Vardhanabhuti Varut, Pang Chun-Lap, Tenant Sean, Taylor James, Hyde Christopher, Roobottom Carl
Plymouth University Peninsula Schools of Medicine and Dentistry, John Bull Building, Plymouth, PL6 8BU, United Kingdom; Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong.
Plymouth University Peninsula Schools of Medicine and Dentistry, John Bull Building, Plymouth, PL6 8BU, United Kingdom; Department of Radiology, Derriford Hospital, Derriford Road, Plymouth, PL6 8DH, United Kingdom.
Eur J Radiol. 2017 Jun;91:130-141. doi: 10.1016/j.ejrad.2017.04.006. Epub 2017 Apr 15.
To determine the diagnostic accuracy of lung nodule detection in thoracic CT using 2 reduced dose protocols comparing 3 available CT reconstruction algorithms (filtered back projection-FBP, adaptive statistical reconstruction-ASIR and model-based iterative reconstruction-MBIR) in a western population.
A prospective single-center study recruited 98 patients with written consent. Standard dose (STD) thoracic CT followed by 2 reduced-dose protocols using automatic tube current modulation (RD1) and fixed tube current (RD2) were performed and reconstructed with FBP, ASIR and MBIR with subsequent diagnostic accuracy analysis for nodule detection.
108 solid nodules, 47 subsolid nodules and 89 purely calcified nodules were analyzed. RD1 was superior to RD2 for assessment of solid nodules ≤4mm, and subsolid nodules ≤5mm (p<0.05). Deterioration of RD2 is correlated to patient's body mass index and least affected by MBIR. For solid nodules ≤4mm, MBIR area under curve (AUC) for RD1 was 0.935/0.913 and AUC for RD2 was 0.739/0.739, for rater 1/rater2 respectively. For subsolid nodules ≤5mm, MBIR AUC for RD1 was 0.971/0.986 and AUC for RD2 was 0.914/0.914, for rater 1/rater2 respectively. For calcified nodules excellent detection accuracy was maintained regardless of reconstruction algorithms with AUC >0.97 for both readers across all dose and reconstruction algorithms.
Diagnostic performance of lung nodule is affected by nodule size, protocol, reconstruction algorithm and patient's body habitus. The protocol in this study showed that RD1 was superior to RD2 for assessment of solid nodules ≤4mm, and subsolid nodules ≤5mm and deterioration of RD2 is related to patient's body mass index.
在西方人群中,使用两种低剂量方案并比较三种可用的CT重建算法(滤波反投影-FBP、自适应统计重建-ASIR和基于模型的迭代重建-MBIR),确定胸部CT中肺结节检测的诊断准确性。
一项前瞻性单中心研究招募了98名签署书面同意书的患者。进行标准剂量(STD)胸部CT,随后采用自动管电流调制(RD1)和固定管电流(RD2)的两种低剂量方案,并使用FBP、ASIR和MBIR进行重建,随后对结节检测进行诊断准确性分析。
分析了108个实性结节、47个亚实性结节和89个纯钙化结节。在评估≤4mm的实性结节和≤5mm的亚实性结节时,RD1优于RD2(p<0.05)。RD2的质量下降与患者的体重指数相关,且受MBIR的影响最小。对于≤4mm的实性结节,RD1的MBIR曲线下面积(AUC)对于评估者1/评估者2分别为0.935/0.913,RD2的AUC为0.739/0.739。对于≤5mm的亚实性结节,RD1的MBIR AUC对于评估者1/评估者2分别为0.971/0.986,RD2的AUC为0.914/0.914。对于钙化结节,无论采用何种重建算法,检测准确性均保持良好,所有剂量和重建算法下两位读者的AUC均>0.97。
肺结节的诊断性能受结节大小、方案、重建算法和患者身体状况的影响。本研究中的方案表明,在评估≤4mm的实性结节和≤5mm的亚实性结节时,RD1优于RD2,且RD2的质量下降与患者的体重指数有关。