Abstract
Objective: The objective of our study was to evaluate the incidence of and the risk factors for pneumothorax and intercostal catheter insertion (ICC) after CT-guided lung biopsy and to generate a risk prediction model for developing a pneumothorax and requiring an ICC. It is a retrospective study.
Materials and Methods: 255 CT-guided lung biopsies performed for 249 lesions in 249 patients from August 2014 to August 2019 were retrospectively analysed in this study. Relevant risk factors associated with post-procedural pneumothorax and ICC insertion were analysed using multivariate logistic regression analysis. Risk prediction models for pneumothorax and ICC insertion were established using backward stepwise variable selection and likelihood ratio tests. Internal validation of the models were performed by randomly splitting the data into a training and testing set, two-thirds and one-third respectively.
Results: The overall incidence of pneumothorax was 30.2% (77/255). ICC insertion was required for 8.32% (21/255) of all procedures. The significant independent risk factors for pneumothorax were lesions not in contact with pleura (p < 0.001), a shorter skin-to-pleura distance (p = 0.01), the needle crossing a fissure (p = 0.004) and emphysema (p = 0.01); those for ICC insertion for pneumothorax were a needle through emphysema (p < 0.001) and lesions in the upper lobe (p = 0.017). AUC of the predictive models for pneumothorax and ICC insertion were 0.800 (95% CI, 0.745 – 0.856) and 0.859 (95% CI, 0.779 – 0.939) respectively. Upon internal validation, AUC of the testing sets of pneumothorax and ICC insertion were 0.769 and 0.822 on average respectively.
Conclusion: The complication rates of pneumothorax and ICC insertion after CT-guided lung biopsy at our institution are comparable to results from previously reported studies. This study provides highly accurate risk prediction models of pneumothorax and ICC insertion for patients undergoing CT-guided lung biopsies.
DOI: 10.1111/1754-9485.13187

**Abstract**
**Objective:** The objective of our study was to evaluate the incidence of and the risk factors for pneumothorax and intercostal catheter insertion (ICC) after CT-guided lung biopsy and to generate a risk prediction model for developing a pneumothorax and requiring an ICC. It is a retrospective study.
**Materials and Methods:** 255 CT-guided lung biopsies performed for 249 lesions in 249 patients from August 2014 to August 2019 were retrospectively analysed in this study. Relevant risk factors associated with post-procedural pneumothorax and ICC insertion were analysed using multivariate logistic regression analysis. Risk prediction models for pneumothorax and ICC insertion were established using backward stepwise variable selection and likelihood ratio tests. Internal validation of the models were performed by randomly splitting the data into a training and testing set, two-thirds and one-third respectively.
**Results:** The overall incidence of pneumothorax was 30.2% (77/255). ICC insertion was required for 8.32% (21/255) of all procedures. The significant independent risk factors for pneumothorax were lesions not in contact with pleura (_p_ < 0.001), a shorter skin-to-pleura distance (_p_ = 0.01), the needle crossing a fissure (_p_ = 0.004) and emphysema (_p_ = 0.01); those for ICC insertion for pneumothorax were a needle through emphysema (_p_ < 0.001) and lesions in the upper lobe (_p_ = 0.017). AUC of the predictive models for pneumothorax and ICC insertion were 0.800 (95% CI, 0.745 – 0.856) and 0.859 (95% CI, 0.779 – 0.939) respectively. Upon internal validation, AUC of the testing sets of pneumothorax and ICC insertion were 0.769 and 0.822 on average respectively.
**Conclusion:** The complication rates of pneumothorax and ICC insertion after CT-guided lung biopsy at our institution are comparable to results from previously reported studies. This study provides highly accurate risk prediction models of pneumothorax and ICC insertion for patients undergoing CT-guided lung biopsies.
**DOI:** 10.1111/1754-9485.13187

Development of a risk prediction model for pneumothorax in percutaneous CT guided lung biopsy

The Winter Course 2021 covers a variety of topics from basics in interstitial lung disease, infections including Covid-19, malignancies, lung cancer screening, and artificial intelligence. The combination of topics is aimed to serve as a good introduction to radiologists embarking on a career in thoracic imaging as well as a solid refresher for experienced thoracic radiologists.

[ESTI Winter Course 2021 Evaluation Form](https://www.surveymonkey.com/r/PP9WFTJ?sid=%5Bsid_value%5D&uid=%5Buid_value%5D&tkn=%5Btkn_value%5D&cgrid=%5Bcgrid_value)

ESTI Winter Course 2021

A Computed Tomography-based Radiomics Model for Patient Prognostic Stratification in Non-Small Cell Lung Cancer

Break Video

CT-Guided Microcoil placement for VATS Resection of Pulmonary Nodules

Evaluation of an AI program in thoracic imaging: Performance in detection of thoracic aorta ectasia

A Single Centre Institutional Study on 2295 patients for COVID-19 Detection from Radiographs Using a Deep Learning Model - Our Experience and Insights

Evaluation of AI applications in thoracic imaging: Performance in the detection of vertebral body alterations

Can inclusion of the combination of chemical shift ratio and signal intensity increase the number of patient’s classified as definitively benign on thymic MRI beyond use of chemical shift ratio alone? Experience from a UK thoracic tertiary referral centre

Relative contribution of emphysema and airway disease to disease severity in COPD patients GOLD stages I to IV using quantitative computed tomography

Lung Thermal Ablation: Comparison between an Augmented Reality Computed Tomography (CT) 3D Navigation System (SIRIO) and Standard CT-Guided Technique

Differentiating COVID-19 pneumonia from atypical bacterial, fungal and non-COVID-19 viral pneumonia on Chest-CT: Is it possible?

Reliability of Ultra-Short Echo Time MRI sequence in the assessment of Interstitial Lung Disease related to Systemic Sclerosis

Assessing longitudinal changes in lung gas transfer in dyspnoeic post-COVID-19 patients using hyperpolarized Xenon-129 Magnetic Resonance Imaging

Session Introduction