Clinical evaluation of the normalized metal artefact reduction algorithm caused by dental fillings in CT.
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ABSTRACT:
SUBMITTER: Gong XY
PROVIDER: S-EPMC3667513 | biostudies-other | 2013
REPOSITORIES: biostudies-other
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Project description:ObjectivesThe susceptibility of CT imaging to metallic objects gives rise to strong streak artefacts and skewed information about the attenuation medium around the metallic implants. This metal-induced artefact in CT images leads to inaccurate attenuation correction in PET/CT imaging. This study investigates the potential of deep learning-based metal artefact reduction (MAR) in quantitative PET/CT imaging.MethodsDeep learning-based metal artefact reduction approaches were implemented in the image (DLI-MAR) and projection (DLP-MAR) domains. The proposed algorithms were quantitatively compared to the normalized MAR (NMAR) method using simulated and clinical studies. Eighty metal-free CT images were employed for simulation of metal artefact as well as training and evaluation of the aforementioned MAR approaches. Thirty 18F-FDG PET/CT images affected by the presence of metallic implants were retrospectively employed for clinical assessment of the MAR techniques.ResultsThe evaluation of MAR techniques on the simulation dataset demonstrated the superior performance of the DLI-MAR approach (structural similarity (SSIM) = 0.95 ± 0.2 compared to 0.94 ± 0.2 and 0.93 ± 0.3 obtained using DLP-MAR and NMAR, respectively) in minimizing metal artefacts in CT images. The presence of metallic artefacts in CT images or PET attenuation correction maps led to quantitative bias, image artefacts and under- and overestimation of scatter correction of PET images. The DLI-MAR technique led to a quantitative PET bias of 1.3 ± 3% compared to 10.5 ± 6% without MAR and 3.2 ± 0.5% achieved by NMAR.ConclusionThe DLI-MAR technique was able to reduce the adverse effects of metal artefacts on PET images through the generation of accurate attenuation maps from corrupted CT images.Key points• The presence of metallic objects, such as dental implants, gives rise to severe photon starvation, beam hardening and scattering, thus leading to adverse artefacts in reconstructed CT images. • The aim of this work is to develop and evaluate a deep learning-based MAR to improve CT-based attenuation and scatter correction in PET/CT imaging. • Deep learning-based MAR in the image (DLI-MAR) domain outperformed its counterpart implemented in the projection (DLP-MAR) domain. The DLI-MAR approach minimized the adverse impact of metal artefacts on whole-body PET images through generating accurate attenuation maps from corrupted CT images.
| S-EPMC8270868 | biostudies-literature
Project description:Metal objects in the body such as hip prostheses cause artifacts in CT images. When CT images degraded by artifacts are used for treatment planning of radiotherapy, the artifacts can yield inaccurate dose calculations and, for particle beams, erroneous penetration depths. A metal artifact reduction software (O-MAR) installed on a Philips Brilliance Big Bore CT has been tested for applications in treatment planning of proton radiotherapy. Hip prostheses mounted in a water phantom were used as test objects. Images without metal objects were acquired and used as reference data for the analysis of artifact-affected regions outside of the metal objects in both the O-MAR corrected and the uncorrected images. Water equivalent thicknesses (WET) based on proton stopping power data were calculated to quantify differences in the calculated proton beam penetration for the different image sets. The WET to a selected point of interest between the hip prostheses was calculated for several beam directions of clinical relevance. The results show that the calculated differences in WET relative to the reference case were decreased when the O-MAR algorithm was applied. WET differences up to 2.0 cm were seen in the uncorrected case while, for the O-MAR corrected case, the maximum difference was decreased to 0.4 cm. The O-MAR algorithm can significantly improve the accuracy in proton range calculations. However, there are some residual effects, and the use of proton beam directions along artifact streaks should only be used with caution and appropriate margins.
| S-EPMC5711074 | biostudies-literature
Project description:PurposeTo compare and combine dual-energy based and iterative metal artefact reduction on hip prosthesis and dental implants in CT.Material and methodsA total of 46 patients (women:50%,mean age:63±15years) with dental implants or hip prostheses (n = 30/20) were included and examined with a second-generation Dual Source Scanner. 120kV equivalent mixed-images were derived from reconstructions of the 100/Sn140kV source images using no metal artefact reduction (NOMAR) and iterative metal artefact reduction (IMAR). We then generated monoenergetic extrapolations at 130keV from source images without IMAR (DEMAR) or from source images with IMAR, (IMAR+DEMAR). The degree of metal artefact was quantified for NOMAR, IMAR, DEMAR and IMAR+DEMAR using a Fourier-based method and subjectively rated on a five point Likert scale by two independent readers.ResultsIn subjects with hip prosthesis, DEMAR and IMAR resulted in significantly reduced artefacts compared to standard reconstructions (33% vs. 56%; for DEMAR and IMAR; respectively, p<0.005), but the degree of artefact reduction was significantly higher for IMAR (all p<0.005). In contrast, in subjects with dental implants only IMAR showed a significant reduction of artefacts whereas DEMAR did not (71%, vs. 8% p<0.01 and p = 0.1; respectively). Furthermore, the combination of IMAR with DEMAR resulted in additionally reduced artefacts (Hip prosthesis: 47%, dental implants 18%; both p<0.0001).ConclusionIMAR allows for significantly higher reduction of metal artefacts caused by hip prostheses and dental implants, compared to a dual energy based method. The combination of DE-source images with IMAR and subsequent monoenergetic extrapolation provides an incremental benefit compared to both single methods.
| S-EPMC4658024 | biostudies-literature
Project description:BACKGROUND AND PURPOSE:Two techniques for metal artefact reduction for computed tomography were studied in order to identify their impact on tumour delineation in radiotherapy. MATERIALS AND METHODS:Using specially designed phantoms containing metal implants (dental, spine and hip) as well as patient images, we investigated the impact of two methods for metal artefact reduction on (A) the size and severity of metal artefacts and the accuracy of Hounsfield Unit (HU) representation, (B) the visual impact of metal artefacts on image quality and (C) delineation accuracy. A metal artefact reduction algorithm (MAR) and two types of dual energy virtual monochromatic (DECT VM) reconstructions were used separately and in combination to identify the optimal technique for each implant site. RESULTS:The artefact area and severity was reduced (by 48-76% and 58-79%, MAR and DECT VM respectively) and accurate Hounsfield-value representation was increased by 22-82%. For each energy, the observers preferred MAR over non-MAR reconstructions (p?<?0.01 for dental and hip cases, p?<?0.05 for the spine case). In addition, DECT VM was preferred for spine implants (p?<?0.01). In all cases, techniques that improved target delineation significantly (p?<?0.05) were identified. CONCLUSIONS:DECT VM and MAR techniques improve delineation accuracy and the optimal of reconstruction technique depends on the type of metal implant.
| S-EPMC5864514 | biostudies-literature
Project description:Severe artifacts in kilovoltage-CT simulation images caused by large metallic implants can significantly degrade the conspicuity and apparent CT Hounsfield number of targets and anatomic structures, jeopardize the confidence of anatomical segmentation, and introduce inaccuracies into the radiation therapy treatment planning process. This study evaluated the performance of the first commercial orthopedic metal artifact reduction function (O-MAR) for radiation therapy, and investigated its clinical applications in treatment planning.Both phantom and clinical data were used for the evaluation. The CIRS electron density phantom with known physical (and electron) density plugs and removable titanium implants was scanned on a Philips Brilliance Big Bore 16-slice CT simulator. The CT Hounsfield numbers of density plugs on both uncorrected and O-MAR corrected images were compared. Treatment planning accuracy was evaluated by comparing simulated dose distributions computed using the true density images, uncorrected images, and O-MAR corrected images. Ten CT image sets of patients with large hip implants were processed with the O-MAR function and evaluated by two radiation oncologists using a five-point score for overall image quality, anatomical conspicuity, and CT Hounsfield number accuracy. By utilizing the same structure contours delineated from the O-MAR corrected images, clinical IMRT treatment plans for five patients were computed on the uncorrected and O-MAR corrected images, respectively, and compared.Results of the phantom study indicated that CT Hounsfield number accuracy and noise were improved on the O-MAR corrected images, especially for images with bilateral metal implants. The γ pass rates of the simulated dose distributions computed on the uncorrected and O-MAR corrected images referenced to those of the true densities were higher than 99.9% (even when using 1% and 3 mm distance-to-agreement criterion), suggesting that dose distributions were clinically identical. In all patient cases, radiation oncologists rated O-MAR corrected images as higher quality. Formerly obscured critical structures were able to be visualized. The overall image quality and the conspicuity in critical organs were significantly improved compared with the uncorrected images: overall quality score (1.35 vs 3.25, P = 0.0022); bladder (2.15 vs 3.7, P = 0.0023); prostate and seminal vesicles∕vagina (1.3 vs 3.275, P = 0.0020); rectum (2.8 vs 3.9, P = 0.0021). The noise levels of the selected ROIs were reduced from 93.7 to 38.2 HU. On most cases (8∕10), the average CT Hounsfield numbers of the prostate∕vagina on the O-MAR corrected images were closer to the referenced value (41.2 HU, an average measured from patients without metal implants) than those on the uncorrected images. High γ pass rates of the five IMRT dose distribution pairs indicated that the dose distributions were not significantly affected by the CT image improvements.Overall, this study indicated that the O-MAR function can remarkably reduce metal artifacts and improve both CT Hounsfield number accuracy and target and critical structure visualization. Although there was no significant impact of the O-MAR algorithm on the calculated dose distributions, we suggest that O-MAR corrected images are more suitable for the entire treatment planning process by offering better anatomical structure visualization, improving radiation oncologists' confidence in target delineation, and by avoiding subjective density overrides of artifact regions on uncorrected images.
| S-EPMC3618095 | biostudies-other
Project description:To evaluate the influence of dual-energy CT (DECT) and Virtual monochromatic spectral (VMS) imaging on: (1) the artefact size of geometrically identical orthopaedic implants consisting of three different compositions and (2) the image quality of the surrounding bone, three similar phantoms-each featuring one femoral stem composed of either titanium, chrome-cobalt or stainless steel surrounded by five calcium pellets (200 mg hydroxyapatite/calcium carbonate) to simulate bony tissue and one reference pellet located away from the femoral stem-were built. DECT with two sequential scans (80 kVp and 140 kVp; scan-to-scan technique) was performed, and VMS images were calculated between 40 and 190 keV. The artefact sizes were measured volumetrically by semiautomatic selection of regions of interest (ROIs), considering the VMS energies and the polychromatic spectres. Moreover, density and image noise within the pellets were measured. All three phantoms exhibit artefact size reduction as energy increases from 40 to 190 keV. Titanium exhibited a stronger reduction than chrome-cobalt and stainless steel. The artefacts were dependent on the diameter of the stem. Image quality increases with higher energies on VMS with a better depiction of surrounding structures. Monoenergetic energies 70 keV and 140 keV demonstrate superior image quality to those produced by spectral energies 80 kVp and 140 kVp.
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Project description:We propose a novel metal artifact reduction (MAR) algorithm for CT images that completes a corrupted sinogram along the metal trace region. When metal implants are located inside a field of view, they create a barrier to the transmitted X-ray beam due to the high attenuation of metals, which significantly degrades the image quality. To fill in the metal trace region efficiently, the proposed algorithm uses multiple prior images with residual error compensation in sinogram space. Multiple prior images are generated by applying a recursive active contour (RAC) segmentation algorithm to the pre-corrected image acquired by MAR with linear interpolation, where the number of prior image is controlled by RAC depending on the object complexity. A sinogram basis is then acquired by forward projection of the prior images. The metal trace region of the original sinogram is replaced by the linearly combined sinogram of the prior images. Then, the additional correction in the metal trace region is performed to compensate the residual errors occurred by non-ideal data acquisition condition. The performance of the proposed MAR algorithm is compared with MAR with linear interpolation and the normalized MAR algorithm using simulated and experimental data. The results show that the proposed algorithm outperforms other MAR algorithms, especially when the object is complex with multiple bone objects.
| S-EPMC5467844 | biostudies-literature
Project description:Metal nanoparticles can either quench or enhance the emission of dyes in their vicinity, but the precise measurement and understanding of this effect is still hindered by experimental artifacts, especially for particles in colloidal dispersion. Here, we introduce a new methodology to correct the inner filter effect of the metal on the dye emission. To test the method, we developed new hybrid nanoparticles with a gold core and a silica shell of precise thickness (tuned from 7 to 13 nm), with a high quantum yield perylenediimide dye on the surface. This novel approach effectively avoids fluorescence quenching, allowing us to measure emission enhancements of 5 to 30 times, with no change on the dye fluorescence lifetime. Being able to measure the emission enhancement in dye-metal hybrid nanoparticles in dispersion, free from inner filter and quenching artifacts, offers excellent prospects to guide the development of more efficient fluorescent probes, sensors and photonic devices.
| S-EPMC5446421 | biostudies-literature
Project description:BACKGROUND:Two novel methods of image reconstruction, xSPECT Quant (xQ) and xSPECT Bone (xB), that use an ordered subset conjugate gradient minimizer (OSCGM) for SPECT/CT reconstruction have been proposed. The present study compares the performance characteristics of xQ, xB, and conventional Flash3D (F3D) reconstruction using images derived from phantoms and patients. METHODS:A custom-designed body phantom for bone SPECT was scanned using a Symbia Intevo (Siemens Healthineers), and reconstructed xSPECT images were evaluated. The phantom experiments proceeded twice with different activity concentrations and sphere sizes. A phantom with 28-mm spheres containing a 99mTc-background and tumor-to-normal bone ratios (TBR) of 1, 2, 4, and 10 were generated, and convergence property against various TBR was evaluated across 96 iterations. A phantom with four spheres (13-, 17-, 22-, and 28-mm diameters), containing a 99mTc-background at TBR4, was also generated. The full width at half maximum of an imaged spinous process (10?mm), coefficients of variance (CV), contrast-to-noise ratio (CNR), and recovery coefficients (RC) were evaluated after reconstructing images of a spine using Flash 3D (F3D), xQ, and xB. We retrospectively analyzed images from 20 patients with suspected bone metastases (male, n = 13) which were acquired using [99mTc]Tc-(H)MDP SPECT/CT, then CV and standardized uptake values (SUV) at the 4th vertebral body (L4) were compared after xQ and xB reconstruction in a clinical setup. RESULTS:Mean activity concentrations with various TBR converged according to increasing numbers of iterations. The spatial resolution of xB was considerably superior to xQ and F3D, and it approached almost the actual size regardless of the iteration numbers during reconstruction. The CV and RC were better for xQ and xB than for F3D. The CNR peaked at 24 iterations for xQ and 48 iterations for F3D and xB, respectively. The RC between xQ and xB significantly differed at lower numbers of iterations but were almost equivalent at higher numbers of iterations. The reconstructed xQ and xB images of the clinical patients showed a significant difference in the SUVmax and SUVpeak. CONCLUSIONS:The reconstructed xQ and xB images were more accurate than those reconstructed conventionally using F3D. The xB for bone SPECT imaging offered essentially unchanged spatial resolution even when the numbers of iterations did not converge. The xB reconstruction further enhanced SPECT image quality using CT data. Our findings provide important information for understanding the performance characteristics of the novel xQ and xB algorithms.
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Project description:The presence of motion artefacts in ECG signals can cause misleading interpretation of cardiovascular status. Recently, reducing the motion artefact from ECG signal has gained the interest of many researchers. Due to the overlapping nature of the motion artefact with the ECG signal, it is difficult to reduce motion artefact without distorting the original ECG signal. However, the application of an adaptive noise canceler has shown that it is effective in reducing motion artefacts if the appropriate noise reference that is correlated with the noise in the ECG signal is available. Unfortunately, the noise reference is not always correlated with motion artefact. Consequently, filtering with such a noise reference may lead to contaminating the ECG signal. In this paper, a two-stage filtering motion artefact reduction algorithm is proposed. In the algorithm, two methods are proposed, each of which works in one stage. The weighted adaptive noise filtering method (WAF) is proposed for the first stage. The acceleration derivative is used as motion artefact reference and the Pearson correlation coefficient between acceleration and ECG signal is used as a weighting factor. In the second stage, a recursive Hampel filter-based estimation method (RHFBE) is proposed for estimating the ECG signal segments, based on the spatial correlation of the ECG segment component that is obtained from successive ECG signals. Real-World dataset is used to evaluate the effectiveness of the proposed methods compared to the conventional adaptive filter. The results show a promising enhancement in terms of reducing motion artefacts from the ECG signals recorded by a cost-effective single lead ECG sensor during several activities of different subjects.
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