Model-Based Iterative Reconstruction Technique for Ultralow-Dose Computed Tomography of the Lung

氡变换 迭代重建 医学 核医学 图像质量 断层摄影术 威尔科克森符号秩检验 放射科 人工智能 计算机科学 图像(数学) 曼惠特尼U检验 内科学
作者
Yoshitake Yamada,Masahiro Jinzaki,Yutaka Tanami,Eisuke Shiomi,Hiroaki Sugiura,Takayuki Abe,Sachio Kuribayashi
出处
期刊:Investigative Radiology [Lippincott Williams & Wilkins]
卷期号:47 (8): 482-489 被引量:133
标识
DOI:10.1097/rli.0b013e3182562a89
摘要

The aim of this study was to assess the effectiveness of a model-based iterative reconstruction (MBIR) in improving image quality and diagnostic performance of ultralow-dose computed tomography (ULDCT) of the lung.The institutional review board approved this study, and all patients provided written informed consent. Fifty-two patients underwent low-dose computed tomography (LDCT) (screening-dose, 50 mAs) and ULDCT (4 mAs) of the lung simultaneously. The LDCT images were reconstructed with filtered back projection (LDCT-FBP images) and ULDCT images were reconstructed with both MBIR (ULDCT-MBIR images) and FBP (ULDCT-FBP images). On all the 156 image series, objective image noise was measured in the thoracic aorta, and 2 blinded radiologists independently assessed subjective image quality. Another 2 blinded radiologists independently evaluated the ULDCT-MBIR and ULDCT-FBP images for the presence of noncalcified and calcified pulmonary nodules; LDCT-FBP images served as the reference. Paired t test, Wilcoxon signed rank sum test, and free-response receiver-operating characteristic analysis were used for statistical analysis of the data.Compared with LDCT-FBP and ULDCT-FBP, ULDCT-MBIR had significantly reduced objective noise (both P <; 0.001). Subjective noise on the ULDCT-MBIR images was comparable with that on the LDCT-FBP images but lower than that on the ULDCT-FBP images (P <; 0.001). Artifacts on ULDCT-MBIR images were more numerous than those on the LDCT-FBP images (P = 0.007) but fewer than those on the ULDCT-FBP images (P <; 0.001). Compared with the LDCT-FBP images, ULDCT-MBIR and ULDCT-FBP images showed reduced image sharpness (both P <; 0.001). All the ULDCT-MBIR images showed a blotchy pixelated appearance; however, the performance of ULDCT-MBIR was significantly superior to that of ULDCT-FBP for the detection of noncalcified pulmonary nodules (P = 0.002). The average true-positive fractions for significantly sized noncalcified nodules (≥4 mm) and small noncalcified nodules (<;4 mm) on the ULDCT-MBIR images were 0.944 and 0.884, respectively, when LDCT-FBP images were used as reference. All of the calcified nodules were detected by both the observers on both the ULDCT-MBIR and ULDCT-FBP images.As compared with FBP, MBIR enables significant reduction of the image noise and artifacts and also better detection of noncalcified pulmonary nodules on ULDCT of the lung. Compared with LDCT-FBP images, ULDCT-MBIR images showed significantly reduced objective noise and comparable subjective image noise. Almost all of the noncalcified nodules and all of the calcified nodules could be detected on the ULDCT-MBIR images, when LDCT-FBP images were used as the reference.
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