Improvement of image quality and diagnostic confidence using Smart MAR – a projection-based CT protocol in patients with orthopedic metallic implants in hip, spine, and shoulder

Abstract

Background In computed tomography (CT) scans, artifacts caused by metallic orthopedic implants still hamper the visualization of important, periprosthetic tissues. Smart MAR metal artifact reduction tool is a promising three-stage, projection-based, post-processing algorithm. Purpose To determine whether the Smart MAR tool improves subjective and objective image quality and diagnostic confidence in patients with orthopedic implants of the hip, spine, and shoulder. Material and Methods Seventy-two patients with orthopedic screws, hip/shoulder replacement, or spine spondylodesis were included. CT scans were performed on a single-source multislice CT scanner, raw data were post-processed using Smart MAR. Image quality was evaluated both quantitatively (ROI-based) and qualitatively (rater-based) and compared to iterative reconstructions (ASIR V). As comparative standard for artificial prosthetic breaks or loosening, follow-up examinations were used. Results Smart MAR reconstructions of the hip (n = 23), spine (n = 26), and shoulder (n = 23) showed a significantly reduced attenuation and noise of regions adjacent to metallic implants ( P<0.002). Subjective image quality ( P<0.005, shoulder P = 0.038/ P = 0.046) and overall diagnostic confidence were higher in Smart MAR (all regions P<0.002). Signal-to-noise ratio (SNR; P = 0.72/ P = 0.96) was not improved. Compared to standard ASIR V new, artificial metal extinctions (up to 50%) or periprosthetic hem lines (48%–73%) were introduced by Smart MAR. Conclusion Smart MAR improved image quality of the hip, spine, and shoulder CT scans resulting in higher diagnostic confidence in evaluation of periprosthetic soft tissues. As shown for spine implants, it should be used with caution and as a complementary tool for evaluation of periprosthetic loosening or integrity of metal implant, as in many cases it introduced new artifacts.

Metal artifact reduction on musculoskeletal CT: a phantom and clinical study

“…Several studies [ 7 , 9 , 12 , 13 , 15 ] investigating metal artifact reduction report that Siemens iMAR and Canon SEMAR decreases both mean HU and SD in areas affected by metal artifacts, during the interpolation process when reconstructing images, which was also the case for the measurements in soft tissue in the present study. However, as shown by the results of the VIA, lower SD does not necessarily lead to higher visual scores.…”

“…In this study (Table 2 ), the mean dose levels (CTDI vol ) were lower for spine compared to those reported by Feldhaus et al with 11.3 ± 3.0 mGy [ 12 ] and for sacroiliac joint compared to those reported by Selles et al with 20.05 ± 9.99 mGy [ 21 ]. These studies were conducted with different protocols and equipment from other vendors, so any direct comparison is not possible.…”

“…For the visual image assessment (VIA) of the clinical images, all the images were anonymized, randomized, and presented to three observers; two radiologists (readers 1 and 2) and one orthopedic surgeon (reader 3), all with more than 15 years of clinical experience. The VIA consisted of the following criteria that radiologists use to evaluate typical patient cases [ 12 ]: (1) qualitative noise; (2) visualization of the metal implant; (3) visualization of periprosthetic cortical bone; (4) visualization of periprosthetic soft tissue; (5) extent of artifacts; and (6) diagnostic confidence. Likert scale scores from 0 to 5 with 5 being the highest possible score per each criteria indicating a perfect image in relation to the specific criteria, such as no noise (criterion 1) or no artifacts (criterion 5).…”

“…Likert scale scores from 0 to 5 with 5 being the highest possible score per each criteria indicating a perfect image in relation to the specific criteria, such as no noise (criterion 1) or no artifacts (criterion 5). Scale criteria 2, 3, and 4 focused on the visualization of metal itself and the tissue in close proximity [ 7 , 12 , 13 ]. Scoring was performed using Sectra PACS.…”

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.…”