Clinical Evaluation of an Innovative Metal-Artifact-Reduction Algorithm in FD-CT Angiography in Cerebral Aneurysms Treated by Endovascular Coiling or Surgical Clipping

Treated cerebral aneurysms (IA) require follow-up imaging to ensure occlusion. Metal artifacts complicate radiologic assessment. Our aim was to evaluate an innovative metal-artifact-reduction (iMAR) algorithm for flat-detector computed tomography angiography (FD-CTA) regarding image quality (IQ) and detection of aneurysm residua/reperfusion in comparison to 2D digital subtraction angiography (DSA). Patients with IAs treated by endovascular coiling or clipping underwent both FD-CTA and DSA. FD-CTA datasets were postprocessed with/without iMAR algorithm (MAR+/MAR-). Evaluation of all FD-CTA and DSA datasets regarding qualitative (IQ, MAR) and quantitative (coil package diameter /CPD) parameters was performed. Aneurysm occlusion was assessed for each dataset and compared to DSA findings. In total, 40 IAs were analyzed (n(coiling) = 24; n(clipping) = 16). All iMAR+ datasets demonstrated significantly better IQ (p(IQ coiling) < 0.0001; p(IQ clipping) < 0.0001). iMAR significantly reduced the metal-artifact burden but did not affect the CPD. iMAR significantly improved the detection of aneurysm residua/reperfusion with excellent agreement with DSA (n(aneurysm detection) (MAR+/MAR-/DSA) = 22/1/26). The iMAR algorithm significantly improves IQ by effective reduction of metal artifacts in FD-CTA datasets. The proposed algorithm enables reliable detection of aneurysm residua/reperfusion with good agreement to DSA. Thus, iMAR can help to reduce the need for invasive follow-up in treated IAs.