Optimising image quality in intravenous cerebral cone beam computed tomography.

INTRODUCTION: The efficacy of intravenous cerebral Cone Beam Computed Tomography (IV CBCT) is well established; however, image quality has only ever been authenticated by subjective evaluation. The aim of this study was to quantify the factors pertinent to achieving consistent and optimal image quality when performing IV CBCT. METHODS: Between 1 March 2021 and 30 October 2022, 79 patients received IV CBCT. These candidates were divided into three main acquisition field size categories (22/32, 42 and 48 cm) according to the clinical indication. The images were analysed using both a quantitative assessment and a subjective evaluation. Here, a comparison of Hounsfield units (HUs), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and noise index was conducted for each study and compared relative to the acquisition field size. The subjective analysis was performed in a non-blinded fashion where the diagnostic value (DV) of the exam was determined according to a graded scale. A phantom analysis for each of the acquisition field sizes was conducted and modulation transfer function (MTF) graphed. RESULTS: Significantly higher HU, SNR, CNR and lower noise indices were achieved with the 42-cm protocol than the 22/32 and 48-cm protocols. Here a greater DV was also reported. The MTF demonstrates marginally improved spatial resolution for the 22-cm protocol, but this is near equivocal for the 32-, 42 and 48-cm protocols. CONCLUSION: The use of larger acquisition field sizes provides improved image quality when performing IV CBCT as an alternative to intra-arterial (IA) CBCT.

Artificial intelligence in medical imaging: implications for patient radiation safety.

Artificial intelligence, including deep learning, is currently revolutionising the field of medical imaging, with far reaching implications for almost every facet of diagnostic imaging, including patient radiation safety. This paper introduces basic concepts in deep learning and provides an overview of its recent history and its application in tomographic reconstruction as well as other applications in medical imaging to reduce patient radiation dose, as well as a brief description of previous tomographic reconstruction techniques. This review also describes the commonly used deep learning techniques as applied to tomographic reconstruction and draws parallels to current reconstruction techniques. Finally, this paper reviews some of the estimated dose reductions in CT and positron emission tomography in the recent literature enabled by deep learning, as well as some of the potential problems that may be encountered such as the obscuration of pathology, and highlights the need for additional clinical reader studies from the imaging community.

Technique, radiation safety and image quality for chest X-ray imaging through glass and in mobile settings during the COVID-19 pandemic.

The COVID-19 pandemic in 2020 has led to preparations within our hospital for an expected surge of patients. This included developing a technique to perform mobile chest X-ray imaging through glass, allowing the X-ray unit to remain outside of the patient's room, effectively reducing the cleaning time associated with disinfecting equipment. The technique also reduced the infection risk of radiographers. We assessed the attenuation of different types of glass in the hospital and the technique parameters required to account for the glass filtration and additional source to image distance (SID). Radiation measurements were undertaken in a simulated set-up to determine the appropriate position for staff inside and outside the room to ensure occupational doses were kept as low as reasonably achievable. Image quality was scored and technical parameter information collated. The alternative to imaging through glass is the standard portable chest X-ray within the room. The radiation safety requirements for this standard technique were also assessed. Image quality was found to be acceptable or borderline in 90% of the images taken through glass and the average patient dose was 0.02 millisieverts (mSv) per image. The majority (67%) of images were acquired at 110 kV, with an average 5.5 mAs and with SID ranging from 180 to 300 cm. With staff positioned at greater than 1 m from the patient and at more than 1 m laterally from the tube head outside the room to minimise scatter exposure, air kerma values did not exceed 0.5 microgray (µGy) per image. This method has been implemented successfully.