Department of Radiology, Seoul National University Bundang Hospital, 82, Gumi-ro 173beon-gil, Bundang-gu, Seongnam-si, Gyeongi-do, 13620, Korea.
Monitor Corporation, Seoul, Korea.
Eur Radiol. 2021 Sep;31(9):7184-7191. doi: 10.1007/s00330-021-07800-5. Epub 2021 Mar 17.
To assess interobserver agreement in Lung CT Screening Reporting and Data System (Lung-RADS) categorisation in subsolid nodule-enriched low-dose screening CTs.
A retrospective review of low-dose screening CT reports from 2013 to 2017 using keyword searches for subsolid nodules identified 54 baseline CT scans. With an additional 108 negative screening CT scans, a total of 162 CT scans were categorised according to the Lung-RADS by two fellowship-trained thoracic radiologists in consensus. We randomly selected 20, 20, 10, and 10 scans from categories 1/2, 3, 4A, and 4B CT scans, respectively, to ensure balanced category representation. Five radiologists classified the 60 CT scans into Lung-RADS categories. The frequencies of concordance and minor and major discordance were calculated, with major discordance defined as at least 6 months of management discrepancy. We used Cohen's κ statistics to analyse reader agreement.
An average of 60.3% (181 of 300) of all cases and 45.0% (90 of 200) of positive screens were correctly categorised. The minor and major discordance rates were 12.3% and 27.3% overall and 18.5% and 36.5% in positive screens, respectively. The concordance rate was significantly higher among experienced thoracic radiologists. Overall, the interobserver agreement was moderate (mean κ, 0.45; 95% confidence interval: 0.40-0.51). The proportion of part-solid risk-dominant nodules was significantly higher in cases with low rates of accurate categorisation.
This retrospective study observed variable accuracy and moderate interobserver agreement in radiologist categorisation of subsolid nodules in screening CTs. This inconsistency may affect management recommendations for lung cancer screening.
• Diagnostic performance for Lung-RADS categorisation is variable among radiologists with fair to moderate interobserver agreement in subsolid nodule-enriched CT scans. • Experienced thoracic radiologists showed more accurate and consistent Lung-RADS categorisation than radiology residents. • The relative abundance of part-solid nodules was a potential factor related to increased disagreement in Lung-RADS categorisation.
评估在富含亚实性结节的低剂量筛查 CT 中使用 Lung CT 筛查报告和数据系统(Lung-RADS)对亚实性结节进行分类的观察者间一致性。
通过对 2013 年至 2017 年低剂量筛查 CT 报告进行回顾性研究,使用关键词搜索识别出 54 例基线 CT 扫描。结合另外 108 例阴性筛查 CT 扫描,由两名胸部放射学 fellowship培训的放射科医生对总共 162 例 CT 扫描进行了 Lung-RADS 分类。我们随机选择了来自类别 1/2、3、4A 和 4B CT 扫描的 20、20、10 和 10 个扫描,以确保类别代表的均衡。五名放射科医生将 60 个 CT 扫描分为 Lung-RADS 类别。计算了一致性、轻微和重大分歧的频率,其中重大分歧定义为至少 6 个月的管理差异。我们使用 Cohen's κ 统计来分析读者的一致性。
所有病例的平均正确分类率为 60.3%(300 例中的 181 例),阳性筛查的平均正确分类率为 45.0%(200 例中的 90 例)。总体而言,轻微和重大分歧的发生率分别为 12.3%和 27.3%,阳性筛查的轻微和重大分歧的发生率分别为 18.5%和 36.5%。经验丰富的胸部放射科医生的一致性明显更高。总体而言,观察者间的一致性为中度(平均κ值为 0.45;95%置信区间:0.40-0.51)。在正确分类率较低的情况下,部分实性风险为主的结节的比例明显更高。
这项回顾性研究观察到在富含亚实性结节的筛查 CT 中,放射科医生对亚实性结节进行分类的准确性和观察者间一致性存在差异。这种不一致性可能会影响肺癌筛查的管理建议。
在富含亚实性结节的 CT 扫描中,放射科医生对 Lung-RADS 分类的诊断性能存在差异,观察者间的一致性为中等至较好。
与放射科住院医师相比,经验丰富的胸部放射科医生在 Lung-RADS 分类方面表现出更准确和一致的分类。
部分实性结节的相对丰度是导致 Lung-RADS 分类中分歧增加的一个潜在因素。