Deep learning-based reconstruction (DLR) significantly improved image quality in temporal bone ultrahigh-resolution CT (UHR-CT) for both adult and paediatric protocols, reducing noise and enhancing visualisation, according to a new study.

"Our findings suggest that deep learning-based image reconstruction of the temporal bone with ultrahigh-resolution CT significantly improves image quality and enhances diagnostic performance, hereby potentially affecting treatment decisions," the authors wrote.

The study was led by Lavinia Brockstedt, MD, University Medical Centre Mainz, Mainz, Germany. It was published online on February 24, 2025, in Academic Radiology.

The study's limitations included a relatively small sample size, particularly in the paediatric protocol group; a single-centre study design; and the inclusion of only patients without pathological findings to standardise the analysis of multiple small anatomical structures.

No funding information was provided for this study. One author reported receiving financial support from Canon Medical Systems Corporation, including funding grants and speaker and lecture fees.