CT Systems

Development of a nanometre scale X-ray speckle-based CT technique through the 3-D histological assessment of an acute respiratory distress syndrome model

The study of biological soft tissue structures at the micron scale details the function of healthy and pathological tissues, which is vital in the diagnosis and treatment of diseases. Speckle based X-ray phase contrast tomographic scans at a nanometer scale have the potential to thoroughly analyse such tissues in a quantitative and qualitative manner. Diamond light source, the UKs national synchrotron facility developed and refined a 1-D X-ray speckle-based imaging technique, referred to as Fly scan mode. This novel image acquisition technique was used to perform a rapid structural composition scan of rodent lung histology samples. The rodent samples were taken from healthy and Staphylococcus aureus induced acute respiratory distress syndrome models. The analysis and cross comparison of the fly scan method, absorption-based tomography and conventional histopathology H&E staining microscopy are discussed in this paper. This analysis and cross comparison outline the ways the speckle-based technique can be of benefit. These advantages include improved soft tissue contrast, 3-D volumetric rendering, segmentation of specific gross tissue structures, quantitative analysis of gross tissue volume. A further advantage is the analysis of cellular distribution throughout the volumetric rendering of the tissue sample. The study also details the current limitations of this technique and points to ways in which future work on this imaging modality may progress.

Fully automated sinogram-based deep learning model for detection and classification of intracranial hemorrhage

PURPOSE

To propose an automated approach for detecting and classifying Intracranial Hemorrhages (ICH) directly from sinograms using a deep learning framework. This method is proposed to overcome the limitations of the conventional diagnosis by eliminating the time-consuming reconstruction step and minimizing the potential noise and artifacts that can occur during the Computed Tomography (CT) reconstruction process.

METHODS

This study proposes a two-stage automated approach for detecting and classifying ICH from sinograms using a deep learning framework. The first stage of the framework is Intensity Transformed Sinogram Sythesizer, which synthesizes sinograms that are equivalent to the intensity-transformed CT images. The second stage comprises of a cascaded Convolutional Neural Network-Recurrent Neural Network (CNN-RNN) model that detects and classifies hemorrhages from the synthesized sinograms. The CNN module extracts high-level features from each input sinogram, while the RNN module provides spatial correlation of the neighborhood regions in the sinograms. The proposed method was evaluated on a publicly available RSNA dataset consisting of a large sample size of 8652 patients.

RESULTS

The results showed that the proposed method had a notable improvement as high as 27% in patient-wise accuracies when compared to state-of-the-art methods like ResNext-101, Inception-v3 and Vision Transformer. Furthermore, the sinogram-based approach was found to be more robust to noise and offset errors in comparison to CT image-based approaches. The proposed model was also subjected to a multi-label classification analysis to determine the hemorrhage type from a given sinogram. The learning patterns of the proposed model were also examined for explainability using the activation maps.

CONCLUSION

The proposed sinogram-based approach can provide an accurate and efficient diagnosis of ICH without the need for the time-consuming reconstruction step and can potentially overcome the limitations of CT image-based approaches. The results show promising outcomes for the use of sinogram-based approaches in detecting hemorrhages, and further research can explore the potential of this approach in clinical settings.

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.

Photon-Counting Detectors in Computed Tomography: A Review

Photon-counting computed tomography (CT) is a new technique that has the potential to revolutionize clinical CT and is predicted to be the next significant advancement. In recent years, tremendous research has been conducted to demonstrate the developments in hardware assembly and its working principles. The articles in this review were obtained by conducting a search of the MEDLINE database. Photon-counting detectors (PCDs) provide excellent quality diagnostic images with high spatial resolution, reduced noise, artifacts, increased contrast-to-noise ratio, and multienergy data acquisition as compared with conventionally used energy-integrating detector (EID). The search covered articles published between 2011 and 2021. The title and abstract of each article were reviewed as determined by the search strategy. From these, eligible studies and articles that provided the working and clinical application of PCDs were selected. This article aims to provide a systematic review of the basic working principles of PCDs, emphasize the uses and clinical applications of PCDs, and compare it to EIDs. It provides a nonmathematical explanation and understanding of photon-counting CT systems for radiologists as well as clinicians.

Evaluation of Organ Dose and Image Quality Metrics of Pediatric CT Chest-Abdomen-Pelvis (CAP) Examination: An Anthropomorphic Phantom Study

The aim of this study is to investigate the impact of CT acquisition parameter setting on organ dose and its influence on image quality metrics in pediatric phantom during CT examination. The study was performed on 64-slice multidetector CT scanner (MDCT) Siemens Definition AS (Siemens Sector Healthcare, Forchheim, Germany) using various CT CAP protocols (P1–P9). Tube potential for P1, P2, and P3 protocols were fixed at 100 kVp while P4, P5, and P6 were fixed at 80 kVp with used of various reference noise values. P7, P8, and P9 were the modification of P1 with changes on slice collimation, pitch factor, and tube current modulation (TCM), respectively. TLD-100 chips were inserted into the phantom slab number 7, 9, 10, 12, 13, and 14 to represent thyroid, lung, liver, stomach, gonads, and skin, respectively. The image quality metrics, signal to noise ratio (SNR) and contrast to noise ratio (CNR) values were obtained from the CT console. As a result, this study indicates a potential reduction in the absorbed dose up to 20% to 50% along with reducing tube voltage, tube current, and increasing the slice collimation. There is no significant difference (p > 0.05) observed between the protocols and image metrics.

Spectral Computed Tomography: Fundamental Principles and Recent Developments

CT is a diagnostic tool with many clinical applications. The CT voxel intensity is related to the magnitude of X-ray attenuation, which is not unique to a given material. Substances with different chemical compositions can be represented by similar voxel intensities, making the classification of different tissue types challenging. Compared to the conventional single-energy CT, spectral CT is an emerging technology offering superior material differentiation, which is achieved using the energy dependence of X-ray attenuation in any material. A specific form of spectral CT is dual-energy imaging, in which an additional X-ray attenuation measurement is obtained at a second X-ray energy. Dual-energy CT has been implemented in clinical settings with great success. This paper reviews the theoretical basis and practical implementation of spectral/dual-energy CT.

Therapeutic Role of Water-Soluble Contrast Media in Adhesive Small Bowel Obstruction: a Systematic Review and Meta-Analysis

BACKGROUND

Adhesive small bowel obstruction (ASBO) is a common post-operative cause of hospitalisation. Water-soluble contrast media (WSCM) has become a popular non-surgical approach to treatment. However, previous reviews have concluded with conflicting results. This meta-analysis of randomised controlled trials (RCTs) re-evaluated the therapeutic value of WSCM in the management of ASBO.

METHODS

A comprehensive search of PubMed, Embase, and Cochrane databases was undertaken to identify RCTs from January 2000 to November 2018. The primary outcomes of length of stay and secondary outcomes of time to resolution, need for surgery, and mortality were extracted from the included studies. Quantitative pooling of the data was based on the random effects model.

RESULTS

Eight hundred and seventy-nine patients from the nine studies were included in the analysis. The administration of oral WSCM reduced the length of hospital stay (weighted mean difference - 0.15 days, P < 0.0001). However, WSCM does not reduce the need for surgery (relative risk 0.84, P < 0.009) and makes no difference to mortality rate (RR 0.99, P < 1.000). The definition of time to resolution of ASBO differed between the studies, ranging from time to passing flatus, to cessation of abdominal pain, and time to initiating oral intake. The significant differences in definition precluded meaningful quantitative pooling of this outcome.

CONCLUSIONS

This meta-analysis evaluating the therapeutic value of WSCM has shown that it does not reduce the need for operative management in ASBO or impact mortality rates. It shortens hospital stay by 0.15 days (3.6 h) which is not clinically significant.

Diagnostic accuracy of Magnetic Resonance Imaging using liver tissue specific contrast agents and contrast enhanced Multi Detector Computed Tomography: A systematic review of diagnostic test in Hepatocellular Carcinoma (HCC)

OBJECTIVES

The aim of this systematic review is to investigate diagnostic accuracy of Magnetic Resonance Imaging (MRI) scans using liver specific tissue contrast media over contrast enhanced Multi Detector CT (MDCT) in diagnoses of Hepatocellular Carcinoma (HCC) in patients with chronic liver disease.

KEY FINDINGS

A total of 8 diagnostic studies were identified and generally considered of high quality. The studies reported sufficient evidence on sensitivity and specificity, which was synthesised and summarised providing an overview of the evidence. Findings indicate that MRI scans using liver specific tissue contrast have a better diagnostic performance compared to contrast enhanced MDCT in diagnostic work-up of HCC in patients with chronic liver disease.

CONCLUSION

The current review identified sufficient high quality studies reporting statistical difference (P < 0.05), to establish the superiority of gadoxetetic acid enhanced MRI for sensitivity and specificity in comparison to MDCT in the diagnosis of HCC in chronic liver disease.