Cardiac Magnetic Resonance Imaging (CMRI) Applications in Patients with Chest Pain in the Emergency Department: A Narrative Review.

CMRI is the exclusive imaging technique capable of identifying myocardial edema, endomyocardial fibrosis, pericarditis accompanied by pericardial effusions, and apical thrombi within either the left or right ventricle. In this work, we examine the research literature on the use of CMRI in the diagnosis of chest discomfort, employing randomized controlled trials (RCTs) to evaluate its effectiveness. The research outlines the disorders of the chest and the machine learning approaches for detecting them. In conclusion, the study ends with an examination of a fundamental illustration of CMRI analysis. To find a comprehensive review, the Scopus scientific resource is analyzed. The issue, based on the findings, is to distinguish ischemia from non-ischemic cardiac causes of chest pain in individuals presenting with sudden chest pain or discomfort upon arrival at the emergency department (ED). Due to the failure of conventional methods in accurately diagnosing acute cardiac ischemia, individuals are still being inappropriately discharged from the ED, resulting in a heightened death rate.

Motion in nuclear cardiology imaging: types, artifacts, detection and correction techniques.

In this paper, the authors review the field of motion detection and correction in nuclear cardiology with single photon emission computed tomography (SPECT) and positron emission tomography (PET) imaging systems. We start with a brief overview of nuclear cardiology applications and description of SPECT and PET imaging systems, then explaining the different types of motion and their related artefacts. Moreover, we classify and describe various techniques for motion detection and correction, discussing their potential advantages including reference to metrics and tasks, particularly towards improvements in image quality and diagnostic performance. In addition, we emphasize limitations encountered in different motion detection and correction methods that may challenge routine clinical applications and diagnostic performance.

Attenuation correction in single-photon emission computed tomography for NURBS-based cardiac-torso phantom using dual-energy acquisition.

Single photon emission tomography is widely used to detect photons emitted from the patient. Some of these emitted photons suffer from scattering and absorption because of the attenuation occurred through their path in patient's body. Therefore, the attenuation is the most important problem in single-photon emission computed tomography (SPECT) imaging. Some of the radioisotopes emit gamma rays in different energy levels, and consequently, they have different counts and attenuation coefficients. Calculation of the parameters used in the attenuation equation N out=αNin = e- µ l Nin by mathematical methods is useful for the attenuation correction. Nurbs-based cardiac-torso (NCAT) phantom with an adequate attenuation coefficient and activity distribution is used in this study. Simulations were done using SimSET in 20-70 and 20-167 keV. A total of 128 projections were acquired over 360°. The corrected and reference images were compared using a universal image quality index (UIQI). The simulation repeated using NCAT phantom by SimSET. In the first group, no attenuation correction was used, but the Zubal coefficients were used for attenuation correction in the second image group. After the image reconstruction, a comparison between image groups was done using optimized UIQI to determine the quality of used reconstruction methods. Similarities of images were investigated by considering the average sinogram for every block size. The results showed that the proposed method improved the image quality. This study showed that simulation studies are useful tools in the investigation of nuclear medicine researches. We produced a nonattenuated model using Monte Carlo simulation method and compared it with an attenuated model. The proposed reconstruction method improved image resolution and contrast. Regional and general similarities of images could be determined, respectively, from acquired UIQI of small and large block sizes. Resulted curves from both small and large block sizes showed a good similarity between reconstructed and ideal images.