Quantitative Effect of Metal Artefact Reduction on CT-based attenuation correction in FDG PET/CT in patients with hip prosthesis

Background Metal artefact reduction (MAR) techniques still are in limited use in positron emission tomography/computed tomography (PET/CT). This study aimed to investigate the effect of Smart MAR on quantitative PET analysis in the vicinity of hip prostheses. Materials and methods Activities were measured on PET/CT images in 6 sources with tenfold activity concentration contrast to background, attached to the head, neck and the major trochanter of a human cadaveric femur, and in the same sources in similar locations after a hip prosthesis (titanium cup, ceramic head, chrome-cobalt stem) had been inserted into the femur. Measurements were compared between PET attenuation corrected using either conventional or MAR CT. In 38 patients harbouring 49 hip prostheses, standardized uptake values (SUV) in 6 periprosthetic regions and the bladder were compared between PET attenuation corrected with either conventional or MAR CT. Results Using conventional CT, measured activity decreased with 2 to 13% when the prosthesis was inserted. Use of MAR CT increased measured activity by up to 11% compared with conventional CT and reduced the relative difference with the reference values to under 5% in all sources. In all regions, to the exception of the prosthesis shaft, SUVmean increased significantly (p < 0.001) by use of MAR CT. Median (interquartile range) percentual increases of SUVmean were 1.4 (0.0–4.2), 4.0 (1.8–7.8), 7.8 (4.1–12.4), 1.5 (0.0–3.2), 1.4 (0.8–2.8) in acetabulum, lateral neck, medial neck, lateral diaphysis and medial diaphysis, respectively. Except for the shaft, the coefficient of variation did not increase significantly. Except for the erratic changes in the prosthesis shaft, decreases in SUVmean were rare and small. Bladder SUVmean increased by 0.9% in patients with unilateral prosthesis and by 4.1% in patients with bilateral prosthesis. Conclusions In a realistic hip prosthesis phantom, Smart MAR restores quantitative accuracy by recovering counts in underestimated sources. In patient studies, Smart MAR increases SUV in all areas surrounding the prosthesis, most markedly in the femoral neck region. This proves that underestimation of activity in the PET image is the most prevalent effect due to metal artefacts in the CT image in patients with hip prostheses. Smart MAR increases SUV in the urinary bladder, indicating effects at a distance from the prosthesis.

CBCT image artefacts generated by implants located inside the field of view or in the exomass

Objectives: To compare artefacts in cone-beam computed tomography (CBCT) arising from implants of different materials located either inside the field-of-view (FOV) or in the exomass, and to test different image-acquisition parameters to reduce them. Methods: CBCT scans of a human mandible prepared with either a titanium, titanium-zirconium, or zirconia implant were acquired with the Planmeca ProMax utilizing FOV sizes of 8 × 5 cm and 4 × 5 cm, which placed the implant inside the FOV (8 × 5 cm) or in the exomass (4 × 5 cm). The scanning parameters considered three conditions of metal artefact reduction (MAR), disabled, low, and high, and two kVp levels (80 and 90). The standard deviation (SD) of grey values of regions of interest was obtained. The effects of implant material, implant position, MAR condition, kVp level, and their interactions were evaluated by Analysis of Variance (α = 5%). Results: The zirconia implant produced the highest SD values (more heterogeneous grey values, corresponding to greater artefact expression), followed by titanium-zirconium, and titanium. In general, implants in the exomass produced images with higher SD values than implants inside the FOV. MAR was effective in decreasing SD values, especially from the zirconia implant, only when the implant was inside the FOV. Images with 80 kVp had higher SD values than those with 90 kVp, regardless of the other factors (p < 0.05). Conclusions: Implants in the exomass lead to greater artefact expression than when they are inside the FOV. Special attention should be paid to scanning parameters that reduce metal-related artefacts, such as MAR activation and increasing kVp. This is especially important with a zirconia implant inside the FOV.

Localising ingested metallic foreign bodies to guide surgical planning: A novel use for the CT metal artefact reduction algorithm

We present the case of a 20 year old female patient who presented following ingestion of multiple button magnets. She remained clinically well however serial abdominal radiographs demonstrated the magnets were not passing through the gastrointestinal tract and a CT was therefore performed for further assessment and to aid surgical planning. Artefact from the magnets made interpretation of the CT challenging. The use of a Metal Artefact Reduction (MAR) algorithm however enabled accurate localisation of the magnets thus guiding subsequent surgical intervention. Whilst MAR algorithms are usually used in the assessment of iatrogenic metallic devices (e.g., joint prostheses), this case demonstrates an example of their potential wider use.

The Dosimetric Evaluation of An In-House Software Developed For Metal Artefact Reduction On Two Different Radiotherapy Treatment Planning Systems

Metal Artefact Reduction (MAR) is very important in terms of dose calculation in radiotherapy. It was aimed to develop an in-house MAR software as an alternative to commercial software programs and to examine its effectiveness by comparing it with the SMART-MAR software which was available commercially. A phantom containing metal with high atomic number was designed and computed tomography (CT) images of this phantom were taken (Without-MAR images). The obtained CT images were processed with the SMART-MAR software and the developed In-House MAR software. Processed images were compared in terms of Hounsfield unit (HU), absolute dose values ​​in the Accuray and CMS XiO treatment planning systems, and gamma evaluation. The best HU improvement was observed in the developed In-House MAR. The maximum mean percentage differences in absorbed doses at the determined points in Accuray was found 33.3% and 32.5% between Without MAR - SMART MAR and Without MAR- In-House MAR, respectively. The In-House MAR software developed by using MATLAB was shown similar results with the SMART MAR software. Although in-house MAR software needs to be investigated clinically, it is more advantageous than commercially available software in terms of being cost-free, applicability in a shorter time and without reconstruction.

Metal artefact reduction in the oral cavity using deep learning reconstruction algorithm in ultra-high-resolution computed tomography: a phantom study

Objectives: This study aimed to improve the impact of the metal artefact reduction (MAR) algorithm for the oral cavity by assessing the effect of acquisition and reconstruction parameters on an ultra-high-resolution CT (UHRCT) scanner. Methods: The mandible tooth phantom with and without the lesion was scanned using super-high-resolution, high-resolution (HR), and normal-resolution (NR) modes. Images were reconstructed with deep learning-based reconstruction (DLR) and hybrid iterative reconstruction (HIR) using the MAR algorithm. Two dental radiologists independently graded the degree of metal artefact (1, very severe; 5, minimum) and lesion shape reproducibility (1, slight; 5, almost perfect). The signal-to-artefact ratio (SAR), accuracy of the CT number of the lesion, and image noise were calculated quantitatively. The Tukey-Kramer method with a p-value of less than 0.05 was used to determine statistical significance. Results: The HRDLR visual score was better than the NRHIR score in terms of degree of metal artefact (4.6 ± 0.5 and 2.6 ± 0.5, p < 0.0001) and lesion shape reproducibility (4.5 ± 0.5 and 2.9 ± 1.1, p = 0.0005). The SAR of HRDLR was significantly better than that of NRHIR (4.9 ± 0.4 and 2.1 ± 0.2, p < 0.0001), and the absolute percentage error of the CT number in HRDLR was lower than that in NRHIR (0.8% in HRDLR and 23.8% in NRIR). The image noise of HRDLR was lower than that of NRHIR (15.7 ± 1.4 and 51.6 ± 15.3, p < 0.0001). Conclusions: Our study demonstrated that the combination of HR mode and DLR in UHRCT scanner improved the impact of the MAR algorithm in the oral cavity.

Deep learning–based metal artefact reduction in PET/CT imaging

Objectives The 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. Methods Deep 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. Results The 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. Conclusion The 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.

Feasibility of photon-counting spectral CT in dental applications—a comparative qualitative analysis

Purpose The goal of this study was to demonstrate the feasibility of using photon-counting spectral CT for dental applications. This paper qualitatively analyzes the visibility of accessory canals (ACs) and metal artefacts from dental implants for cone-beam CT (CBCT), microtomography (microCT), and photon-counting spectral CT (PCSCT). Materials and methods All of the teeth in this study were extracted, and eight teeth in total were scanned on a CBCT scanner, a microCT scanner and on a PCSCT scanner. Six of the teeth that were scanned have accessory canals, one has a titanium rod attached to it, and one has a gutta-percha point inside it. Qualitative analysis was done to compare the different imaging modalities. Results The subjective image analysis demonstrated similar performance in AC detection and visualisation for PCSCT and CBCT (p value >0.05). Both PCSCT and microCT performed similarly for metal artefact reduction, and both were superior to CBCT (p value <0.05). Conclusion Although microCT provides detailed information about small anatomical structures, it is not suitable for in vivo use. However, the PCSCT scanner was able to detect small anatomical structures in teeth comparable to CBCT, as well as being superior in reducing metal artefacts from dental implants. This study showed that PCSCT is a promising modality for future dentistry applications.

Metal artefact reduction of different alloys with dual energy computed tomography (DECT)

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.