Thursday, December 4 | 1:30 p.m.-1:40 p.m. | R6-SSCH10-1 | Room E451A
In this Thursday afternoon session, researchers will share findings from a study that suggests that deep-learning image reconstruction with ultralow-dose chest CT shows promise as a scanning option for pneumonia patients.
A group led by Guangming Ma, MD, of Xi'an Jiaotong University in China, conducted a study that included data from 40 patients with pneumonia who underwent both standard-dose CT and ultralow-dose CT (for the latter, the tube current was based on body mass index).
The images were reconstructed using a 40% adaptive statistical iterative reconstruction (ASIR-V40%) for standard CT (Group A), ASIR-V40% for ultralow-dose CT (Group B1), and high-strength deep learning image reconstruction for ultralow-dose CT (Group B2). Two radiologists rated the overall quality and pneumonia visualization of the three image sets using a 5-point scale.
What exactly did the team discover in terms of image quality and radiation dose reduction among the three groups? You'll have to attend this session to find out.
