Iterative metal artifact reduction on a clinical photon counting system—technical possibilities and reconstruction selection for optimal results dependent on the metal scenario

Abstract

To give an overview about technical possibilities for metal artifact reduction of the first clinical photon-counting CT system and assess optimal reconstruction settings in a phantom study, assessing monoenergetic imaging (VMI) and iterative metal artifact reduction (iMAR). Scans were performed with 120 kV and Sn140 kV on the first clinical photon-counting detector CT scanner. To quantify artifact reduction, anthropomorphic phantoms (hip, dental, spine, neuro) were assessed, in addition to a tissue characterization phantom (Gammex) to quantify the HU restoration accuracy, all with removable metal inserts. Each setup was reconstructed with and without dedicated iMAR, and VMIs were computed in 10 keV steps from 40 keV (60 keV at Sn140 kV) to 190 keV for all setups (ground truth and metal with and without iMAR). To find the optimal energy, pixel-wise errors were computed in relevant ROIs in water-equivalent tissue around the metal in each phantom setup. To assess HU restoration potential, measurements were performed in the Gammex phantom’s inserts. Large metal objects (hip head) or metal with high atomic numbers (dental and neuro) do not benefit from higher-energetic reconstructions. The hip shaft (large, low atomic number) comprises a lower base artifact level than the head, still without an energetic optimum. Within the spine (short penetration length, low atomic number) an energy optimum could be identified for both spectra (100 keV for 120 kV and 120 keV for Sn140 kV). The Gammex showed best HU restoration at 100 keV for 120 kV and at 110 keV for Sn140 kV. In all cases, additional iMAR reduced the base artifact level. This study shows that a novel photon-counting CT system has the capability to reduce metal artifacts in metal types with low atomic number and low penetration length by applying VMI. For all other metal types, additional iMAR is required to reduce artifacts.

Artifact Reduction From Dental Material in Photon-Counting Detector Computed Tomography Data Sets Based on High-keV Monoenergetic Imaging and Iterative Metal Artifact Reduction Reconstructions—Can We Combine the Best of Two Worlds?

“…This might have been one reason for the weaker artifact suppression by high keV VMIs than has previously been described and would concur with Zhu et al 5 who reported that higher keV VMIs especially reduced artifacts caused by small dental fillings. Anhaus et al 17 even tested multiple materials in their phantom study on a PCD-CT scanner and found no benefit by high-energy VMI on metal with high atomic number as used for dental restauration. Kernel choice does not influence average CT values in ROIs of the size used in our analysis; yet, it affects image noise, resulting in higher AIXs for sharper reconstruction kernels, a trivial consequence of the higher spatial resolution.…”

“…This might have been one reason for the weaker artifact suppression by high keV VMIs than has previously been described and would concur with Zhu et al 5 who reported that higher keV VMIs especially reduced artifacts caused by small dental fillings. Anhaus et al 17 even tested multiple materials in their phantom study on a PCD-CT scanner and found no benefit by high-energy VMI on metal with high atomic number as used for dental restauration.…”

“…Several techniques have been developed to mitigate these artifacts, most commonly based on iterative reconstruction algorithms, 10,11 virtual monoenergetic imaging (VMI) reconstructions from multienergy imaging data, 4,5,12,13 or a combination thereof. [14][15][16][17] The recently introduced photon-counting detector CT (PCD-CT) technology is especially promising in this regard because of its routine acquisition of spectral data. 18,19 From these, high-keV VMI reconstructions can be derived, which should reduce dental artifacts.…”

A nonlinear scaling‐based normalized metal artifact reduction to reduce low‐frequency artifacts in energy‐integrating and photon‐counting CT

“…Each of those threshold images includes only X‐ray photons with an energy exceeding a predefined energy threshold 33,34 . As it is implemented in conventional iterative MAR in the routine of the clinical PCD‐CT system, the described method was applied on both threshold images of the PCD scan separately, and the monoenergetic images are then generated from both threshold images 35 . The PCD images are shown at an energy level of 65 keV as the standard energy level for a 120 kV scan.…”

Metal artifact correction in photon‐counting detector computed tomography: metal trace replacement using high‐energy data

“…Anhaus et al. recently showed that iterative metal artifact reduction (iMAR) could be combined with VMIs with a clinical PCD‐CT scanner to obtain better MAR 48 . It is possible that similar results could be obtained by first applying TRMAR to obtain a reduced artifact image, and then an additional method could be applied to further improve the results.…”