Incidental imaging findings from head to toe: challenges and management: introductory editorial

First do no harm in responding to incidental imaging findings

“…Several such reviews have recently been published. 27 Multivariable risk prediction models that integrate lesion and patient characteristics warrant greater use, while new machine learning-based imaging applications may perform even better in predicting malignancy among, for example, thyroid and lung nodules. 28,29 At a more basic level, when interpreting a new image, retrieving past images or reports aids in identifying pre-existing incidentalomas and any interval change suggesting progressive disease.…”

“…All radiologists should familiarise themselves with systematically developed reviews for common, organ‐specific incidentalomas that emphasise features distinguishing benign from clinically important lesions, according to imaging modality. Several such reviews have recently been published 27 . Multivariable risk prediction models that integrate lesion and patient characteristics warrant greater use, while new machine learning‐based imaging applications may perform even better in predicting malignancy among, for example, thyroid and lung nodules 28,29 .…”