High-kVp Assisted Metal Artifact Reduction for X-ray Computed Tomography

Bismuth Nanoparticle and Polyhydroxybutyrate Coatings Enhance the Radiopacity of Absorbable Inferior Vena Cava Filters for Fluoroscopy-Guided Placement and Longitudinal Computed Tomography Monitoring in Pigs

Inferior vena cava filters (IVCFs) constructed with poly-p-dioxanone (PPDO) are promising alternatives to metallic filters and their associated risks and complications. Incorporating high-Z nanoparticles (NPs) improves PPDO IVCFs' radiopacity without adversely affecting their safety or performance. However, increased radiopacity from these studies are insufficient for filter visualization during fluoroscopy-guided PPDO IVCF deployment. This study focuses on the use of bismuth nanoparticles (BiNPs) as radiopacifiers to render sufficient signal intensity for the fluoroscopy-guided deployment and long-term CT monitoring of PPDO IVCFs. The use of polyhydroxybutyate (PHB) as an additional layer to increase the surface adsorption of NPs resulted in a 2-fold increase in BiNP coating (BiNP-PPDO IVCFs, 3.8%; BiNP-PPDO + PHB IVCFs, 6.2%), enabling complete filter visualization during fluoroscopy-guided IVCF deployment and, 1 week later, clot deployment. The biocompatibility, clot-trapping efficacy, and mechanical strength of the control PPDO (load-at-break, 6.23 ± 0.13 kg), BiNP-PPDO (6.10 ± 0.09 kg), and BiNP-PPDO + PHB (6.15 ± 0.13 kg) IVCFs did not differ significantly over a 12-week monitoring period in pigs. These results indicate that BiNP-PPDO + PHB can increase the radiodensity of a novel absorbable IVCF without compromising device strength. Visualizing the device under conventional radiographic imaging is key to allow safe and effective clinical translation of the device.

A Survey of Dental Caries Segmentation and Detection Techniques

Dental caries detection, in the past, has been a challenging task given the amount of information got from various radiographic images. Several methods have been introduced to improve the quality of images for faster caries detection. Deep learning has become the methodology of choice when it comes to analysis of medical images. This survey gives an in-depth look into the use of deep learning for object detection, segmentation, and classification. It further looks into literature on segmentation and detection methods of dental images through deep learning. From the literature studied, we found out that methods were grouped according to the type of dental caries (proximal, enamel), type of X-ray images used (extraoral, intraoral), and segmentation method (threshold-based, cluster-based, boundary-based, and region-based). From the works reviewed, the main focus has been found to be on threshold-based segmentation methods. Most of the reviewed papers have preferred the use of intraoral X-ray images over extraoral X-ray images to perform segmentation on dental images of already isolated parts of the teeth. This paper presents an in-depth analysis of recent research in deep learning for dental caries segmentation and detection. It involves discussing the methods and algorithms used in segmenting and detecting dental caries. It also discusses various existing models used and how they compare with each other in terms of system performance and evaluation. We also discuss the limitations of these methods, as well as future perspectives on how to improve their performance.

Optimizing Identification of Power Injectable Ports on the Scout Images for Multidetector Computed Tomography Procedures

OBJECTIVE

The objective of this study was to assess the impact of tube voltage and image display on the identification of power ports features on anterior-posterior scout images to inform optimal workflow for multidetector computed tomography (MDCT) examinations.

MATERIALS AND METHODS

Four ports, representing variable material composition (titanium/silicone), shapes, and computed tomography (CT) markings, were imaged on an adult anthropomorphic chest phantom using a dual-source MDCT at variable peak tube voltages (80, 100, 120, 150, and Sn150 kVp). Images were reviewed at variable image display setting by 5 blinded readers to assess port features of material composition, shape, and text markings as well as overall preferred image quality.

RESULTS

Material composition was correctly identified for all ports by all readers across all kilovoltage-peak settings. The identification by shape was more reliable than CT markers for all but one of the ports. CT marker identification was up to 80% for titanium ports at window level settings optimized for metal (window width, 200; window center, -150) and at a soft tissue setting (window width, 400; window center, 40) for silicone ports. Interreader agreement for best image quality per kilovoltage-peak setting was moderate to substantial for 3 ports (k = 0.5-0.62) but only fair for 1 port (k = 0.27). The highest overall rank for image quality was given unanimously to Sn150 kVp for imaging titanium ports and 100 kVp for silicone ports.

CONCLUSIONS

Power port identification on MDCT scout images can be optimized with modification of MDCT scout acquisition and display settings based on the main port material.

[A Simple Method for Computationally Generating Metal Artifacts in CT Images for Treatment Planning: A Pilot Phantom Study]

PURPOSE

In treatment planning for radiation therapy, the use of computed tomography (CT) images including metal artifacts causes a reduction in the dose calculation accuracy. In clinical practice, the artifacts are manually contoured and assigned an appropriate fixed CT number. To validate the procedure, images taken before and after metal insertion into a patient are required, which may be impractical. We propose a simple method for computationally generating metal artifacts in clinical images.

METHODS

In the proposed method, a clinical image free of metal artifacts is used. To simulate metal inside a patient, CT numbers of a region in the image are replaced with a fixed extremely high value. A sinogram is created by the forward projection of the image. Data values of the sinogram in the metal region are converted into smaller values. From the sinogram, an image including artifacts is reconstructed with the filtered back projection.

RESULTS

The simulated artifacts consisted of dark and bright bands and were observed to be similar to the actual metal artifacts. CT numbers in multiple small regions of interest in the image obtained by the proposed method showed a good agreement with those in the actual image.

CONCLUSION

The proposed method was demonstrated to generate the metal artifacts additionally on the clinical images. The method would be potentially applicable to a validation study for the clinical procedure of manually contouring and assigning CT numbers to metal artifacts.

Estimation of the radiation dose for dental spectral cone-beam CT

OBJECTIVES

The purpose of this study was to estimate the radiation dose for a dental spectral cone-beam CT (SCBCT) unit at different scanning parameters.

METHODS

Radiation dose measurements were performed for a commercially available dental SCBCT. Scans were obtained at different exposure times and fields of view (FOV), both for non-spectral (25×18 cm, 14×18 cm, 14×12 cm, 9×9 cm, 6×6 cm) and spectral modes (14×18 cm, 14×12 cm, 9×9 cm, 6×6 cm) with the tube voltage alternating between 80 and 110 kV for spectral mode, and fixed at 110 kV for non-spectral mode. An ion chamber was used for air kerma and dose area product (DAP) measurements. The effective dose was estimated based on the mAs using previously published logarithmic curves for CBCT units with a similar X-ray spectrum.

RESULTS

The adult effective dose, in non-spectral mode, was 44-269 µSv for small FOVs, 131-336 µSv for the medium FOV, and 163-476 µSv for the large FOV. In spectral mode, the estimated adult effective doses were 96-206 µSv for small, 299 µSv for medium and 372 µSv for large FOV protocols. Paediatric effective doses were estimated to be 75% higher than corresponding adult doses.

CONCLUSION

SCBCT showed comparable doses with other CBCT devices, but DAP values were generally above currently published DRLs. Spectral imaging might allow for artefact reduction at comparable dose levels, which should be assessed in further image quality studies at both a technical and diagnostic levels.

Artefacts at different distances from titanium and zirconia implants in cone-beam computed tomography: effect of tube current and metal artefact reduction

OBJECTIVES

To evaluate the effect of cone-beam computed tomography (CBCT) tube current (mA) on the magnitude of artefacts at different distances from titanium or zirconia implants, with and without activation of a proprietary metal artefact reduction (MAR).

MATERIAL AND METHODS

Human mandibles were scanned on an OP300 Maxio CBCT unit (Instrumentarium, Tuusula, Finland) before and after the installation of dental implants, with four different tube currents (4 mA, 6.3 mA, 8 mA and 10 mA), with and without activation of proprietary MAR. The effect of mA on the standard deviation (SD) of gray values and contrast to noise ratio (CNR) were assessed in regions of interest located 1.5 cm, 2.5 cm, and 3.5 cm from implants.

RESULTS

In the presence of titanium implants, a significant decrease in SD was found by increasing tube current from 4 mA to 6.3 mA or 8 mA. For zirconia implants, 8 mA yielded better results for all distances. MAR improved CNR in the presence of zirconia implants at all distances, whereas no differences were observed with the use of MAR for titanium implants.

CONCLUSION

Increased tube current can improve overall image quality in the presence of implants, at all the distances tested. When a zirconia implant is present, such increase in mA should be higher in comparison to that for examinations with titanium implants. Activation of OP300 Maxio proprietary MAR improved image quality only among examinations with zirconia implants.

CLINICAL RELEVANCE

Artefact-generating implants are common in the field of view of CBCT examinations. Optimal exposure parameters, such as tube current, ensure high image quality with lowest possible radiation exposure.

A dual-stream deep convolutional network for reducing metal streak artifacts in CT images

Machine learning and deep learning are rapidly finding applications in the medical imaging field. In this paper, we address the long-standing problem of metal artifacts in computed tomography (CT) images by training a dual-stream deep convolutional neural network for streak removal. While many metal artifact reduction methods exist, even state-of-the-art algorithms fall short in some clinical applications. Specifically, proton therapy planning requires high image quality with accurate tumor volumes to ensure treatment success. We explore a dual-stream deep network structure with residual learning to correct metal streak artifacts after a first-pass by a state-of-the-art interpolation-based algorithm, NMAR. We provide the network with a mask of the streaks in order to focus attention on those areas. Our experiments compare a mean squared error loss function with a perceptual loss function to emphasize preservation of image features and texture. Both visual and quantitative metrics are used to assess the resulting image quality for metal implant cases. Success may be due to the duality of information processing, with one network stream performing local structure correction, while the other stream provides an attention mechanism to destreak effectively. This study shows that image-domain deep learning can be highly effective for metal artifact reduction (MAR), and highlights the benefits and drawbacks of different loss functions for solving a major CT reconstruction challenge.

Cone-beam computed tomography imaging of dentoalveolar and mandibular fractures

Three-dimensional imaging methods have an important role in the diagnosis of dentomaxillofacial fractures that can not be seen on the plain films. Cone-beam computed tomography (CBCT) is one of the three-dimensional imaging methods and has facilitated dental professionals' access to cross-sectional imaging. CBCT units allow different technical parameters and the data acquired by CBCT, can be reformatted. Osseous structures are correctly examined with this technique but the technique is not useful for the examination of soft tissues. Therefore, the purpose of its use should be based on the expected diagnostic gain. The aim of this review is to present the use of CBCT with different multi-planar reformatted sections and three-dimensional reconstructions of dentoalveolar and mandibular fractures.

Evaluation of the dental spectral cone beam CT for metal artefact reduction

OBJECTIVES:

Metal artefacts are highly common in dental CT images because of the high X-ray attenuation of metallic dental fillings and implants. This study presents an evaluation of the virtual monochromatic imaging for metal artefact reduction by a recently introduced dental spectral cone beam CT, which is the first commercial dental spectral CBCT with flat-panel detector.

METHODS:

We carried out phantom experiments and clinical trials in this study. In the phantom study, the head phantom with metallic dental fillings and implants of various materials was scanned. Moreover, standard deviation, metal artefact index, and contrast-to-noise ratio were analyzed for fixed region of interest. Patient study included 23 patients with metallic fillings and metal implants. Traditional CT images and virtual monochromatic images were produced in a single scan, ensuring that the comparison can be made within the same patient and same location. Standard deviation and metal artefact index were analyzed for fixed region of interest.

RESULTS:

The phantom study and patient study showed that the metal artefacts caused by metallic dental fillings are well-suppressed by the virtual monochromatic imaging. Moreover, the improvements in virtual monochromatic imaging in terms of image quality are more pronounced for small dental fillings.. The noise increase in image slices without metallic objects is a side-effect of the virtual monochromatic images.

CONCLUSIONS:

Virtual monochromatic imaging by spectral cone beam CT reduces the metal artefact and improves the image contrast-to-noise ratio around dental metallic fillings. This kind of imaging would be recommended for patients with dental metallic fillings.