Shungo Sawamura, Shingo Kato, Yoshinori Funama, Seitaro Oda, Harumi Mochizuki, Sayuri Inagaki, Yuka Takeuchi, Tsubasa Morioka, Toshiharu Izumi, Yoichiro Ota, Hironori Kawagoe, Shihyao Cheng, Naoki Nakayama, Kazuki Fukui, Takashi Tsutsumi, Tae Iwasawa, Daisuke Utsunomiya
BACKGROUND: Despite advancements in coronary computed tomography angiography (CTA), challenges in positive predictive value and specificity remain due to limited spatial resolution. The purpose of this experimental study was to investigate the effect of 2nd generation deep learning-based reconstruction (DLR) on the quantitative and qualitative image quality in coronary CTA. METHODS: A vessel model with stepwise non-calcified plaque was scanned using 320-detector CT...
April 3, 2024: Quantitative Imaging in Medicine and Surgery