Abstract
Background
The increasing use of metal internal fixation devices has heightened clinical concerns about peri-implant complications, such as osteoporosis, fracture risk, and hardware loosening. Quantitative computed tomography (QCT) is employed for the quantitative assessment of bone mineral density (BMD) at specific anatomical sites in clinical settings, while conventional CT is used to visualize the structures surrounding the implant. However, significant metal artifacts present in the images can impede the observation and diagnosis of adjacent bone structures. This study systematically evaluates the combined use of orthopedic metal artifact reduction (O-MAR) algorithms and virtual monoenergetic imaging (VMI) to improve image quality and the accuracy of BMD measurements within QCT protocols.
Methods
Three metal screws were inserted into each of five porcine femoral specimens, followed by dual-layer spectral detector CT scanning. Reconstructed images were divided into five groups: conventional imaging (CI), O-MAR, VMI, VMI + O-MAR, and CI images after metal implant removal (CI*). Quantitative analysis was conducted by recording attenuation (HU), calculating the signal-to-noise ratio (SNR) and artifact index (AI) of cancellous bone, and measuring BMD via QCT.
Results
Significant differences in HU, SNR, and AI were observed among metal artifact reduction methods. The CI group demonstrated the highest attenuation and SNR (P < 0.05 vs. other groups), while VMI and VMI + O-MAR showed reduced HU values and the lowest SNR (P < 0.05). Both VMI groups exhibited superior artifact reduction (lower AI) compared to other groups. QCT indicated that BMD measurements were lower in the VMI groups compared to the CI or CI* groups (P < 0.05), though O-MAR maintained BMD accuracy comparable to CI*.
Conclusion
O-MAR and VMI effectively reduced metal artifacts, although excessive suppression of artifacts by high-energy VMI may compromise bone quality assessment. The standalone application of O-MAR may facilitate more accurate BMD quantification.
Keywords: Quantitative computed tomography, Bone mineral density, Orthopedic metal artifact reduction, Virtual monoenergetic images
Introduction
Joint replacement surgery and metallic implant fixation are commonly utilized in middle-aged and elderly populations to address conditions such as femoral head necrosis, advanced degenerative osteoarthritis, and traumatic fractures. These interventions, however, are associated with several complications, including implant failure, periprosthetic infections, and aseptic loosening. Extended periods of postoperative immobilization can lead to disuse osteoporosis, thereby increasing the risk of fractures in adjacent anatomical regions [1, 2]. Therefore, a thorough assessment of bone quality and cancellous bone mineral density (BMD) at the implant-bone interface is clinically essential.
Computed tomography (CT) is the primary imaging modality utilized in joint arthroplasty and internal fracture fixation for both preoperative planning and postoperative assessment. This imaging technique is particularly effective for evaluating peri-implant osseous structures, often outperforming other imaging methods. Quantitative computed tomography (QCT), which employs calibrated phantom measurements, facilitates accurate quantification of site-specific BMD [3, 4]. Nevertheless, the presence of metallic implants can lead to significant streak artifacts, which undermine diagnostic accuracy and reduce the reliability of BMD measurements. Conventional CT reconstruction algorithms demonstrate limited efficacy in evaluating metal-bone interfaces [5, 6]. The generation of metallic artifacts is primarily attributed to two physical processes: (1) the preferential absorption of low-energy photons, known as beam hardening, and (2) inadequate photon flux penetration, referred to as photon starvation. These phenomena collectively produce hypodense and hyperdense banding artifacts surrounding materials with high atomic numbers [7, 8]. Specifically, beam hardening, characterized by the energy-dependent attenuation of polychromatic X-rays as they traverse high atomic number materials, results in pronounced alternating hypodense and hyperdense streaks along the horizontal axis of implants [5, 9–11].
Current artifact mitigation strategies employ multi-parametric approaches. Elevated tube potential (kVp) and current (mAs) settings enhance photon penetration while exacerbating patient radiation exposure [7]. Collimation optimization, spectral filtration, and iterative calibration algorithms demonstrate partial artifact reduction [6]. The orthopedic metal artifact reduction (O-MAR) algorithm, clinically validated since 2012, employs projection data segmentation and inpainting techniques to correct photon-deficient projections without dose escalation [12]. This computational approach specifically addresses primary artifacts by rectifying corrupted data in the sinogram space [11, 13, 14]. Dual-energy CT (DECT) represents an advanced imaging paradigm utilizing dual-spectral acquisition to generate virtual monochromatic images (VMIs). By optimizing energy-specific attenuation coefficients, VMIs at high energy levels effectively minimize beam hardening artifacts while preserving tissue contrast [15–18]. Emerging evidence suggests synergistic artifact reduction when combining VMI with projection-based correction algorithms, particularly in cardiac device and spinal implant imaging [19–21]. Nevertheless, the combined efficacy of O-MAR and VMI for improving BMD measurement accuracy in peri-implant bone regions remains unexplored.
This prospective study aims to: (1) Quantitatively evaluate the individual and combined effects of O-MAR and VMI on BMD measurement accuracy in metallic artifact environments; (2) Assess their differential impacts on objective image quality parameters; (3) Establish an optimized protocol for metal artifact mitigation during bone density assessments.
Materials and methods
This experimental study utilized animal specimens obtained from a private farm, which were reviewed and approved by the Animal Ethics Committee of the Third Hospital of Hebei Medical University, in accordance with the guidelines established by the Chinese Animal Protection Committee.
Selection of the subject model
Five intact mature porcine femurs with fresh tissue preservation were selected for analysis. Pre-experimental CT scans confirmed absence of pathological lesions. The soft tissue attachments were surgically removed while preserving cortical integrity. The mean femoral shaft length measured 21.6 cm (range: 20.8–22.3). Specimens were aligned in the supine decubitus position with their longitudinal axes parallel to the scanner bed, femoral head oriented to the left. Three pure titanium surgical screws, measuring 5.0 mm in diameter and 80 mm in length, were inserted from the lateral side: one in the proximal metaphyseal region and two in the distal diaphysis(Fig. 1).
Fig. 1.
Flow chart of image acquisition and data measurement
Image acquisition and reconstruction
All CT examinations were performed using a dual-layer spectral detector CT system (IQon, Philips Healthcare), with the scanning range encompassing the entire specimen. Scanning parameters included: 120 kVp tube voltage, 250 effective mAs, 1.0 mm slice thickness, and 512 × 512 acquisition matrix. A field of view (FOV) of 215 × 215 mm² was maintained.
Conventional images (CI) were reconstructed using an iterative reconstruction algorithm (iDose⁴, level 3; Philips Healthcare), consistent with standard clinical protocols. Additionally, all specimen images underwent reconstruction with an orthopedic metal artifact reduction algorithm (O-MAR, Philips Healthcare). To optimize metal artifact reduction, the previously validated optimal energy level [16] was applied. Virtual monochromatic images (VMIs) were generated through a dedicated spectral reconstruction algorithm at 200 keV. Furthermore, synergistic artifact reduction was investigated by combining 200 keV VMIs with O-MAR processing. In addition to the aforementioned four reconstruction approaches, we performed CI following removal of the metal implants, designated as CI*. (Figures 2 and 3).
Fig. 2.
Axial reconstruction images demonstrating metal implants and associated artifacts (window level: 450; width: 1500). Five reconstruction images are compared: conventional iterative (CI) (A), orthopedic metal artifact reduction (O-MAR) (B), virtual monoenergetic imaging (VMI) (C), combined VMI + O-MAR (D), and post-explant CI (E). (A) demonstrates prominent hyperdense artifacts along the axial direction of the specimen. (B) shows a substantial reduction in hyperdense artifacts compared to the CI reconstruction. (C) reveals circumferential hypodense artifacts surrounding the implant. (D) successfully eliminates hyperdense artifacts, although new hypodense artifacts are observed. (E) serves as the reference-standard CI reconstruction following the removal of the metal implant
Fig. 3.
Sagittal reconstruction images demonstrating metal implants and associated artifacts (window level: 450; width: 1500). Five reconstruction images are compared: conventional iterative (CI) (A), orthopedic metal artifact reduction (O-MAR) (B), virtual monoenergetic imaging (VMI) (C), combined VMI + O-MAR (D), and post-explant CI (E). (A) demonstrates hyperdense artifacts along implant trajectory. (B) exhibits partial artifact reduction with new peripheral hyperdense striations (indicated by a thin arrow). (C) achieves near-complete resolution of hyperdense artifacts but introduces hypodense regions (indicated by a thick arrow). (D) shows marked density reduction along the implant axis while generating new hyperdense striations at the periphery. (E) serves as the reference-standard CI reconstruction following the removal of the metal implant
Image analysis
Measurement of the image quality evaluation index
In this study, we focused specifically on hyperdense metallic artifacts. Image analysis was initiated using a dedicated post-processing workstation (IntelliSpace Portal, Philips Healthcare). Regions of interest (ROIs) were delineated within a standardized bone window (slice thickness: 1 mm; window level: 450; width: 1500) on representative axial conventional CT images. ROIs were positioned in cancellous bone adjacent to metal implant (Fig. 4), with dimensions standardized between 100 and 160 mm². These predefined ROIs were subsequently superimposed onto corresponding O-MAR, VMI, and VMI + O-MAR reconstructions using identical spatial coordinates and sizing parameters. Quantitative measurements included mean CT attenuation values (Hounsfield units, HU) and their standard deviations (SD) within each ROI. Signal-to-noise ratios (SNR) were calculated using the formula: SNR = µ/SD, where µ represents the mean HU value within the ROI. Artifact index (AI) was computed as follows: AI= 
, where 
denotes the SD of CT attenuation in metal-adjacent regions and 
represents the SD in artifact-free reference areas.
Fig. 4.
Schematic representation of peri-implant CT attenuation and associated SD in metal implant (window level: 450; width: 1500). Conventional Iterative (CI) (A), orthopedic metal artifact reduction (O-MAR) (B), virtual monoenergetic imaging (VMI) (C), combined VMI + O-MAR (D). CT attenuation and SD values were measured within manually delineated ROIs on each image. These ROIs were then consistently transferred to the analogous sections of other reconstructed series, ensuring uniformity in the background area
Measurement of cancellous bone mineral density
BMD quantification was conducted using a dedicated QCT postprocessing workstation (QCT PRO version 6.1, Mindways Software). For sagittal plane BMD measurements (Fig. 5A), three ROIs (diameter: 7 mm, cross-sectional area: 38.4 mm², height: 7 mm) were positioned at 3.5 mm, 7 mm, and 10.5 mm from the metal implant periphery, demonstrating mean BMD values within corresponding anatomical regions. These measurements were systematically implemented across three reconstruction protocols: CI, O-MAR, and CI*.
Fig. 5.
Schematic diagram of BMD measurement based on QCT (window level: 450; width: 1500). A. In the sagittal plane of the specimen, ROIs were delineated, with their centers (denoted by the red line) positioned at distances of 3.5 mm, 7 mm, and 10.5 mm from the edge of the implant. B, C. The ROI was delineated in the axial plane of the specimen, with the ROI positioned at 0 mm, 7 mm, and 14 mm from the implant’s edge, respectively
Subsequent axial plane BMD quantification (Fig. 5B-C) focused on the most artifact-prominent level. ROIs (diameter: 7 mm, cross-sectional area: 38.4 mm², height: 3 mm) were positioned at 0 mm, 7 mm, and 14 mm from the implant periphery while avoiding adjacent hyperdense streak artifacts. These measurements were systematically implemented across three reconstruction protocols: CI, O-MAR, VMI, O-MAR + VMI, and CI*. To ensure measurement validity, cortical bone and gas-density shadows were excluded from all ROIs.
Statistical analysis
Statistical analysis were performed using SPSS 25.0. Normality of data was evaluated using the Kolmogorov-Smirnov test, with normally distributed quantitative variables expressed as mean ± standard deviation (SD) and non-normally distributed variables reported as median with interquartile range (IQR). Interobserver agreement for sagittal bone mineral density (BMD) measurements was quantified through intraclass correlation coefficient (ICC), categorized as < 0.40 (poor), 0.40–0.74 (good), or ≥ 0.75 (excellent). Group comparisons employed paired t-tests for BMD analysis and two-tailed Kruskal-Wallis tests for evaluating CT values, SD, SNR, and AI. Statistical significance was determined at P < 0.05.
Results
Qualitative analysis of image quality
Significant intergroup differences emerged in attenuation, SNR, and AI measurements (Table 1). ROI analysis revealed the highest median CT attenuation in the CI group (583.6; IQR 465.2-756.7). Both O-MAR and VMI, whether used alone or in combination (VMI + O-MAR), showed significantly lower median attenuation compared with CI.
Table 1.
Comparison of CT attenuation, SD, SNR and AI at different distances from the metal implant on axial images
| Trabecular bone | SNR | AI(HU) | ||
|---|---|---|---|---|
| Mean attenuation (HU) | SD value | |||
| CI | 583.6(465.2,756.7) | 140.2(87.7,174.2) | 4.29(3.45,5.53) | 142.22(83.61,173.41) |
| O-MAR | 253.2(207.9,447.4) | 125.0(96.5,169.2) | 2.23(1.35,4.31) | 105.68(88.43,156.68) |
| VMI | 52.7(18.0,145.5) | 98.4(75.5,124.1) | 0.46(0.18,1.43) | 85.96(69.59,125.64) |
| VMI + O-MAR | 54.5(−114.2,95.8) | 113.2(67.4,121.3) | 0.71(−1.69,0.95) | 75.41(55.53,97.50) |
| p value | <0.001 | 0.157 | <0.001 | 0.023 |
| CI vs. O-MAR | 0.035 | N/A | 0.047 | 0.681 |
| CI vs. VMI | <0.001 | N/A | <0.001 | 0.090 |
| CI vs. VMI + O-MAR | <0.001 | N/A | <0.001 | 0.006 |
| O-MAR vs. VMI | 0.003 | N/A | 0.007 | 0.187 |
| O-MAR vs. VMI + O-MAR | <0.001 | N/A | 0.001 | 0.019 |
| VMI vs. VMI + O-MAR | 0.601 | N/A | 0.623 | 0.411 |
CI conventional iterative reconstruction, O-MAR orthopedic metal artifact reduction, VMI virtual monoenergetic imaging, VMI+O-MAR combined VMI and O-MAR
In SNR comparisons, the CI group exhibited the highest value (4.29; IQR 3.45–5.53), whereas VMI and VMI + O-MAR groups displayed the lowest values. Regarding AI quantification, VMI (85.96; IQR 69.59-125.64) and VMI + O-MAR (75.41; IQR 55.53–97.50) demonstrated optimal artifact reduction, though differences between CI and O-MAR alone failed to reach statistical significance. Notably, trabecular bone structural analysis revealed no significant intergroup variation in SD measurements.
Reliability of the BMD measurements
Quantitative analysis demonstrated excellent intrarater reliability for sagittal plane BMD measurements adjacent to the metal implant (intraclass correlation coefficient [ICC] range: 0.945–0.966), with all values exceeding the threshold for excellent reliability (ICC > 0.75). The composite BMD assessment on sagittal imaging achieved an ICC of 0.953 (Table 2), collectively indicating high measurement consistency across all evaluated periprosthetic regions.
Table 2.
Repeatability analysis of BMD values on sagittal images (mg/cm3, x ± s)
| Distance(mm) | BMD1(mg/cm3, x ± s) | BMD2(mg/cm3, x ± s) | ICC | 95%confidence interval |
|---|---|---|---|---|
| 3.5 | 220.90 ± 204.57 | 218.56 ± 202.03 | 0.945 | (0.918,0.964) |
| 7 | 228.03 ± 163.89 | 229.77 ± 163.13 | 0.952 | (0.927,0.968) |
| 10.5 | 261.74 ± 158.08 | 261.96 ± 160.71 | 0.966 | (0.949.0.978) |
| Total | 236.89 ± 176.97 | 236.76 ± 176.61 | 0.953 | (0.941,0.963) |
Distance:the distance between the area of interest and the metal implant
Quantitative analysis of BMD
Sagittal image analysis revealed no significant BMD differences between the CI and O-MAR groups, nor between O-MAR and CI* groups at distances of 3.5 mm, 7 mm and 10.5 mm (all P < 0.05; Table 3). The BMD analysis results at the axis level are shown in Fig. 6. At distances of 0 mm, 7 mm, and 14 mm, the BMD values for the VMI, O-MAR, VMI + O-MAR and CI* groups significantly decreased compared to those of the CI group. We defined the BMD values of CI* as the gold standard, and no significant difference was observed between the BMD values of CI* and O-MAR groups. Compared to CI*, both VMI and VMI + O-MAR groups showed significant BMD decreases. While VMI and VMI + O-MAR exhibited comparable BMD values at 0 mm (P > 0.05), VMI + O-MAR demonstrated significantly lower BMD than VMI alone at 7 mm and 14 mm distances. Notably, CI + O-MAR maintained equivalent BMD measurements to CI* across all measured distances (0, 7, and 14 mm; P > 0.05).
Table 3.
Comparison of BMD at different distances from the metal implant on sagittal images (mg/cm3, x ± s)
| Distance | 3.5 mm | 7 mm | 10.5 mm |
|---|---|---|---|
| CI | 83.082 ± 101.22 | 60.897 ± 89.44 | 39.98 ± 90.20 |
| O-MAR | 88.256 ± 96.90 | 66.577 ± 86.74 | 45.95 ± 90.60 |
| CI* | 96.868 ± 100.23 | 68.18 ± 89.32 | 44.67 ± 89.52 |
CI conventional iterative reconstruction, O-MAR orthopedic metal artifact reduction, CI* CI after removing the metal
*Significant difference compared to CI*. #Significant difference compared to CIDistance: the distance between the area of interest and the metal implant
Fig. 6.
Comparison of the BMD at different distances from the metal implant on axial plane (mg/cm3, x ± s) *There was a significant difference between the two groups CI: conventional iterative reconstruction. O-MAR: orthopedic metal artifact reduction. VMI: virtual monoenergetic imaging. VMI + O-MAR: combined VMI and O-MAR. CI*: CI after removing the metal
Discussion
This study assessed the impact of O-MAR and VMI on BMD quantification using QCT, as well as their respective effects on artifact reduction. Quantitative analysis indicated that O-MAR, VMI, and their combination yielded lower BMD values around metal implants compared to CI protocols. Notably, O-MAR reconstruction exhibited superior accuracy, with BMD measurements closely aligning with baseline values. The AI quantification demonstrated that both VMI and the combined VMI + O-MAR reconstructions achieved statistically significant reductions in metal artifacts, with the greatest artifact suppression observed in the combined approach. These findings are consistent with those of previous studies [19–22].
CT attenuation values, SNR, and AI were quantified to assess image quality and the severity of metal artifacts. Our findings demonstrate that various metal artifact reduction reconstruction methods exhibit efficacy in artifact suppression to varying degrees and enhance the visualization of peri-implant structures. The SNR, which reflects the ratio of signal to noise within images, is generally associated with lower noise levels and improved image quality. The results revealed no significant differences in image noise among the four experimental groups. Considering that this study addresses hyperdense artifacts, which are known to elevate CT values in adjacent regions, the reduction of CT values following the application of metal artifact reduction techniques will inevitably result in a corresponding decrease in SNR.
The results demonstrate that compared to the CI group, the O-MAR group exhibited a slight reduction in CT attenuation values, while the application of VMI and its combination with O-MAR led to a significant decrease in trabecular bone attenuation values. Furthermore, the AI for VMI and VMI + O-MAR was the lowest among the four groups. These findings suggest that while both VMI and VMI + O-MAR are effective in reducing metal artifact interference, the substantial attenuation reduction caused by VMI in peri-implant regions may adversely affect the assessment of bone quality surrounding metallic prostheses. A study on total hip arthroplasty patients reported that VMI was superior for osseous evaluation, which contrasts with our findings. We attribute this discrepancy to variations in energy levels, as the VMI in the present study was set at the highest energy level [23]. Osteolysis occurs as an immune response, wherein macrophages accumulate and release cytokines with osteolytic effects, leading to localized bone resorption around the prosthesis [24]. While VMI and its combination with MAR techniques may facilitate early assessment of periprosthetic bone loss in clinical practice, the specific energy level settings warrant further investigation.
The findings of this study revealed no significant differences in BMD measured along the sagittal plane adjacent to metal implants across the experimental groups. Analysis of the raw images demonstrated that artifacts predominantly distributed along the horizontal axial direction of specimens, without affecting trabecular bone density above or below the metal implants. These observations are consistent with the principle of photon starvation effect, which posits that artifacts preferentially occur along the direction of maximum attenuation [9]. Previous studies have confirmed that regions superior to hip prostheses remain unaffected by metal artifacts, with no artifacts oriented along the longitudinal plane generated by the prostheses [25, 26]. Although different types of implants were used in these studies, their findings partially support our results. This evidence suggests the potential for accurate BMD measurements to be conducted directly along the longitudinal axis of metal implants.
In axial specimen sections, all experimental groups employing metal artifact reduction techniques exhibited significantly lower BMD values compared to the CI group. Notably, the groups utilizing VMI and VMI + O-MAR demonstrated substantially reduced BMD measurements relative to the CI* group. In contrast, the O-MAR group alone did not show a significant difference in BMD values compared to CI*. This indicates that the standalone application of O-MAR may facilitate more accurate BMD quantification, closely approximating true physiological values. Given the fixed VMI energy level of 200 keV used in this study, our results imply that high-energy VMI may not be the optimal configuration for precise quantification of trabecular bone BMD.
Bodén et al. conducted a longitudinal follow-up study involving 14 patients who underwent total hip arthroplasty (THA), with a follow-up period extending over 10 years. The study utilized dual-energy X-ray absorptiometry (DXA) to assess BMD, revealing the most pronounced BMD loss in Gruen zones 1 and 7 during the first two postoperative years [27]. A related investigation similarly reported significant BMD reduction in Gruen zone 7 among THA patients, irrespective of the prosthesis material used [28]. Both studies share methodological similarities, notably the use of DXA for BMD assessment and the observation of marked BMD reduction in Gruen zone 7, a proximal femoral region prone to metal artifacts. As a planar imaging modality, DXA is limited in its ability to distinguish between cortical and trabecular bone and is insufficient for visualizing postoperative BMD reduction in the posterior acetabular region and periprosthetic bone resorption [29, 30]. The limitations of CT in post-implant BMD quantification are primarily due to artifacts surrounding metal implant, which can adversely affect measurement accuracy. Despite the use of ex vivo animal specimens in this study, the findings indicate that O-MAR has the potential to enhance the clinical utility of CT in assessing periprosthetic BMD. This advancement may contribute to improved planning of revision surgeries, the refinement of therapeutic strategies, and the evaluation of the effects of prosthesis materials, positioning, and surgical techniques on periprosthetic BMD.
The CT attenuation values and BMD measurements derived from VMI and its combination with O-MAR were significantly lower than the reference standard. This discrepancy may be attributable to two principal factors. Firstly, VMI primarily mitigates beam hardening artifacts, and previous studies have confirmed that higher VMI energy levels more effectively suppress such artifacts [15, 16, 22, 31, 32]. The 200 keV energy level employed in this study substantially reduced metal artifact interference. Secondly, a strip-shaped hypodense area surrounding the screw (indicated by thick arrows in Fig. 3) was observed, consistent with findings from previous investigations [17, 31]. Future research should aim to refine the grading system to identify a reconstruction method that produces BMD measurements more closely aligned with the reference standard than those obtained using O-MAR alone.
Limitation
This study is subject to several limitations. Firstly, the small sample size may have introduced bias into the results. Secondly, the investigation was restricted to a single type of metal implant, without consideration of the effects of variations in composition, size, implant location, or orientation. Thirdly, as the study was conducted on animal models, the generalizability of the findings to human subjects is uncertain. Lastly, although the VMI can enhance image quality, it may also introduce biases in quantitative BMD measurements due to variations in CT attenuation. Further research is warranted to explore whether modifications to the energy level of VMI can achieve both enhanced image quality and more accurate quantitative BMD assessments.
Conclusion
In conclusion, the application of O-MAR, VMI, and their combined use demonstrates efficacy in reducing metal artifacts. However, it is noteworthy that high-energy VMI might lead to excessive artifact suppression, potentially hindering the assessment of nearby osseous structures. The longitudinal absence of metal artifacts indicates unaffected BMD measurements in this orientation. Moreover, the use of O-MAR reconstruction independently improves the precision of BMD assessments in the axial plane adjacent to metal implant.
Acknowledgements
This work was supported by Clinical Science, Philips Healthcare, and we acknowledge the technical support from them.
Authors’ contributions
R.Z. and S.D. designed the research study and wrote the manuscript. B.L. and Y.W. participated in the data collection and analysis. Z.H. and Y.Y participated in the data collection. P.Z and J.Z. provided experimental guidance during the study and revised the paper critically. All authors read and approved the final manuscript.
Funding
The study did not receive any specific funding from funding agencies in the public, commercial or non-profit sectors.
Data availability
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
All animal samples were purchased from private farms. The purpose of sample usage was disclosed to the suppliers, and their informed consent was obtained. The procurement and use of these samples have been examined and approved by the Animal Ethics Committee of the Third Hospital of Hebei Medical University in compliance with the guidelines of the Chinese Animal Protection Committee for the use of animals. All methods of this test were performed in accordance with the relevant guidelines and regulations.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Jian Zhao, Email: 37400408@hebmu.edu.cn.
Ping Zhang, Email: 38500364@hebmu.edu.cn.
References
- 1.Rolvien T, Amling M. Disuse Osteoporosis: Clinical and Mechanistic Insights. Calcified Tissue Int; 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Lau RY, Guo X. A review on current osteoporosis research: with special focus on disuse bone loss. J Osteoporos. 2011;2011:293808. [DOI] [PMC free article] [PubMed]
- 3.Mao SS, Li D, Luo YT, Syed YS, Budoff MJ. Application of quantitative computed tomography for assessment of trabecular bone mineral density, microarchitecture and mechanical property. Clin Imag. 2016;40:330–8. [DOI] [PubMed] [Google Scholar]
- 4.Carey JJ, Buehring B. Current imaging techniques in osteoporosis. Clin Exp Rheumatol. 2018;36:115–26. [PubMed] [Google Scholar]
- 5.Boas FE, Fleischmann D. CT artifacts: causes and reduction techniques. Imag Med. 2012;4:229–40. [Google Scholar]
- 6.Lee MJ, Kim SJ, Lee SA, Song HT, Huh YM, Kim DH, Han SH, Suh JS. Overcoming artifacts from metallic orthopedic implants at high-field-strength MR imaging and multidetector CT. Radiographics. 2007;27:791–803. [DOI] [PubMed] [Google Scholar]
- 7.Barrett JF, Keat N. Artifacts in CT: recognition and avoidance. Radiographics. 2004;24:1679–91. [DOI] [PubMed] [Google Scholar]
- 8.Man BD, DuPont P, Marchal G. Metal streak artifacts in X-ray computed tomography: a simulation study. IEEE Trans Nucl Sci. 1999;46:691. [Google Scholar]
- 9.Katsura M, Sato J, Akahane M, Kunimatsu A, Abe O. Current and novel techniques for metal artifact reduction at CT: practical guide for radiologists. Radiographics. 2018;38:450–61. [DOI] [PubMed] [Google Scholar]
- 10.Mori I, Machida Y, Osanai M, Linuma K. Photon starvation artifacts of X-ray CT: their true cause and a solution. Radiol Phys Technol. 2013;6:130–41. [DOI] [PubMed] [Google Scholar]
- 11.Wellenberg RH, Hakvoort ET, Slump CH, Boomsma MF, Maas M, Streekstra GJ. Metal artifact reduction techniques in musculoskeletal CT-imaging. Eur J Radiol. 2018;107:60–9. [DOI] [PubMed] [Google Scholar]
- 12.Li H, Noel C, Chen H, Li HH, Low D, Moore K, Klahr P, Michalski J, Gay HA, Thorstad W, Mutic S. Clinical evaluation of a commercial orthopedic metal artifact reduction tool for CT simulations in radiation therapy. Med Phys. 2012;39:7507–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Kidoh M, Utsunomiya D, Oda S, Nakaura T, Funama Y, Yuki H, Hirata K, Hatemura M, Namimoto T, Yamashita Y. CT venography after knee replacement surgery: comparison of dual-energy CT-based monochromatic imaging and single-energy metal artifact reduction techniques on a 320-row CT scanner. Acta Radiol Open. 2017;6:1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Woo H, Chai JW, Choi YH, Jin KN. Metal artifact reduction for orthopedic prosthesis in lower extremity CT venography: evaluation of image quality and vessel conspicuity. Cardiovasc Intervent Radiol. 2019;42:1619–26. [DOI] [PubMed] [Google Scholar]
- 15.Laukamp KR, Hokamp NG, Alabar O, Obmann vc, Lennartz S, Zopfs D, Gilkeson R, Ramaiya N, Gupta A. Metal artifacts from sternal wires: evaluation of virtual monoenergetic images from spectral-detector CT for artifact reduction. Clin Imag. 2020;60:249–56. [DOI] [PubMed] [Google Scholar]
- 16.Kosmas C, Hojjati M, Young PC, Abedi A, Gholamrezanezhad A, Rajiah P. Dual-layer spectral computerized tomography for metal artifact reduction: small versus large orthopedic devices. Skeletal Radiol. 2019;48:1981–90. [DOI] [PubMed] [Google Scholar]
- 17.Yoo HJ, Hong SH, Chung BM, Moon SJ, Choi JY, Chae HD, Chang MY. Metal artifact reduction in virtual monoenergetic spectral Dual-Energy CT of patients with metallic orthopedic implants in the distal radius. Am J Roentgenol. 2018;211:1083–91. [DOI] [PubMed] [Google Scholar]
- 18.Filograna L, Magarelli N, Leone A, Waure CD, Calabro GE, Finkenstaedt T, Thali MJ, Bonomo L. Performances of low-dose dual-energy CT in reducing artifacts from implanted metallic orthopedic devices. Skeletal Radiol. 2016;45:937–47. [DOI] [PubMed] [Google Scholar]
- 19.Hokamp NG, Neuhaus V, Abdullayev N, Laukamp K, Lennartz S, Mpotsaris A, Borggrefe J. Reduction of artifacts caused by orthopedic hardware in the spine in spectral detector CT examinations using virtual monoenergetic image reconstructions and metal-artifact-reduction algorithms. Skeletal Radiol. 2018;47:195–201. [DOI] [PubMed] [Google Scholar]
- 20.Pennig L, Zopfs D, Gertz R, Bremm J, Zaeske C, Hokamp NG, Celik E, Goertz L, Langenbach M, Persigehl T, Gupta A, Borggrefe J, Lennartz S, Laukamp KR. Reduction of CT artifacts from cardiac implantable electronic devices using a combination of virtual monoenergetic images and post-processing algorithms. Eur Radiol. 2021;31:7151–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Neuhaus V, Hokamp NG, Zopfs D, Laukamp K, Lennartz S, Abdullayev N, Maintz D, Borggrefe J. Reducing artifacts from total hip replacements in dual layer detector CT: combination of virtual monoenergetic images and orthopedic metal artifact reduction. Eur J Radiol. 2019;111:14–20. [DOI] [PubMed] [Google Scholar]
- 22.Chae HD, Hong SH, Shin M, Choi JY, Yoo HJ. Combined use of virtual monochromatic images and projection-based metal artifact reduction methods in evaluation of total knee arthroplasty. Eur Radiol. 2020;30:5298–307. [DOI] [PubMed] [Google Scholar]
- 23.Laukamp KR, Lennartz S, Neuhaus VF, Hokamp NG, Rau R, Blanc ML, Abdullayev N, Mpotsaris A, Maintz D, Borggrefe J. CT metal artifacts in patients with total hip replacements: for artifact reduction monoenergetic reconstructions and post-processing algorithms are both efficient but not similar. Eur Radiol. 2018;28:4524–33. [DOI] [PubMed] [Google Scholar]
- 24.Goodman SB, Gallo J. Periprosthetic osteolysis: mechanisms, prevention and treatment. J Clin Med. 2019;8:2091. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Boomsma MF, Slouwerhof I, Dalen JA, Edens MA, Mueller D, Milles J, Maas M. Use of internal references for assessing CT density measurements of the pelvis as replacement for use of an external Phantom. Skeletal Radiol. 2015;44:1597–602. [DOI] [PubMed] [Google Scholar]
- 26.Boomsma MF, Slouwerhof I, Lingen CV, Pakvis FM, Dalen JA, Edens MA, Ettema HB, Verheyen C. CT-based quantification of bone stock in large head metal-on-metal unilateral total hip replacements. Eur J Radiol. 2016;85:760–3. [DOI] [PubMed] [Google Scholar]
- 27.Bodén HS, Sköldenberg OG, Salemyr MO, Lundberg HJ, Adolphson PY. Continuous bone loss around a tapered unce-mented femoral stem: a long-term evaluation with DEXA. Acta Orthop. 2006;77(6):877–85. [DOI] [PubMed] [Google Scholar]
- 28.Tapaninen T, Kröger H, Venesmaa P. Periprosthetic BMD after cemented and uncemented total hip arthroplasty: a 10-year follow-up study. J Orthop Sci. 2015;20:657–62. [DOI] [PubMed] [Google Scholar]
- 29.Zingler K, Haeberle L, Kress A, Holzwarth U, Forst R, Mueller LA, Schmidt R. Comparison of cortical and cancellous bone remodeling of the pelvis after press-fit cup total hip arthroplasty dependent on patient and prosthesis-specific characteristics: a computed tomography-assisted osteodensitometry study in vivo. Biomed Tech (Berl). 2011;56:267–75. [DOI] [PubMed] [Google Scholar]
- 30.Robertson TS, Pijls BG, Munn Z, Solomon LB, Nelissen RG, Callary SA. Change in CT-measured acetabular bone density following total hip arthroplasty: a systematic review and meta-analysis. Acta Orthop. 2023;94:191–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Lewis M, Reid K, Toms AP. Reducing the effects of metal artifact using high KeV monoenergetic reconstruction of dual energy CT (DECT) in hip replacements. Skeletal Radiol. 2012;42:275–82. [DOI] [PubMed] [Google Scholar]
- 32.Kuchenbecker S, Faby S, Sawall S, Lell M, Kachelrieb M. Dual energy CT: how well can Pseudomonochromatic imaging reduce metal artifacts? Med Phys. 2015;42:1023–36. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.