Center for Computer Vision and Imaging Biomarkers and Thoracic Imaging Research Group, Department of Radiological Sciences, David Geffen School of Medicine, University of California-Los Angeles, 924 Westwood Blvd, suite 650, Los Angeles, CA 90024, USA.
Eur Radiol. 2012 Feb;22(2):302-9. doi: 10.1007/s00330-011-2278-0. Epub 2011 Oct 8.
To propose and evaluate a technique for automatic quantification of fissural completeness from chest computed tomography (CT) in a database of subjects with severe emphysema.
Ninety-six CT studies of patients with severe emphysema were included. The lungs, fissures and lobes were automatically segmented. The completeness of the fissures was calculated as the percentage of the lobar border defined by a fissure. The completeness score of the automatic method was compared with a visual consensus read by three radiologists using boxplots, rank sum tests and ROC analysis.
The consensus read found 49% (47/96), 15% (14/96) and 67% (64/96) of the right major, right minor and left major fissures to be complete. For all fissures visually assessed as being complete the automatic method resulted in significantly higher completeness scores (mean 92.78%) than for those assessed as being partial or absent (mean 77.16%; all p values <0.001). The areas under the curves for the automatic fissural completeness were 0.88, 0.91 and 0.83 for the right major, right minor and left major fissures respectively.
An automatic method is able to quantify fissural completeness in a cohort of subjects with severe emphysema consistent with a visual consensus read of three radiologists.
• Lobar fissures are important for assessing the extent and distribution of lung disease • Modern CT allows automatic lobar segmentation and assessment of the fissures • This segmentation can also assess the completeness of the fissures. • Such assessment is important for decisions about novel therapies (eg for emphysema).
提出并评估一种从严重肺气肿患者的 CT 数据库中自动量化裂隙完整性的技术。
纳入 96 例严重肺气肿患者的 CT 研究。自动分割肺部、裂隙和肺叶。裂隙的完整性通过裂隙定义的肺叶边界的百分比来计算。自动方法的完整性评分与三位放射科医生的视觉共识阅读进行比较,使用箱线图、秩和检验和 ROC 分析。
共识阅读发现 49%(47/96)、15%(14/96)和 67%(64/96)的右主、右小和左主裂隙完整。对于所有视觉上评估为完整的裂隙,自动方法的完整性评分显著高于部分或缺失的裂隙(平均 92.78%比 77.16%;所有 p 值均<0.001)。自动裂隙完整性的曲线下面积分别为右主、右小和左主裂隙的 0.88、0.91 和 0.83。
一种自动方法能够定量评估严重肺气肿患者队列中裂隙的完整性,与三位放射科医生的视觉共识阅读一致。
• 肺裂对于评估肺疾病的范围和分布很重要。• 现代 CT 允许自动进行肺叶分割和评估裂隙。• 这种分割还可以评估裂隙的完整性。• 这种评估对于新型治疗方法(例如肺气肿)的决策很重要。