Artificial Intelligence helps detect Post Lung Biopsy Pneumothorax on follow-up chest radiographs
Percutaneous transthoracic needle biopsy (PTNB) is a highly accurate, widely used method for the diagnosis of lung lesions. However, the most frequent complication of PTNB is pneumothorax, which occurs in 16.2%–38.4% of PTNB procedures. In a recent study, researchers developed a deep learning-based computer-aided detection system that showed promising results in the detection of pneumothorax after lung biopsy.
The study findings were published in the journal Radiology on January 25, 2022.
Chest radiography is the recommended imaging technique for diagnosing PTNB-related pneumothorax. A recent study showed that a deep learning algorithm appropriately identified pneumothorax on post-PTNB radiographs in retrospectively collected consecutive diagnostic cohorts, with a sensitivity of 70.5% and specificity of 97.7%. However, the validation of a deep learning algorithm to improve diagnostic performance in real-world clinical practise has not previously been established. Therefore, Dr Chang Min Park and his team conducted a study to investigate whether a deep learning-based CAD system can improve detection performance for pneumothorax on chest radiographs after PTNB in clinical practice.
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