Improved image quality and dose reduction in abdominal CT with deep-learning reconstruction algorithm: a phantom study

图像质量 成像体模 神经组阅片室 医学 迭代重建 图像噪声 核医学 算法 噪音(视频) 介入放射学 图像分辨率 人工智能 降噪 超声波 放射科 计算机科学 图像(数学) 精神科 神经学
作者
Joël Greffier,Quentin Durand,Julien Frandon,Salim Si‐Mohamed,Maeliss Loisy,Fabien de Oliveira,Jean‐Paul Beregi,Djamel Dabli
出处
期刊:European Radiology [Springer Nature]
卷期号:33 (1): 699-710 被引量:15
标识
DOI:10.1007/s00330-022-09003-y
摘要

ObjectivesTo assess the impact of a new artificial intelligence deep-learning reconstruction (Precise Image; AI-DLR) algorithm on image quality against a hybrid iterative reconstruction (IR) algorithm in abdominal CT for different clinical indications.MethodsAcquisitions on phantoms were performed at 5 dose levels (CTDIvol: 13/11/9/6/1.8 mGy). Raw data were reconstructed using level 4 of iDose4 (i4) and 3 levels of AI-DLR (Smoother/Smooth/Standard). Noise power spectrum (NPS), task-based transfer function (TTF) and detectability index (d′) were computed: d′ modelled detection of a liver metastasis (LM) and hepatocellular carcinoma at portal (HCCp) and arterial (HCCa) phases. Image quality was subjectively assessed on an anthropomorphic phantom by 2 radiologists.ResultsFrom Standard to Smoother levels, noise magnitude and average NPS spatial frequency decreased and the detectability (d′) of all simulated lesions increased. For both inserts, TTF values were similar for all three AI-DLR levels from 13 to 6 mGy but decreased from Standard to Smoother levels at 1.8 mGy. Compared to the i4 used in clinical practice, d′ values were higher using the Smoother and Smooth levels and close for the Standard level. For all dose levels, except at 1.8 mGy, radiologists considered images satisfactory for clinical use for the 3 levels of AI-DLR, but rated images too smooth using the Smoother level.ConclusionUse of the Smooth and Smoother levels of AI-DLR reduces the image noise and improves the detectability of lesions and spatial resolution for standard and low-dose levels. Using the Smooth level is apparently the best compromise between the lowest dose level and adequate image quality.Key Points • Evaluation of the impact of a new artificial intelligence deep-learning reconstruction (AI-DLR) on image quality and dose compared to a hybrid iterative reconstruction (IR) algorithm. • The Smooth and Smoother levels of AI-DLR reduced the image noise and improved the detectability of lesions and spatial resolution for standard and low-dose levels. • The Smooth level seems the best compromise between the lowest dose level and adequate image quality.
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