Protocol can minimize dose for CT scans when viral testing is less available.
Even though CT scans aren’t recommended for COVID-19 detection, radiologists still need a strategy for using the modality – and minimizing radiation dose exposure – for cases where other detection options aren’t readily available, according to industry experts.
To provide some guidance for imaging patients with suspected COVID-19 infection, a team of experts from the Iranian Society of Radiology, led by Mehran Arab-Ahmadi, M.D., MPH, outlined a strategy in Academic Radiology for imaging when there’s a shortage of the gold standard of testing, reverse transcriptase-polymerase chain reaction (RT-PCR).
“Low dose high-resolution CT might have more advantages than RT-PCR, especially in highly infected societies with low availability of PCR-kits,” the team wrote. “Our primary goal of screening and evaluation is to detect COVID-19 infection in patients with highly suspicious clinical conditions and laboratory findings.”
The Society developed a protocol for use with patients who have a high probability of COVID-19. It was created to work with all CT scanners with four or more detectors, the team said, and it’s defined for each manufacturer and model.
To find ground glass opacities in the typical sub-pleural location, the team made these suggestions:
Kvp: 100-120
mAs: 50-100
Pitch: 0.8-1.5
Thickness: 1-3 mm
Study Reveals Benefits of Photon-Counting CT for Assessing Acute Pulmonary Embolism
April 23rd 2024In comparison to energy-integrating detector CT for the workup of suspected acute pulmonary embolism, the use of photon-counting detector CT reduced radiation dosing by 48 percent, according to newly published research.
The Reading Room: Racial and Ethnic Minorities, Cancer Screenings, and COVID-19
November 3rd 2020In this podcast episode, Dr. Shalom Kalnicki, from Montefiore and Albert Einstein College of Medicine, discusses the disparities minority patients face with cancer screenings and what can be done to increase access during the pandemic.
AI Adjudication Bolsters Chest CT Assessment of Lung Adenocarcinoma
April 11th 2024The inclusion of simulated adjudication for resolving discordant nodule classifications in a deep learning model for assessing lung adenocarcinoma on chest CT resulted in a 12 percent increase in sensitivity rate.