Deep learning reconstruction of equilibrium phase CT images in obese patients. Issue 133 (December 2020)

• Record Type: Journal Article
• Authors: Akagi, Motonori; Nakamura, Yuko; Higaki, Toru; Narita, Keigo; Honda, Yukiko; Awai, Kazuo
• Is Part Of: European journal of radiology. Issue 133(2020)
• Publication Date: 2020-12
• Subjects: NAFLD nonalcoholic fatty liver disease -- HCC hepatocellular carcinoma -- HAP hepatic arterial phase -- EP equilibrium phase -- DLR deep learning reconstruction -- AiCE Advanced Intelligent Clear-IQ Engine -- MBIR model-based iterative reconstruction -- BMI body mass index -- HU Hounsfield units -- PVP portal venous phase -- CTDIvol CT dose index -- DLP dose-length product -- SSDE size-specific dose estimate -- AIDR3D adaptive iterative dose reduction 3-dimensional -- FIRST forward-projected model-based iterative reconstruction solution -- ROI region of interest -- SD standard deviation -- CNR contrast-to-noise ratio -- CI confidence interval; Deep learning reconstruction -- Artificial intelligence -- Equilibrium phase -- Obese patients; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2020.109349
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: DLR preserved the quality of EP images obtained in obese patients. Neither hybrid-IR nor MBIR may improve the quality of EP images of obese patients. Radiation dose is relatively insufficient for obese patients. Abstract: Purpose: To compare abdominal equilibrium phase (EP) CT images of obese and non-obese patients to identify the reconstruction method that preserves the diagnostic value of images obtained in obese patients. Methods: We compared EP images of 50 obese patients whose body mass index (BMI) exceeded 25 (group 1) with EP images of 50 non-obese patients (BMI < 25, group 2). Group 1 images were subjected to deep learning reconstruction (DLR), hybrid iterative reconstruction (hybrid-IR), and model-based IR (MBIR), group 2 images to hybrid-IR; group 2 hybrid-IR images served as the reference standard. A radiologist recorded the standard deviation of attenuation in the paraspinal muscle as the image noise. The overall image quality was assessed by 3 other radiologists; they used a confidence scale ranging from 1 (unacceptable) to 5 (excellent). Non-inferiority and potential superiority were assessed. Results: With respect to the image noise, group 1 DLR- were superior to group 2 hybrid-IR images; group 1 hybrid-IR- and MBIR images were neither superior nor non-inferior to group 2 hybrid-IR images. The quality scores of only DLR images in group 1 were superior to hybrid-IR images of group 2 while the quality scores of group 1 hybrid-IR- and MBIR images were neither superior nor non-inferior to group 2 hybrid-IR images. Conclusions: DLR preserved the quality of EP images obtained in obese patients.