Shin Cheong-Il, Kim Se Hyung, Im Jong Pil, Kim Sang Gyun, Yu Mi Hye, Lee Eun Sun, Han Joon Koo
Department of Radiology, Seoul National University Hospital, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, Republic of Korea.
Department of Radiology, Seoul National University Hospital, Republic of Korea; Department of Radiology, Seoul National University College of Medicine, Republic of Korea.
Eur J Radiol. 2016 Mar;85(3):641-8. doi: 10.1016/j.ejrad.2015.12.030. Epub 2016 Jan 7.
To analyze the effect of different reconstruction algorithms on image noise and radiologists' performance at ultra-low dose CT colonography (CTC) in human subjects.
This retrospective study had institutional review board approval, with waiver of the need to obtain informed consent. CTC and subsequent colonoscopy were performed at the same day in 28 patients. CTC was scanned at the supine/prone positions using 120/100kVp and fixed 10mAs, and reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model-based IR (Veo) algorithms. Size-specific dose estimates (SSDE) and effective radiation doses were recorded. Image noise was compared among the three datasets using repeated measures analysis of variance (ANOVA). Per-polyp sensitivity and figure-of-merits were compared among the datasets using the McNemar test and jackknife alternative free-response receiver operating characteristic (JAFROC) analysis, respectively, by one novice and one expert reviewer in CTC.
Mean SSDE and effective radiation dose of CTC were 1.732mGy and 1.002mSv, respectively. Mean image noise at supine/prone position datasets was significantly lowest with Veo (17.2/13.3), followed by ASIR (52.4/38.9) and FBP (69.9/50.8) (P<0.0001). Forty-two polyps in 25 patients were reference polyps. For both readers, per-polyp sensitivity of all 42 polyps was highest with Veo reconstruction (81.0%, 64.3%), followed by ASIR (73.8%, 54.8%) and FBP (57.1%, 50.0%) with statistical significance between Veo and FBP for reader 1 (P=0.002). JAFROC analysis revealed that the figure-of-merit for the detection of polyps was highest with Veo (0.917, 0.786), followed by ASIR (0.881, 0.750) and FBP (0.750, 0.746) with statistical significances between Veo or ASIR and FBP for reader 1 (P<0.05).
One-mSv CTC was not feasible using the standard FBP algorithm. However, diagnostic performance expressed as per-polyp sensitivity and figures-of-merit can be improved with the application of IR algorithms, particularly Veo.
分析不同重建算法对人体超低剂量CT结肠成像（CTC）图像噪声及放射科医生诊断表现的影响。
本回顾性研究经机构审查委员会批准，无需获取知情同意书。28例患者于同一天接受了CTC检查及后续结肠镜检查。CTC检查时患者取仰卧位/俯卧位，采用120/100kVp及固定的10mAs进行扫描，并分别使用滤波反投影（FBP）、自适应统计迭代重建（ASIR）和基于模型的迭代重建（Veo）算法进行重建。记录特定尺寸剂量估计值（SSDE）和有效辐射图像噪声及有效辐射剂量。采用重复测量方差分析（ANOVA）比较三个数据集的图像噪声。由一名新手和一名专家阅片者分别采用McNemar检验和留一法交替自由响应接收者操作特征（JAFROC）分析比较各数据集的息肉检出敏感度及综合评价指标。
CTC的平均SSDE和有效辐射剂量分别为1.732mGy和1.002mSv。仰卧位/俯卧位数据集的平均图像噪声在Veo算法重建时最低（17.2/13.3），其次是ASIR算法（52.4/38.9）和FBP算法（69.9/50.8）（P<0.0001）。25例患者共检出42个息肉作为参考息肉。对于两位阅片者，42个息肉的息肉检出敏感度在Veo算法重建时最高（81.0%，64.3%），其次是ASIR算法（73.8%，54.8%）和FBP算法（57.1%，50.0%），阅片者1在Veo算法和FBP算法之间差异具有统计学意义（P=0.002）。JAFROC分析显示，息肉检测的综合评价指标在Veo算法时最高（0.917，0.786），其次是ASIR算法（0.881，0.750）和FBP算法（0.750，0.746），阅片者1在Veo算法或ASIR算法与FBP算法之间差异具有统计学意义（P<0.05）。
使用标准FBP算法时，1mSv的CTC剂量不可行。然而，应用迭代重建算法，尤其是Veo算法，可以提高以息肉检出敏感度和综合评价指标表示的诊断性能。
