Reduction of Artifacts Caused by Deep Brain Stimulating Electrodes in Cranial Computed Tomography Imaging by Means of Virtual Monoenergetic Images, Metal Artifact Reduction Algorithms, and Their Combination

Use of virtual monoenergetic images for reduction of extensive dental implant associated artifacts in photon-counting detector CT

Aim of this study was to assess the impact of virtual monoenergetic images (VMI) on dental implant artifacts in photon-counting detector computed tomography (PCD-CT) compared to standard reconstructed polychromatic images (PI). 30 scans with extensive (≥ 5 dental implants) dental implant-associated artifacts were retrospectively analyzed. Scans were acquired during clinical routine on a PCD-CT. VMI were reconstructed for 100-190 keV (10 keV steps) and compared to PI. Artifact extent and assessment of adjacent soft tissue were rated using a 5-point Likert grading scale for qualitative assessment. Quantitative assessment was performed using ROIs in most pronounced hypodense and hyperdense artifacts, artifact-impaired soft tissue, artifact-free fat and muscle tissue. A corrected attenuation was calculated as difference between artifact-impaired tissue and tissue without artifacts. Qualitative assessment of soft palate and cheeks improved for all VMI compared to PI (Median PI: 1 (Range: 1-3) and 1 (1-3); e.g. VMI130 keV 2 (1-5); p < 0.0001 and 2 (1-4); p < 0.0001). In quantitative assessment, VMI130 keV showed best results with a corrected attenuation closest to 0 (PI: 30.48 ± 98.16; VMI130 keV: - 0.55 ± 73.38; p = 0.0026). Overall, photon-counting deducted VMI reduce the extent of dental implant-associated artifacts. VMI of 130 keV showed best results and are recommended to support head and neck CT scans.

Dual-energy CT revisited: a focused review of clinical use cases

BACKGROUND

 Dual-energy CT (DECT) has been available for more than 15 years and has undergone continuous technical development and refinement. Recently, the first photon-counting CT scanner became clinically available and has the potential to further expand the possibilities of spectral imaging. Numerous studies on DECT have been published since its creation, highlighting the clinical applications of the various reconstructions enabled by DECT.

METHODS

 The aim of this focused review is to succinctly summarize basic principles and available technical concepts of DECT and to discuss established applications relevant to the daily clinical routine.

RESULTS/CONCLUSION

 DECT is instrumental for a broad variety of clinical use cases. While some DECT applications can enhance day-to-day clinical practice, others are still subject to broad-scale validation and should therefore be handled with restraint in the clinical routine.

KEY POINTS

  · Virtual monoenergetic images, virtual unenhanced images, and iodine maps are the most well-investigated and relevant dual-energy CT reconstructions for clinical application.. · Low-keV virtual monoenergetic images (VMIs) yield superior image and iodine contrast, which can be leveraged for improved vessel assessment and lesion conspicuity, or to reduce contrast media or radiation dose. VMIs at intermediate energies can serve as a replacement for conventional grey-scale images. VMIs at high keV enable efficient artifact reduction, which can be further optimized in combination with dedicated metal artifact reduction algorithms.. · Iodine maps and virtual unenhanced images can improve lesion detection in oncologic imaging and enable lesion assessment in monophasic CT examinations, which may allow a reduction of correlative and follow-up imaging..

Metal artifact reduction by virtual monoenergetic reconstructions from spectral brain CT

Purpose

Conventional computed tomography (CT) images are severely affected by metal artifacts in patients with intracranial coils. Monoenergetic images have been suggested to reduce metal artifacts.The aim of this study was to assess metal artifacts in virtual monoenergetic images (VMIs) reconstructed from spectral brain CT.

Methods

Thirty-two consecutive patients with intracranial coils examined by spectral non contrast brain CT (NCCT) at our center between November 2017 and April 2019 were included. Attenuation and standard deviations were measured in regions of interest (ROIs) at predefined areas in artifact-free and artifact-affected areas. Measurements were performed in conventional polyenergetic images (CIs) and the corresponding data for VMIs were retrieved through spectral diagrams for the each ROI. Subjective analysis was performed by visual grading of CIs and specific VMIs by two neuroradiologists, independently.

Results

In artefact-affected image areas distal from the metal objects, the attenuation values decreased with higher energy level VMIs. The same effect was not seen for artefact-affected image areas close to the metal.Subjective rating of the artefact severity was significantly better in VMIs at 50 keV for one of the two reviewers compared to the CIs. Overall image quality and tissue differentiation scores were significantly higher for both reviewers in VMIs at 60 and 70 keV compared to CIs.

Conclusion

Our quantitative and qualitative image analysis shown that there is a small significant reduction of intracranial coils artifacts severity by all monoenergetic reconstructions from 50 to 200 keV with preserved or increased overall subjective image quality compared to conventional images.

Low-Dose CT Imaging of the Pelvis in Follow-up Examinations-Significant Dose Reduction and Impact of Tin Filtration: Evaluation by Phantom Studies and First Systematic Retrospective Patient Analyses

OBJECTIVES

Low-dose (LD) computed tomography (CT) is still rarely used in musculoskeletal (MSK) radiology. This study evaluates the potentials of LD CT for follow-up pelvic imaging with special focus on tin filtration (Sn) technology for normal and obese patients with and without metal implants.

MATERIALS AND METHODS

In a phantom study, 5 different LD and normal-dose (ND) CT protocols with and without tin filtration were tested using a normal and an obese phantom. Iterative reconstruction (IR) and filtered back projection (FBP) were used for CT image reconstruction. In a subsequent retrospective patient study, ND CT images of 45 patients were compared with follow-up tin-filtered LD CT images with a 90% dose reduction. Sixty-four percent of patients contained metal implants at the follow-up examination. Computed tomography images were objectively (image noise, contrast-to-noise ratio [CNR], dose-normalized contrast-to-noise ratio [CNRD]) and subjectively, using a 6-point Likert score, evaluated. In addition, the figure of merit was calculated. For group comparisons, paired t tests, Wilcoxon signed rank test, analysis of variance, or Kruskal-Wallis tests were used, where applicable.

RESULTS

The LD Sn protocol with 67% dose reduction resulted in equal values in qualitative (Likert score) and quantitative image analysis (image noise) compared with the ND protocol in the phantom study. For follow-up examinations, dose could be reduced up to 90% by using Sn LD CT scans without impairment in the clinical study. However, metal implants resulted in a mild impairment of Sn LD as well as ND CT images. Cancellous bone ( P < 0.001) was assessed worse and cortical bone ( P = 0.063) equally in Sn LD CT images compared with ND CT images. Figure of merit values were significant ( P ≤ 0.02) lower and hence better in Sn LD as in ND protocols. Obese patients benefited in particular from tin filtration in LD MSK imaging in terms of image noise and CNR ( P ≤ 0.05).

CONCLUSIONS

Low-dose CT scans with tin filtration allow maximum dose reduction while maintaining high image quality for certain clinical purposes, for example, follow-up examinations, especially metal implant position, material loosening, and consolidation controls. Overweight patients benefit particularly from tin filter technology. Although metal implants decrease image quality in ND as well as in Sn LD CT images, this is not a relevant limitation for assessability.

Combination of Iterative Metal Artifact Reduction and Virtual Monoenergetic Reconstruction Using Split-Filter Dual-Energy CT in Patients With Dental Artifact on Head and Neck CT

Background: Head and neck CT may be limited by dental hardware artifact. Both post-processing based iterative metal artifact reduction (iMAR) and virtual monoenergetic reconstruction (VMR) from dual-energy CT (DECT) can reduce metal artifact. Their combination is poorly described for single-source DECT systems. Objective: To compare metal artifact reduction between VMR, iMAR, and their combination, using split-filter single-source DECT in patients with severe dental hardware artifact. Methods: This retrospective study included 44 patients (9 female, 35 male; mean age 66.0±10.4 years) who underwent head and neck CT exhibiting severe dental hardware artifact. Standard images, VMR, iMAR, and VMRi-MAR were reconstructed; VMR and VMRiMAR used 40, 70, 100, 120, 150, and 190 keV. ROIs were placed to measure corrected attenuation in pronounced hyperattenuating and hypoattenuating artifacts and artifact-impaired soft tissue, as well as corrected artifact-impaired soft tissue noise. Two radiologists independently assessed soft tissue interpretability (1-5 scale); pooled ratings were analyzed. Readers selected the preferred reconstruction for each patient. Results: Mean hyperattenuating artifact corrected attenuation was 521.0 for standard, 496.4-892.2 for VMR, 48.2 for iMAR, and 32.8-91.0 for VMRiMAR. Mean hypoattenuating artifact corrected attenuation was -455.1 for standard, -408.5 to -679.9 for VMR, -37.3 for iMAR, and -17.8 to -36.9 for VMRiMAR. Mean artifact-impaired soft tissue corrected attenuation was 10.8 for standard, -0.6 to 24.9 for VMR, 4.3 for iMAR, and -2.0 to 7.8 for VMRiMAR. Mean artifact-impaired soft tissue corrected noise was 58.7 for standard, 38.2-129.7 for VMR, 11.0 for iMAR, and 5.8-45.6 for VMRiMAR. Median soft tissue interpretability was 1.2 for standard, 1.1-1.2 for VMR, 3.7 for iMAR, and 2.0-3.8 for VMRiMAR. Artifact-impaired soft tissue corrected attenuation and soft tissue interpretability were significantly improved (p<.05) for VMRiMAR versus iMAR only at 100 keV. Readers preferred VMRiMAR at 100 keV in 56.8% and 59.1% of examinations. Conclusion: For reducing severe dental material artifact, iMAR has greater impact than VMR. Though iMAR and VMRiMAR were overall similar, VMRiMAR exhibited small benefit at 100 keV. Clinical Impact: VMR and iMAR techniques, using split-filter DECT, may be combined for clinical head and neck imaging to reduce artifact from dental hardware and improve image quality.

Reduction of CT artifacts from cardiac implantable electronic devices using a combination of virtual monoenergetic images and post-processing algorithms

OBJECTIVES

To evaluate the reduction of artifacts from cardiac implantable electronic devices (CIEDs) by virtual monoenergetic images (VMI), metal artifact reduction (MAR) algorithms, and their combination (VMI_MAR) derived from spectral detector CT (SDCT) of the chest compared to conventional CT images (CI).

METHODS

In this retrospective study, we included 34 patients (mean age 74.6 ± 8.6 years), who underwent a SDCT of the chest and had a CIED in place. CI, MAR, VMI, and VMI_MAR (10 keV increment, range: 100-200 keV) were reconstructed. Mean and standard deviation of attenuation (HU) among hypo- and hyperdense artifacts adjacent to CIED generator and leads were determined using ROIs. Two radiologists qualitatively evaluated artifact reduction and diagnostic assessment of adjacent tissue.

RESULTS

Compared to CI, MAR and VMI_MAR ≥ 100 keV significantly increased attenuation in hypodense and significantly decreased attenuation in hyperdense artifacts at CIED generator and leads (p < 0.05). VMI ≥ 100 keV alone only significantly decreased hyperdense artifacts at the generator (p < 0.05). Qualitatively, VMI ≥ 100 keV, MAR, and VMI_MAR ≥ 100 keV provided significant reduction of hyper- and hypodense artifacts resulting from the generator and improved diagnostic assessment of surrounding structures (p < 0.05). Diagnostic assessment of structures adjoining to the leads was only improved by MAR and VMI_MAR 100 keV (p < 0.05), whereas keV values ≥ 140 with and without MAR significantly worsened diagnostic assessment (p < 0.05).

CONCLUSIONS

The combination of VMI and MAR as well as MAR as a standalone approach provides effective reduction of artifacts from CIEDs. Still, higher keV values should be applied with caution due to a loss of soft tissue and vessel contrast along the leads.

KEY POINTS

• The combination of VMI and MAR as well as MAR as a standalone approach enables effective reduction of artifacts from CIEDs. • Higher keV values of both VMI and VMI_MAR at CIED leads should be applied with caution since diagnostic assessment can be hampered by a loss of soft tissue and vessel contrast. • Recommended keV values for CIED generators are between 140 and 200 keV and for leads around 100 keV.

CT artifacts after contrast media injection in chest imaging: evaluation of post-processing algorithms, virtual monoenergetic images and their combination for artifact reduction

Background

After injection into a brachial vein, high contrast media concentration in axillary and subclavian veins can cause artifacts that impair diagnostic utility. This study assessed artifact reduction by artifact-reduction-algorithms (ARA) and virtual-monoenergetic-images (VMI), as well as their combination (VMI_ARA) compared to conventional CT-images (CI).

Methods

Forty-six spectral-detector-CT (SDCT) examinations of patients that received ARA-reconstructions due to perivenous-artifacts were included in this retrospective study. CI, ARA, VMI, and VMI_ARA (range: 70-200 keV) were reconstructed. Objective analysis was performed with ROI-based assessment of mean and standard deviation of attenuation (HU) in hypo- and hyperdense artifacts and impaired muscle and arteries as well as artifact-free reference-tissue. Extent of artifact reduction, assessment of surrounding soft tissue and vessels, and appearance of new artifacts were rated visually by two radiologists.

Results

Hypo- and hyperdense artifacts showed significant improvement as evidenced by decreasing attenuation differences between artifact impaired and artifact-free reference tissue in ARA, VMI ≥80 keV, and VMI_ARA between 70-200 keV (e.g., CI/ARA/VMI_100keV/VMI_ARA100keV: hypodense artifacts, (-)264.8±150.9/(-)87.1±78.9/(-)48.6±64.6/9.9±63.9 HU; P<0.001); hyperdense artifacts, 164.2±51.1/82.1±73.2/7.9±34.7/(-)17.3±50.7 HU; P<0.001). Artifacts impairing surrounding muscle and arteries were also reduced by all three approaches. In visual assessment, ARA, VMI ≥100 keV, and VMI_ARA between 70-200 keV also showed significant artifact reduction and improved assessment; however, for assessment of arteries improvement was not significant using ARA alone. New artifacts were reported, particularly at higher keV-values.

Conclusions

In presence of perivenous-artifacts, ARA, VMI and their combination allow for significant artifact reduction; however, their combination and VMI as a standalone approach yielded best results and should therefore be used, if available.

Quantification of metal artifacts in computed tomography: methodological considerations

Numerous methods for artifact quantification in computed tomography (CT) imaging have been suggested. This study evaluated their utility with regards to correspondence with visual artifact perception and reproducibility. Two titanium rods (5 and 10 mm) were examined with 25 different scanning- and image-reconstruction parameters resulting in different types and extents of artifacts. Four radiologists evaluated every image against each other using an in-house developed software. Rating was repeated two times (2,400 comparisons = 2 times × 4 readers × 300 comparisons). Rankings were combined to obtain a reference ranking. Proposed approaches for artifact quantification include manual measurement of attenuation, standard deviation and noise and sophisticated algorithm-based approaches within the image- and frequency-domain. Two radiologists conducted manual measurements twice while the aforementioned algorithms were implemented within the Matlab-Environment allowing for automated image analysis. The reference ranking was compared to all aforementioned methods for artifact quantification to identify suited approaches. Besides visual analysis, Kappa-statistics and intraclass correlation coefficients (ICC) were used. Intra- and Inter-reader agreements of visual artifact perception were excellent (ICC 0.85-0.92). No quantitative method was able to represent the exact ranking of visually perceived artifacts; however, ICC for manual measurements were low (ICC 0.25-0.97). The method that showed best correspondence and reproducibility used a Fourier-transformed linear ROI and lower-end frequency bins. Automated measurements of artifact extent should be preferred over manual measurements as the latter show a limited reproducibility. One method that allows for automated quantification of such artefacts is made available as an electronic supplement.

Virtual monoenergetic images and post-processing algorithms effectively reduce CT artifacts from intracranial aneurysm treatment

To evaluate artifact reduction by virtual monoenergetic images (VMI) and metal artifact reduction algorithms (MAR) as well as the combination of both approaches (VMI_MAR) compared to conventional CT images (CI) as standard of reference. In this retrospective study, 35 patients were included who underwent spectral-detector CT (SDCT) with additional MAR-reconstructions due to artifacts from coils or clips. CI, VMI, MAR and VMI_MAR (range: 100-200 keV, 10 keV-increment) were reconstructed. Region-of-interest based objective analysis was performed by assessing mean and standard deviation of attenuation (HU) in hypo- and hyperdense artifacts from coils and clips. Visually, extent of artifact reduction and diagnostic assessment were rated. Compared to CI, VMI ≥ 100 keV, MAR and VMI_MAR between 100-200 keV increased attenuation in hypoattenuating artifacts (CI/VMI_200keV/MAR/VMI_MAR200keV, HU: -77.6 ± 81.1/-65.1 ± 103.2/-36.9 ± 27.7/-21.1 ± 26.7) and decreased attenuation in hyperattenuating artifacts (HU: 47.4 ± 32.3/42.1 ± 50.2/29.5 ± 18.9/20.8 ± 25.8). However, differences were only significant for MAR in hypodense and VMI_MAR in hypo- and hyperdense artifacts (p < 0.05). Visually, hypo- and hyperdense artifacts were significantly reduced compared to CI by VMI_{≥140/100keV}, MAR and VMI_MAR≥100keV. Diagnostic assessment of surrounding brain tissue was significantly improved in VMI_≥100keV, MAR and VMI_MAR≥100keV. The combination of VMI and MAR facilitates a significant reduction of artifacts adjacent to intracranial coils and clips. Hence, if available, these techniques should be combined for optimal reduction of artifacts following intracranial aneurysm treatment.

Metal Artifact Reduction in Head CT Performed for Patients with Deep Brain Stimulation Devices: Effectiveness of a Single-Energy Metal Artifact Reduction Algorithm

BACKGROUND AND PURPOSE

Deep brain stimulation electrodes induce massive artifacts on CT images, deteriorating the diagnostic value of examinations. We aimed to investigate the usefulness and potential limitations of a single-energy metal artifact reduction algorithm in head CT performed in patients with implanted deep brain stimulation devices.

MATERIALS AND METHODS

Thirty-four patients with deep brain stimulation (bilateral, n = 28) who underwent head CT on a 320-detector row scanner and whose images were reconstructed with and without single-energy metal artifact reduction at the examinations were retrospectively included. The severity of artifacts around electrodes was assessed objectively using SDs and an artifact index. Two radiologists subjectively evaluated the severity of artifacts from electrodes, the visibility of electrode localization and surrounding structures, and overall diagnostic confidence on 4-point scales. Background image quality (GM-WM contrast and image noise) was subjectively and objectively assessed. The presence and location of artifacts newly produced by single-energy metal artifact reduction were analyzed.

RESULTS

Single-energy metal artifact reduction provided lower objective and subjective metal artifacts and improved visualization of electrode localization and surrounding structures and diagnostic confidence compared with non-single-energy metal artifact reduction images, with statistical significance (all, P < .01). No significant differences were observed in GM-WM contrast and image noise (all, P ≥ .11). The new artifacts from single-energy metal artifact reduction were prominently observed in patients with bilateral deep brain stimulation at high convexity, possibly induced by deep brain stimulation leads placed under the parietal scalp.

CONCLUSIONS

Single-energy metal artifact reduction substantially reduces the metal artifacts from deep brain stimulation electrodes and improves the visibility of intracranial structures without affecting background image quality. However, non-single-energy metal artifact reduction images should be simultaneously reviewed to accurately assess the entire intracranial area, particularly in patients with bilateral deep brain stimulation.

Reduction of Metal Artifacts and Improvement in Dose Efficiency Using Photon-Counting Detector Computed Tomography and Tin Filtration

OBJECTIVES

The aim of this study was to investigate the impact on metal artifacts and dose efficiency of using a tin filter in combination with high-energy threshold (TH) images of a photon-counting detector (PCD) computed tomography (CT) system.

MATERIALS AND METHODS

A 3D-printed spine with pedicle screws was scanned on a PCD-CT system with and without tin filtration. Image noise and severity of artifacts were measured for low-energy threshold (TL) and TH images. In a prospective, institutional review board-approved, Health Insurance Portability and Accountability Act-compliant study, 20 patients having a clinical energy-integrating detector (EID) CT were scanned on a PCD-CT system using tin filtration. Images were reviewed by 3 radiologists to evaluate visualization of anatomic structures, diagnostic confidence, and image preference. Artifact severity and image noise were measured. Wilcoxon signed rank was used to test differences between PCD-CT TH and EID-CT images.

RESULTS

Phantom TH images with tin filtration reduced metal artifacts and had comparable noise (32 HU) to TL images (29 HU) acquired without tin filtration. Visualization scores for the cortex, trabeculae, and implant-trabecular interface from PCD-CT TH images (4.4 ± 0.9, 4.4 ± 1.0, and 4.4 ± 1.0) were significantly higher (P < 0.0001) than EID-CT images (3.3 ± 1.3, 3.3 ± 1.2, and 3.3 ± 1.6). A strong preference was shown for PCD-CT TH images due to improved diagnostic confidence and decreased artifact severity. Noise in PCD-CT TH images (93 ± 41 HU) was significantly lower than that in EID-CT images (133 ± 92 HU, P < 0.05).

CONCLUSIONS

Threshold high images acquired with tin filtration on PCD-CT demonstrated a substantial decrease in metal artifacts and an increase in dose efficiency compared with EID-CT.

Dual-layer spectral computerized tomography for metal artifact reduction: small versus large orthopedic devices

INTRODUCTION

Metal artifacts limit the diagnostic utility of computerized tomography (CT) for implant-related complications. Dual-layer spectral detector CT imaging has been suggested for artifact reduction. Our objective was to evaluate the utility of spectral CT in artifact reduction in patients with small and large metal implants.

METHODS

In this prospective study, patients with metallic orthopedic implants underwent CT imaging using a prototype spectral detector CT scanner. Conventional images were generated with iterative reconstruction at 120 kVp, and virtual monochromatic images were generated at 20-keV intervals between 40 to 200 keV. Conventional and monochromatic images were compared quantitatively using signal-to-noise ratio (SNR) and artifact improvement. Qualitative analysis was performed independently by two musculoskeletal radiologists and included six image quality indicators.

RESULTS

A total of 12 patients were scanned. In monochromatic images, as the energy level increased, the artifact size decreased progressively (p < 0.01). When conventional and monochromatic images were compared, maximum reduction was seen at 200 keV. Using qualitative assessments, 160 and 180 keV levels had the best overall diagnostic image quality. With increased energy level, there was improvement in qualitative ratings of bone-metal interface conspicuity (p = 0.002), degree of streak artifact (p = 0.010) and trabecular bone definition at 1 cm from implant (p = 0.023), and a trend towards significance for bone definition at 5 cm, soft tissue detail and overall diagnostic quality. Subgroup analysis revealed superior artifact reduction in small implants compared to large hardware.

DISCUSSION

Our results support the utility of dual-layer spectral CT in metal artifact reduction. Virtual monochromatic images were diagnostically superior, especially for smaller implants. Virtual monoenergetic images at 160-180 keV are ideal for reducing artifacts.

Dose independent characterization of renal stones by means of dual energy computed tomography and machine learning: an ex-vivo study

OBJECTIVES

To predict the main component of pure and mixed kidney stones using dual-energy computed tomography and machine learning.

METHODS

200 kidney stones with a known composition as determined by infrared spectroscopy were examined using a non-anthropomorphic phantom on a spectral detector computed tomography scanner. Stones were of either pure (monocrystalline, n = 116) or compound (dicrystalline, n = 84) composition. Image acquisition was repeated twice using both, normal and low-dose protocols, respectively (ND/LD). Conventional images and low and high keV virtual monoenergetic images were reconstructed. Stones were semi-automatically segmented. A shallow neural network was trained using data from ND1 acquisition split into training (70%), testing (15%) and validation-datasets (15%). Performance for ND2 and both LD acquisitions was tested. Accuracy on a per-voxel and a per-stone basis was calculated.

RESULTS

Main components were: Whewellite (n = 80), weddellite (n = 21), Ca-phosphate (n = 39), cysteine (n = 20), struvite (n = 13), uric acid (n = 18) and xanthine stones (n = 9). Stone size ranged from 3 to 18 mm. Overall accuracy for predicting the main component on a per-voxel basis attained by ND testing dataset was 91.1%. On independently tested acquisitions, accuracy was 87.1-90.4%.

CONCLUSIONS

Even in compound stones, the main component can be reliably determined using dual energy CT and machine learning, irrespective of dose protocol.

KEY POINTS

• Spectral Detector Dual Energy CT and Machine Learning allow for an accurate prediction of stone composition. • Ex-vivo study demonstrates the dose independent assessment of pure and compound stones. • Lowest accuracy is reported for compound stones with struvite as main component.

Virtual Monoenergetic Images from Spectral Detector CT Enable Radiation Dose Reduction in Unenhanced Cranial CT

BACKGROUND AND PURPOSE

Our aim was to evaluate whether improved gray-white matter differentiation in cranial CT by means of 65- keV virtual monoenergetic images enables a radiation dose reduction compared to conventional images.

MATERIALS AND METHODS

One hundred forty consecutive patients undergoing 171 spectral detector CTs of the head between February and November 2017 (56 ± 19 years of age; male/female ratio, 56%/44%) were retrospectively included. The tube current-time product was reduced during the study period, resulting in 61, 55, and 55 patients being examined with 320, 290, and 260 mAs, respectively. All other scanning parameters were kept identical. The volume CT dose index was recorded. ROIs were placed in gray and white matter on conventional images and copied to identical positions in 65- keV virtual monoenergetic images. The contrast-to-noise ratio was calculated. Two radiologists blinded to the reconstruction technique evaluated image quality on a 5-point Likert-scale. Statistical assessment was performed using ANOVA and Wilcoxon test adjusted for multiple comparisons.

RESULTS

The mean volume CT dose index was 55, 49.8, and 44.7 mGy using 320, 290, and 260 mAs, respectively. Irrespective of the volume CT dose index, noise was significantly lower in 65- keV virtual monoenergetic images compared with conventional images (65- keV virtual monoenergetic images/conventional images: extraocular muscle with 49.8 mGy, 3.7 ± 1.3/5.6 ± 1.6 HU, P < .001). Noise slightly increased with a reduced radiation dose (eg, extraocular muscle in conventional images: 5.3 ± 1.4/5.6 ± 1.6/6.1 ± 2.1 HU). Overall, the contrast-to-noise ratio in 65- keV virtual monoenergetic images was superior to that in conventional images irrespective of the volume CT dose index (P < .001). Particularly, 65-keV virtual monoenergetic images with 44.7 mGy showed significantly lower noise and a higher contrast-to-noise ratio than conventional images with 55 mGy (P < .001). Subjective analysis confirmed better image quality in 65- keV virtual monoenergetic images, even using 44.7 mGy.

CONCLUSIONS

The 65-keV virtual monoenergetic images from spectral detector CT allow radiation dose reduction in cranial CT. While this proof of concept included a radiation dose reduction of 19%, our data suggest that even greater reduction appears achievable.

Dual energy computed tomography virtual monoenergetic imaging: technique and clinical applications

Dual energy CT (DECT) has evolved into a commonly applied imaging technique in clinical routine due to its unique post-processing opportunities for improved evaluation of all body areas. Reconstruction of virtual monoenergetic imaging (VMI) series has shown beneficial effects for both non-contrast and contrast-enhanced DECT due to the flexibility to calculate low-keV VMI reconstructions to increase contrast and iodine attenuation, or to compute high-keV VMI reconstructions to reduce beam-hardening artefacts. The goal of this review article is to explain the technical background of VMI and noise-optimized VMI+ algorithms and to give an overview of useful clinical applications of the VMI technique in DECT of various body regions.

Utility of virtual monoenergetic images from spectral detector computed tomography in improving image segmentation for purposes of 3D printing and modeling

BACKGROUND

One of the key steps in generating three-dimensional (3D) printed models in medicine is segmentation of radiologic imaging. The software tools used for segmentation may be automated, semi-automated, or manual which rely on differences in material density, attenuation characteristics, and/or advanced software algorithms. Spectral Detector Computed Tomography (SDCT) is a form of dual energy computed tomography that works at the detector level to generate virtual monoenergetic images (VMI) at different energies/ kilo-electron volts (keV). These VMI have varying contrast and attenuation characteristics relative to material density. The purpose of this pilot project is to explore the use of VMI in segmentation for medical 3D printing in four separate clinical scenarios. Cases were retrospectively selected based on varying complexity, value of spectral data, and across multiple clinical disciplines (Vascular, Cardiology, Oncology, and Orthopedic).

RESULTS

In all four clinical cases presented, the segmentation process was qualitatively reported as easier, faster, and increased the operator's confidence in obtaining accurate anatomy. All cases demonstrated a significant difference in the calculated Hounsfield Units between conventional and VMI data at the level of targeted segmentation anatomy. Two cases would not have been feasible for segmentation and 3D printing using conventional images only. VMI data significantly reduced conventional CT artifacts in one of the cases.

CONCLUSION

Utilization of VMI from SDCT can improve and assist the segmentation of target anatomy for medical 3D printing by enhancing material contrast and decreasing CT artifact.

Metal artifacts in patients with large dental implants and bridges: combination of metal artifact reduction algorithms and virtual monoenergetic images provides an approach to handle even strongest artifacts

OBJECTIVES

This study compares reduction of strong metal artifacts from large dental implants/bridges using spectral detector CT-derived virtual monoenergetic images (VMI), metal artifact reduction algorithms/reconstructions (MAR), and a combination of both methods (VMI_MAR) to conventional CT images (CI).

METHODS

Forty-one spectral detector CT (SDCT) datasets of patients that obtained additional MAR reconstructions due to strongest artifacts from large oral implants were included. CI, VMI, MAR, and VMI_MAR ranging from 70 to 200 keV (10 keV increment) were reconstructed. Objective image analyses were performed ROI-based by measurement of attenuation (HU) and standard deviation in most pronounced hypo-/hyperdense artifacts as well as artifact impaired soft tissue (mouth floor/soft palate). Extent of artifact reduction, diagnostic assessment of soft tissue, and appearance of new artifacts were rated visually by two radiologists.

RESULTS

The hypo-/hyperattenuating artifacts showed an increase and decrease of HU values in MAR and VMI_MAR (CI/MAR/VMI_MAR-200keV: - 369.8 ± 239.6/- 37.3 ± 109.6/- 46.2 ± 71.0 HU, p < 0.001 and 274.8 ± 170.2/51.3 ± 150.8/36.6 ± 56.0, p < 0.001, respectively). Higher keV values in hyperdense artifacts allowed for additional artifact reduction; however, this trend was not significant. Artifacts in soft tissue were reduced significantly by MAR and VMI_MAR. Visually, high-keV VMI, MAR, and VMI_MAR reduced artifacts and improved diagnostic assessment of soft tissue. Overcorrection/new artifacts were reported that mostly did not hamper diagnostic assessment. Overall interrater agreement was excellent (ICC = 0.85).

CONCLUSIONS

In the presence of strong artifacts due to large oral implants, MAR is a powerful mean for artifact reduction. For hyperdense artifacts, MAR should be supplemented by VMI ranging from 140 to 200 keV. This combination yields optimal artifact reduction and improves the diagnostic image assessment in imaging of the head and neck.

KEY POINTS

• Large oral implants can cause strong artifacts. • MAR is a powerful tool for artifact reduction considering such strong artifacts. • Hyperdense artifact reduction is supplemented by VMI of 140-200 keV from SDCT.