Department of Medicine, Division of Allergy, Pulmonary and Critical Care, Vanderbilt University Medical Center, Nashville, TN, United States of America.
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States of America.
PLoS One. 2023 Oct 25;18(10):e0290393. doi: 10.1371/journal.pone.0290393. eCollection 2023.
To evaluate the reliability of a novel segmentation-based volume rendering approach for quantification of benign central airway obstruction (BCAO).
A retrospective single-center cohort study.
Data were ascertained using electronic health records at a tertiary academic medical center in the United States.
Patients with airway stenosis located within the trachea on two-dimensional (2D) computed tomography (CT) imaging and documentation of suspected benign etiology were included. Four readers with varying expertise in quantifying tracheal stenosis severity were selected to manually segment each CT using a volume rendering approach with the available free tools in the medical imaging viewing software OsiriX (Bernex, Switzerland). Three expert thoracic radiologists were recruited to quantify the same CTs using traditional subjective methods on a continuous and categorical scale.
The interrater reliability for continuous variables was calculated by the intraclass correlation coefficient (ICC) using a two-way mixed model with 95% confidence intervals (CI).
Thirty-eight patients met the inclusion criteria, and fifty CT scans were selected for measurement. The most common etiology of BCAO was iatrogenic in 22 patients (58%). There was an even distribution of chest and neck CT imaging within our cohort. The average ICC across all four readers for the volume rendering approach was 0.88 (95% CI, 0.84 to 0.93), suggesting good to excellent agreement. The average ICC for thoracic radiologists for subjective methods on the continuous scale was 0.38 (95% CI, 0.20 to 0.55), suggesting poor to fair agreement. The kappa for the categorical approach was 0.26, suggesting a slight to fair agreement amongst the raters.
In this retrospective cohort study, agreement was good to excellent for raters with varying expertise in airway cross-sectional imaging using a novel segmentation-based volume rendering approach to quantify BCAO. This proposed measurement outperformed our expert thoracic radiologists using conventional subjective grading methods.
评估一种新的基于分割的容积渲染方法在量化良性中央气道阻塞（BCAO）中的可靠性。
回顾性单中心队列研究。
数据来自美国一家三级学术医疗中心的电子健康记录。
纳入二维（2D）计算机断层扫描（CT）成像上气道狭窄位于气管内并记录有疑似良性病因的患者。选择了 4 位具有不同量化气管狭窄严重程度专业知识的读者，使用医学成像查看软件 OsiriX（瑞士 Bernex）中提供的免费工具进行容积渲染分割。招募了 3 位胸部放射学专家，使用传统的主观方法对相同的 CT 进行连续和分类尺度的量化。
38 例患者符合纳入标准，选择了 50 次 CT 扫描进行测量。BCAO 的最常见病因是 22 例（58%）医源性的。我们的队列中胸部和颈部 CT 成像的分布均匀。所有 4 位读者的容积渲染方法的平均 ICC 为 0.88（95%CI，0.84 至 0.93），提示具有良好至极好的一致性。胸部放射科医生对连续尺度主观方法的平均 ICC 为 0.38（95%CI，0.20 至 0.55），提示一致性差至尚可。分类方法的κ值为 0.26，提示评分者之间存在轻度至中度的一致性。
在这项回顾性队列研究中，具有不同气道横截面成像专业知识的评分者使用新的基于分割的容积渲染方法对 BCAO 进行量化，其一致性良好至极好。这种新的测量方法优于我们的胸部放射学专家使用传统的主观分级方法。
