医学
图像质量
迭代重建
核医学
放射科
体质指数
图像噪声
腹部
双重能量
内科学
人工智能
图像(数学)
骨矿物
计算机科学
骨质疏松症
作者
Eric Fair,Mark Profio,Naveen V. Kulkarni,Peter S Laviolette,Bret Barnes,Samuel Bobholz,Maureen Levenhagen,Robin Ausman,Michael O. Griffin,Petar Duvnjak,Adam P Zorn,W D Foley
出处
期刊:Journal of Computer Assisted Tomography
[Ovid Technologies (Wolters Kluwer)]
日期:2022-04-27
卷期号:46 (4): 604-611
被引量:5
标识
DOI:10.1097/rct.0000000000001316
摘要
Objective The aim of this study was to evaluate image quality in vascular and oncologic dual-energy computed tomography (CT) imaging studies performed with a deep learning (DL)–based image reconstruction algorithm in patients with body mass index of ≥30. Methods Vascular and multiphase oncologic staging dual-energy CT examinations were evaluated. Two image reconstruction algorithms were applied to the dual-energy CT data sets: standard of care Adaptive Statistical Iterative Reconstruction (ASiR-V) and TrueFidelity DL image reconstruction at 2 levels (medium and high). Subjective quality criteria were independently evaluated by 4 abdominal radiologists, and interreader agreement was assessed. Signal-to-noise ratio (SNR) and contrast-to-noise ratio were compared between image reconstruction methods. Results Forty-eight patients were included in this study, and the mean patient body mass index was 39.5 (SD, 7.36). TrueFidelity-High (DL-High) and TrueFidelity-Medium (DL-Med) image reconstructions showed statistically significant higher Likert scores compared with ASiR-V across all subjective image quality criteria (P < 0.001 for DL-High vs ASiR-V; P < 0.05 for DL-Med vs ASiR-V), and SNRs for aorta and liver were significantly higher for DL-High versus ASiR-V (P < 0.001). Contrast-to-noise ratio for aorta and SNR for aorta and liver were significantly higher for DL-Med versus ASiR-V (P < 0.05). Conclusions TrueFidelity DL image reconstruction provides improved image quality compared with ASiR-V in dual-energy CTs obtained in obese patients.
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