Computed tomography features associated with pneumothorax susceptibility in pectus excavatum: a retrospective case-control study of lobar morphometry, attenuation metrics, and machine-learning projection.
原发性自发性气胸（PSP）可在无明显肺大疱或肺小疱的情况下发生，提示存在更广泛的结构易感性。漏斗胸（PE）与PSP的高发生率相关。我们评估了基于胸部计算机断层扫描（CT）的PSP肺叶特征，并检验PE是否表现出PSP样表型。回顾性将20~30岁年轻成人分为首发PSP组[自发性气胸患者（PT）]、无气胸史的PE组或健康对照（HC）组。使用3D Slicer从CT数据集中提取肺叶形态学指标[体积、表面积（SA）、表面积与体积比（SA/V）及形状描述符]和基于Hounsfield单位（HU）的衰减指标。按肺叶及受试者内上下不对称性（Δ分析）评估组间差异。训练五种侧别特异性机器学习算法，利用交叉验证预测区分PT与HC。将Youden最优受试者工作特征（ROC）阈值应用于PE队列而不重新训练，以量化气胸样结构易感性。共分析561个（右侧282个，左侧279个）侧别特异性肺叶。与HC相比，PT显示更高的SA/V、更不紧凑的肺叶几何形态及更宽的高衰减尾部。在Δ分析中，基于衰减的差值 consistently 区分各组，而PE显示更多几何驱动的不对称性，包括Δ平坦度降低。支持向量机（SVM）判别效果最佳[曲线下面积（AUC）：右侧0.937；左侧0.953]。在Youden阈值（右侧0.811；左侧0.841）下，高风险/PT样分类在PE中较HC富集（右侧30/67 vs 1/158；左侧38/67 vs 1/158；均P<0.001）。定量CT识别出PT中独特的形态学-衰减表型，并揭示PE中存在显著的PT样特征，值得通过纵向气胸结局进行前瞻性验证。
Primary spontaneous pneumothorax (PSP) can occur without visible blebs or bullae, suggesting a broader structural susceptibility. Pectus excavatum (PE) is associated with a high incidence of PSP. We evaluated chest computed tomography (CT)-based lobar signatures of PSP and tested whether PE exhibits a PSP-like phenotype. Young adults aged 20-30 years were retrospectively grouped as first-episode PSP [patients with spontaneous pneumothorax (PT)], PE without prior pneumothorax, or healthy controls (HC). Using 3D Slicer, we extracted lobar morphometric indices [volume, surface area (SA), surface area-to-volume ratio (SA/V), and shape descriptors] and Hounsfield unit (HU)-derived attenuation metrics from CT datasets. Group differences were assessed per lobe and by within-subject upper-lower asymmetry (Δ analysis). Five side-specific machine learning algorithms were trained to discriminate PT from HC using cross-validated predictions. Youden-optimal receiver operating characteristic (ROC) thresholds were applied to the PE cohort without retraining to quantify pneumothorax-like structural susceptibility. A total of 561 (right 282 and left 279) side-specific lobes were analyzed. PT showed higher SA/V and less compact lobar geometry than HC and broader high-attenuation tails. In Δ analyses, attenuation-based deltas consistently separated groups, whereas PE showed more geometry-driven asymmetry, including reduced Δ-flatness. support vector machine (SVM) discrimination was the most excellent [area under the curve (AUC): right 0.937; left 0.953]. At Youden thresholds (right 0.811; left 0.841), high-risk/PT-like classifications were enriched in PE versus HC (right 30/67 1/158; left 38/67 1/158; both P<0.001). Quantitative CT identifies distinct morphometric-attenuation phenotypes in PT and reveals a substantial PT-like signature in PE, warranting prospective validation with longitudinal pneumothorax outcomes.
In Sub Kim, Jae Jun Kim, Kyong Shil Im, Yoon Ho Kim, Jeong Hwan Ryu. Computed tomography features associated with pneumothorax susceptibility in pectus excavatum: a retrospective case-control study of lobar morphometry, attenuation metrics, and machine-learning projection.. Journal of thoracic disease. 2026; doi:10.21037/jtd-2026-0589.
In Sub Kim, Jae Jun Kim, Kyong Shil Im, Yoon Ho Kim, Jeong Hwan Ryu (2026). Computed tomography features associated with pneumothorax susceptibility in pectus excavatum: a retrospective case-control study of lobar morphometry, attenuation metrics, and machine-learning projection.. Journal of thoracic disease. https://doi.org/10.21037/jtd-2026-0589
In Sub Kim, Jae Jun Kim, Kyong Shil Im, Yoon Ho Kim, Jeong Hwan Ryu. Computed tomography features associated with pneumothorax susceptibility in pectus excavatum: a retrospective case-control study of lobar morphometry, attenuation metrics, and machine-learning projection.[J]. Journal of thoracic disease, 2026 doi:10.21037/jtd-2026-0589.
翻译全文 · AI 文献问答 · PDF 原文下载 · 引用导出