OBJECTIVES

While established for energy-integrating detector computed tomography (CT), the effect of virtual monoenergetic imaging (VMI) and iterative metal artifact reduction (iMAR) in photon-counting detector (PCD) CT lacks thorough investigation. This study evaluates VMI, iMAR, and combinations thereof in PCD-CT of patients with dental implants.

MATERIAL AND METHODS

In 50 patients (25 women; mean age 62.0 ± 9.9 years), polychromatic 120 kVp imaging (T3D), VMI, T3D, and VMI were compared. VMIs were reconstructed at 40, 70, 110, 150, and 190 keV. Artifact reduction was assessed by attenuation and noise measurements in the most hyper- and hypodense artifacts, as well as in artifact-impaired soft tissue of the mouth floor. Three readers subjectively evaluated artifact extent and soft tissue interpretability. Furthermore, new artifacts through overcorrection were assessed.

RESULTS

iMAR reduced hyper-/hypodense artifacts (T3D 1305.0/-1418.4 versus T3D 103.2/-46.9 HU), soft tissue impairment (106.7 versus 39.7 HU), and image noise (16.9 versus 5.2 HU) compared to non-iMAR datasets (p ≤ 0.001). VMI ≥ 110 keV subjectively enhanced artifact reduction over T3D (p ≤ 0.023). Without iMAR, VMI displayed no measurable artifact reduction (p ≥ 0.186) and facilitated no significant denoising over T3D (p ≥ 0.366). However, VMI ≥ 110 keV reduced soft tissue impairment (p ≤ 0.009). VMI ≥ 110 keV resulted in less overcorrection than T3D (p ≤ 0.001). Inter-reader reliability was moderate/good for hyperdense (0.707), hypodense (0.802), and soft tissue artifacts (0.804).

CONCLUSION

While VMI alone holds minimal metal artifact reduction potential, iMAR post-processing enabled substantial reduction of hyperdense and hypodense artifacts. The combination of VMI ≥ 110 keV and iMAR resulted in the least extensive metal artifacts.

CLINICAL RELEVANCE

Combining iMAR with VMI represents a potent tool for maxillofacial PCD-CT with dental implants achieving substantial artifact reduction and high image quality.

KEY POINTS

• Post-processing of photon-counting CT scans with an iterative metal artifact reduction algorithm substantially reduces hyperdense and hypodense artifacts arising from dental implants. • Virtual monoenergetic images presented only minimal metal artifact reduction potential. • The combination of both provided a considerable benefit in subjective analysis compared to iterative metal artifact reduction alone.