Iterative metal artefact reduction in CT: can dedicated algorithms improve image quality after spinal...

Area of Science:

• Radiology
• Medical Imaging
• Image Processing

Background:

• Spinal instrumentation can cause metal artefacts in computed tomography (CT) scans.
• These artefacts degrade image quality, hindering diagnosis.
• Iterative metal artefact reduction (iMAR) algorithms aim to mitigate these issues.

Purpose of the Study:

• To evaluate the effectiveness of two dedicated CT iMAR algorithms for spinal instrumentation.
• To compare the performance of iMAR algorithms adjusted for spinal implants versus large metallic implants.

Main Methods:

• Retrospective analysis of 24 post-surgical spinal CT scans.
• Image reconstruction using standard weighted filtered back projection (WFBP) and two iMAR algorithms (iMAR-Algo1 for spinal, iMAR-Algo2 for hip implants).
• Objective quantification of density changes and subjective assessment of anatomical structure visibility.

Main Results:

• Both iMAR algorithms significantly reduced metal artefacts compared to WFBP (p<0.0001).
• iMAR algorithms improved visualization of soft-tissue and bone structures compared to WFBP (p<0.0001).
• iMAR-Algo2 demonstrated superior objective artefact reduction and subjective image quality over iMAR-Algo1 (p<0.0001).

Conclusions:

• Both tested iMAR algorithms effectively reduce metal artefacts in spinal CT.
• The iMAR algorithm optimized for large metallic implants (iMAR-Algo2) yielded better results than the one for spinal implants (iMAR-Algo1).
• This suggests tailored iMAR settings are crucial for optimal artefact reduction in post-surgical spine imaging.