Available online 13 May 2024

Ultra-high-resolution CT of the temporal bone with deep learning reconstruction can be performed with up to a tenfold reduction in radiation dose by comparison with conventional high-resolution CT while maintaining image quality.

The use of deep learning with ultra-high-resolution CT at the same radiation dose as conventional high-resolution CT allows a marked increase in image quality of the middle and inner ear.

The use of deep learning with ultra-high-resolution CT helps achieve more complete bony coverage of the facial nerve and better representation of the cochlear spiral osseous lamina compared to hybrid iterative reconstruction algorithms.

The purpose of this study was to evaluate the achievable radiation dose reduction of an ultra-high resolution computed tomography (UHR-CT) scanner using deep learning reconstruction (DLR) while maintaining temporal bone image quality equal to or better than high-resolution CT (HR-CT).

UHR-CT acquisitions were performed with variable tube voltages and currents at eight different dose levels (volumic CT dose index [CTDIvol] range: 4.6–79 mGy), 10242 matrix, and 0.25 mm slice thickness and reconstructed using DLR and hybrid iterative reconstruction (HIR) algorithms. HR-CT images were acquired using a standard protocol (120 kV/220 mAs; CTDI vol, 54.2 mGy, 5122 matrix, and 0.5 mm slice thickness). Two radiologists rated the image quality of seven structures using a five point confidence scale on six cadaveric temporal bone CTs. A global image quality score was obtained for each CT protocol by summing the image quality scores of all structures.

With DLR, UHR-CT at 120 kV/220 mAs (CTDIvol, 50.9 mGy) and 140 kV/220 mAs (CTDIvol, 79 mGy) received the highest global image quality scores (4.88 ± 0.32 [standard deviation (SD)] [range: 4–5] and 4.85 ± 0.35 [range: 4–5], respectively; P = 0.31), while HR-CT at 120 kV/220 mAs and UHR-CT at 120 kV/20 mAs received the lowest (i.e., 3.14 ± 0.75 [SD] [range: 2–5] and 2.97 ± 0.86 [SD] [range: 1–5], respectively; P = 0.14). All the DLR protocols had better image quality scores than HR-CT with HIR.

UHR-CT with DLR can be performed with up to a tenfold reduction in radiation dose compared to HR-CT with HIR while maintaining or improving image quality.

Computed tomography

Deep learning

Image enhancement

Image reconstruction

Temporal bone

Advanced Intelligent Clear-IQ Engine

Deep learning reconstruction

High-resolution computed tomography

Hybrid iterative reconstruction

Ultra-high resolution computed tomography

© 2024 The Author(s). Published by Elsevier Masson SAS on behalf of Société française de radiologie.