Spectral CT with metal artifacts reduction software for improvement of tumor visibility in the vicinity of gold fiducial markers

Imaging lung tumor motion using integrated-mode proton radiography-A phantom study towards tumor tracking in proton radiotherapy

BACKGROUND

Motion of lung tumors during radiotherapy leads to decreased accuracy of the delivered dose distribution. This is especially true for proton radiotherapy due to the finite range of the proton beam. Methods for mitigating motion rely on knowing the position of the tumor during treatment.

PURPOSE

Proton radiography uses the treatment beam, at an energy high enough to traverse the patient, to produce a radiograph. This work shows the first results of using an integrated-mode proton radiography system to track the position of moving objects in an experimental phantom study; demonstrating the potential of using this method for measuring tumor motion.

METHODS

Proton radiographs of an anthropomorphic lung phantom, with a motor-driven tumor insert, were acquired approximately every 1 s, using tumor inserts of 10, 20, and 30 mm undergoing a known periodic motion. The proton radiography system used a monolithic scintillator block and digital cameras to capture the residual range of each pencil beam passing through the phantom. These ranges were then used to produce a water equivalent thickness map of the phantom. The centroid of the tumor insert in the radiographs was used to determine its position. This measured position was then compared to the known motion of the phantom to determine the accuracy.

RESULTS

Submillimeter accuracy on the measurement of the tumor insert was achieved when using a 30 mm tumor insert with a period of 24 s and was found to be improved for decreasing motion amplitudes with a mean absolute error (MAE) of 1.0, 0.9, and 0.7 mm for 20, 15, and 10 mm respectively. Using smaller tumor inserts reduced the accuracy with a MAE of 1.8 and 1.9 mm for a 20 and 10 mm insert respectively undergoing a periodic motion with an amplitude of 20 mm and a period of 24 s. Using a shorter period resulted in significant motion artifacts reducing the accuracy to a MAE of 2.2 mm for a 12 s period and 3.1 mm for a 6 s period for the 30 mm insert with an amplitude of 20 mm.

CONCLUSIONS

This work demonstrates that the position of a lung tumor insert in a realistic anthropomorphic phantom can be measured with high accuracy using proton radiographs. Results show that the accuracy of the position measurement is the highest for slower tumor motions due to a reduction in motion artifacts. This indicates that the primary obstacle to accurate measurement is the speed of the radiograph acquisition. Although the slower tumor motions used in this study are not clinically realistic, this work demonstrates the potential for using proton radiography for measuring tumor motion with an increased scanning speed that results in a decreased acquisition time.

Needle artifact reduction during interventional CT procedures using a silver filter

BACKGROUND

MAR algorithms have not been productized in interventional imaging because they are too time-consuming. Application of a beam hardening filter can mitigate metal artifacts and doesn't increase computational burden. We evaluate the ability to reduce metal artifacts of a 0.5 mm silver (Ag) additional filter in a Multidetector Computed Tomography (MDCT) scanner during CT-guided biopsy procedures.

METHODS

A biopsy needle was positioned inside the lung field of an anthropomorphic phantom (Lungman, Kyoto Kagaku, Kyoto, Japan). CT acquisitions were performed with beam energies of 100 kV, 120 kV, 135 kV, and 120 kV with the Ag filter and reconstructed using a filtered back projection algorithm. For each measurement, the CTDIvol was kept constant at 1 mGy. Quantitative profiles placed in three regions of the artifact (needle, needle tip, and trajectory artifacts) were used to obtain metrics (FWHM, FWTM, width at - 100 HU, and absolute error in HU) to evaluate the blooming artifact, artifact width, change in CT number, and artifact range. An image quality analysis was carried out through image noise measurement. A one-way analysis of variance (ANOVA) test was used to find significant differences between the conventional CT beam energies and the Ag filtered 120 kV beam.

RESULTS

The 120 kV-Ag is shown to have the shortest range of artifacts compared to the other beam energies. For needle tip and trajectory artifacts, a significant reduction of - 53.6% (p < 0.001) and - 48.7% (p < 0.001) in the drop of the CT number was found, respectively, in comparison with the reference beam of 120 kV as well as a significant decrease of up to - 34.7% in the artifact width (width at - 100 HU, p < 0.001). Also, a significant reduction in the blooming artifact of - 14.2% (FWHM, p < 0.001) and - 53.3% (FWTM, p < 0.001) was found in the needle artifact. No significant changes (p > 0.05) in image noise between the conventional energies and the 120 kV-Ag were found.

CONCLUSIONS

A 0.5 mm Ag additional MDCT filter demonstrated consistent metal artifact reduction generated by the biopsy needle. This reduction may lead to a better depiction of the target and surrounding structures while maintaining image quality.

Evaluation of computed tomography metal artifact and CyberKnife fiducial recognition for novel size fiducial markers

PURPOSE

This study aimed to compare fiducial markers used in CyberKnife treatment in terms of metal artifact intensity observed in CT images and fiducial recognition in the CyberKnife system affected by patient body thickness and type of marker.

METHODS

Five markers, ACCULOC 0.9 mm × 3 mm, Ball type Gold Anchor (GA) 0.28 mm × 10 mm, 0.28 mm × 20 mm, and novel size GA 0.4 mm × 10 mm, 0.4 mm × 20 mm were evaluated. To evaluate metal artifacts of CT images, two types of CT images of water-equivalent gels with each marker were acquired using Aquilion LB CT scanner, one applied SEMAR (SEMAR-on) and the other did not apply this technique (SEMAR-off). The evaluation metric of artifact intensity (MSD ) which represents a variation of CT values were compared for each marker. Next, 5, 15, and 20 cm thickness of Tough Water (TW) was placed on the gel under the condition of overlapping the vertebral phantom in the Target Locating System, and the live image of each marker was acquired to compare fiducial recognition.

RESULTS

The mean MSD of SEMAR-off was 78.80, 74.50, 97.25, 83.29, and 149.64 HU for ACCULOC, GA0.28 mm × 10 mm, 20 mm, and 0.40 mm × 10 mm, 20 mm, respectively. In the same manner, that of SEMAR-on was 23.52, 20.26, 26.76, 24.89, and 33.96 HU, respectively. Fiducial recognition decreased in the order of 5, 15, and 20 cm thickness, and GA 0.4 × 20 mm showed the best recognition at thickness of 20 cm TW.

CONCLUSIONS

We demonstrated the potential to reduce metal artifacts in the CT image to the same level for all the markers we evaluated by applying SEMAR. Additionally, the fiducial recognition of each marker may vary depending on the thickness of the patient's body. Particularly, we showed that GA 0.40 × 20 mm may have more optimal recognition for CyberKnife treatment in cases of high bodily thickness in comparison to the other markers.

Diagnosis and Management of Persistent Pulmonary Arterio-venous Malformations following Embolotherapy

Embolotherapy is the primary treatment for pulmonary arterio-venous malformations (PAVMs). Approximately, 2-25% of PAVMs demonstrate persistence following embolization. Early identification and treatment of persistent PAVMs are critical to mitigating life threatening complications. The presence of prior embolic devices and complex angioarchitecture of persistent PAVMs pose technical challenges during repeat embolotherapy. In this article, we review patterns of persistence, factors affecting the persistence, endovascular treatment techniques, and outcomes.

Feasibility study of deep learning-based markerless real-time lung tumor tracking with orthogonal X-ray projection images

PURPOSE

The feasibility of a deep learning-based markerless real-time tumor tracking (RTTT) method was retrospectively studied with orthogonal kV X-ray images and clinical tracking records acquired during lung cancer treatment.

METHODS

Ten patients with lung cancer treated with marker-implanted RTTT were included. The prescription dose was 50 Gy in four fractions, using seven- to nine-port non-coplanar static beams. This corresponds to 14-18 X-ray tube angles for an orthogonal X-ray imaging system rotating with the gantry. All patients underwent 10 respiratory phases four-dimensional computed tomography. After a data augmentation approach, for each X-ray tube angle of a patient, 2250 digitally reconstructed radiograph (DRR) images with gross tumor volume (GTV) contour labeled were obtained. These images were adopted to train the patient and X-ray tube angle-specific GTV contour prediction model. During the testing, the model trained with DRR images predicted GTV contour on X-ray projection images acquired during treatment. The predicted three-dimensional (3D) positions of the GTV were calculated based on the centroids of the contours in the orthogonal images. The 3D positions of GTV determined by the marker-implanted RTTT during the treatment were considered as the ground truth. The 3D deviations between the prediction and the ground truth were calculated to evaluate the performance of the model.

RESULTS

The median GTV volume and motion range were 7.42 (range, 1.18-25.74) cm³ and 22 (range, 11-28) mm, respectively. In total, 8993 3D position comparisons were included. The mean calculation time was 85 ms per image. The overall median value of the 3D deviation was 2.27 (interquartile range: 1.66-2.95) mm. The probability of the 3D deviation smaller than 5 mm was 93.6%.

CONCLUSIONS

The evaluation results and calculation efficiency show the proposed deep learning-based markerless RTTT method may be feasible for patients with lung cancer.

Accuracy and consistency of intensity-based deformable image registration in 4DCT for tumor motion estimation in liver radiotherapy planning

We investigate the accuracy of intensity-based deformable image registration (DIR) for tumor localization in liver stereotactic body radiotherapy (SBRT). We included 4DCT scans to capture the breathing motion of eight patients receiving SBRT for liver metastases within a retrospective clinical study. Each patient had three fiducial markers implanted. The liver and the tumor were delineated in the mid-ventilation phase, and their positions in the other phases were estimated with deformable image registration. We tested referenced and sequential registrations strategies. The fiducial markers were the gold standard to evaluate registration accuracy. The registration errors related to measured versus estimated fiducial markers showed a mean value less than 1.6mm. The positions of some fiducial markers appeared not stable on the 4DCT throughout the respiratory phases. Markers’ center of mass tends to be a more reliable measurement. Distance errors of tumor location based on registration versus markers center of mass were less than 2mm. There were no statistically significant differences between the reference and the sequential registration, i.e., consistency and errors were comparable to resolution errors. We demonstrated that intensity-based DIR is accurate up to resolution level for locating the tumor in the liver during breathing motion.

Reduction of Peristalsis-Related Streak Artifacts on the Liver with Dual-Layer Spectral CT

Background: Peristalsis-related streak artifacts on the liver compromise image quality and diagnostic accuracy. Purpose: To assess dual-layer spectral-detector computed tomography (CT) image reconstructions for reducing intestinal peristalsis-related streak artifacts on the liver. Methods: We retrospectively evaluated 220 contrast-enhanced abdominal dual-energy CT scans in 131 consecutive patients (mean age: 68 ± 10 years, 120 men) who underwent routine clinical dual-layer spectral-detector CT imaging (120 kVp, 40 keV, 200 keV, virtual non-contrast (VNC), iodine images). Two independent readers evaluated bowel peristalsis streak artifacts on the liver qualitatively on a five-point Likert scale (1 = none to 5 = severe) and quantitatively by depth of streak artifact extension into the liver and measurements of Hounsfield Unit and iodine concentration differences from normal liver. Artifact severity between image reconstructions were compared by Wilcoxon signed-rank and paired t-tests. Results: 12 scans were excluded due to missing spectral data, artifacts on the liver originating from metallic foreign materials, or oral contrast material. Streak artifacts on the liver were seen in 51/208 (25%) scans and involved the left lobe only in 49/51 (96%), the right lobe only in 0/51 (0%), and both lobes in 2/51 (4%) scans. Artifact frequency was lower in iodine than in 120 kVp images (scans 18/208 vs. 51/208, p < 0.001). Artifact severity was less in iodine than in 120 kVp images (median score 1 vs. 3, p < 0.001). Streak artifact extension into the liver was shorter in iodine than 120 kVp images (mean length 2 ± 4 vs. 12 ± 5 mm, p < 0.001). Hounsfield Unit and iodine concentration differed significantly between bright streak artifacts and normal liver in 120 kVp, 40 keV, 200 keV, and VNC images (p < 0.001, each), but not in iodine images (p = 0.23). Conclusion: Intestinal peristalsis-related streak artifacts commonly affect the left liver lobe at CT and can be substantially reduced by viewing iodine dual-energy CT image reconstructions.

Development of a deep learning-based patient-specific target contour prediction model for markerless tumor positioning

PURPOSE

For pancreatic cancer patients, image guided radiation therapy and real-time tumor tracking (RTTT) techniques can deliver radiation to the target accurately. Currently, for the radiation therapy machine with kV X-ray imaging systems, internal markers must be implemented to facilitate tumor tracking. The purpose of this study was to develop a markerless deep learning-based pancreatic tumor positioning procedure for real-time tumor tracking with a kV X-ray imaging system.

METHODS AND MATERIALS

Fourteen pancreatic cancer patients treated with intensity-modulated radiation therapy from six fixed gantry angles with a gimbal-head radiotherapy system were included in this study. For a gimbal-head radiotherapy system, the three-dimensional (3D) intrafraction target position can be determined using an orthogonal kV X-ray imaging system. All patients underwent four-dimensional computed tomography (4DCT) simulations for treatment planning, which were divided into 10 respiratory phases. After a patient's 4DCT was acquired, for each X-ray tube angle, 10 digitally reconstructed radiograph (DRR) images were obtained. Then, a data augmentation procedure was conducted. The data augmentation procedure first rotated the CT volume around the superior-inferior and anterior-posterior directions from -3^° to 3^° in 1.5^° intervals. Then, the Super-SloMo model was adapted to interpolate 10 frames between respiratory phases. In total, the data augmentation procedure expanded the data scale 250-fold. In this study, for each patient, 12 datasets containing the DRR images from each specific X-ray tube angle based on the radiation therapy plan were obtained. The augmented dataset was randomly divided into training and testing datasets. The training dataset contained 2000 DRR images with clinical target volume (CTV) contours labeled for fine-tuning the pre-trained target contour prediction model. After the fine-tuning, the patient and X-ray tube angle-specific CTV contour prediction model was acquired. The testing dataset contained the remaining 500 images to evaluate the performance of the CTV contour prediction model. The dice similarity coefficient (DSC) between the area enclosed by the CTV contour and predicted contour was calculated to evaluate the model's contour prediction performance. The 3D position of the CTV was calculated based on the centroid of the contour in the orthogonal DRR images, and the 3D error of the prediction position was calculated to evaluate the CTV positioning performance. For each patient, the DSC results from 12 X-ray tube angles and 3D error from 6 gantry angles were calculated, representing the novelty of this study.

RESULTS

The mean and standard deviation (SD) of all patients' DSCs were 0.98 and 0.015, respectively. The mean and SD of the 3D error were 0.29 mm and 0.14 mm, respectively. The global maximum 3D error was 1.66 mm, and the global minimum DSC was 0.81. The mean calculation time for CTV contour prediction was 55 ms per image. This fulfills the requirement of RTTT.

CONCLUSIONS

Regarding the positioning accuracy and calculation efficiency, the presented procedure can provide a solution for markerless real-time tumor tracking for pancreatic cancer patients. This article is protected by copyright. All rights reserved.

Preoperative normalized iodine concentration derived from spectral CT is correlated with early recurrence of hepatocellular carcinoma after curative resection

OBJECTIVES

To investigate whether normalized iodine concentration (NIC) correlates with tumor microvessel density and early recurrence in patients with HCC.

MATERIALS AND METHODS

We included 71 patients with surgically resected single HCC in this prospective study who underwent preoperative spectral CT between November 2014 and June 2016. Two observers independently measured the NIC in the arterial phase (AP) and portal venous phase (PVP). The relationship between NIC and microvessel density was evaluated. Univariate and multivariate logistic regression was performed to evaluate independent predictors of early recurrence.

RESULTS

Early recurrence occurred in 28 of 71 patients (39.4%) during the 2-year follow-up. NIC-AP positively correlated with microvessel density for the two observers (r = 0.593 and 0.527). Based on multivariate analysis, independent risk factors for early HCC recurrence were tumor size (odds ratio, 1.200; p = 0.043) and NIC-AP (odds ratio, 2.522; p = 0.005). For the two observers, areas under the receiver operating characteristic curve for predicting early HCC recurrence were 0.719 and 0.677. Early recurrence rates were significantly higher among patients with NIC-AP values higher than the optimal cutoff than among those with values below the cutoff.

CONCLUSION

Normalized iodine concentration in the arterial phase from spectral CT reflects tumor-derived angiogenesis and is a potential predictive biomarker for early recurrence of hepatocellular carcinoma.

KEY POINTS

• Normalized iodine concentration in the arterial phase positively correlated with microvessel density of hepatocellular carcinoma. • In the patients with hepatocellular carcinoma, tumor size and normalized iodine concentration in the arterial phase were independent risk factors for early hepatocellular carcinoma recurrence. • Early hepatocellular carcinoma recurrence rates were significantly higher when normalized iodine concentration in the arterial phase values was above the optimal cutoff.

Improvement of image quality and diagnostic confidence using Smart MAR - a projection-based CT protocol in patients with orthopedic metallic implants in hip, spine, and shoulder

BACKGROUND

In computed tomography (CT) scans, artifacts caused by metallic orthopedic implants still hamper the visualization of important, periprosthetic tissues. Smart MAR metal artifact reduction tool is a promising three-stage, projection-based, post-processing algorithm.

PURPOSE

To determine whether the Smart MAR tool improves subjective and objective image quality and diagnostic confidence in patients with orthopedic implants of the hip, spine, and shoulder.

MATERIAL AND METHODS

Seventy-two patients with orthopedic screws, hip/shoulder replacement, or spine spondylodesis were included. CT scans were performed on a single-source multislice CT scanner, raw data were post-processed using Smart MAR. Image quality was evaluated both quantitatively (ROI-based) and qualitatively (rater-based) and compared to iterative reconstructions (ASIR V). As comparative standard for artificial prosthetic breaks or loosening, follow-up examinations were used.

RESULTS

Smart MAR reconstructions of the hip (n = 23), spine (n = 26), and shoulder (n = 23) showed a significantly reduced attenuation and noise of regions adjacent to metallic implants (P<0.002). Subjective image quality (P<0.005, shoulder P = 0.038/P = 0.046) and overall diagnostic confidence were higher in Smart MAR (all regions P<0.002). Signal-to-noise ratio (SNR; P = 0.72/P = 0.96) was not improved. Compared to standard ASIR V new, artificial metal extinctions (up to 50%) or periprosthetic hem lines (48%-73%) were introduced by Smart MAR.

CONCLUSION

Smart MAR improved image quality of the hip, spine, and shoulder CT scans resulting in higher diagnostic confidence in evaluation of periprosthetic soft tissues. As shown for spine implants, it should be used with caution and as a complementary tool for evaluation of periprosthetic loosening or integrity of metal implant, as in many cases it introduced new artifacts.

Diagnostic Value of Model-Based Iterative Reconstruction Combined with a Metal Artifact Reduction Algorithm during CT of the Oral Cavity

BACKGROUND AND PURPOSE

Metal artifacts reduce the quality of CT images and increase the difficulty of interpretation. This study compared the ability of model-based iterative reconstruction and hybrid iterative reconstruction to improve CT image quality in patients with metallic dental artifacts when both techniques were combined with a metal artifact reduction algorithm.

MATERIALS AND METHODS

This retrospective clinical study included 40 patients (men, 31; women, 9; mean age, 62.9 ± 12.3 years) with oral and oropharyngeal cancer who had metallic dental fillings or implants and underwent contrast-enhanced ultra-high-resolution CT of the neck. Axial CT images were reconstructed using hybrid iterative reconstruction and model-based iterative reconstruction, and the metal artifact reduction algorithm was applied to all images. Finally, hybrid iterative reconstruction + metal artifact reduction algorithms and model-based iterative reconstruction + metal artifact reduction algorithm data were obtained. In the quantitative analysis, SDs were measured in ROIs over the apex of the tongue (metal artifacts) and nuchal muscle (no metal artifacts) and were used to calculate the metal artifact indexes. In a qualitative analysis, 3 radiologists blinded to the patients' conditions assessed the image-quality scores of metal artifact reduction and structural depictions.

RESULTS

Hybrid iterative reconstruction + metal artifact reduction algorithms and model-based iterative reconstruction + metal artifact reduction algorithms yielded significantly different metal artifact indexes of 82.2 and 73.6, respectively (95% CI, 2.6-14.7; P < .01). The latter algorithms resulted in significant reduction in metal artifacts and significantly improved structural depictions(P < .01).

CONCLUSIONS

Model-based iterative reconstruction + metal artifact reduction algorithms significantly reduced the artifacts and improved the image quality of structural depictions on neck CT images.

Single-Energy Retrospective Metal Artifact Reduction Using Adaptive Thresholding for Metal Implants in the Abdomen and Pelvis

OBJECTIVE

To assess impact of single-energy metal artifact reduction (SEMAR) algorithm utilizing retrospective adaptive thresholding in reducing metal artifacts in the abdomen and pelvis.

METHODS

In this prospective institutional review board-approved, Health Insurance Portability and Accountability Act-compliant study, 90 patients with various metals (n = 97) on computed tomography of abdomen and pelvis (Canon Medical, Aquilion ONE and PRIME) scanned 07/2017-09/2018 with SEMAR retrospectively applied were included. Density was measured in the near and far field to the metals. Density standard deviation (SD), representing artifact severity, was compared with and without SEMAR applied. Two trained human observers independently evaluated severity of artifacts on a five-point scale (0, no artifact; 5, severe artifact).

RESULTS

The SEMAR significantly decreased artifact severity in the near field of high-density metal implants (SD of 204 ± 101HU without vs. 66 ± 40HU with SEMAR, P < 0.001). In the far field, the artifact severity was similar (40 ± 31HU without vs. 36 ± 27HU with SEMAR, P = 0.41). Artifact severity was decreased adjacent to low-density metal in the near field (SD of 86 ± 56HU without vs 49 ± 30HU with SEMAR, P < 0.001). In the far field to the low-density metals artifact severity was similar (33 ± 29HU without vs. 31 ± 27HU with SEMAR, P = 0.79). Subjectively, artifacts severity decreased for high-density metals in near field by 1.3 ± 1.0, and in far field by 0.7 ± 0.7 and for low-density metals in the near field by 0.7 ± 1.0, far field 0.4 ± 0.5, all P < 0.05.

CONCLUSIONS

The SEMAR retrospective algorithm with adaptive thresholding subjectively and objectively reduced near-field artifacts generated by high- and low-density metals.

Clinical application of multi-material artifact reduction (MMAR) technique in Revolution CT to reduce metallic dental artifacts

Background

This study aimed to explore the performance of Revolution CT virtual monoenergetic images (VMI) combined with the multi-material artifact reduction (MMAR) technique in reducing metal artifacts in oral and maxillofacial imaging.

Results

There were significant differences in image quality scores between VMI + MMAR images and VMI+MARS (multiple artifact reduction system) images at each monochromatic energy level (p = 0.000). Compared with the MARS technology, the MMAR technology further reduced metal artifacts and improved the image quality. At VMI_{90 keV} and VMI_{110 keV}, the SD, CNR, and AI in the Revolution CT group were significantly lower than in the Discovery CT, but no significant differences in these parameters were found between two groups at VMI_{50 keV}, VMI_{70 keV}, and VMI_{130 keV} (p > 0.05). The attenuation was comparable between two groups at any energy level (p > 0.05).

Conclusions

Compared with the MARS reconstruction technique of Discovery CT, the MMAR technique of Revolution CT is better to reduce the artifacts of dental implants in oral and maxillofacial imaging, which improves the image quality and the diagnostic value of surrounding soft tissues.

White paper on pancreatic ductal adenocarcinoma from society of abdominal radiology's disease-focused panel for pancreatic ductal adenocarcinoma: Part II, update on imaging techniques and screening of pancreatic cancer in high-risk individuals

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive gastrointestinal malignancy with a poor 5-year survival rate. Its high mortality rate is attributed to its aggressive biology and frequently late presentation. While surgical resection remains the only potentially curative treatment, only 10-20% of patients will present with surgically resectable disease. Over the past several years, development of vascular bypass graft techniques and introduction of neoadjuvant treatment regimens have increased the number of patients who can undergo resection with a curative intent. While the role of conventional imaging in the detection, characterization, and staging of patients with PDAC is well established, its role in monitoring treatment response, particularly following neoadjuvant therapy remains challenging because of the complex anatomic and histological nature of PDAC. Novel morphologic and functional imaging techniques (such as DECT, DW-MRI, and PET/MRI) are being investigated to improve the diagnostic accuracy and the ability to measure response to therapy. There is also a growing interest to detect PDAC and its precursor lesions at an early stage in asymptomatic patients to increase the likelihood of achieving cure. This has led to the development of pancreatic cancer screening programs. This article will review recent updates in imaging techniques and the current status of screening and surveillance of individuals at a high risk of developing PDAC.

Evaluation of the Visibility and Artifacts of 11 Common Fiducial Markers for Image Guided Stereotactic Body Radiation Therapy in the Abdomen

PURPOSE

The purpose of this study was to quantitatively evaluate the visibility and artifacts of commercially available fiducial markers to optimize their selection for image guided stereotactic body radiation therapy.

METHODS AND MATERIALS

From 6 different vendors, we selected 11 fiducials commonly used in image guided radiation therapy. The fiducials varied in material composition (e.g., gold, platinum, carbon), shape (e.g., cylindrical, notched/linear, coiled, ball-like, step), and size measured in terms of diameter (0.28-1.0 mm) and length (3.0-20.0 mm). Each fiducial was centered in 4-mm bolus within a 13-cm-thick water-equivalent phantom. Fiducials were imaged with the use of a simulation computed tomography (CT) scanner, a CT-on-rails system, and an onboard cone beam CT system. Acquisition parameters were set according to clinical protocols. Visibility was assessed in terms of contrast (Δ Hounsfield unit [HU]) and the Michelson visibility metric. Artifacts were quantified in terms of relative standard deviation and relative streak artifacts level (rSAL). Twelve radiation oncologists ranked each fiducial in terms of clinical usefulness.

RESULTS

Contrast and artifacts increased with fiducial size. For CT imaging, maximum contrast (2722 HU) and artifacts (rSAL = 2.69) occurred for the largest-diameter (0.75 mm) platinum fiducial. Minimum contrast (551 HU) and reduced artifacts (rSAL = 0.65) were observed for the smallest-diameter (0.28 mm) gold fiducial. Carbon produced the least severe artifacts (rSAL = 0.29). The survey indicated that physicians preferred gold fiducials with a 0.35- to 0.43-mm diameter, 5- to 10-mm length, and coiled or cylindrical shape that balanced contrast and artifacts.

CONCLUSIONS

We evaluated 11 different fiducials in terms of visibility and artifacts. The results of this study may assist radiation oncologists who seek to maximize contrast, minimize artifacts, or balance contrast versus artifacts by fiducial selection.

Block matching frame based material reconstruction for spectral CT

Spectral computed tomography (CT) has a great potential in material identification and decomposition. To achieve high-quality material composition images and further suppress the x-ray beam hardening artifacts, we first propose a one-step material reconstruction model based on Taylor's first-order expansion. Then, we develop a basic material reconstruction method named material simultaneous algebraic reconstruction technique (MSART). Considering the local similarity of each material image, we incorporate a powerful block matching frame (BMF) into the material reconstruction (MR) model and generate a BMF based MR (BMFMR) method. Because the BMFMR model contains the L 0-norm problem, we adopt a split-Bregman method for optimization. The numerical simulation and physical phantom experiment results validate the correctness of the material reconstruction algorithms and demonstrate that the BMF regularization outperforms the total variation and no-local mean regularizations.

Quantifying the angiogenesis of C6 glioma in rats based on CT quantitative parameters

Background

Glioma is the most common neoplasm that is neuroepithelial in nature. However, Spectral computed tomography (CT) has rarely been reported to detect angiogenesis in tumors.

Purpose

To investigate the value of multi-parameter spectral CT for the detection of angiogenesis in C6 glioma in rats.

Material and Methods

Fifteen male Wistar rats were seeded with C6 glioma cells in the right basal ganglia and spectral CT-enhanced scanning was performed at days 7, 10, and 14 after the C6 glioma cells were seeded. The spectral CT parameters were measured in three areas: the solid tumor; the peritumoral area; and the contralateral mirror area. After different periods of scanning, the rats’ brain tissue was stained with HE and CD105 immunohistochemical staining. Different periods of spectral CT quantitative parameters and pathological images were analyzed.

Results

The spectral CT parameter and CD105 among the solid tumor, peritumoral area, and contralateral mirror area were significantly different: monochromatic CT value (211.30 ± 34.67 HU, 119.16 ± 13.31 HU, and 55.59 ± 7.87 HU, P < 0.001); CD105 (16.14 ± 1.91, 6.79 ± 1.31, and 2.50 ± 0.51, P < 0.001); spectral curve slope (10.35 ± 1.89, 5.33 ± 0.87, 0.88 ± 0.26, P < 0.001); iodine (water) value (49.75 ± 9.02, 26.04 ± 4.32, 4.36 ± 1.18, P < 0.001). CD105 correlated strongly with the CT value at 65 keV (correlation coefficient r = 0.98, P < 0.001).

Conclusion

Multi-parameter spectral CT can reflect the formation of tumor angiogenesis in rat C6 glioma to a certain extent and can be used as an effective means to evaluate glioma.

Noise-optimised virtual monoenergetic imaging of dual-energy CT: effect on metal artefact reduction in patients with lumbar internal fixation

PURPOSE

The purpose of this study was to evaluate the effects of noise-optimised virtual monoenergetic imaging (VMI+) reconstructions on reducing metal artefacts compared to traditional virtual monoenergetic imaging (VMI) and linearly blended (M_0.6) reconstructions in patients with lumbar metal internal fixation in dual-energy CT (DECT).

METHODS

Forty patients who underwent DECT were evaluated in this retrospective study. Images were reconstructed with M_0.6 and with VMI+ and VMI at 10-keV intervals from 40 keV to 190 keV. Attenuation and noise were measured in the hyperdense artefacts, hypodense artefacts, spinal canal, abdominal aorta (AA), and inferior vena cava (IVC). An artefact index (AI) was calculated. A subjective evaluation of the metal-bone interface, surrounding soft tissue, spinal canal, AA, and IVC was conducted.

RESULTS

The AI values for the hypodense artefacts, spinal canal, and IVC were lowest in the 130 keV VMI+ series, for the hyperdense artefacts in the 120 keV VMI+ series, and for the AA in the 190 keV VMI+ series. Except for the hypodense artefacts, the AI values were lower compared to the M_0.6 images and all the VMI series (all p < 0.05). The subjective image quality was highest at 130 keV VMI+ for the metal-bone interface, surrounding soft tissue, AA, and IVC, and at 120 keV VMI+ for the spinal canal. Except for the AA, these rating scores were higher compared to the M_0.6 images and the entire VMI series (all p < 0.05).

CONCLUSIONS

DECT with high-keV VMI+ efficiently reduces metal artefacts and shows superior image quality in patients with lumbar internal fixation. These slides can be retrieved from Electronic Supplementary Material.

Orthopedic metallic hardware in routine abdomino-pelvic CT scans: occurrence and clinical significance

PURPOSE

To study the occurrence of orthopedic metallic hardware in routine abdomen/pelvic computed tomography (CT) scans and their impact on image quality (IQ) and diagnostic evaluation.

MATERIAL AND METHODS

In this retrospective single institution study, we analyzed 3500 consecutive abdomen/pelvis CT scans for occurrence of orthopedic metallic hardware. In the cohort of patients with metallic hardware detected on CT scans, subjective and objective IQ analysis was performed to estimate diagnostic acceptability (DA, 4-point scale), subjective noise (SN, 3-point scale), presence of artifacts (PA, 4-point scale) and objective noise. The clinical significance of metallic hardware was determined by evaluating the impact of artifacts on radiological diagnosis according to the clinical indication and disease type.

RESULTS

Orthopedic metallic hardware was encountered in 4.97% of abdomino-pelvic CT scans (n = 174/3500), and artifacts related to the hardware in the region of clinical interest were identified in 82% (n = 144/174) of scans. The overall mean DA was 2.66 (n = 174), and it was severely limited (score < 2) in 32% of cases particularly affecting patients with bilateral hip implants (92.6%, n = 25/27). The artifacts due to hardware significantly limited diagnostic evaluation in 58.6% of cases (PA score ≥ 3), and the image noise was unacceptable in 71% of cases (SN score > 2) in the region of clinical interest.

CONCLUSION

Orthopedic metallic hardware is encountered in nearly 5% of abdomino-pelvic CT scans and causes significant image degradation limiting diagnostic evaluation in the region of clinical interest.

Quality of CT Imaging of Periocular Metallic Foreign Bodies Using Artifact Reduction Software

PURPOSE

CT is the standard of care for assessment of ocular and orbital trauma; however, artifacts from metallic foreign bodies can limit the utility of CT. The authors hypothesize that implementation of metal artifact reduction techniques can improve image quality and diagnostic confidence for a diverse group of interpreters.

METHODS

A case series of ten subjects with retained periocular metallic foreign bodies imaged with CT were identified retrospectively from a large urban trauma center. Postacquisition images were processed with an iterative-based metal streak artifact reduction software. The severity of the metal streak artifact was assessed by clinicians including radiologists (4), ophthalmologists (4), and oculoplastic specialists (3) using a numeric scale to grade images on seven clinically relevant criteria. Each image was also analyzed to measure the size of the artifact and degree of streaking.

RESULTS

Overall confidence in diagnosis and severity of metallic streak was improved with metallic artifact reduction (p < 0.001, Wilcoxon signed-rank test). Similarly, confidence in assessing specific features-including extra-ocular muscle, optic nerve, globe rupture, orbital fracture and identification of foreign bodies-was improved after metallic artifact reduction (p < 0.001, Wilcoxon signed-rank test). The standard deviation of pixel intensity for a path surrounding the foreign body as well as the area of the streak artifact decreased in the metallic artifact reduction-processed images (p < 0.001, paired t test).

CONCLUSIONS

Metal artifact reduction in CT has potential benefits in improving image quality and reader confidence for periocular trauma cases in real-world settings.

[Effect of Hybrid Iterative Reconstruction on CT Image Quality Using Metal Artifact Reduction]

PURPOSE

This study aimed to evaluate the effect of adaptive iterative dose reduction 3D (AIDR 3D) on the computed tomography (CT) image quality by using single energy metal artifact reduction (SEMAR).

MATERIALS & METHODS

A water phantom (22 cmφ) with the stem for total hip arthroplasty made of titanium was scanned. The volume CT dose index (CTDI_vol) was set to 8.9 and 5.0 mGy. The reconstruction was performed using filtered back projection and AIDR 3D by soft kernel (FC13) and SEMAR. The averaged profile method was used for the quantitative evaluation of artifacts. We placed a rectangular region-of-interest on the artifact part, and obtained the x-direction averaged profile (Profile A). Profile B was obtained using a water phantom without metal. Profiles A and B were normalized as Profiles A' and B' using the mean value calculated from Profile B. Based on the standard deviation (SD) calculated from Profile B', the background variation level was defined as ±2SD, and subtracted from Profile A' (Profile A″). Finally, the area of Profile A″ was calculated and defined as Artifact_total. Artifact_over, and Artifact_under, respectively, the positive- and negative-side components of Artifact_total.

RESULTS

Both Artifact_total and Artifact_under increased according to the strength of AIDR 3D. The variations of Artifact_over and Artifact_under, due to the AIDR 3D strength, were small and large, respectively. Further, in comparison with a high dose, the effect of artifact emphasis increased at low dose. Therefore, it should be noted that stronger AIDR 3D can emphasize the residual metal artifact.

Evaluation of Orthopedic Metal Artifact Reduction Application in Three-Dimensional Computed Tomography Reconstruction of Spinal Instrumentation: A Single Saudi Center Experience

Aim of the Study:

The aim of the study was to evaluate the commercially available orthopedic metal artifact reduction (OMAR) technique in postoperative three-dimensional computed tomography (3DCT) reconstruction studies after spinal instrumentation and to investigate its clinical application.

Materials and Methods:

One hundred and twenty (120) patients with spinal metallic implants were included in the study. All had 3DCT reconstruction examinations using the OMAR software after obtaining the informed consents and approval of the Institution Ethical Committee. The degree of the artifacts, the related muscular density, the clearness of intermuscular fat planes, and definition of the adjacent vertebrae were qualitatively evaluated. The diagnostic satisfaction and quality of the 3D reconstruction images were thoroughly assessed.

Results:

The majority (96.7%) of 3DCT reconstruction images performed were considered satisfactory to excellent for diagnosis. Only 3.3% of the reconstructed images had rendered unacceptable diagnostic quality.

Conclusion:

OMAR can effectively reduce metallic artifacts in patients with spinal instrumentation with highly diagnostic 3DCT reconstruction images.

How Well Does Dual-energy CT with Fast Kilovoltage Switching Quantify CT Number and Iodine and Calcium Concentrations?

RATIONALE AND OBJECTIVES

Because it is imperative for understanding the performance of dual-energy computed tomography scanner to determine clinical diagnosis, we aimed to assess the accuracy of quantitative measurements using dual-energy computed tomography with fast kilovoltage switching.

MATERIALS AND METHODS

Quantitative measurements were performed for 16 reference materials (physical density, 0.965-1.550 g/cm³; diameter of rod, 2.0-28.5 mm; iodine concentration, 2-15 mg/mL; and calcium concentration, 50-300 mg/mL) with varying scanning settings, and the measured values were compared to their theoretical values.

RESULTS

For high-density material, the maximum differences in Hounsfield unit values in the virtual monochromatic images at 50, 70, and 100 keV were -176.2, 61.0, and -35.2 HU, respectively, and the standard deviations over short- and long-term periods were 11.1, 6.1, and 3.5 HU at maximum. The accuracy of the Hounsfield unit measurement at 50 and 70 keV was significantly higher (P < 0.05) with higher radiation output and smaller phantom size. The difference in the iodine and calcium measurements in the large phantom were up to -2.6 and -60.4 mg/mL for iodine (5 mg/mL with 2-mm diameter) and calcium (300 mg/mL) materials, and the difference was improved with a small phantom. Metal artifact reduction software improved subjective image quality; however, the quantitative values were significantly underestimated (P < 0.05) (-49.5, -26.9, and -15.3 HU for 50, 70, and 100 keV, respectively; -1.0 and -17 mg/mL for iodine and calcium concentration, respectively) compared to that acquired without a metal material.

CONCLUSIONS

The accuracy of quantitative measurements can be affected by material density and the size of the object, radiation output, phantom size, and the presence of metal materials.

Investigation of radiomic signatures for local recurrence using primary tumor texture analysis in oropharyngeal head and neck cancer patients

Radiomics is one such "big data" approach that applies advanced image refining/data characterization algorithms to generate imaging features that can quantitatively classify tumor phenotypes in a non-invasive manner. We hypothesize that certain textural features of oropharyngeal cancer (OPC) primary tumors will have statistically significant correlations to patient outcomes such as local control. Patients from an IRB-approved database dispositioned to (chemo)radiotherapy for locally advanced OPC were included in this retrospective series. Pretreatment contrast CT scans were extracted and radiomics-based analysis of gross tumor volume of the primary disease (GTVp) were performed using imaging biomarker explorer (IBEX) software that runs in Matlab platform. Data set was randomly divided into a training dataset and test and tuning holdback dataset. Machine learning methods were applied to yield a radiomic signature consisting of features with minimal overlap and maximum prognostic significance. The radiomic signature was adapted to discriminate patients, in concordance with other key clinical prognosticators. 465 patients were available for analysis. A signature composed of 2 radiomic features from pre-therapy imaging was derived, based on the Intensity Direct and Neighbor Intensity Difference methods. Analysis of resultant groupings showed robust discrimination of recurrence probability and Kaplan-Meier-estimated local control rate (LCR) differences between "favorable" and "unfavorable" clusters were noted.

Dosimetry Effects Caused by Unilateral and Bilateral Hip Prostheses: A Monte Carlo Case Study in Megavoltage Photon Radiotherapy for Computed Tomography Data without Metal Artifacts

Background:

Hip prostheses (HPs) are routinely used in hip augmentation to replace painful or dysfunctional hip joints. However, high-density and high-atomic-number (Z) inserts may cause dose perturbations in the target volume and interface regions.

Aim:

To evaluate the dosimetric influence of various HPs during megavoltage conformal radiotherapy (RT) of the prostate using Monte Carlo (MC) simulations.

Materials and Methods:

BEAMnrc and DOSXYZnrc MC user-codes were respectively used to simulate the linac head and to calculate 3D absorbed dose distributions in a computed tomography (CT)-based phantom. A novel technique was used to synthetically introduce HPs into the raw patient CT dataset. The prosthesis materials evaluated were stainless steel (SS316L), titanium (Ti6Al4V), and ultra-high-molecular-weight polyethylene (UHMWPE). Four, five, and six conformal photon fields of 6–20 MV were used.

Results:

The absorbed dose within and beyond metallic prostheses dropped significantly due to beam attenuation. For bilateral HPs, the target dose reduction ranged up to 23% and 17% for SS316L and Ti6Al4V, respectively. For unilateral HP, the respective dose reductions were 19% and 12%. Dose enhancement was always <1% for UHMWPE. The 6-field plan produced the best target coverage. Up to 38% dose increase was found at the bone–SS316L proximal interface.

Conclusions:

The novel technique used enabled the complete exclusion of metal artifacts in the CT dataset. High-energy plans with more oblique beams can help minimize dose attenuation through HPs. Shadowing and interface effects are density dependent and greatest for SS316L, while UHMWPE poses negligible dose perturbation.

Reduction of Metallic Artifacts of the Post-treatment Intracranial Aneurysms: Effects of Single Energy Metal Artifact Reduction Algorithm

PURPOSE

This study evaluated the quality of computed tomography (CT) and CT angiography images generated using the single-energy metal artifact reduction (SEMAR) algorithm during perfusion examination in patients who had undergone reconstruction with neurosurgical clipping or endovascular coiling for treatment of aneurysms.

METHODS

A total of 55 patients with implanted intracranial clips or coils (24 men and 31 women; mean age 60.15 ± 15.86 years) underwent perfusion studies evaluated by CT and CT angiography with a 320-row CT scanner. Images were reconstructed with either the SEMAR algorithm combined with iterative reconstruction (SEMAR group), or by iterative reconstruction only (non-SEMAR group control). The SEMAR and control images were compared for artifacts (index and maximum diameter), image quality, cerebral perfusion parameters, noise (images with the worst artifacts), and contrast-to-noise ratio. The metallic artifacts were visually evaluated by two radiologists using a four-point scale in a double-blinded manner.

RESULTS

The noise, artifact diameter, and artifact index of the SEMAR images were significantly lower than that of the control images, and the subjective image quality score and contrast-to-noise ratio were significantly higher (P < 0.01, all). The cerebral perfusion parameters of the SEMAR and control images were comparable (i. e. blood flow, blood volume, and mean transit time).

CONCLUSION

For imaging intracranial metallic implants, the SEMAR algorithm produced images with significantly fewer artifacts than the iterative reconstruction alone, with no statistical changes in perfusion parameters. Thus, SEMAR reconstruction can be instrumental in improving CT image quality and may ultimately improve the detection of postoperative complications and patient prognosis.

Dual-energy CT with virtual monochromatic images and metal artifact reduction software for reducing metallic dental artifacts

Background Metallic dental prostheses may degrade image quality on head and neck computed tomography (CT). However, there is little information available on the use of dual-energy CT (DECT) and metal artifact reduction software (MARS) in the head and neck regions to reduce metallic dental artifacts. Purpose To assess the usefulness of DECT with virtual monochromatic imaging and MARS to reduce metallic dental artifacts. Material and Methods DECT was performed using fast kilovoltage (kV)-switching between 80-kV and 140-kV in 20 patients with metallic dental prostheses. CT data were reconstructed with and without MARS, and with synthesized monochromatic energy in the range of 40-140-kiloelectron volt (keV). For quantitative analysis, the artifact index of the tongue, buccal, and parotid areas was calculated for each scan. For qualitative analysis, two radiologists evaluated 70-keV and 100-keV images with and without MARS for tongue, buccal, parotid areas, and metallic denture. The locations and characteristics of the MARS-related artifacts, if any, were also recorded. Results DECT with MARS markedly reduced metallic dental artifacts and improved image quality in the buccal area ( P < 0.001) and the tongue ( P < 0.001), but not in the parotid area. The margin and internal architecture of the metallic dentures were more clearly delineated with MARS ( P < 0.001) and in the higher-energy images than in the lower-energy images ( P = 0.042). MARS-related artifacts most commonly occurred in the deep center of the neck. Conclusion DECT with MARS can reduce metallic dental artifacts and improve delineation of the metallic prosthesis and periprosthetic region.

A whole-heart motion-correction algorithm: Effects on CT image quality and diagnostic accuracy of mechanical valve prosthesis abnormalities

BACKGROUND

We aimed to determine the effect of a whole-heart motion-correction algorithm (new-generation snapshot freeze, NG SSF) on the image quality of cardiac computed tomography (CT) images in patients with mechanical valve prostheses compared to standard images without motion correction and to compare the diagnostic accuracy of NG SSF and standard CT image sets for the detection of prosthetic valve abnormalities.

METHODS

A total of 20 patients with 32 mechanical valves who underwent wide-coverage detector cardiac CT with single-heartbeat acquisition were included. The CT image quality for subvalvular (below the prosthesis) and valvular regions (valve leaflets) of mechanical valves was assessed by two observers on a four-point scale (1 = poor, 2 = fair, 3 = good, and 4 = excellent). Paired t-tests or Wilcoxon signed rank tests were used to compare image quality scores and the number of diagnostic phases (image quality score≥3) between the standard image sets and NG SSF image sets. Diagnostic performance for detection of prosthetic valve abnormalities was compared between two image sets with the final diagnosis set by re-operation or clinical findings as the standard reference.

RESULTS

NG SSF image sets had better image quality scores than standard image sets for both valvular and subvalvular regions (P < 0.05 for both). The number of phases that were of diagnostic image quality per patient was significantly greater in the NG SSF image set than standard image set for both valvular and subvalvular regions (P < 0.0001). Diagnostic performance of NG SSF image sets for the detection of prosthetic abnormalities (20 pannus and two paravalvular leaks) was greater than that of standard image sets (P < 0.05).

CONCLUSION

Application of NG SSF can improve CT image quality and diagnostic accuracy in patients with mechanical valves compared to standard images.

Dual-Energy CT for the Musculoskeletal System

The principal advantages of dual-energy computed tomography (CT) over conventional CT in the musculoskeletal setting relate to the additional information provided regarding tissue composition, artifact reduction, and image optimization. This article discusses the manifestations of these in clinical practice-urate and bone marrow edema detection, metal artifact reduction, and tendon analysis, with potential in arthrography, bone densitometry, and metastases surveillance. The basic principles of dual-energy CT physics and scanner design will also be discussed. ^© RSNA, 2016.

Value and Clinical Application of Orthopedic Metal Artifact Reduction Algorithm in CT Scans after Orthopedic Metal Implantation

Objective

To evaluate orthopedic metal artifact reduction algorithm (O-MAR) in CT orthopedic metal artifact reduction at different tube voltages, identify an appropriate low tube voltage for clinical practice, and investigate its clinical application.

Materials and Methods

The institutional ethical committee approved all the animal procedures. A stainless-steel plate and four screws were implanted into the femurs of three Japanese white rabbits. Preoperative CT was performed at 120 kVp without O-MAR reconstruction, and postoperative CT was performed at 80–140 kVp with O-MAR. Muscular CT attenuation, artifact index (AI) and signal-to-noise ratio (SNR) were compared between preoperative and postoperative images (unpaired t test), between paired O-MAR and non-O-MAR images (paired Student t test) and among different kVp settings (repeated measures ANOVA). Artifacts' severity, muscular homogeneity, visibility of inter-muscular space and definition of bony structures were subjectively evaluated and compared (Wilcoxon rank-sum test). In the clinical study, 20 patients undertook CT scan at low kVp with O-MAR with informed consent. The diagnostic satisfaction of clinical images was subjectively assessed.

Results

Animal experiments showed that the use of O-MAR resulted in accurate CT attenuation, lower AI, better SNR, and higher subjective scores (p < 0.010) at all tube voltages. O-MAR images at 100 kVp had almost the same AI and SNR as non-O-MAR images at 140 kVp. All O-MAR images were scored ≥ 3. In addition, 95% of clinical CT images performed at 100 kVp were considered satisfactory.

Conclusion

O-MAR can effectively reduce orthopedic metal artifacts at different tube voltages, and facilitates low-tube-voltage CT for patients with orthopedic metal implants.

Approaches to reducing photon dose calculation errors near metal implants

PURPOSE

Dose calculation errors near metal implants are caused by limitations of the dose calculation algorithm in modeling tissue/metal interface effects as well as density assignment errors caused by imaging artifacts. The purpose of this study was to investigate two strategies for reducing dose calculation errors near metal implants: implementation of metal-based energy deposition kernels in the convolution/superposition (C/S) dose calculation method and use of metal artifact reduction methods for computed tomography (CT) imaging.

METHODS

Both error reduction strategies were investigated using a simple geometric slab phantom with a rectangular metal insert (composed of titanium or Cerrobend), as well as two anthropomorphic phantoms (one with spinal hardware and one with dental fillings), designed to mimic relevant clinical scenarios. To assess the dosimetric impact of metal kernels, the authors implemented titanium and silver kernels in a commercial collapsed cone C/S algorithm. To assess the impact of CT metal artifact reduction methods, the authors performed dose calculations using baseline imaging techniques (uncorrected 120 kVp imaging) and three commercial metal artifact reduction methods: Philips Healthcare's o-mar, GE Healthcare's monochromatic gemstone spectral imaging (gsi) using dual-energy CT, and gsi with metal artifact reduction software (mars) applied. For the simple geometric phantom, radiochromic film was used to measure dose upstream and downstream of metal inserts. For the anthropomorphic phantoms, ion chambers and radiochromic film were used to quantify the benefit of the error reduction strategies.

RESULTS

Metal kernels did not universally improve accuracy but rather resulted in better accuracy upstream of metal implants and decreased accuracy directly downstream. For the clinical cases (spinal hardware and dental fillings), metal kernels had very little impact on the dose calculation accuracy (<1.0%). Of the commercial CT artifact reduction methods investigated, the authors found that o-mar was the most consistent method, resulting in either improved dose calculation accuracy (dental case) or little impact on calculation accuracy (spine case). gsi was unsuccessful at reducing the severe artifacts caused by dental fillings and had very little impact on calculation accuracy. gsi with mars on the other hand gave mixed results, sometimes introducing metal distortion and increasing calculation errors (titanium rectangular implant and titanium spinal hardware) but other times very successfully reducing artifacts (Cerrobend rectangular implant and dental fillings).

CONCLUSIONS

Though successful at improving dose calculation accuracy upstream of metal implants, metal kernels were not found to substantially improve accuracy for clinical cases. Of the commercial artifact reduction methods investigated, o-mar was found to be the most consistent candidate for all-purpose CT simulation imaging. The mars algorithm for gsi should be used with caution for titanium implants, larger implants, and implants located near heterogeneities as it can distort the size and shape of implants and increase calculation errors.

Reduction of metal artifacts due to dental hardware in computed tomography angiography: assessment of the utility of model-based iterative reconstruction

PURPOSE

The aim of this study is to assess the value of adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) for reduction of metal artifacts due to dental hardware in carotid CT angiography (CTA).

METHODS

Thirty-seven patients with dental hardware who underwent carotid CTA were included. CTA was performed with a GE Discovery CT750 HD scanner and reconstructed with filtered back projection (FBP), ASIR, and MBIR. We measured the standard deviation at the cervical segment of the internal carotid artery that was affected most by dental metal artifacts (SD₁) and the standard deviation at the common carotid artery that was not affected by the artifact (SD₂). We calculated the artifact index (AI) as follows: AI = [(SD₁)2 - (SD₂)2]1/2 and compared each AI for FBP, ASIR, and MBIR. Visual assessment of the internal carotid artery was also performed by two neuroradiologists using a five-point scale for each axial and reconstructed sagittal image. The inter-observer agreement was analyzed using weighted kappa analysis.

RESULTS

MBIR significantly improved AI compared with FBP and ASIR (p < 0.001, each). We found no significant difference in AI between FBP and ASIR (p = 0.502). The visual score of MBIR was significantly better than those of FBP and ASIR (p < 0.001, each), whereas the scores of ASIR were the same as those of FBP. Kappa values indicated good inter-observer agreements in all reconstructed images (0.747-0.778).

CONCLUSIONS

MBIR resulted in a significant reduction in artifact from dental hardware in carotid CTA.

Metal implants on CT: comparison of iterative reconstruction algorithms for reduction of metal artifacts with single energy and spectral CT scanning in a phantom model

PURPOSE

To assess single energy metal artifact reduction (SEMAR) and spectral energy metal artifact reduction (MARS) algorithms in reducing artifacts generated by different metal implants.

MATERIALS AND METHOD

Phantom was scanned with and without SEMAR (Aquilion One, Toshiba) and MARS (Discovery CT750 HD, GE), with various metal implants. Images were evaluated objectively by measuring standard deviation in regions of interests and subjectively by two independent reviewers grading on a scale of 0 (no artifact) to 4 (severe artifact). Reviewers also graded new artifacts introduced by metal artifact reduction algorithms.

RESULTS

SEMAR and MARS significantly decreased variability of the density measurement adjacent to the metal implant, with median SD (standard deviation of density measurement) of 52.1 HU without SEMAR, vs. 12.3 HU with SEMAR, p < 0.001. Median SD without MARS of 63.1 HU decreased to 25.9 HU with MARS, p < 0.001. Median SD with SEMAR is significantly lower than median SD with MARS (p = 0.0011). SEMAR improved subjective image quality with reduction in overall artifacts grading from 3.2 ± 0.7 to 1.4 ± 0.9, p < 0.001. Improvement of overall image quality by MARS has not reached statistical significance (3.2 ± 0.6 to 2.6 ± 0.8, p = 0.088). There was a significant introduction of artifacts introduced by metal artifact reduction algorithm for MARS with 2.4 ± 1.0, but minimal with SEMAR 0.4 ± 0.7, p < 0.001.

CONCLUSION

CT iterative reconstruction algorithms with single and spectral energy are both effective in reduction of metal artifacts. Single energy-based algorithm provides better overall image quality than spectral CT-based algorithm. Spectral metal artifact reduction algorithm introduces mild to moderate artifacts in the far field.

Dual energy CT angiography: pros and cons of dual-energy metal artifact reduction algorithm in patients after endovascular aortic repair

PURPOSE

To evaluate the value of metal artifact reduction (MAR) post-processing and iodine MD images in fast kV-switching dual-energy computed tomography (DECT) in patients after endovascular aortic repair (EVAR).

MATERIALS AND METHODS

Twenty-four consecutive EVAR patients (age 76 ± 9 years, 7/24 (29%) with coils, 9/24 (37.5%) with 10 endoleaks) who underwent DECT angiography were included in this HIPAA-compliant, IRB-approved retrospective study. Monochromatic reconstructions included 55, 60, 65, 70, and 75 keV with and without MAR and iodine MD images. Near field, far field, and vessel artifacts were assessed subjectively (1 = none; 5 = severe) and objectively by measuring noise and contrast-to-noise ratio. Visibility of endoleak was evaluated (1 = optimal; 5 = not visible).

RESULTS

MAR objectively decreased artifacts from EVAR stents in the near field (60.7 ± 25.4 HU vs. 70.1 ± 34.2; p = .002) and subjectively increased near field (3.2 ± 0.9 vs. 2.8 ± 0.6; p < .001), far field (2.2 ± 0.6 vs. 1.6 ± 0.6; p < .001), and vessel (3.1 ± 1.1 vs. 2.5 ± 0.9; p < .001) artifacts. Near-field artifacts from coils were reduced by the MAR objectively (72.4 ± 24.8 vs. 182.7 ± 57.3 HU; p < .001) and subjectively (4.5 ± 0.5 vs. 4.9 ± 0.4; p = .02). CNR of standard reconstructions was optimal at 60 keV (38.3 ± 16.8). Reconstructions without MAR and iodine MD images provided improved endoleak visualization in 6/10 (60%) of cases (median 1 for both) compared to MAR (median 3) (p < 0.001). However, MAR improved visualization in 1/10 (10%) cases due to endoleak location adjacent to a coil.

CONCLUSION

DECT with MAR reduced artifacts from coils and improved endoleak visualization in 1/10 (10%) cases due to location adjacent to a coil. However, MAR impaired endoleak visualization in 6/10 (60%) cases and should be reviewed combined with 60 keV standard reconstructions and iodine MD images.

Metal Artifact Reduction in Computed Tomography After Deep Brain Stimulation Electrode Placement Using Iterative Reconstructions

OBJECTIVES

Diagnostic accuracy of intraoperative computed tomography (CT) after deep brain stimulation (DBS) electrode placement is limited due to artifacts induced by the metallic hardware, which can potentially mask intracranial postoperative complications. Different metal artifact reduction (MAR) techniques have been introduced to reduce artifacts from metal hardware in CT. The purpose of this study was to assess the impact of a novel iterative MAR technique on image quality and diagnostic performance in the follow-up of patients with DBS electrode implementation surgery.

MATERIALS AND METHODS

Seventeen patients who had received routine intraoperative CT of the head after implantation of DBS electrodes between March 2015 and June 2015 were retrospectively included. Raw data of all patients were reconstructed with standard weighted filtered back projection (WFBP) and additionally with a novel iterative MAR algorithm. We quantified frequencies of density changes to assess quantitative artifact reduction. For evaluation of qualitative image quality, the visibility of numerous cerebral anatomic landmarks and the detectability of intracranial electrodes were scored according to a 4-point scale. Furthermore, artifact strength overall and adjacent to the electrodes was rated.

RESULTS

Our results of quantitative artifact reduction showed that images reconstructed with iterative MAR (iMAR) contained significantly lower metal artifacts (overall low frequency values, 1608.6 ± 545.5; range, 375.5-3417.2) compared with the WFBP (overall low frequency values, 4487.3 ± 875.4; range, 2218.3-5783.5) reconstructed images (P < 0.004). Qualitative image analysis showed a significantly improved image quality for iMAR (overall anatomical landmarks, 2.49 ± 0.15; median, 3; range, 0-3; overall electrode characteristics, 2.35 ± 0.16; median, 2; range, 0-3; artifact characteristics, 2.16 ± 0.08; median, 2.5; range, 0-3) compared with WFBP (overall anatomical landmarks, 1.21 ± 0.64; median, 1; range, 0-3; overall electrode characteristics, 0.74 ± 0.37; median, 1; range, 0-2; artifact characteristics, 0.51 ± 0.15; median, 0.5; range, 0-2; P < 0.002).

CONCLUSIONS

Reconstructions of cranial CT images with the novel iMAR algorithm in patients after DBS implantation allows an efficient reduction of metal artifacts near DBS electrodes compared with WFBP reconstructions. We demonstrated an improvement of quantitative and qualitative image quality of iMAR compared with WFBP in patients with DBS electrodes.

The value of spectral imaging to reduce artefacts in the body after 125 I seed implantation

INTRODUCTION

To explore the value of gemstone spectral imaging (GSI) and metal artefact reduction sequence (MARs) to reduce the artefacts of metal seeds.

METHODS

Thirty-five patients with ¹²⁵ I seed implantation in their abdomens underwent GSI CT. Six types of monochromatic images and the corresponding MARs images at 60-110 keV (interval of 10 keV) were reconstructed. The differences in the quality of the images of three imaging methods were subjectively assessed by three radiologists. Length of artefacts, the CT value and noise value of tissue adjacent to ¹²⁵ I seeds, contrast-to-noise ratio (CNR), and artefact index (AI) were recorded.

RESULTS

The differences in subjective scoring were statistically significant (t = 10.87, P < 0.001). Images at 70 keV showed the best CNR (0.84 ± 0.17) of tissues adjacent to ¹²⁵ I seeds, and received the highest subjective score (2.82 ± 0.18). Images at 80 keV had the lowest AI (70.67 ± 19.17). Images at 110 keV had the shortest artefact lengths. High-density metal artefacts in the MARs spectral images were reduced. The length of metal artefacts in images at 110 keV was shorter than that of the polychromatic images and MARs spectral images (t = 3.35, 3.89, P < 0.05). The difference in CNR between MARs spectral images and polychromatic images, and images at 70 keV was statistically significant (t = 3.57, 4.16, P < 0.01).

CONCLUSIONS

Gemstone spectral imaging technique can reduce metal artefacts of ¹²⁵ I seeds effectively in CT images, and improve the quality of images, and improve the display of tissues adjacent to ¹²⁵ I seeds after implantation. MARs technique cannot reduce the artefacts caused by radioactive seeds effectively.

Single-energy metal artifact reduction in postimplant computed tomography for I-125 prostate brachytherapy: Impact on seed identification

PURPOSE

To evaluate the effectiveness of the single-energy metal artifact reduction (SEMAR) technique for improving the accuracy of I-125 seed identification in postimplant computed tomography (CT) after prostate brachytherapy.

METHODS AND MATERIALS

Postimplant CT images of 40 patients treated with I-125 prostate brachytherapy were acquired. For all patients, 2 data sets were reconstructed, 1 with SEMAR algorithms (SEMAR image), and the other without SEMAR algorithms (non-SEMAR image). Seed locations are automatically detected by the automatic seed finder tool, and their locations were compared between the SEMAR and non-SEMAR images. Dosimetric parameters using seed locations as detected were compared.

RESULTS

The true-positive fraction of properly detected seeds on the SEMAR image as determined from a reference seed distribution defined by one investigator was significantly higher than the true-positive fraction on the non-SEMAR image (p = 0.011). The variabilities in D₉₀ (p = 0.001), V₁₀₀ (p = 0.007), and V₁₅₀ (p = 0.007) were significantly reduced for seed location on the SEMAR image as compared with non-SEMAR image.

CONCLUSIONS

Prostate postimplant CT with SEMAR improved the accuracy of seed localization and postimplant dosimetric parameters.

Differentiation of malignant cervical lymphadenopathy by dual-energy CT: a preliminary analysis

The accurate diagnosis of malignant cervical lymphadenopathy remains challenging. In this study, we determined the value of quantitative parameters derived from dual-energy computed tomography (DECT) for differentiating malignant cervical lymphadenopathy caused by thyroid carcinoma (TC), salivary gland carcinoma (SC), squamous cell carcinoma (SCC) and lymphoma. We retrospectively analysed 92 patients with pathologically confirmed cervical lymphadenopathy due to TC, SC, SCC and lymphoma. All patients received a DECT scan before therapy. Using GSI (gemstone spectral imaging) Volume Viewer software, we analysed the enhanced monochromatic data, and the quantitative parameters we acquired included the iodine concentration (IC), water concentration (WC) and the slope of the spectral HU curve (λ_HU). One-way ANOVA showed significant differences in the IC and λ_HU among different groups (P < 0.05). Post-hoc pairwise comparisons demonstrated the IC and λ_HU of TC group were significantly higher than those of SC, SCC and lymphoma groups (P < 0.05). In addition, the IC and λ_HU of SC group were significantly higher than those of the SCC and lymphoma groups (P < 0.05). Other comparisons of IC and λ_HU values showed no significant differences (P > 0.05). The quantitative parameters derived from DECT were useful supplements to conventional computed tomography images and were helpful for distinguishing different malignant cervical lymphadenopathies.