Validation of a Metal Artifact Reduction Algorithm Using 1D Linear Interpolation for Cone Beam CT after Endovascular Coiling Therapy for Cerebral Aneurysms

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 (ncoiling = 24; nclipping = 16). All iMAR+ datasets demonstrated significantly better IQ (pIQ coiling < 0.0001; pIQ 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 (naneurysm 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.

Value of virtual monochromatic spectral images with metal artifact reduction algorithm in dual-energy computed tomography-guided microcoil localization of pulmonary nodules

To evaluate the clinical value of virtual monochromatic spectral (VMS) images with metal artifact reduction (MAR) algorithm in dual-energy computed tomography (DECT)-guided microcoil localization of pulmonary nodules.Fifty-one patients underwent DECT after placement of microcoils on small pulmonary nodules before video-assisted thoracoscopic surgery (VATS). Optimal energy level (in keV) was defined as the level at which CT values of nodules were equivalent to those of 120 kVp images and with no serious metal artifacts. VMS images at optimal keV and at 50, 90,110, and 140 keV with and without MAR were reconstructed. Image quality was scored using a 3-point scale: 1 = excellent, minimal artifacts; 2 = good, mild artifacts; and 3 = poor, extensive artifacts. Image quality scores between the VMS-only and VMS + MAR groups were compared;74 keV was found to be the optimal level for VMS images. The image quality of the VMS + MAR images at 74 keV were significantly better than VMS-only images (1.35 ± 0.59 vs 2.11 ± 0.87, P = .005). There was no difference in image quality score among VMS + MAR images at 74 keV and higher energy levels.VMS images from DECT at 74 keV with MAR can reduce artifacts from microcoils and improve image quality for microcoil localization of pulmonary nodules.

Metal Artifact Reduction in Cone-Beam Computed Tomography for Head and Neck Radiotherapy

PURPOSE

To evaluate a method for reducing metal artifacts, arising from dental fillings, on cone-beam computed tomography images.

MATERIALS AND METHODS

A projection interpolation algorithm is applied to cone-beam computed tomography images containing metal artifacts from dental fillings. This technique involves identifying metal regions in individual cone-beam computed tomography projections and interpolating the surrounding values to remove the metal from the projection data. Axial cone-beam computed tomography images are then reconstructed, resulting in a reduction in the streak artifacts produced by the metal. Both phantom and patient imaging data are used to evaluate this technique.

RESULTS

The interpolation substitution technique successfully reduced metal artifacts in all cases. Corrected images had fewer or no streak artifacts compared to their noncorrected counterparts. Quantitatively, regions of interest containing the artifacts showed reduced variance in the corrected images versus the uncorrected images. Average pixel values in regions of interest around the metal object were also closer in value to nonmetal regions after artifact reduction. Artifact correction tended to perform better on patient images with less complex metal objects versus those with multiple large dental fillings.

CONCLUSION

The interpolation substitution is potentially an efficient and effective technique for reducing metal artifacts caused by dental fillings on cone-beam computed tomography image. This technique may be effective in reducing such artifacts in patients with head and neck cancer receiving daily image-guided radiotherapy.