Reduction of metal artifacts from knee tumor prostheses on CT images: value of the single energy metal artifact reduction (SEMAR) algorithm

Abstract

Background To evaluate the effect of the single energy metal artifact reduction (SEMAR) algorithm with a multidetector CT (MDCT) for knee tumor prostheses. Methods First, a phantom of knee tumor prosthesis underwent a MDCT scan. The raw data was reconstructed by iterative reconstruction (IR) alone and IR plus SEMAR. The mean value of the CT number and the image noise were measured around the prosthesis at the stem level and articular level. Second, 95 consecutive patients with knee tumor prostheses underwent MDCT scans. The raw data were also reconstructed by the two methods. Periprosthetic structures were selected at the similar two levels. Four radiologists visually graded the image quality on a scale from 0 to 5. Additionally, the readers also assessed the presence of prosthetic complication and tumor recurrence on a same scale. Results In the phantom, when the SEMAR was used, the CT numbers were closer to normal value and the noise of images using soft and sharper kernel were respectively reduced by up to 77.1% and 43.4% at the stem level, and by up to 82.2% and 64.5% at the articular level. The subjective scores increased 1 ~ 3 points and 1 ~ 4 points at the two levels, respectively. Prosthetic complications and tumor recurrence were diagnosed in 66 patients. And the SEMAR increased the diagnostic confidence of prosthetic complications and tumor recurrence (4 ~ 5 vs. 1 ~ 1.5). Conclusions The SEMAR algorithm can significantly reduce the metal artifacts and increase diagnostic confidence of prosthetic complications and tumor recurrence in patients with knee tumor prostheses.

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

“…iMAR has demonstrated its capability to reduce artifacts in various studies on most body regions, such as the spine, 3,4 the head, [4][5][6][7][8] for surgical clips, 9 the shoulder, 4 knees, 4,8 hips, 4,10 or the chest. 11,12 Other examples for clinical sinograminpainting-based MAR methods are single-energy MAR (SEMAR; Canon Medical Systems Corporation, Tustin, CA, USA) 13,14 or MAR for Orthopedic Implants (O-MAR; Philips Medical Systems, Amsterdam, Netherlands). 15,16 On the other hand, since its introduction in 2010, most recent publications on MAR in CT use NMAR 17 or its base-algorithm linear interpolation MAR (LIMAR) as their reference algorithm.…”

Nonlinearly scaled prior image‐controlled frequency split for high‐frequency metal artifact reduction in computed tomography

“…[1][2][3][4][5] Among various introduced approaches addressing MAR, sinogram inpainting has proven to be dominant in clinical routine. Examples for clinical implementations of sinogram inpainting are single-energy MAR (SEMAR, Canon Medical Systems Corporation 6,7 ), MAR for orthopedic implants (O-MAR, Philips Medical Systems 8,9 ), Smart MAR (GE Healthcare 10,11 ), and iterative MAR (iMAR, Siemens Healthcare GmbH [12][13][14] ). Sinogram inpainting addresses the correction of metal data by linearly interpolating in between metal projections in the sinogram domain.…”

Optimization of the “Perth CT” Protocol for Preoperative Planning and Postoperative Evaluation in Total Knee Arthroplasty

“…Various methods have been introduced to reduce the metal artifacts, including higher peak voltage, higher tube charge, MAR algorithms and dual-energy CT techniques [38,39]. However, higher peak voltage and tube charge may only reduce metal artifacts to a minor degree and may lead to a higher radiation dose for the patient [40]. Therefore, CT with metal artifact reduction (MAR) and dual-energy techniques are currently used to reduce the metal artifacts.…”

“…Zhang at al. [40] showed that the SEMAR algorithm plus IR can significantly reduce metal artifacts and increase diagnostic confidence of prosthetic complications and tumor recurrence in patients with knee tumor prostheses than IR alone.…”