Impact of radiomics features, pulmonary emphysema score and muscle mass on the rate of pneumothorax and chest tube insertion in CT-guided lung biopsies.

阅读:4
作者:Leonhardi Jakob, Dahms Ulrike, Schnarkowski Benedikt, Struck Manuel Florian, Höhn Anne-Kathrin, Krämer Sebastian, Ebel Sebastian, Prasse Gordian, Frille Armin, Denecke Timm, Meyer Hans-Jonas
Iatrogenic pneumothorax is a relevant complication of computed tomography (CT)-guided percutaneous lung biopsy. The aim of the present study was to analyze the prognostic significance of texture analysis, emphysema score and muscle mass derived from CT-imaging to predict postinterventional pneumothorax after CT-guided lung biopsy. Consecutive patients undergoing CT-guided percutaneous lung biopsy between 2012 and 2021 were analyzed. Multivariate logistic regression analysis included clinical risk factors and CT-imaging features to detect associations with pneumothorax development. Overall, 479 patients (178 females, mean age 65 ± 11.7 years) underwent CT-guided percutaneous lung biopsy of which 180 patients (37.5%) developed pneumothorax including 55 patients (11.5%) requiring chest tube placement. Risk factors associated with pneumothorax were chronic-obstructive pulmonary disease (COPD) (p = 0.03), age (p = 0.02), total lung capacity (p < 0.01) and residual volume (p = 0.01) as well as interventional parameters needle length inside the lung (p < 0.001), target lesion attached to pleura (p = 0.04), and intervention duration (p < 0.001). The combined model demonstrated a prediction accuracy of the occurrence of pneumothorax with an AUC of 0.78 [95%CI: 0.70-0.86] with a resulting sensitivity 0.80 and a specificity of 0.66. In conclusion, radiomics features of the target lesion and the lung lobe CT-emphysema score are predictive for the occurrence of pneumothorax and need for chest insertion after CT-guided lung biopsy.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。