Metal artifact reduction by virtual monoenergetic reconstructions from spectral brain CT.

Purpose: Conventional computed tomography (CT) images are severely affected by metal artifacts in patients with intracranial coils. Monoenergetic images have been suggested to reduce metal artifacts.The aim of this study was to assess metal artifacts in virtual monoenergetic images (VMIs) reconstructed from spectral brain CT.
Methods: Thirty-two consecutive patients with intracranial coils examined by spectral non contrast brain CT (NCCT) at our center between November 2017 and April 2019 were included. Attenuation and standard deviations were measured in regions of interest (ROIs) at predefined areas in artifact-free and artifact-affected areas. Measurements were performed in conventional polyenergetic images (CIs) and the corresponding data for VMIs were retrieved through spectral diagrams for the each ROI. Subjective analysis was performed by visual grading of CIs and specific VMIs by two neuroradiologists, independently.
Results: In artefact-affected image areas distal from the metal objects, the attenuation values decreased with higher energy level VMIs. The same effect was not seen for artefact-affected image areas close to the metal.Subjective rating of the artefact severity was significantly better in VMIs at 50 keV for one of the two reviewers compared to the CIs. Overall image quality and tissue differentiation scores were significantly higher for both reviewers in VMIs at 60 and 70 keV compared to CIs.
Conclusion: Our quantitative and qualitative image analysis shown that there is a small significant reduction of intracranial coils artifacts severity by all monoenergetic reconstructions from 50 to 200 keV with preserved or increased overall subjective image quality compared to conventional images.
Competing Interests: None of the authors have any conflicts of interests related to the study. JW is a founder and shareholder of Uman Sense AB and has received speaker honoraria from Siemens Healthineers, BALT group and Medtronic Inc.
(© 2023 The Authors.)