imaging (MRI) diagnostics while also playing a therapeutic role. This review was based on recent articles on multifunctional sonosensitizers that were used in SDT for the treatment of cancer and have the potential for clinical USI, CT, and MRI applications. Next, some of the shortcomings of the clinical examination and the results of sonosensitizers in animal imaging were described. Finally, this paper attempted to inform the future development of sonosensitizers in the field of integrative diagnostics and therapeutics and to point out current problems and prospects for their application.

On Krylov methods for large-scale CBCT reconstruction.

Krylov subspace methods are a powerful family of iterative solvers for linear systems of equations, which are commonly used for inverse problems due to their intrinsic regularization properties. Moreover, these methods are naturally suited to solve large-scale problems, as they only require matrix-vector products with the system matrix (and its adjoint) to compute approximate solutions, and they display a very fast convergence. Even if this class of methods has been widely researched and studied in the numerical linear algebra community, its use in applied medical physics and applied engineering is still very limited. e.g. in realistic large-scale computed tomography (CT) problems, and more specifically in cone beam CT (CBCT). This work attempts to breach this gap by providing a general framework for the most relevant Krylov subspace methods applied to 3D CT problems, including the most well-known Krylov solvers for non-square systems (CGLS, LSQR, LSMR), possibly in combination with Tikhonov regularization, and methods that incorporate total variation regularization. This is provided within an open source framework: the tomographic iterative GPU-based reconstruction toolbox, with the idea of promoting accessibility and reproducibility of the results for the algorithms presented. Finally, numerical results in synthetic and real-world 3D CT applications (medical CBCT andμ-CT datasets) are provided to showcase and compare the different Krylov subspace methods presented in the paper, as well as their suitability for different kinds of problems.

Performance of a Ge-doped optical fibre dosimeter for CT real-time measurements

This study investigates the dosimetric characteristics of a real-time radioluminescence (RL) Ge-doped optical fiber sensor, model LS-1000, providing measurement of absorbed dose in terms of counts in use of a computed tomography (CT) system. A CT dose index head phantom has been used as the reference tool. The response of the LS-1000 sensor has been compared against that of two other forms of dosimeter - a RaySafe X2 CT sensor (an ionization chamber system) and a Black Piranha CT dose profiler (a point dose solid-state detector). The three dosimeters have been irradiated in each of five available holes within the CT dose index head phantom. The results show RL response at the position of the peripheral holes of around 250 counts/gate for a gate time of 10 ms, while at the position of the central hole the response was 80 counts/gate. The maximum dose rate for the RaySafe X2 CT sensor has been found to be 5 mGy/s while that observed for the CT dose profiler was 6 mGy/s. In respect of CT applications, this trial of the luminescence device demonstrates that the germanium-doped optical fiber device may offer a promising alternative to conventional dosimeters, also allowing measurements at high accuracy and precision.

Modelling Polarization Effects in a CdZnTe Sensor at Low Bias.

Semi-insulating CdTe and CdZnTe crystals fabricated into pixelated sensors and integrated into radiation detection modules have demonstrated a remarkable ability to operate under rapidly changing X-ray irradiation environments. Such challenging conditions are required by all photon-counting-based applications, including medical computed tomography (CT), airport scanners, and non-destructive testing (NDT). Although, maximum flux rates and operating conditions differ in each case. In this paper, we investigated the possibility of using the detector under high-flux X-ray irradiation with a low electric field satisfactory for maintaining good counting operation. We numerically simulated electric field profiles visualized via Pockels effect measurement in a detector affected by high-flux polarization. Solving coupled drift-diffusion and Poisson's equations, we defined the defect model, consistently depicting polarization. Subsequently, we simulated the charge transport and evaluated the collected charge, including the construction of an X-ray spectrum on a commercial 2-mm-thick pixelated CdZnTe detector with 330 µm pixel pitch used in spectral CT applications. We analyzed the effect of allied electronics on the quality of the spectrum and suggested setup optimization to improve the shape of the spectrum.

Characterization of self-piercing rivet joints using X-ray computed tomography

Self-piercing rivet (SPR) joining is a process that has been adopted in the automotive industry, and it is important to be able to characterize SPR joints non-destructively. X-ray computed tomography (CT) allows visualizing the internal structure of the sample whilst preserving the workpiece. In this work, the application of X-ray CT to SPR joint characterization is investigated. Many features of a riveted joint can be observed. This includes the boundary between sheet interfaces and the positions where the substrates and rivet meet, which are important to quality assessment. In the case of similar materials, some of these features become difficult to observe but the presence of adhesive between the sheets enables the features to be more easily observed. Furthermore, substrate fracture and rivet cracks, radial cracks and the asymmetry of SPR joints can be detected due to the difference in greyscale to the surrounding materials. It is also revealed that image resolution plays an important role in defect detectability of the X-ray CT technique.