Virtual monochromatic imaging with projection-based material decomposition algorithm for metal artifacts reduction in photon-counting detector computed tomography

Abstract

Metal artifacts present a major challenge to computed tomography (CT) because they reduce the image quality in medical diagnosis and treatment. Several metal artifact reduction (MAR) methods have been proposed to address this issue in previous studies. This study aimed to synthesize a virtual monochromatic image for MAR in CT images using projection-based material decomposition (MD) algorithms. We developed a spectral micro-CT prototype system equipped with a photon-counting detector (PCD) and PCD-CT imaging simulator to assess the performances of different MAR methods. Two projection-based MD algorithms were implemented and evaluated for their MAR performances in CT images and compared with conventional sinogram inpainting MAR methods. Different parts of digital 4D-extended cardiac torso (XCAT) phantoms with metal implants were designed to simulate various real scenarios. A homemade metal artifact evaluation (MAE) phantom was used to evaluate the MAR performance in experiments. The simulated results of the XCAT phantom indicated that the projection-based virtual monochromatic CT (VMCT) images provided better image quality than the conventional MAR images without blurring the normal tissues at the position of the metal artifacts. Various quantitative indicators support this conclusion. Additionally, the experimental results of the MAE phantom reveal that projection-based VMCT images can avoid image distortion caused by metal artifacts, unlike conventional MAR methods. In regards to the projection-based VMCT images, the simulated and experimental results demonstrated that using the linear maximum likelihood estimators with an error correction look-up table algorithm yielded better MAR performance compared to that obtained using a polynomial algorithm. Furthermore, projection-based VMCT images can not only reduce metal artifacts effectively but also simultaneously prevents object blurring at the metal artifact position and image distortion of the metal implants. Hence, the CT image quality can be further improved to increase the abilities for both preoperative and postoperative assessment of metal implants.

The impact of metal implants on the dose and clinical outcome of radiotherapy (Review)

“…There are also commercially available techniques to minimize metal artifacts such as iterative metal artifact reduction (IMAR; Siemens Healthineers) ( 48 ), O-MAR (Philips Medical Systems, Inc.) ( 49 ), single-energy metal artifact reduction (SEMAR; Toshiba Medical Systems; Canon Medical Systems) ( 50 ), and smart metal artifact reduction (Smart MAR (General Electric Healthcare) ( 51 , 52 ). The technique based on projection data and image-based metal segmentation method was used recently, and VM imaging with projection-based material decomposition algorithm can not only reduce metal artifacts effectively, but also simultaneously prevent object blurring at the metal artifact position and image distortion of the metal implants ( 53 , 54 ). Ceccarelli et al ( 55 ) considered that combining information from virtual monoenergetic reconstructions and MAR software images could be the best way to solve the issue of metal artifacts on CT images.…”

Photon-counting detector CT – first experiences in the field of musculoskeletal radiology

“…The first phantom-based studies on a PCD-CT scanner assessed the value of IMAR [78], tin filtration [79], VMI [80], projectionbased material decomposition [81,82,83], as well as the combination of IMAR and VMI [84,85].…”