Landmark constellation models for central venous catheter malposition detection

Start Page
1132
End Page
1136
Article Number
9434022
Citation
IEEE 18th International Symposium on Biomedical Imaging (ISBI 2021)
Contribution to Conference
IEEE 18th International Symposium on Biomedical Imaging (ISBI 2021)  
Publisher DOI
10.1109/ISBI48211.2021.9434022
Scopus ID
2-s2.0-85107185032
ISBN of container
978-166541246-9
The placement of a central venous catheter (CVC) for venous access is a common clinical routine. Nonetheless, various clinical studies report that CVC insertions are unsuccessful in up to 20% of all cases. Among other, typical complications include the incidence of a pneumothorax, hemothorax, arterial puncture, venous air embolism, arrhythmias or catheter knotting. In order to detect the CVC tip in chest X-ray (CXR) images, and to evaluate the catheter placement, we propose a HRNet-based key point detection approach in combination with a probabilistic constellation model. In a cross-validation study, we show that our approach not only enables the exact localization of the CVC tip, but also of relevant anatomical landmarks. Moreover, the probabilistic model provides a likelihood score for tip position which allows us to identify malpositioned CVCs.
Subjects
Central venous catheter
Constellation model
Landmark detection
Malposition detection
X-ray