Using a limited field of view to improve training for pulmonary nodule detection on radiographs

Perceptual error is a significant cause of medical errors in radiology. Given the amount of information in a medical image, an image interpreter may become distracted by information unrelated to their search pattern. This may be especially challenging for novices. We aim to examine teaching medical trainees to evaluate chest radiographs (CXRs) for pulmonary nodules on limited field-of-view (LFOV) images, with the field of view (FOV) restricted to the lungs and mediastinum.

Healthcare trainees with limited exposure to interpreting images were asked to identify pulmonary nodules on CXRs, half of which contained nodules. The control and experimental groups evaluated two sets of CXRs. After the first set, the experimental group was trained to evaluate LFOV images, and both groups were again asked to assess CXRs for pulmonary nodules. Participants were given surveys after this educational session to determine their thoughts about the training and symptoms of computer vision syndrome (CVS).

There was a significant improvement in performance in pulmonary nodule identification for both the experimental and control groups, but the improvement was more considerable in the experimental group ( $p\text{-}\text{value}=0.022$ ). Survey responses were uniformly positive, and each question was statistically significant (all $p\text{-}\text{values}<0.001$ ).

Our results show that using LFOV images may be helpful when teaching trainees specific high-yield perceptual tasks, such as nodule identification. The use of LFOV images was associated with reduced symptoms of CVS.