Hemorrhage risk prediction after computed tomography-guided lung biopsy: Clinical parameters and quantitative pulmonary vascular analysis

Keng-Chian Lin; Wei-Chun Ko; Yu-Dian Tsai; Chia-Yun Chang; Yung-Hsuan Yang; Yu-Sen Huang; Yeun-Chung Chang

doi:10.1016/j.jfma.2024.03.011

Hemorrhage risk prediction after computed tomography-guided lung biopsy: Clinical parameters and quantitative pulmonary vascular analysis

J Formos Med Assoc. 2024 Mar 20:S0929-6646(24)00172-4. doi: 10.1016/j.jfma.2024.03.011. Online ahead of print.

Authors

Keng-Chian Lin¹, Wei-Chun Ko¹, Yu-Dian Tsai¹, Chia-Yun Chang¹, Yung-Hsuan Yang¹, Yu-Sen Huang², Yeun-Chung Chang³

Affiliations

¹ Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan.
² Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan; Department of Radiology, National Taiwan University College of Medicine, Taipei, Taiwan. Electronic address: yusen0814@gmail.com.
³ Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan; Department of Radiology, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan.

PMID: 38514373
DOI: 10.1016/j.jfma.2024.03.011

Abstract

Background/purpose: We evaluated the utility of combining quantitative pulmonary vasculature measures with clinical factors for predicting pulmonary hemorrhage after computed tomography (CT)-guided lung biopsy.

Methods: Patients who underwent CT-guided lung biopsy were retrospectively included in this study. Clinical and radiographic vasculature variables were evaluated as predictors of pulmonary hemorrhage. The radiographic pulmonary vascular analysis included vessel count, density, diameter, and area, and also blood volume in small vessels with a cross-sectional area ≤5 mm² (BV5) and total blood vessel volume (TBV) in the lungs. Univariate and multivariate logistic regressions were used to identify the independent risk factors of higher-grade pulmonary hemorrhage and establish the prediction model presented as a nomogram.

Results: The study included 126 patients; discovery cohort n = 103, and validation cohort n = 23. All pulmonary hemorrhage, higher-grade (grade ≥2) pulmonary hemorrhage, and hemoptysis occurred in 42.9%, 15.9%, and 3.2% of patients who underwent CT-guided lung biopsies. In the discovery cohort, patients with larger lesion depth (p = 0.013), higher vessel density (p = 0.033), and higher BV5 (p = 0.039) were more likely to experience higher-grade hemorrhage. The nomogram prediction model for higher-grade hemorrhage built by the discovery cohort showed similar performance in the validation cohort.

Conclusions: Higher-grade pulmonary hemorrhage may occur after CT-guided lung biopsy. Lesion depth, vessel density, and BV5 are independent risk factors for higher-grade pulmonary hemorrhage. Nomograms integrating clinical parameters and radiographic pulmonary vasculature measures offer enhanced capability for assessing hemorrhage risk following CT-guided lung biopsy, thereby facilitating improved patient clinical care.

Keywords: Computerized tomography; Lung biopsy; Lung cancer; Pulmonary hemorrhage; Quantitative pulmonary vasculature analysis.