Iterative Metal Artifact Reduction Algorithm Research Articles

Comparison of dual-energy computed tomography (DECT) polychromatic and monochromatic images with and without iterative metal artifact reduction algorithm in patients with dental implants.

Dual-energy computed tomography (DECT) and iterative metal artifact reduction (iMAR) algorithms are valuable tools for reducing metal artifacts. Different parameters of these technologies and their combination can achieve different performance. This study compared various polychromatic and monochromatic images obtained via DECT with and without using iMAR algorithm to reduce artifacts in patients with dental implants. This study included 30 patients with dental implants who underwent DECT for head and neck imaging. The computed tomography (CT) image sets comprised DECT polychromatic image sets [dual-energy (DE) polychromatic] that linearly blended 100 kV and tin-filtered 140 kV images using composition ratios of -1, -0.6, -0.3, 0, and 0.6, and virtual monochromatic images (DE monochromatic) at 90, 110, 130, 150, and 170 keV. These image sets were obtained with and without using iMAR, resulting in a total of 20 image sets. For subjective analysis, metal artifacts and image quality were assessed using a 5-point Likert scale. For objective analysis, CT attenuation, standard deviation (SD), contrast-to-noise ratio (CNR) and artifact index (AI) were evaluated. In addition, subgroup analysis was performed based on implant size. In the subjective evaluation, iMAR + DE polychromatic (-0.3) images exhibited the lowest metal artifact scores [median (interquartile range): 2 (2-3)]. iMAR + DE monochromatic (110 keV) images demonstrated optimal image quality scores [median (interquartile range): 2 (2-3)]. In the objective evaluation, none of the images demonstrated a significant difference in the CNR, except polychromatic images with a composition of -1 and 0.6. iMAR + DE polychromatic (0) exhibited the lowest AI [median (interquartile range): 8.7 (5.9-14.5)]. There was no significant difference between the two groups with different implant sizes for the techniques combined with iMAR (all P>0.05). iMAR + DE polychromatic (-0.3 and 0) and iMAR + DE monochromatic (110 keV) images exhibited better image quality and substantial metal artifact reduction (MAR) compared with the other image sets. The performance of the techniques combined with iMAR was not affected by the size of the implant.

A New Iterative Metal Artifact Reduction Algorithm for Both Energy-Integrating and Photon-Counting CT Systems.

The aim of this study was to introduce and evaluate a new metal artifact reduction framework (iMARv2) that addresses the drawbacks (residual artifacts after correction and user preferences for image quality) associated with the current clinically applied iMAR. A new iMARv2 has been introduced, combining the current iMAR with new modular components to remove residual metal artifacts after image correction. The postcorrection image impression is adjustable with user-selectable strength settings. Phantom scans from an energy-integrating and a photon-counting detector CT were used to assess image quality, including a Gammex phantom and anthropomorphic phantoms. In addition, 36 clinical cases (with metallic implants such as dental fillings, hip replacements, and spinal screws) were reconstructed and evaluated in a blinded and randomized reader study. The Gammex phantom showed lower HU errors compared with the uncorrected image at almost all iMAR and iMARv2 settings evaluated, with only minor differences between iMAR and the different iMARv2 settings. In addition, the anthropomorphic phantoms showed a trend toward lower errors with higher iMARv2 strength settings. On average, the iMARv2 strength 3 performed best of all the clinical reconstructions evaluated, with a significant increase in diagnostic confidence and decrease in artifacts. All hip and dental cases showed a significant increase in diagnostic confidence and decrease in artifact strength, and the improvements from iMARv2 in the dental cases were significant compared with iMAR. There were no significant improvements in the spine. This work has introduced and evaluated a new method for metal artifact reduction and demonstrated its utility in routine clinical datasets. The greatest improvements were seen in dental fillings, where iMARv2 significantly improved image quality compared with conventional iMAR.

Combining virtual monoenergetic imaging and iterative metal artifact reduction in first-generation photon-counting computed tomography of patients with dental implants

ObjectivesWhile established for energy-integrating detector computed tomography (CT), the effect of virtual monoenergetic imaging (VMI) and iterative metal artifact reduction (iMAR) in photon-counting detector (PCD) CT lacks thorough investigation. This study evaluates VMI, iMAR, and combinations thereof in PCD-CT of patients with dental implants.Material and methodsIn 50 patients (25 women; mean age 62.0 ± 9.9 years), polychromatic 120 kVp imaging (T3D), VMI, T3DiMAR, and VMIiMAR were compared. VMIs were reconstructed at 40, 70, 110, 150, and 190 keV. Artifact reduction was assessed by attenuation and noise measurements in the most hyper- and hypodense artifacts, as well as in artifact-impaired soft tissue of the mouth floor. Three readers subjectively evaluated artifact extent and soft tissue interpretability. Furthermore, new artifacts through overcorrection were assessed.ResultsiMAR reduced hyper-/hypodense artifacts (T3D 1305.0/−1418.4 versus T3DiMAR 103.2/−46.9 HU), soft tissue impairment (106.7 versus 39.7 HU), and image noise (16.9 versus 5.2 HU) compared to non-iMAR datasets (p ≤ 0.001). VMIiMAR ≥ 110 keV subjectively enhanced artifact reduction over T3DiMAR (p ≤ 0.023). Without iMAR, VMI displayed no measurable artifact reduction (p ≥ 0.186) and facilitated no significant denoising over T3D (p ≥ 0.366). However, VMI ≥ 110 keV reduced soft tissue impairment (p ≤ 0.009). VMIiMAR ≥ 110 keV resulted in less overcorrection than T3DiMAR (p ≤ 0.001). Inter-reader reliability was moderate/good for hyperdense (0.707), hypodense (0.802), and soft tissue artifacts (0.804).ConclusionWhile VMI alone holds minimal metal artifact reduction potential, iMAR post-processing enabled substantial reduction of hyperdense and hypodense artifacts. The combination of VMI ≥ 110 keV and iMAR resulted in the least extensive metal artifacts.Clinical relevanceCombining iMAR with VMI represents a potent tool for maxillofacial PCD-CT with dental implants achieving substantial artifact reduction and high image quality.Key Points• Post-processing of photon-counting CT scans with an iterative metal artifact reduction algorithm substantially reduces hyperdense and hypodense artifacts arising from dental implants.• Virtual monoenergetic images presented only minimal metal artifact reduction potential.• The combination of both provided a considerable benefit in subjective analysis compared to iterative metal artifact reduction alone.

Influence of Scan Parameters of Single and Dual-Energy CT Protocols in Combination with Metal Artifact Suppression Algorithms for THA: An ex Vivo Study.

Metal artifacts caused by hip arthroplasty stems limit the diagnostic value of computed tomography (CT) in the evaluation of periprosthetic fractures or implant loosening. The aim of this ex vivo study was to evaluate the influence of different scan parameters and metal artifact algorithms on image quality in the presence of hip stems. Nine femoral stems, 6 uncemented and 3 cemented, that had been implanted in subjects during their lifetimes were exarticulated and investigated after death and anatomical body donation. Twelve CT protocols consisting of single-energy (SE) and single-source consecutive dual-energy (DE) scans with and without an iterative metal artifact reduction algorithm (iMAR; Siemens Healthineers) and/or monoenergetic reconstructions were compared. Streak and blooming artifacts as well as subjective image quality were evaluated for each protocol. Metal artifact reduction with iMAR significantly reduced the streak artifacts in all investigated protocols (p = 0.001 to 0.01). The best subjective image quality was observed for the SE protocol with a tin filter and iMAR. The least streak artifacts were observed for monoenergetic reconstructions of 110, 160, and 190 keV with iMAR (standard deviation of the Hounsfield units: 151.1, 143.7, 144.4) as well as the SE protocol with a tin filter and iMAR (163.5). The smallest virtual growth was seen for the SE with a tin filter and without iMAR (4.40 mm) and the monoenergetic reconstruction of 190 keV without iMAR (4.67 mm). This study strongly suggests that metal artifact reduction algorithms (e.g., iMAR) should be used in clinical practice for imaging of the bone-implant interface of prostheses with either an uncemented or cemented femoral stem. Among the iMAR protocols, the SE protocol with 140 kV and a tin filter produced the best subjective image quality. Furthermore, this protocol and DE monoenergetic reconstructions of 160 and 190 keV with iMAR achieved the lowest levels of streak and blooming artifacts. Diagnostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Metal implants on abdominal CT: does split-filter dual-energy CT provide additional value over iterative metal artifact reduction?

PurposeTo assess image quality and metal artifact reduction in split-filter dual-energy CT (sfDECT) of the abdomen with hip or spinal implants using virtual monoenergetic images (VMI) and iterative metal artifact reduction algorithm (iMAR).Methods102 portal-venous abdominal sfDECTs of patients with hip (n = 71) or spinal implants (n = 31) were included in this study. Images were reconstructed as 120kVp-equivalent images (Mixed) and VMI (40–190 keV), with and without iMAR. Quantitative artifact and image noise was measured using 12 different ROIs. Subjective image quality was rated by two readers using a five-point Likert-scale in six categories, including overall image quality and vascular contrast.ResultsLowest quantitative artifact in both hip and spinal implants was measured in VMI190keV-iMAR. However, it was not significantly lower than in MixediMAR (for all ROIs, p = 1.00), which were rated best for overall image quality (hip: 1.00 [IQR: 1.00–2.00], spine: 3.00 [IQR:2.00–3.00]). VMI50keV-iMAR was rated best for vascular contrast (hip: 1.00 [IQR: 1.00–2.00], spine: 2.00 [IQR: 1.00–2.00]), which was significantly better than Mixed (both, p < 0.001). VMI50keV-iMAR provided superior overall image quality compared to Mixed for hip (1.00 vs 2.00, p < 0.001) and similar diagnostic image quality for spinal implants (2.00 vs 2.00, p = 0.51).ConclusionFor abdominal sfDECT with hip or spinal implants MixediMAR images should be used. High keV VMI do not further improve image quality. IMAR allows the use of low keV images (VMI50keV) to improve vascular contrast, compared to Mixed images.Graphical abstract

Metal artifact reduction in ultra-high-resolution cone-beam CT imaging with a twin robotic X-ray system

Cone-beam computed tomography (CBCT) has been shown to be a powerful tool for 3D imaging of the appendicular skeleton, allowing for detailed visualization of bone microarchitecture. This study was designed to compare artifacts in the presence of osteosynthetic implants between CBCT and multidetector computed tomography (MDCT) in cadaveric wrist scans. A total of 32 scan protocols with varying tube potential and current were employed: both conventional CBCT and MDCT studies were included with tube voltage ranging from 60 to 140 kVp as well as additional MDCT protocols with dedicated spectral shaping via tin prefiltration. Irrespective of scanner type, all examinations were conducted in ultra-high-resolution (UHR) scan mode. For reconstruction of UHR-CBCT scans an additional iterative metal artifact reduction algorithm was employed, an image correction tool which cannot be used in combination with UHR-MDCT. To compare applied radiation doses between both scanners, the volume computed tomography dose index for a 16 cm phantom (CTDIvol) was evaluated. Images were assessed regarding subjective and objective image quality. Without automatic tube current modulation or tube potential control, radiation doses ranged between 1.3 mGy (with 70 kVp and 50.0 effective mAs) and 75.2 mGy (with 140 kVp and 383.0 effective mAs) in UHR-MDCT. Using the pulsed image acquisition method of the CBCT scanner, CTDIvol ranged between 2.3 mGy (with 60 kVp and 0.6 mean mAs per pulse) and 61.0 mGy (with 133 kVp and 2.5 mean mAs per pulse). In essence, all UHR-CBCT protocols employing a tube potential of 80 kVp or more were found to provide superior overall image quality and artifact reduction compared to UHR-MDCT (all p < .050). Interrater reliability of seven radiologists regarding image quality was substantial for tissue assessment and moderate for artifact assessment with Fleiss kappa of 0.652 (95% confidence interval 0.618–0.686; p < 0.001) and 0.570 (95% confidence interval 0.535–0.606; p < 0.001), respectively. Our results demonstrate that the UHR-CBCT scan mode of a twin robotic X-ray system facilitates excellent visualization of the appendicular skeleton in the presence of metal implants. Achievable image quality and artifact reduction are superior to dose-comparable UHR-MDCT and even MDCT protocols employing spectral shaping with tin prefiltration do not achieve the same level of artifact reduction in adjacent soft tissue.

3D Printing of Tooth Impressions Based on Multi-Detector Computed Tomography Images Combined with Beam Hardening Artifact Reduction in Metal Structures

We investigated the role of metal artifact reduction by taking 3D print impressions using 3D data of Computed Tomography (CT) images based on the algorithm applied. We manufactured a phantom of a human mandible tooth made of gypsum and nickel alloy to measure the metal artifacts. CT images were obtained by changing the phantom tube voltage and tube current. The signal intensity of the image generated by the metal artifacts before and after the iterative metal artifact reduction algorithm (iMAR) was measured. A 3D printing process was performed after converting the images, before and after iMAR application, into STL files using InVesalius version 3.1.1 by selecting the conditions that minimized the effect of the artifact. Regarding metal artifacts, the Hounsfield unit (HU) value showed low as the tube voltage increased. The iMAR-applied images acquired under the same conditions showed a significantly lower HU. The artifacts, in the form of flashes, persisted in the 3D-printed product of the image not subjected to iMAR, but were largely removed in the 3D-printed product following iMAR application. In this study, the application of iMAR and data acquired using high tube voltage eliminated a significant portion of the metal artifacts, resulting in an impression shape that was consistent with the human body.

Comparison of the Quality of Various Polychromatic and Monochromatic Dual-Energy CT Images with or without a Metal Artifact Reduction Algorithm to Evaluate Total Knee Arthroplasty.

ObjectiveTo compare the quality of various polychromatic and monochromatic images with or without using an iterative metal artifact reduction algorithm (iMAR) obtained from a dual-energy computed tomography (CT) to evaluate total knee arthroplasty.Materials and MethodsWe included 58 patients (28 male and 30 female; mean age [range], 71.4 [61–83] years) who underwent 74 knee examinations after total knee arthroplasty using dual-energy CT. CT image sets consisted of polychromatic image sets that linearly blended 80 kVp and tin-filtered 140 kVp using weighting factors of 0.4, 0, and −0.3, and monochromatic images at 130, 150, 170, and 190 keV. These image sets were obtained with and without applying iMAR, creating a total of 14 image sets. Two readers qualitatively ranked the image quality (1 [lowest quality] through 14 [highest quality]). Volumes of high- and low-density artifacts and contrast-to-noise ratios (CNRs) between the bone and fat tissue were quantitatively measured in a subset of 25 knees unaffected by metal artifacts.ResultsiMAR-applied, polychromatic images using weighting factors of −0.3 and 0.0 (P−0.3i and P0.0i, respectively) showed the highest image-quality rank scores (median of 14 for both by one reader and 13 and 14, respectively, by the other reader; p < 0.001). All iMAR-applied image series showed higher rank scores than the iMAR-unapplied ones. The smallest volumes of low-density artifacts were found in P−0.3i, P0.0i, and iMAR-applied monochromatic images at 130 keV. The smallest volumes of high-density artifacts were noted in P−0.3i. The CNRs were best in polychromatic images using a weighting factor of 0.4 with or without iMAR application, followed by polychromatic images using a weighting factor of 0.0 with or without iMAR application.ConclusionPolychromatic images combined with iMAR application, P−0.3i and P0.0i, provided better image qualities and substantial metal artifact reduction compared with other image sets.

Clinical evaluation of a new adaptive iterative metal artifact reduction method in whole-body low-dose CT skeletal survey examinations.

To evaluate a new adaptive iterative metal artifact reduction algorithm (AiMAR) in whole-body low-dose CT (WBLDCT) skeletal survey examinations. Projection data were retrospectively obtained from 25 clinical WBLDCT skeletal survey patients, each with two types of metal implants. Images were reconstructed with bone and soft tissue kernels using four settings-original and AiMAR with strengths of 2, 4, and 5. All images were anonymized and randomized for a reader study, where three musculoskeletal radiologists independently determined the overall ranking of all series based on diagnostic quality, and local scoring of metal artifact and anatomy visualization for each implant. Quantitative image noise analysis was performed in areas close to the implants. Intraclass correlation coefficients (ICC) and Krippendorff's alpha were computed for inter-rater reliability. AiMAR 4 was ranked the highest for 64.3% of the series across eight types of implants. For local scoring task, AiMAR 4 showed better metal artifact and anatomy visualization than the original and AiMAR 2. AiMAR 4 was comparable in anatomy visualization but inferior to AiMAR 5 in metal artifact scores. AiMAR 4 led to 56.3% noise reduction around the implant areas compared with the original images, and AiMAR 5 68.1% but also resulted in anatomy blurring in 40% of the implants. ICC and Krippendorff's alpha revealed at least substantial reliability in the local scores among the readers. AiMAR was evaluated in WBLDCT skeletal surveys. AiMAR 4 demonstrated the highest overall quality ranking and improved local scores with noise reduction around implant areas.

Efficiency of Iterative Metal Artifact Reduction Algorithm (iMAR) Applied to Brain Volume Perfusion CT in the Follow-up of Patients after Coiling or Clipping of Ruptured Brain Aneurysms

Metal artifacts resulting from coiling or clipping of a brain aneurysm degrade image quality and reduce diagnostic usefulness of computed tomography perfusion CTP. Our aim was to assess the diagnostic value of the iterative metal artifact reduction algorithm (iMAR) in CTP studies after coiling or clipping of ruptured intracranial aneurysms. Fifty-eight CTP exams performed in 32 patients were analysed. iMAR was applied to the source images from the CT scanner. Perfusion maps were generated from datasets both with and without iMAR, and both datasets were compared qualitatively and quantitatively. Qualitative analysis included evaluation of intensity of artifacts, image quality, presence of new artifacts, and the reader’s confidence in their diagnosis as well as diagnostic impression. Quantitative analysis included evaluation of tissue attenuation curves, evaluation of region of interest (ROI)-based measurement of perfusion values at levels that do and do not contain metal, compared to previously published reference ranges of perfusion values. Our results showed that application of iMAR reduced artifacts and significantly improved image quality. New artifacts were observed adjacent to metallic implants, but did not limit the evaluation of other regions. After correction for artifact readers’ confidence in their diagnosis increased from 41.3% to 87.9%, and the diagnostic impression changed in 31% of the exams. No difference between tissue attenuation curves was found. For slices without metal, no difference was noted between values measured before and after iMAR, and the total number of ROIs in the reference range of perfusion values was unchanged. At the level of the metal implant, 89.85% of ROIs obtained before using iMAR showed calculation errors. After using iMAR, only 1.7% showed errors. Before iMAR 3.1% of values were in the reference range, whereas after iMAR this increased to 33.1%. In conclusion, our results show that iMAR is an excellent tool for reducing artifacts in CTP. It is therefore recommended for use in clinical practice, particularly when severe artifacts are present, or when hypoperfusion is suspected at the level of the coil or clip. After the application of iMAR, the perfusion values at the level of the metal can be better calculated, but may not lie within the reference range; therefore, quantitative analysis at the level of artifacts is not advisable.

Application of Iterative Metal Artifact Reduction Algorithm to CT Urography for Patients With Hip Prostheses.

OBJECTIVE. The purpose of this study is to retrospectively assess the impact of iterative metal artifact reduction (IMAR) with iterative reconstruction (IR) on the image quality and diagnostic performance of CT urography in the evaluation of patients with hip prostheses, compared with IR alone. MATERIALS AND METHODS. CT urography examinations that were reconstructed using IR with and without IMAR were analyzed for 57 patients (29 women and 28 men; mean age, 74 years [range, 22-94 years]) with hip prostheses (40 unilateral and 17 bilateral). For quantitative analysis, image noise within the bladder was measured. Two radiologists (radiologist 1 [RAD1] and radiologist 2 [RAD2]) qualitatively evaluated the images using both a 5-point scale to assess the degree of visualization of artifacts and a 6-point scale to determine diagnostic confidence in visualization of the bladder, ureters, prostate or uterus, pelvic calcifications, and genitourinary abnormalities involving the bladder, distal ureters, prostate, uterus, and ovaries. RESULTS. The combination of IMAR and an IR technique provided improvement in quantitative and qualitative measurements (p < 0.05). Forty-three genitourinary abnormalities were detected in 29 patients. Quantitative and qualitative comparisons of scans obtained with and without the use of IMAR, respectively, revealed image noise of 99.6 versus 173.3 HU and the following radiologist scores: for improvement of artifacts, 3.2 versus 1.6 (for RAD1) and 3.1 versus 1.6 (for RAD2); for visualization of the bladder, 3.6 versus 1.5 (RAD1) and 3.8 versus 1.6 (RAD2); visualization of the ureters, 3.8 versus 1.6 (RAD1) and 3.9 versus 1.7 (RAD2); visualization of the uterus, 4.3 versus 2.8 (RAD1) and 4.3 versus 2.6 (RAD2); visualization of the prostate, 4.5 versus 2.3 (RAD1) and 4.5 versus 2.2 (RAD2); diagnostic confidence for calcifications, 4.7 versus 3.5 (RAD1) and 4.7 versus 3.3 (RAD2); and diagnostic confidence for genitourinary abnormalities, 5.0 versus 3.2 (RAD1) and 4.8 versus 2.9 (RAD2), respectively. CONCLUSION. The addition of IMAR to IR led to statistically significant improvement in the retrospective diagnostic performance and image quality of CT urography for patients with hip prostheses, compared with IR alone.

Artifact Reduction in the Diagnosis of Vasospasm in Computed Tomographic Perfusion: Potential of Iterative Metal Artifact Reduction.

This study aimed to analyze the possibility of artifact reduction using a new iterative metal artifact reduction algorithm (iMAR) in the diagnosis of perfusion deficits due to vasospasms and to evaluate its clinical relevance. Sixty-one volume perfusion computed tomographies of 24 patients after coiling or aneurysm clipping were reconstructed using standard-filtered back-projection and iMAR retrospectively. The degree of artifacts was evaluated as well as the size of the nonevaluable area. Diagnostic performance was evaluated compared with digital subtraction angiography. Artifacts were present in 39 of 61 volume perfusion computed tomography examinations. Image quality (score, 1.0 vs 1.6; P < 0.01) was higher and the size of the signal loss was reduced significantly by iMAR (intracranial metal artifacts, 887 mm vs 359 mm [P < 0.01]; cranial bolt, 3008 mm vs 837 mm [P < 0.01]). Digital subtraction angiography confirmed vasospasms in 11 (92%) of 12 patients. The iMAR yields higher image quality by reducing artifacts compared with filtered back-projection.

Comparison of Metal Artifact Reduction in Dual- and Single-Source CT: A Vertebral Phantom Study.

The objective of this study was to compare the capability of two algorithms for metal artifact reduction and virtual monoenergetic imaging (VME), a metal artifact reduction application for dual-source CT. A bovine vertebra phantom with 16 artificial osteolyses and two 20 × 4.5 mm stainless steel screws was scanned on two single-source CT scanner and one dual-source CT scanner at a dose identical to the single-source acquisitions. Datasets were reconstructed with a metal artifact reduction algorithm for orthopedic implants (O-MAR, Philips Healthcare), an iterative metal artifact reduction algorithm (iMAR, Siemens Healthineers), and VME. Blinded to the method used for artifact reduction, three independent observers evaluated datasets regarding the extent of metal artifacts using a 4-point scale. Depicted osteolyses were counted and screw diameters measured for each reconstruction. Interobserver variability was evaluated using the Kendall coefficient of concordance for ordinal variables and the intraclass correlation coefficient for continuous data. VME showed the best metal artifact reduction capability among evaluated methods; overall artifacts were rated 1.08 ± 0.29 for VME, 3.33 ± 0.65 for iMAR, and 3.91 ± 0.29 for O-MAR (p < 0.01). VME resulted in better representation of the cortical bone, trabecular structure, and soft tissue compared with the other two algorithms. VME provided the most realistic reconstruction of screw diameter. However, VME missed osteolyses. Good to almost perfect agreement was achieved for nearly all evaluated attributes. In our vertebral phantom, VME led to the most detailed representation of the osteosynthesis screw, caused the lowest amount of artifact, and represented the adjacent tissue best. Thus, VME should be considered as an alternative method to evaluate implants when other algorithms fail.

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.

The aim of this study was to evaluate the reduction of artifacts from deep brain stimulation electrodes (DBS) using an iterative metal artifact reduction algorithm (O-MAR), virtual monoenergetic images (VMI), and both in combination in postoperative spectral detector computed tomography using a dual-layer detector (spectral detector computed tomography [SDCT]) of the head. Nonanthropomorphic phantoms with different DBS leads were examined on SDCT; in 1 phantom periprocedural bleeding was simulated. A total of 20 patients who underwent SDCT after DBS implantation between October 2016 and April 2017 were included in this institutional review board-approved retrospective study. Images were reconstructed using standard-of-care iterative reconstruction (CI) and VMI, each with and without O-MAR processing (IR and MAR). Artifacts were quantified by determining the percentage integrity uniformity in an annular region of 1.4 cm around the DBS lead; a percentage integrity uniformity of 100% indicates the absence of artifacts. In phantoms, conspicuity of blood was determined on a binary scale, whereas in patients, image quality, DBS lead assessment, and extent of artifact reduction were assessed on Likert scales by 2 radiologists. Statistical significance was assessed using analysis of variance and Wilcoxon tests; sensitivity and specificity were calculated. The O-MAR processing significantly decreased artifacts in phantom and patients (P ≤ 0.05), whereas VMI did not reduce artifact burden compared with corresponding CI (P > 0.05): for example, CI-IR/MAR and 200 keV-IR/MAR for patients: 76.3%/90.7% and 75.9%/91.2%, respectively. Qualitatively, overall image quality was not improved (P > 0.05) and MAR improved DBS assessment (CI-IR/MAR: 2 [1-3]/3 [2-4]; P ≤ 0.05) and reduced artifacts significantly (P ≤ 0.05). The O-MAR processing increased sensitivity for bleeding by 160%. In some cases, new artifacts were induced through O-MAR processing, none of which impaired diagnostic image assessment. The investigated O-MAR algorithm reduces artifacts from DBS electrodes and should be used in the assessment of postoperative patients; however, combination with VMI does not provide an additional benefit.

4:03 PM Abstract No. 259 Utility of metal artifact reduction to improve visualization of therapeutic ice ball in CT-guided cryoablation of musculoskeletal metastases

To evaluate the effects of metal artifact reduction (MAR) on cryoprobe-induced artifact for improvement of therapeutic ice ball visualization in CT-guided cryoablation of musculoskeletal (MSK) metastases. An iterative MAR algorithm (Siemens, Germany) was retrospectively applied to 12 cases of CT-guided MSK cryoablation in 11 patients from November 2016 to August 2017. The final cryoablation CT image with greatest metal artifact caused by the cryoprobe was compared before and after application of MAR. Three experienced interventional radiologists performed a blinded, qualitative evaluation of side-by-side images with and without MAR using a modified 4-point scale (0-3; 0 denotes no artifact, 3 severe artifact). The metal artifact beyond and adjacent to the probe, metallic artifact compromising the ice ball margins, and visualization of critical structures within 1 cm of the margins was scored. Quantitative measurements of CT attenuation (Hounsfield Unit) and standard deviation (noise) were made in four locations: beyond the probe, directly overlying the probe tip, and within and outside of the ice ball margins. Wilcoxon signed-ranks test was used to compare variables. Qualitative analysis showed image quality improvement in MAR images beyond the probe tip (mean score 1.6/0.9, without MAR vs with MAR, p = 0.002), adjacent to the probe (0.8/0.4, p = 0.011), and ice ball conspicuity (1.1/0.5, p = 0.007). There was a trend towards improved visualization of critical structures within 1 cm of ice ball margins (0.8/0.4, p = 0.07). Quantitative analysis confirmed a noise decrease for MAR images beyond the probe (HU 90.5 ± 57.6, 64.8 ± 48.5, without MAR vs with MAR; p = 0.002) and within the ice ball (25.1 ± 8.7, 20.6 ± 7.0; p = 0.008). Noise overlying the probe tip and at critical structures was not significantly improved. MAR provides both qualitative and quantitative improvements for the visualization of the therapeutic ice ball during CT-guided cryoablation of musculoskeletal metastases.

Follow-up CT and CT angiography after intracranial aneurysm clipping and coiling-improved image quality by iterative metal artifact reduction.

This paper aims to evaluate a new iterative metal artifact reduction algorithm for post-interventional evaluation of brain tissue and intracranial arteries. The data of 20 patients that underwent follow-up cranial CT and cranial CT angiography after clipping or coiling of an intracranial aneurysm was retrospectively analyzed. After the images were processed using a novel iterative metal artifact reduction algorithm, images with and without metal artifact reduction were qualitatively evaluated by two readers, using a five-point Likert scale. Moreover, artifact strength was quantitatively assessed in terms of CT attenuation and standard deviation alterations. The qualitative analysis yielded a significant increase in image quality (p=0.0057) in iteratively processed images with substantial inter-observer agreement (ĸ=0.72), while the CTA image quality did not differ (p=0.864) and even showed vessel contrast reduction in six cases (30%). The mean relative attenuation difference was 27% without metal artifact reduction vs. 11% for iterative metal artifact reduction images (p=0.0003). The new iterative metal artifact reduction algorithm enhances non-enhanced CT image quality after clipping or coiling, but in CT-angiography images, the contrast of adjacent vessels can be compromised.

Implementation of iterative metal artifact reduction in the pre-planning-procedure of three-dimensional physical modeling

BackgroundTo assess the impact of metal artifact reduction techniques in 3D printing by evaluating image quality and segmentation time in both phantom and patient studies with dental restorations and/or other metal implants. An acrylic denture apparatus (Kilgore Typodent, Kilgore International, Coldwater, MI) was set in a 20 cm water phantom and scanned on a single-source CT scanner with gantry tilting capacity (SOMATOM Edge, Siemens Healthcare, Forchheim, Germany) under 5 scenerios: (1) Baseline acquisition at 120 kV with no gantry tilt, no jaw spacer, (2) acquisition at 140 kV, (3) acquisition with a gantry tilt at 15°, (4) acquisition with a non-radiopaque jaw spacer and (5) acquisition with a jaw spacer and a gantry tilt at 15°. All acquisitions were reconstructed both with and without a dedicated iterative metal artifact reduction algorithm (MAR). Patients referred for a head-and-neck exam were included into the study. Acquisitions were performed on the same scanner with 120 kV and the images were reconstructed with and without iterative MAR. Segmentation was performed on a dedicated workstation (Materialise Interactive Medical Image Control Systems; Materialise NV, Leuven, Belgium) to quantify volume of metal artifact and segmentation time.ResultsIn the phantom study, the use of gantry tilt, jaw spacer and increased tube voltage showed no benefit in time or artifact volume reduction. However the jaw spacer allowed easier separation of the upper and lower jaw and a better display of the teeth. The use of dedicated iterative MAR significantly reduced the metal artifact volume and processing time. Same observations were made for the four patients included into the study.ConclusionThe use of dedicated iterative MAR and jaw spacer substantially reduced metal artifacts in the head-and-neck CT acquisitions, hence allowing a faster 3D segmentation workflow.

Improving CT-Based PET Attenuation Correction in the Vicinity of Metal Implants by an Iterative Metal Artifact Reduction Algorithm of CT Data and Its Comparison to Dual-Energy-Based Strategies: A Phantom Study.

The aim of this study was to evaluate the potential of iterative metal artifact reduction (IMAR) for the improvement of computed tomography (CT)-based position emission tomography (PET) attenuation correction in the vicinity of metal implants and compare it with dual-energy-based metal artifact reduction strategies. A dedicated dental phantom was constructed consisting of a cylindrical tube filled with [18-F]FDG solution (5300 mL and 50.9 MBq) containing 2 artificial jaws with 1 nonprecious alloy fixed dental prosthesis and 3 single tooth crowns in the lower jaw.Computed tomography measurements of the phantom were acquired on a stand-alone dual-energy CT scanner equipped with IMAR capabilities. A series of 24 CT data sets were obtained using different scan parameters and monoenergetic extrapolation of dual-energy CT acquisitions with and without IMAR reconstruction.Position emission tomography measurements of the phantom were performed on a state-of-art PET/CT scanner. Position emission tomography data were reconstructed using all 24 previously acquired CT data sets.Relative errors in the quantification of activity concentrations using the different CT scanning and reconstruction parameters were quantified by placement of regions of interest within the phantom. Metal artifacts of different extent were observed in all CT data sets. A marked reduction in CT metal artifacts was observed using IMAR. In general, activity concentrations were overestimated/underestimated in areas of high/low-density metal artifacts, respectively.Relative errors in PET quantification ranged between -71% and +70% without IMAR. Using IMAR, these errors were reduced to a range between -40% and +12%. Averaged absolute values of relative PET quantification errors were 27% and 7% without and with the use of IMAR (P < 0.001), respectively. Iterative metal artifact reduction was superior compared with dual-energy-based metal artifact reduction strategies, and the combination of both strategies did not result in further significant improvement of PET quantification. The use of IMAR in PET/CT is a promising approach for markedly improving image quality and PET quantification in the vicinity of metal implants. Further clinical studies are necessary to assess the clinical performance of this algorithm in patients.

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

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. 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. 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). 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.

P11. Hounsfield CT-values correction with iMAR, impact on dosimetrics calculation for radiation therapy

Introduction Some artifacts caused by prosthesis implants or gold seeds for prostate treatment create uncertainties in CT-Scan images (SOMATOM Scope). This will cause several approximations in radiation therapy (contouring, dose calculation). To improve the treatment, Siemens Healthineers, developed an iterative metal artifact reduction algorithm: iMAR. The aim of this study is to compare HU values reconstructed by the CT-Scan with and without iMAR for prostate treatment. And finally, evaluating dosimetrics effects by calculation of dose on iMAR corrected images. Methods The study is based on three steps. Firstly, on 30 patients with and without prosthesis/gold seeds to evaluate the average of HU into and outside prostate, before and after iMAR correction. Secondly, created customized phantom (QuasarTM) with known material inserts (CIRS Model 062) to simulate human pelvic linked with previous results. We have done CT-Scan acquisitions of the phantom to evaluate accuracy in retrieving correct HU values and Standard Deviation (SD). The reference acquisition is made with QuasarTM acrylic insert, and an acquisition with double metals prosthesis inserts (with/without iMAR reconstruction) is performed. Same ROI (4 cm2) are calculated in this three reconstructions CT images to compare HU values and SD. Thirdly, 23MV VMAT treatment plan in the TPS Eclipse® is performed for both reconstruction (iMAR and no iMAR) to evaluate the dose distribution and to be able to do a dose measurement on the Clinac to determine if iMAR reconstruction is more accurate in dose calculation. Results On patients CT images, iMAR allows to regain information lost by metals artefacts. Moreover, the phantom study demonstrating that lost information (up to −100 HU and ± 100 SD) are improved with iMAR correction (up to + 10 HU and ± 15 SD) and outside the streaking artifact, HU and SD are constant. From a dosimetry point of view, the TPS variation in dose calculation may increase up to + 3.32 Gy in one pixel and the dose covering is improved by iMAR for muscle insert (dose constraint is applied). Therefore, iMAR has an impact in the dose calculation. Finally, the dose verification between treatment in Linac and calculation in TPS (in two measured points) shows that calculation in TPS is more accurate with iMAR ( ≠ 3% out of dose constraint and ≠ 0.2% in dose constraint) compared without iMAR ( ≠ 8.1% out of dose constraint and ≠ 1% in dose constraint). Conclusions iMAR algorithm increases confidence in contouring due to a visualisation of organ’s outlines with a very close reproduction of the HU values and SD. This, enables a stability of the information in TPS for dose calculation. Therefore, dose calculation is improved for the dose covering and dose calculation in TPS is closer to reality.