CT-guided transthoracic biopsy performed by expert radiologists is both accurate and safe, and when paired with machine learning, can help physicians predict the likelihood of complications.
Doctors from the University of Pennsylvania’s Perelman School of Medicine examined nearly 800 CTTB procedures performed in a tertiary hospital for their research published in Academic Radiology. In 97% of these minimally invasive procedures, diagnostic yield proved to be “excellent,” with complications occurring in only 2% of cases.
While CTTB is relatively safe and preferred over other methods to biopsy thoracic lesions, first author Eduardo J. Mortani Barbosa Jr., MD, and colleagues found a neural network model could predict the severity of complications when they do happen in up to 94% of situations.
“These results suggest that sophisticated statistical models, especially with machine learning, may be accurate enough to allow pre-procedure prediction of CTTB related complications, based solely on imaging and clinical data, therefore allowing preemptive preventive measures to be applied in higher risk patients,” the authors added.
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