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A combination of AI and Radiology can reduce missed lung cancer diagnosis by 60%
In a study, UK researchers have revealed that combining Artificial Intelligence (AI) with the expertise of radiologists dropped the rate of missed lung cancers on chest X-rays by 60%.
Many patients rely on radiographs to diagnose cancer, despite the efforts to increase CT screening. Experts say that interpreting the images from radiography can prove to be a ‘complex and subjective’ task, with about 90% of cancer misdiagnoses occurring on chest X-rays.
Experts deployed a commercially available algorithm as a first reader of Chest X-rays. When used independently, AI performed similarly to physicians. Although, combining the two drastically dropped misses while standardizing the performance of all radiologists.
Matthew Tam, with the Department of Radiology at Southend University Hospital in Essex, concluded that “The proposed AI implementation pathway stands to reduce radiologist errors and improve clinician reporting performance. Additionally, taking a radiologist-centric approach in the development of clinical AI holds promise for catching systematically missed lung cancers. This represents a tremendous opportunity to improve patient outcomes for lung cancer diagnosis.”
Researchers curated a database of 400 chest X-rays, including 200 difficult-to-diagnose lung cancer cases. Three expert radiologists reviewed the images, and so did an AI algorithm from London-based Behold.ai. The AI and radiologist labels were combined to simulate the triage workflow, Tam et al. noted.
Individually AI was equivalent to an average radiologist, identifying tumors at an overall accuracy rate of 87%. But, combining radiologists and AI proved to be effective. The performance of all three radiologists improved, hitting an average of 90.67%, with a sensitivity of 91.33% and 90% specificity.
“In the present study, implementation of AI-based triage caused a significant reduction in the number of tumors missed by radiologists,” the authors noted. They also added that “the overall reduction in missed cancers of 60% has a great promise in improving patient survival rates through the early identification of lung cancers.”
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