The value of metal artifact reduction and iterative algorithms in dual energy CT angiography in patients after complex endovascular aortic aneurysm repair

Effectiveness of single-energy metal artifact reduction algorithm in CT: application to contrast-enhanced CT with EVAR and coil embolization

This study aimed to evaluate the efficacy of the single-energy metal artifact reduction (SEMAR) algorithm in reducing metal artifacts and enhancing image quality in contrast-enhanced computed tomography (CT) for patients undergoing endovascular aneurysm repair (EVAR) with coil embolization. Thirty-eight patients (mean age 81.0 ± 6 years; 31 men, 7 women) who underwent contrast-enhanced CT following EVAR and internal iliac artery coil embolization between September 2022 and May 2023 were retrospectively analyzed. The Artifact Index (AI) quantified metallic artifacts from internal iliac artery aneurysm coils in CT images, calculated from the standard deviation of the artifact-containing region relative to a reference region. CT values of the external iliac artery at the same slice were also evaluated and compared. Two radiologists independently performed qualitative assessments of SEMAR and non-SEMAR images. SEMAR significantly reduced metal artifacts, decreasing the AI from 171.9 ± 74.5 HU to 35.8 ± 16.9 HU (p < 0.001). The mean CT values of the external iliac artery were similar for SEMAR (259.4 ± 63.7 HU) and non-SEMAR (257.1 ± 63.6 HU, indicating no significant difference. Qualitative assessment scores improved significantly with SEMAR (from 1.0 ± 0.0 to 2.5 ± 0.5; p < 0.001), enhancing visualization of internal iliac artery aneurysms. Interobserver agreement was high (κ = 0.83). The SEMAR algorithm effectively reduces metal artifacts in contrast-enhanced CT, significantly enhancing image quality without altering adjacent artery CT values. These improvements enhance the image quality of post-operative assessments in patients undergoing EVAR with coil embolization.

The Clinical Value of the MAR+ Metal Artifact Reduction Algorithm for Postoperative Assessment of Lumbar Internal Fixation

BACKGROUND

With the widespread use of lumbar pedicle screws for internal fixation, the morphology of the screws and the surrounding tissues should be evaluated. The metal artifact reduction (MAR) technique can reduce the artifacts caused by pedicle screws, improve the quality of computed tomography (CT) images after pedicle fixation, and provide more imaging information to the clinic.

PURPOSE

To explore whether the MAR+ method, a projection-based algorithm for correcting metal artifacts through multiple iterative operations, can reduce metal artifacts and have an impact on the structure of the surrounding metal.

MATERIALS AND METHODS

A total of 57 patients who underwent lumbar spine CT examination after lumbar internal fixation from January to December 2023 in our hospital were retrospectively enrolled. The CT images were reconstructed using MAR+ and non-MAR+ techniques and were subdivided into MAR+ and non-MAR+ groups. The CT number (in Hounsfield units) and the SD noise values of the spinal canal, vertebral body, psoas major muscle, and adjacent fat were measured in the 2 groups of CT images, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The subjective score was evaluated by two diagnostic radiologists using a double-blind method for image quality evaluation of the MAR+ group and the non-MAR+ group, and the image quality was classified on a 5-point scale. The rank-sum test was utilized to compare the subjective and objective scores of the 2 groups.

RESULTS

The SD values of the spinal canal (Z=-4.12, P<0.01), vertebral body (Z=-3.81, P<0.01), and psoas major muscle (Z=-3.87, P<0.01) in the MAR+ group were significantly lower than those in the non-MAR+ group (P<0.05). However, the SD values of the adjacent fat (Z=-2.03, P=0.42) in the MAR+ group, although smaller than those in the non-MAR+ group, were not statistically significant. The CNR values of vertebral canal (Z=-2.67, P=0.008) and fat (Z=-2.60, P=0.009) were higher in the MAR+ group than in the non-MAR+ group, whereas the CNR values of the vertebral body (Z=-6.74, P<0.01) in the MAR+ group were smaller than those in the non-MAR+ group, and the difference of all of them was statistically significant (P<0.05). Furthermore, for both CT and SNR values, the MAR group's values were all less than those of the non-MAR group and were statistically significant (P<0.05). The subjective scores of the measurement points were all higher in the MAR+ group than in the non-MAR+ group.

CONCLUSIONS

The MAR+ technique has a noise reduction effect on different tissues and artifacts are significantly reduced. Although the artifacts caused by metal screws were not completely eliminated, the MAR+ technique was able to reduce the interference of artifacts in the diagnosis of CT images, thus improving their diagnostic quality.

Monoenergetic reconstructions and iodine density maps for visualization of coronary artery stents using 8-cm dual-layer detector spectral computed tomography: an in vitro phantom study

Background

The effectiveness of coronary computed tomography (CT) angiography in assessing stent restenosis is hindered by heavy metal artifacts. This study aimed to evaluate the image quality of monoenergetic reconstructions and iodine density map for coronary stent imaging using an 8-cm dual-layer detector spectral CT.

Methods

In this study, 8 stents with a diameter <3 mm (group A) and 10 with a diameter ≥3 mm (group B) were placed in plastic tubes filled with iodinated contrast media and scanned. The internal diameter of the prepared stents was then measured by intravascular ultrasound. The reconstructed images included iodine density maps, conventional images, and different energy levels. The visualization of the stent lumen and stent structure was subjectively assessed using a 4-point Likert scale. The objective evaluation was performed using the in-stent lumen signal-to-noise ratio (SNRis), non-stent lumen SNR (SNRns), internal diameter difference (IDD), and blooming artifact index (BAI). The Friedman test and analysis of variance were used for multiple comparisons.

Results

For lumen visualization, the optimal monoenergetic images received the highest score for both group A (2.56±0.51) and group B (3.1±0.55). Multiple comparisons showed that there were significant differences between the optimal monoenergetic images and iodine density maps. However, for stent structure, iodine density maps received the highest score for group A (3.0±0.52) and group B (3.8±0.41). For quantitative assessment, the optimal monoenergetic images had the highest SNRis and SNRns, while the iodine density maps had the lowest SNRis and SNRns. For IDD and BAI, the iodine density maps yielded the smallest value.

Conclusions

The monoenergetic images on the second-generation dual-layer detector CT provide better visualization of the lumen and higher SNR. However, iodine density maps are superior for evaluating stent structure and IDD and BAI compared to monoenergetic and conventional reconstructions.

Assessing the diagnostic accuracy of artificial intelligence in post-endovascular aneurysm repair endoleak detection using dual-energy computed tomography angiography

Purpose

The aim of this study was to evaluate the diagnostic accuracy of an artificial intelligence (AI) tool in detecting endoleaks in patients undergoing endovascular aneurysm repair (EVAR) using dual-energy computed tomography angiography (CTA).

Material and methods

The study involved 95 patients who underwent EVAR and subsequent CTA follow-up. Dualenergy scans were performed, and images were reconstructed as linearly blended (LB) and 40 keV virtual monoenergetic (VMI) images. The AI tool PRAEVAorta®2 was used to assess arterial phase images for endoleaks. Two experienced readers independently evaluated the same images, and their consensus served as the reference standard. Key metrics, including accuracy, precision, recall, F1 score, and area under the receiver operating characteristic (ROC) curve (AUC), were calculated.

Results

The final analysis included 94 patients. The AI tool demonstrated an accuracy of 78.7%, precision of 67.6%, recall of 10 71.9%, F1 score of 69.7%, and an AUC of 0.77 using LB images. However, the tool failed to process 40 keV VMI images correctly, limiting further analysis of these datasets.

Conclusions

The AI tool showed moderate diagnostic accuracy in detecting endoleaks using LB images but failed to achieve the reliability needed for clinical use due to the significant number of misdiagnoses.

Enhancing image quality in computed tomography angiography follow-ups after endovascular aneurysm repair: a comparative study of reconstruction techniques

BACKGROUND

The image quality of computed tomography angiography (CTA) images following endovascular aneurysm repair (EVAR) is not satisfactory, since artifacts resulting from metallic implants obstruct the clear depiction of stent and isolation lumens, and also adjacent soft tissues. However, current techniques to reduce these artifacts still need further advancements due to higher radiation doses, longer processing times and so on. Thus, the aim of this study is to assess the impact of utilizing Single-Energy Metal Artifact Reduction (SEMAR) alongside a novel deep learning image reconstruction technique, known as the Advanced Intelligent Clear-IQ Engine (AiCE), on image quality of CTA follow-ups conducted after EVAR.

MATERIALS

This retrospective study included 47 patients (mean age ± standard deviation: 68.6 ± 7.8 years; 37 males) who underwent CTA examinations following EVAR. Images were reconstructed using four different methods: hybrid iterative reconstruction (HIR), AiCE, the combination of HIR and SEMAR (HIR + SEMAR), and the combination of AiCE and SEMAR (AiCE + SEMAR). Two radiologists, blinded to the reconstruction techniques, independently evaluated the images. Quantitative assessments included measurements of image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), the longest length of artifacts (AL), and artifact index (AI). These parameters were subsequently compared across different reconstruction methods.

RESULTS

The subjective results indicated that AiCE + SEMAR performed the best in terms of image quality. The mean image noise intensity was significantly lower in the AiCE + SEMAR group (25.35 ± 6.51 HU) than in the HIR (47.77 ± 8.76 HU), AiCE (42.93 ± 10.61 HU), and HIR + SEMAR (30.34 ± 4.87 HU) groups (p < 0.001). Additionally, AiCE + SEMAR exhibited the highest SNRs and CNRs, as well as the lowest AIs and ALs. Importantly, endoleaks and thrombi were most clearly visualized using AiCE + SEMAR.

CONCLUSIONS

In comparison to other reconstruction methods, the combination of AiCE + SEMAR demonstrates superior image quality, thereby enhancing the detection capabilities and diagnostic confidence of potential complications such as early minor endleaks and thrombi following EVAR. This improvement in image quality could lead to more accurate diagnoses and better patient outcomes.

Angle Dependence of Electrode Lead-Related Artifacts in Single- and Dual-Energy Cardiac ECG-Gated CT Scanning-A Phantom Study

Background: The electrodes of implantable cardiac devices (ICDs) may cause significant problems in cardiac computed tomography (CT) because they are a source of artifacts that obscure surrounding structures and possible pathology. There are a few million patients currently with ICDs, and some of these patients will require cardiac imaging due to coronary artery disease or problems with ICDs. Modern CT scanners can reduce some of the metal artifacts because of MAR software, but in some vendors, it does not work with ECG gating. Introduced in 2008, dual-energy CT scanners can generate virtual monoenergetic images (VMIs), which are much less susceptible to metal artifacts than standard CT images. Objective: This study aimed to evaluate if dual-energy CT can reduce metal artifacts caused by ICD leads by using VMIs. The second objective was to determine how the angle between the electrode and the plane of imaging affects the severity of the artifacts in three planes of imaging. Methods: A 3D-printed model was constructed to obtain a 0-90-degree field at 5-degree intervals between the electrode and each of the planes: axial, coronal, and sagittal. This electrode was scanned in dual-energy and single-energy protocols. VMIs with an energy of 40-140 keV with 10 keV intervals were reconstructed. The length of the two most extended artifacts originating from the tip of the electrode and 2 cm above it-at the point where the thick metallic defibrillating portion of the electrode begins-was measured. Results: For the sagittal plane, these observations were similar for both points of the ICDs that were used as the reference location. VMIs with an energy over 80 keV produce images with fewer artifacts than similar images obtained in the single-energy scanning mode. Conclusions: Virtual monoenergetic imaging techniques may reduce streak artifacts arising from ICD electrodes and improve the quality of the image. Increasing the angle of the electrode as well as the imaging plane can reduce artifacts. The angle between the electrode and the beam of X-rays can be increased by tilting the gantry of the scanner or lifting the upper body of the patient.

The Impact of AI on Metal Artifacts in CBCT Oral Cavity Imaging

OBJECTIVE

This study aimed to assess the impact of artificial intelligence (AI)-driven noise reduction algorithms on metal artifacts and image quality parameters in cone-beam computed tomography (CBCT) images of the oral cavity.

MATERIALS AND METHODS

This retrospective study included 70 patients, 61 of whom were analyzed after excluding those with severe motion artifacts. CBCT scans, performed using a Hyperion X9 PRO 13 × 10 CBCT machine, included images with dental implants, amalgam fillings, orthodontic appliances, root canal fillings, and crowns. Images were processed with the ClariCT.AI deep learning model (DLM) for noise reduction. Objective image quality was assessed using metrics such as the differentiation between voxel values (ΔVVs), the artifact index (AIx), and the contrast-to-noise ratio (CNR). Subjective assessments were performed by two experienced readers, who rated overall image quality and artifact intensity on predefined scales.

RESULTS

Compared with native images, DLM reconstructions significantly reduced the AIx and increased the CNR (p < 0.001), indicating improved image clarity and artifact reduction. Subjective assessments also favored DLM images, with higher ratings for overall image quality and lower artifact intensity (p < 0.001). However, the ΔVV values were similar between the native and DLM images, indicating that while the DLM reduced noise, it maintained the overall density distribution. Orthodontic appliances produced the most pronounced artifacts, while implants generated the least.

CONCLUSIONS

AI-based noise reduction using ClariCT.AI significantly enhances CBCT image quality by reducing noise and metal artifacts, thereby improving diagnostic accuracy and treatment planning. Further research with larger, multicenter cohorts is recommended to validate these findings.

Dual-Energy and Photon-Counting Computed Tomography in Vascular Applications-Technical Background and Post-Processing Techniques

The field of computed tomography (CT), which is a basic diagnostic tool in clinical practice, has recently undergone rapid technological advances. These include the evolution of dual-energy CT (DECT) and development of photon-counting computed tomography (PCCT). DECT enables the acquisition of CT images at two different energy spectra, which allows for the differentiation of certain materials, mainly calcium and iodine. PCCT is a recent technology that enables a scanner to quantify the energy of each photon gathered by the detector. This method gives the possibility to decrease the radiation dose and increase the spatial and temporal resolutions of scans. Both of these techniques have found a wide range of applications in radiology, including vascular studies. In this narrative review, the authors present the principles of DECT and PCCT, outline their advantages and drawbacks, and briefly discuss the application of these methods in vascular radiology.

Performance of different cone-beam computed tomography scan modes with and without metal artifact reduction in detection of recurrent dental caries under various restorative materials

Purpose

We aimed to compare the diagnostic performance of different cone-beam computed tomography (CBCT) scan modes with and without the application of a metal artifact reduction (MAR) option under 5 different restorative materials.

Material and methods

Our research was an in vitro study with 150 caries-free premolars and molars. The teeth were randomly divided into experimental (with artificially induced caries, n = 75) and control (without caries, n = 75) groups and were prepared based on 5 types of restorative materials, including conventional composites (Filtek Z250, Gradia), flow composite, glass ionomer, and amalgam. The teeth were examined under 2 CBCT scan modes (high-resolution [HIRes] and standard) with and without MAR application. Finally, the diagnostic accuracy index values (area under the receiver operating characteristic curve [AUC], sensitivity, and specificity) were calculated.

Results

The AUC of standard scan mode with the MAR option was significantly lower than that of HIRes with MAR (p = 0.018) and without MAR option (p = 0.011) in detecting recurrent caries. Also, without MAR option, the diagnostic accuracy (AUC) of the standard mode was significantly lower than that of the HIRes (p = 0.020). Similar findings were observed for sensitivity and specificity. Moreover, diagnostic performance of standard and HIRes scan modes with and without MAR in the amalgam group was lower than that in other restorative material groups.

Conclusions

Diagnostic performance of HIRes CBCT mode was higher than that of standard mode for recurrent caries and remained unaffected by MAR application. However, the accuracy in detecting recurrent caries was lower in the amalgam group compared with other restorative material groups.

Enhanced visualization in endoleak detection through iterative and AI-noise optimized spectral reconstructions

To assess the image quality parameters of dual-energy computed tomography angiography (DECTA) 40-, and 60 keV virtual monoenergetic images (VMIs) combined with deep learning-based image reconstruction model (DLM) and iterative reconstructions (IR). CT scans of 28 post EVAR patients were enrolled. The 60 s delayed phase of DECTA was evaluated. Objective [noise, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR)] and subjective (overall image quality and endoleak conspicuity - 3 blinded readers assessment) image quality analyses were performed. The following reconstructions were evaluated: VMI 40, 60 keV VMI; IR VMI 40, 60 keV; DLM VMI 40, 60 keV. The noise level of the DLM VMI images was approximately 50% lower than that of VMI reconstruction. The highest CNR and SNR values were measured in VMI DLM images. The mean CNR in endoleak in 40 keV was accounted for as 1.83 ± 1.2; 2.07 ± 2.02; 3.6 ± 3.26 in VMI, VMI IR, and VMI DLM, respectively. The DLM algorithm significantly reduced noise and increased lesion conspicuity, resulting in higher objective and subjective image quality compared to other reconstruction techniques. The application of DLM algorithms to low-energy VMIs significantly enhances the diagnostic value of DECTA in evaluating endoleaks. DLM reconstructions surpass traditional VMIs and IR in terms of image quality.

Review of Clinical Applications of Dual-Energy CT in Patients after Endovascular Aortic Repair

Abdominal aortic aneurysms (AAAs) are a significant cause of mortality in developed countries. Endovascular aneurysm repair (EVAR) is currently the leading treatment method for AAAs. Due to the high sensitivity and specificity of post-EVAR complication detection, CT angiography (CTA) is the reference method for imaging surveillance in patients after EVAR. Many studies have shown the advantages of dual-energy CT (DECT) over standard polyenergetic CTA in vascular applications. In this article, the authors briefly discuss the technical principles and summarize the current body of literature regarding dual-energy computed tomography angiography (DECTA) in patients after EVAR. The authors point out the most useful applications of DECTA in this group of patients and its advantages over conventional CTA. To conduct this review, a search was performed using the PubMed, Google Scholar, and Web of Science databases.