Authors
Johannes T Heverhagen, Philippe Lauber, Miltiadis Krokidis, Alois Komarek, Patrick Dorn, Andreas Christe, Michael Patrick Brönnimann
Published in
Polish journal of radiology. Volume 91. Pages e308-e319. Epub Jun 30, 2026.
Abstract
This study aimed to investigate whether body composition and thoracic morphology parameters could serve as predictors of pneumothorax risk in patients undergoing computed tomography (CT)-guided lung biopsies.
We retrospectively analyzed 147 percutaneous CT-guided lung biopsies performed between January 2019 and December 2023, categorizing patients into groups with and without pneumothorax. Indirect assessment methods for body composition, including body mass index (BMI) and thoracic morphology parameters, were evaluated alongside confounding factors such as access route (AR) through dependent lung areas (DA), patient demographics, lesion characteristics, and procedural details. Statistical analyses included chi-square, Fisher's exact, and Mann-Whitney U tests, while univariate and binomial logistic regression models were used to examine the impact of these factors on pneumothorax occurrence.
BMI ≥ 27.5 (p < 0.01), pectus excavatum at the level of the target lesion (PEL) (p = 0.028), transverse asymmetry at the anatomical reference level, defined as the level of the inferior pulmonary vein (TAA) (p < 0.01), and AR through DA (p < 0.01) were significantly associated with a reduced incidence of peri-interventional pneumothorax. Binary logistic regression confirmed BMI ≥ 27.5, AR through DA, TAA, and PEL as significant protective factors (R² = 0.497, p < 0.001).
Constitutional factors such as higher BMI or the identification of subclinical chest deformities on pre-procedural imaging may facilitate stratification into lower-risk categories, facilitating more precise and confident procedural planning. Especially in the absence of these protective factors, ensuring that the AR traverses the DA becomes particularly important for minimizing the risk of pneumothorax during CT-guided lung biopsies.
PMID:
42569144
Bibliographic data and abstract were imported from PubMed on 08 Aug 2026.
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