Nonlinearly scaled prior image-controlled frequency split for high-frequency metal artifact reduction in computed tomography.

PURPOSE: This paper introduces a new approach for the dedicated reduction of high-frequency metal artifacts, which applies a nonlinear scaling (NLS) transfer function on the high-frequency projection domain to reduce artifacts, while preserving edge information and anatomic detail by incorporating prior image information. METHODS: An NLS function is applied to suppress high-frequency streak artifacts, but to restrict the correction to metal projections only, scaling is performed in the sinogram domain. Anatomic information should be preserved and is excluded from scaling by incorporating a prior image from tissue classification. The corrected high-frequency sinogram is reconstructed and combined with the low-frequency component of a normalized metal artifact reduction (NMAR) image. Scans of different anthropomorphic phantoms were acquired (unilateral hip, bilateral hip, dental implants, and embolization coil). Multiple regions of interest (ROIs) were drawn around the metal implants and hounsfield unit (HU) deviations were analyzed. Clinical data sets including single image slices of dental fillings, a bilateral hip implant, spinal fixation screws, and an aneurysm coil were reconstructed and assessed. RESULTS: The prior image-controlled NLS can remove streak artifacts while preserving anatomic detail within the bone and soft tissue. The qualitative analysis of clinical cases showed a tremendous enhancement within dental fillings and neuro coils, and a significant enhancement within spinal screws or hip implants. The phantom scan measurements support this observation. In all phantom setups, the NLS-corrected result showed lowest HU derivation and the best visualization of the data. CONCLUSIONS: The prior image-controlled NLS provides a method to reduce high-frequency streaks in metal-corrupted computed tomography (CT) data.

Impact of Different Metal Artifact Reduction Techniques on Attenuation Correction of Normal Organs in 18F-FDG-PET/CT.

PURPOSE: To evaluate the impact of different metal artifact reduction algorithms on Hounsfield units (HU) and the standardized uptake value (SUV) in normal organs in patients with different metal implants. METHODS: This study prospectively included 66 patients (mean age of 66.02 ± 13.1 years) with 87 different metal implants. CT image reconstructions were performed using weighted filtered back projection (WFBP) as the standard method, metal artifact reduction in image space (MARIS), and an iterative metal artifacts reduction (iMAR) algorithm for large implants. These datasets were used for PET attenuation correction. HU and SUV measurements were performed in nine predefined anatomical locations: liver, lower lung lobes, descending aorta, thoracic vertebral body, autochthonous back muscles, pectoral muscles, and internal jugular vein. Differences between HU and SUV measurements were compared using paired t-tests. The significance level was determined as p = 0.017 using Bonferroni correction. RESULTS: No significant differences were observed between reconstructed images using iMAR and WFBP concerning HU and SUV measurements in liver (HU: p = 0.055; SUVmax: p = 0.586), lung (HU: p = 0.276; SUVmax: p = 1.0 for the right side and HU: p = 0.630; SUVmax: p = 0.109 for the left side), descending aorta (HU: p = 0.333; SUVmax: p = 0.083), thoracic vertebral body (HU: p = 0.725; SUVmax: p = 0.392), autochthonous back muscles (HU: p = 0.281; SUVmax: p = 0.839), pectoral muscles (HU: p = 0.481; SUVmax: p = 0.277 for the right side and HU: p = 0.313; SUVmax: p = 0.859 for the left side), or the internal jugular vein (HU: p = 0.343; SUVmax: p = 0.194). CONCLUSION: Metal artifact reduction algorithms such as iMAR do not alter the data information of normal organs not affected by artifacts.

Dual-Energy CT Vital Iodine Tumor Burden for Response Assessment in Patients With Metastatic GIST Undergoing TKI Therapy: Comparison With Standard CT and FDG PET/CT Criteria.

BACKGROUND. CT-based criteria for assessing the gastrointestinal stromal tumor (GIST) response to tyrosine kinase inhibitor (TKI) therapy are limited in part because tumor attenuation is influenced by treatment-related changes including hemorrhage and calcification. The iodine concentration may be less impacted by such changes. OBJECTIVE. The purpose of this study was to determine whether the dual-energy CT (DECT) vital iodine tumor burden (TB) allows improved differentiation between treatment responders and nonresponders among patients with metastatic GIST who are undergoing TKI therapy compared with established CT and PET/CT criteria. METHODS. An anthropomorphic phantom with spherical inserts mimicking GIST lesions of varying iodine concentrations and having nonenhancing central necrotic cores underwent DECT to determine a threshold iodine concentration. Forty patients (25 women and 15 men; median age, 57 years) who were treated with TKI for metastatic GIST were retrospectively evaluated. Patients underwent baseline and follow-up DECT and FDG PET/CT. Response assessment was performed using RECIST 1.1, modified Choi (mChoi) criteria, vascular tumor burden (VTB) criteria, DECT vital iodine TB criteria, and European Organization for Research and Treatment of Cancer (EORTC) PET criteria. DECT vital iodine TB criteria used the same percentage changes as RECIST 1.1 response categories. Progression-free survival was compared between responders and nonresponders for each response criterion by use of Cox proportional hazard ratios and Harrell C-indexes (i.e., concordance indexes). RESULTS. The phantom experiment identified a threshold of 0.5 mg/mL to differentiate vital from nonvital tissue. With use of the DECT vital iodine TB, median progression-free survival was significantly different between responders and nonresponders (623 vs 104 days; p < .001).. For nonresponders versus responders, the hazard ratio for disease progression for DECT vital iodine TB was 6.9 versus 7.6 for EORTC PET criteria, 3.3 for VTB criteria, 2.3 for RECIST 1.1, and 2.1 for mChoi criteria. The C-index was 0.74 for EORTC PET criteria, 0.73 for DECT vital iodine TB criteria, 0.67 for VTB criteria, 0.61 for RECIST 1.1, and 0.58 for mChoi criteria. The C-index was significantly greater for DECT vital iodine TB criteria than for RECIST 1.1 (p = .02) and mChoi criteria (p = .002), but it was not different from that for VTB and EORTC PET criteria (p > .05). CONCLUSION. DECT vital iodine TB criteria showed performance comparable to that of EORTC PET criteria and outperformed RECIST 1.1 and mChoi criteria for response assessment of metastatic GIST treated with TKI therapy. CLINICAL IMPACT. DECT vital iodine TB could help guide early management decisions in patients receiving TKI therapy.

Dual-Energy CT Perfusion of Invasive Tumor Front in Non-Small Cell Lung Cancers.

Background Active endothelial cell proliferation occurs at the tumor edge, known as the invading-tumor front. This study focused on perfusion analysis of non-small cell lung cancers. Purpose To analyze dual-phase, dual-energy CT perfusion according to the degree of tumor hypoxia. Materials and Methods This prospective study was performed 2016-2017. A two-phase dual-energy CT protocol was obtained for consecutive participants with operable non-small cell lung cancer. The first pass and delayed iodine concentration within the tumor and normalized iodine uptake, corresponding to the iodine concentration within the tumor normalized to iodine concentration within the aorta, were calculated for the entire tumor and within three peripheral layers automatically segmented (ie, 2-mm-thick concentric subvolumes). The expression of the membranous carbonic anhydrase (mCA) IX, a marker of tumor hypoxia, was assessed in tumor specimens. Comparative analyses according to the histologic subtypes, type of resected tumors, and mCA IX expression were performed. Results There were 33 mCA IX-positive tumors and 16 mCA IX-negative tumors. In the entire tumor, the mean normalized iodine uptake was higher on delayed than on first-pass acquisitions (0.35 ± 0.17 vs 0.13 ± 0.15, respectively; P < .001). A single layer, located at the edge of the tumor, showed higher values of the iodine concentration (median, 0.53 mg/mL vs 0.21 mg/mL, respectively; P = .03) and normalized iodine uptake (0.04 vs 0.02, respectively; P = .03) at first pass in mCA IX-positive versus mCA IX-negative tumors. Within this layer, a functional profile of neovascularization was found in 23 of 33 (70%) of mCA IX-positive tumors, and the median mCA IX score of these tumors was higher than in tumors with a nonfunctional profile of neovascularization (median mCA IX score, 20 vs 2, respectively; P = .03). Conclusion A two-phase dual-energy CT examination depicted higher perfusion between the tumor edge and lung parenchyma in hypoxic tumors. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Murphy and Ryan in this issue.

Impact of different iterative metal artifact reduction (iMAR) algorithms on PET/CT attenuation correction after port implementation.

PURPOSE: To evaluate the effect of various interactive metal artifact reduction (iMAR) algorithms on attenuation correction in the vicinity of port chambers in PET/CT. MATERIAL AND METHODS: In this prospective study, 30 oncological patients (12 female, 18 male, mean age 59.6 ± 10.5y) with implanted port chambers undergoing 18F-FDG PET/CT were included. CT images were reconstructed with standard weighted filtered back projection (WFBP) and three different iMAR algorithms (hip, dental filling (DF) and pacemaker (PM)). PET attenuation correction was performed with all four CT datasets. SUVmean, SUVmax and HU measurements were performed in fat and muscle tissue in the vicinity of the port chamber at the location of the strongest bright and dark band artifacts. Differences between HU and SUV values across all CT- and PET-images were investigated using a paired t-test. Bonferroni correction was used to prevent alpha-error accumulation (p < 0.008). RESULTS: In comparison to WFBP (fat: 94.2 ± 53.9 HU, muscle: 197.6 ± 49.2 HU) all three iMAR algorithms led to a decrease of HU in bright band artifacts. iMAR-DF led to a decrease of 159.2 % (fat: -51.9 ± 58.5 HU, muscle: 94.5 ± 55.3 HU), iMAR-hip of 138.3 % (fat: -30.3 ± 58.5, muscle: 70.4 ± 28.8) and iMAR-PM of 122.3 % (fat: -21.2 ± 47.2 HU, muscle: 72.5 ± 25.1 HU; for all p < 0.008). There was no significant effect of iMAR on SUV measurements in comparison to WFBP. CONCLUSION: iMAR leads to a significant change of HU values in artifacts caused by port catheter chambers in comparison to WFBP. However, no significant differences in attenuation correction and consecutive changes in SUV measurements can be observed.

Correlation of Iodine Quantification and FDG Uptake in Early Therapy Response Assessment of Non-small Cell Lung Cancer: Possible Benefit of Dual-energy CT Scan as an Integral Part of PET/CT Examination.

AIM: To compare iodine-related and fluorine-18 fluorodeoxyglucose (18F-FDG) parameters during staging of lung cancer as well as during early follow-up, while investigating potential use and possible substitutability in the assessment of therapeutic response or prediction. PATIENTS AND METHODS: Patients (n=45) with confirmed lung cancer underwent 18F-FDG positron-emission tomography (PET) using single-source dual-energy computed tomography was performed for staging and early follow-up. Correlation of FDG uptake and iodine-related parameters was assessed and comparison with therapy response was performed. RESULTS: A strong correlation was found between the volumetric FDG parameters metabolic tumour volume (MTV) and total lesion glycolysis (TLG) and iodine uptake (IU) in staging (IU vs. MTV: rs=0.894; p<0.001 and IU vs. TLG: rs=0.874; p<0.001) and follow-up (IU vs. MTV: rs=0.934, p<0.001 and IU vs. TLG: rs=0.935, p<0.001). We also found significant correlation of change in these values between timepoints. We observed a significant correlation of IU, MTV and TLG with early therapy response and IU was found as a possible strong predictor. CONCLUSION: Strong correlation of IU and volume-based FDG parameters was proved in staging, follow-up and change during therapy. Potential role of IU in prediction of early therapy-response was identified. Our study suggests a significant benefit of using the dual-energy computed tomography as a part of 18F-FDG PET/CT in patients with lung cancer.

Semiautomatic Segmentation and Radiomics for Dual-Energy CT: A Pilot Study to Differentiate Benign and Malignant Hepatic Lesions.

OBJECTIVE. This study assessed a machine learning-based dual-energy CT (DECT) tumor analysis prototype for semiautomatic segmentation and radiomic analysis of benign and malignant liver lesions seen on contrast-enhanced DECT. MATERIALS AND METHODS. This institutional review board-approved study included 103 adult patients (mean age, 65 ± 15 [SD] years; 53 men, 50 women) with benign (60/103) or malignant (43/103) hepatic lesions on contrast-enhanced dual-source DECT. Most malignant lesions were histologically proven; benign lesions were either stable on follow-up CT or had characteristic benign features on MRI. Low- and high-kilovoltage datasets were deidentified, exported offline, and processed with the DECT tumor analysis for semiautomatic segmentation of the volume and rim of each liver lesion. For each segmentation, contrast enhancement and iodine concentrations as well as radiomic features were derived for different DECT image series. Statistical analyses were performed to determine if DECT tumor analysis and radiomics can differentiate benign from malignant liver lesions. RESULTS. Normalized iodine concentration and mean iodine concentration in the benign and malignant lesions were significantly different (p < 0.0001-0.0084; AUC, 0.695-0.856). Iodine quantification and radiomic features from lesion rims (AUC, ≤ 0.877) had higher accuracy for differentiating liver lesions compared with the values from lesion volumes (AUC, ≤ 0.856). There was no difference in the accuracies of DECT iodine quantification (AUC, 0.91) and radiomics (AUC, 0.90) for characterizing liver lesions. CONCLUSION. DECT radiomics were more accurate than iodine quantification for differentiating solid benign and malignant hepatic lesions.

Can Dual-Energy Computed Tomography Quantitative Analysis and Radiomics Differentiate Normal Liver From Hepatic Steatosis and Cirrhosis?

OBJECTIVES: This study aimed to assess if dual-energy computed tomography (DECT) quantitative analysis and radiomics can differentiate normal liver, hepatic steatosis, and cirrhosis. MATERIALS AND METHODS: Our retrospective study included 75 adult patients (mean age, 54 ± 16 years) who underwent contrast-enhanced, dual-source DECT of the abdomen. We used Dual-Energy Tumor Analysis prototype for semiautomatic liver segmentation and DECT and radiomic features. The data were analyzed with multiple logistic regression and random forest classifier to determine area under the curve (AUC). RESULTS: Iodine quantification (AUC, 0.95) and radiomic features (AUC, 0.97) differentiate between healthy and abnormal liver. Combined fat ratio percent and mean mixed CT values (AUC, 0.99) were the strongest differentiators of healthy and steatotic liver. The most accurate differentiating parameters of normal liver and cirrhosis were a combination of first-order statistics (90th percentile), gray-level run length matrix (short-run low gray-level emphasis), and gray-level size zone matrix (gray-level nonuniformity normalized; AUC, 0.99). CONCLUSION: Dual-energy computed tomography iodine quantification and radiomics accurately differentiate normal liver from steatosis and cirrhosis from single-section analyses.

Impact of different metal artifact reduction techniques on attenuation correction in 18F-FDG PET/CT examinations.

OBJECTIVE: To evaluate the impact of different metal artifact reduction (MAR) algorithms on Hounsfield unit (HU) and standardized uptake values (SUV) in a phantom setting and verify these results in patients with metallic implants undergoing oncological PET/CT examinations. METHODS AND MATERIALS: In this prospective study, PET-CT examinations of 28 oncological patients (14 female, 14 male, mean age 69.5 ± 15.2y) with 38 different metal implants were included. CT datasets were reconstructed using standard weighted filtered back projection (WFBP) without MAR, MAR in image space (MARIS) and iterative MAR (iMAR, hip algorithm). The three datasets were used for PET attenuation correction. SUV and HU measurements were performed at the site of the most prominent bright and dark band artifacts. Differences between HU and SUV values across the different reconstructions were compared using paired t-tests. Bonferroni correction was used to prevent alpha-error accumulation (p < 0.017). RESULTS: For bright band artifacts, MARIS led to a non-significant mean decrease of 12.0% (345 ± 315 HU) in comparison with WFBP (391 ± 293 HU), whereas iMAR led to a significant decrease of 68.3% (125 ± 185 HU, p < 0.017). For SUVmean, MARIS showed no significant effect in comparison with WFBP (WFBP: 0.99 ± 0.40, MARIS: 0.96 ± 0.39), while iMAR led to a significant decrease of 11.1% (0.88 ± 0.35, p < 0.017). Similar results were observed for dark band artifacts. CONCLUSION: iMAR significantly reduces artifacts caused by metal implants in CT and thus leads to a significant change of SUV measurements in bright and dark band artifacts compared with WFBP and MARIS, thus probably improving PET quantification. ADVANCES IN KNOWLEDGE: The present work indicates that MAR algorithms such as iMAR algorithm in integrated PET/CT scanners are useful to improve CT image quality as well as PET quantification in the evaluation of tracer uptake adjacent to large metal implants. A detailed analysis of oncological patients with various large metal implants using different MAR algorithms in PET/CT has not been conducted yet.

Development of a scanner-specific simulation framework for photon-counting computed tomography.

The aim of this study was to develop and validate a simulation platform that generates photon-counting CT images of voxelized phantoms with detailed modeling of manufacturer-specific components including the geometry and physics of the x-ray source, source filtrations, anti-scatter grids, and photon-counting detectors. The simulator generates projection images accounting for both primary and scattered photons using a computational phantom, scanner configuration, and imaging settings. Beam hardening artifacts are corrected using a spectrum and threshold dependent water correction algorithm. Physical and computational versions of a clinical phantom (ACR) were used for validation purposes. The physical phantom was imaged using a research prototype photon-counting CT (Siemens Healthcare) with standard (macro) mode, at four dose levels and with two energy thresholds. The computational phantom was imaged with the developed simulator with the same parameters and settings used in the actual acquisition. Images from both the real and simulated acquisitions were reconstructed using a reconstruction software (FreeCT). Primary image quality metrics such as noise magnitude, noise ratio, noise correlation coefficients, noise power spectrum, CT number, in-plane modulation transfer function, and slice sensitivity profiles were extracted from both real and simulated data and compared. The simulator was further evaluated for imaging contrast materials (bismuth, iodine, and gadolinium) at three concentration levels and six energy thresholds. Qualitatively, the simulated images showed similar appearance to the real ones. Quantitatively, the average relative error in image quality measurements were all less than 4% across all the measurements. The developed simulator will enable systematic optimization and evaluation of the emerging photon-counting computed tomography technology.

Noise insertion in CT for cocaine body packing: where is the limit of extensive dose reduction?

BACKGROUND: To evaluate the detection rate and image quality in CT-body-packer-screening at different radiation-dose levels and to determine a dose threshold that enables a reliable detection of incorporated body packs and incidental findings with a maximum of dose saving. MATERIALS AND METHODS: We retrospectively included 27 individuals who underwent an abdominal CT with automated exposure control due to suspected body packing. CT images were reconstructed at different radiation-dose levels of 50%, 10, 5% and 1% using iterative reconstructions. All 135 CT reconstructions were evaluated by three independent readers. Reviewers determined the presence of foreign bodies and evaluated the image quality using a 5-point ranking scale. In addition, visualization of incidental findings was assessed. RESULTS: A threshold of 5% (effective dose 0.11 ± 0.07 mSv) was necessary to correctly identify all 27 patients with suspected body packing. Extensive noise insertion to a dose level of 1% (0.02 ± 0.01 mSV) led to false-positive solid cocaine findings in three patients. Image quality was comparable between 100 and 50%. The threshold for correct identification of incidental findings was 10% of the initial dose (effective dose 0.21 ± 0.13 mSv). CONCLUSIONS: Our results indicate that dose of abdominal CT for the detection of intracorporeal cocaine body packets can be markedly reduced to up to 5% of the initial dose while still providing sufficient image quality to detect ingested body packets. However, a minimum effective dose of 0.21 mSv (10% of initial dose) seems to be required to properly identify incidental findings.

Locally advanced gastric cancer: total iodine uptake to predict the response of primary lesion to neoadjuvant chemotherapy.

PURPOSE: Pathologic response to neoadjuvant chemotherapy is a prognostic factor in many cancer types. However, the existing evaluative criteria are deficient. We sought to prospectively evaluate the total iodine uptake derived from dual-energy computed tomography (DECT) in predicting treatment efficacy and progression-free survival (PFS) time in gastric cancer after neoadjuvant chemotherapy. METHODS: From October 2012 to December 2015, 44 patients with locally advanced gastric cancer were examined with DECT 1 week before and three cycles after neoadjuvant chemotherapy. The percentage changes in tumor area (%ΔS), diameter (%ΔD), and density (%ΔHU) were calculated to evaluate the WHO, RESCIST, and Choi criteria. The percentage changes in tumor volume (%ΔV) and total iodine uptake of portal phase (%ΔTIU-p) were also calculated to determine cut-off values by ROC curves. The correlation between the different criteria and histopathologic tumor regression grade (Becker score) or PFS were statistically analyzed. RESULTS: Forty-four patients were divided into responders and non-responders according to 43.34% volume reduction (P = 0.002) and 63.87% (P = 0.002) TIU-p reduction, respectively. The %ΔTIU-p showed strong (r = 0.602, P = 0.000) and %ΔV showed moderate (r = 0.416, P = 0.005), while the WHO (r = 0.075, P = 0.627), RECIST (r = 0.270, P = 0.077) and Choi criteria (r = 0.238, P = 0.120) showed no correlation with the Becker score. The differences in PFS time between the responder and non-responder groups were significant according to %ΔTIU-p and Choi criteria (P = 0.001 and P = 0.013, respectively). CONCLUSIONS: The TIU-p can help predict pathological regression in advanced gastric cancer patients after neoadjuvant chemotherapy. In addition, the %ΔTIU-p could be one of the potentially valuable predictive parameters of the PFS time.

Single-source Dual-energy CT as a Part of 18F-FDG PET/CT: Direct Comparison of Iodine-related and Metabolic Parameters in Non-small Cell Lung Cancer.

Aim: The aim of the study was to assess possible correlation of fluorogeoxyglucose (FDG) uptake and iodine-related attenuation values derived from positron-emission tomography/computed tomography (PET/CT) using single-source dual-energy CT scan (DE-CT) in non-small cell lung cancer (NSCLC). Materials and Methods: Forty-eight patients with histologically-proven NSCLC underwent 18 F-FDG-PET/CT within their staging process. PET/CT included single-source DE-CT in late post-contrast phase. Direct comparison of PET and DE-related values was performed. A sub-study regarding different histological types and various thresholds for quantification of volume metabolic values was also performed. Results: A strong correlation was found of metabolic tumor volume and total lesion glycolysis with total iodine content using Pearson correlation analysis (r=0.965-0.983; p<0.0001) with various thresholds for FDG lesion segmentation. The strongest correlations with iodine content were reached using 10% threshold for segmentation. Only a weak correlation was found between iodine content and the maximal standard uptake value. A significant difference between adenocarcinomas and other histological subtypes was found for selected parameters of metabolic PET and DE-CT data. Conclusion: Our study demonstrated a strong correlation of the iodine content calculated from single-source DE-CT with volumetric FDG parameters in NSCLC. without a significant effect of the threshold value for FDG lesion segmentation.

Techniques for virtual lung nodule insertion: volumetric and morphometric comparison of projection-based and image-based methods for quantitative CT.

Virtual nodule insertion paves the way towards the development of standardized databases of hybrid CT images with known lesions. The purpose of this study was to assess three methods (an established and two newly developed techniques) for inserting virtual lung nodules into CT images. Assessment was done by comparing virtual nodule volume and shape to the CT-derived volume and shape of synthetic nodules. 24 synthetic nodules (three sizes, four morphologies, two repeats) were physically inserted into the lung cavity of an anthropomorphic chest phantom (KYOTO KAGAKU). The phantom was imaged with and without nodules on a commercial CT scanner (SOMATOM Definition Flash, Siemens) using a standard thoracic CT protocol at two dose levels (1.4 and 22 mGy CTDIvol). Raw projection data were saved and reconstructed with filtered back-projection and sinogram affirmed iterative reconstruction (SAFIRE, strength 5) at 0.6 mm slice thickness. Corresponding 3D idealized, virtual nodule models were co-registered with the CT images to determine each nodule's location and orientation. Virtual nodules were voxelized, partial volume corrected, and inserted into nodule-free CT data (accounting for system imaging physics) using two methods: projection-based Technique A, and image-based Technique B. Also a third Technique C based on cropping a region of interest from the acquired image of the real nodule and blending it into the nodule-free image was tested. Nodule volumes were measured using a commercial segmentation tool (iNtuition, TeraRecon, Inc.) and deformation was assessed using the Hausdorff distance. Nodule volumes and deformations were compared between the idealized, CT-derived and virtual nodules using a linear mixed effects regression model which utilized the mean, standard deviation, and coefficient of variation ([Formula: see text], [Formula: see text] and [Formula: see text] of the regional Hausdorff distance. Overall, there was a close concordance between the volumes of the CT-derived and virtual nodules. Percent differences between them were less than 3% for all insertion techniques and were not statistically significant in most cases. Correlation coefficient values were greater than 0.97. The deformation according to the Hausdorff distance was also similar between the CT-derived and virtual nodules with minimal statistical significance in the ([Formula: see text]) for Techniques A, B, and C. This study shows that both projection-based and image-based nodule insertion techniques yield realistic nodule renderings with statistical similarity to the synthetic nodules with respect to nodule volume and deformation. These techniques could be used to create a database of hybrid CT images containing nodules of known size, location and morphology.

Iterative metal artefact reduction (MAR) in postsurgical chest CT: comparison of three iMAR-algorithms.

OBJECTIVES: The purpose of this study was to evaluate the impact of three novel iterative metal artefact (iMAR) algorithms on image quality and artefact degree in chest CT of patients with a variety of thoracic metallic implants. METHODS: 27 postsurgical patients with thoracic implants who underwent clinical chest CT between March and May 2015 in clinical routine were retrospectively included. Images were retrospectively reconstructed with standard weighted filtered back projection (WFBP) and with three iMAR algorithms (iMAR-Algo1 = Cardiac algorithm, iMAR-Algo2 = Pacemaker algorithm and iMAR-Algo3 = ThoracicCoils algorithm). The subjective and objective image quality was assessed. RESULTS: Averaged over all artefacts, artefact degree was significantly lower for the iMAR-Algo1 (58.9 ± 48.5 HU), iMAR-Algo2 (52.7 ± 46.8 HU) and the iMAR-Algo3 (51.9 ± 46.1 HU) compared with WFBP (91.6 ± 81.6 HU, p < 0.01 for all). All iMAR reconstructed images showed significantly lower artefacts (p < 0.01) compared with the WFPB while there was no significant difference between the iMAR algorithms, respectively. iMAR-Algo2 and iMAR-Algo3 reconstructions decreased mild and moderate artefacts compared with WFBP and iMAR-Algo1 (p < 0.01). CONCLUSION: All three iMAR algorithms led to a significant reduction of metal artefacts and increase in overall image quality compared with WFBP in chest CT of patients with metallic implants in subjective and objective analysis. The iMARAlgo2 and iMARAlgo3 were best for mild artefacts. IMARAlgo1 was superior for severe artefacts. Advances in knowledge: Iterative MAR led to significant artefact reduction and increase image-quality compared with WFBP in CT after implementation of thoracic devices. Adjusting iMAR-algorithms to patients' metallic implants can help to improve image quality in CT.

Radiation dose reduction in parasinus CT by spectral shaping.

INTRODUCTION: Spectral shaping aims to narrow the X-ray spectrum of clinical CT. The aim of this study was to determine the image quality and the extent of radiation dose reduction that can be achieved by tin prefiltration for parasinus CT. METHODS: All scans were performed with a third generation dual-source CT scanner. A study protocol was designed using 100 kV tube voltage with tin prefiltration (200 mAs) that provides image noise levels comparable to a low-dose reference protocol using 100 kV without spectral shaping (25 mAs). One hundred consecutive patients were prospectively enrolled and randomly assigned to the study or control group. All patients signed written informed consent. The study protocol was approved by the local Institutional Review Board and applies to the HIPAA. Subjective and objective image quality (attenuation values, image noise, and contrast-to-noise ratio (CNR)) were assessed. Radiation exposure was assessed as volumetric CT dose index, and effective dose was estimated. Mann-Whitney U test was performed for radiation exposure and for image noise comparison. RESULTS: All scans were of diagnostic image quality. Image noise in air, in the retrobulbar fat, and in the eye globe was comparable between both groups (all p > 0.05). CNReye globe/air did not differ significantly between both groups (p = 0.7). Radiation exposure (1.7 vs. 2.1 mGy, p < 0.01) and effective dose (0.055 vs. 0.066 mSv, p < 0.01) were significantly reduced in the study group. CONCLUSION: Radiation dose can be further reduced by 17% for low-dose parasinus CT by tin prefiltration maintaining diagnostic image quality.

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.

Evaluation of bone mineral density of the lumbar spine using a novel phantomless dual-energy CT post-processing algorithm in comparison with dual-energy X-ray absorptiometry.

BACKGROUND: Current techniques for evaluation of bone mineral density (BMD) commonly require phantom calibration. The purpose of this study was to evaluate a novel algorithm for phantomless in vivo dual-energy computed tomography (DECT)-based assessment of BMD of the lumbar spine in comparison with dual-energy X-ray absorptiometry (DEXA). METHODS: Data from clinically indicated DECT and DEXA examinations within two months comprising the lumbar spine of 47 patients were retrospectively evaluated. By using a novel automated dedicated post-processing algorithm for DECT, the trabecular bone of lumbar vertebrae L1-L4 was selected and analysed. Linear correlation was analysed using Pearson's product-moment correlation coefficient for the comparison of the results from DECT and DEXA. RESULTS: A total of 186 lumbar vertebrae in 47 patients (mean age, 58 years; age range, 24-85 years) were analysed, 24 men (mean age, 55 years; age range, 24-85 years) and 23 women (mean age, 59 years; age range, 31-80 years). Mean BMD of L1-L4 determined with DEXA was 0.985 g/cm2 and 20/47 patients (42.6%) showed an osteoporotic BMD (T score lower than - 2.5) of at least two vertebrae. Average DECT-based BMD of L1-L4 was 86.8 mg/cm3. Regression analysis demonstrated a lack of correlation between DECT- and DEXA-based BMD values with a Pearson's product-moment correlation coefficient r = 0.4205. CONCLUSIONS: Dedicated post-processing of DECT data using a novel algorithm for retrospective phantomless BMD assessment of the trabecular bone of lumbar vertebrae from clinically indicated DECT examinations is feasible.

Noise Reduction in Abdominal Computed Tomography Applying Iterative Reconstruction (ADMIRE).

RATIONALE AND OBJECTIVES: The study aimed to compare image quality of filtered back projection (FBP) and iterative reconstruction (advanced modeled iterative reconstruction, ADMIRE) in contrast-enhanced computed tomography (CT) of the abdomen, and to assess the differences of reconstructions according to these methods. It also aimed to investigate the potential for noise reduction of ADMIRE for different reconstructed slice thicknesses. MATERIALS AND METHODS: CT data of the abdomen and pelvis were acquired using a 128-slice single-source CT system using automated kV selection and tube current adaption based on patients' anatomy. Raw data sets from patients scanned at 100 kV were selected, and images were reconstructed with slice thicknesses of 1 mm, 3 mm, and 5 mm, both with FBP and ADMIRE. Filter strength F1, F3, and F5 of the ADMIRE algorithm and the corresponding reconstruction kernels were used. In total, 58 raw data sets from 17 patients were used to reconstruct from the same raw data FBP and ADMIRE images, representing identical body regions. Identical regions of interest were placed at the same position of up to four images and image noise was measured. Differences of reconstructed images and detail preservation were tested using an image subtraction technique, and subjective image quality was assessed using a 5-point Likert scale. RESULTS: On average, for 1-mm slice thickness, noise reduction was 9.15% ± 2.4% with filter strength level F1, 30.2% ± 3.4% with F3, and 54.4% ± 7.0% with F5 as compared to FBP. For a slice thickness of 3 mm, noise reduction was 8.5% ± 3.7% with F1, 28.6% ± 3.9% with F3, and 52.2% ± 9.1% with F5. For 5 mm, the corresponding values are 8.9% ± 2.7%, 31.4% ± 2.8%, and 52.7% ± 7.7%. On subtraction images, edge information of tissue classes with a high attenuation gradient was found, but structures with small differences in attenuation were not detectable on subtraction images, confirming that no relevant details were lost in the iterative reconstruction process. CONCLUSIONS: ADMIRE is able to reduce image noise considerably (up to 50%) without any obvious negative impact on lesion depiction as assessed visually. Noise reduction of ADMIRE seems to be independent of slice thickness.

Dual-Phase Dual-Energy CT in Patients Treated with Erlotinib for Advanced Non-Small Cell Lung Cancer: Possible Benefits of Iodine Quantification in Response Assessment.

OBJECTIVES: To investigate the relationship of dual-phase dual-energy CT (DE-CT) and tumour size in the evaluation of the response to anti-EGFR therapy in patients with advanced non-small cell lung cancer (NSCLC). METHODS: Dual-phase DE-CT was performed in 31 patients with NSCLC before the onset of anti-EGFR (erlotinib) therapy and as follow-up (mean 8 weeks). Iodine uptake (IU; mg/mL) was quantified using prototype software in arterial and venous phases; arterial enhancement fraction (AEF) was calculated. The change of IU before and after therapy onset was compared with anatomical evaluation in maximal transverse diameter and volume (responders vs. non-responders). RESULTS: A significant decrease of IU in venous phase was proved in responders according to all anatomical parameters (p=0.002-0.016). In groups of non-responders, a significant change of IU was not proved with variable trends of development. The most significant change was observed using the anatomical parameter of volume (cut-off 73 %). A significant difference of percentage change in AEF was proved between responding and non-responders (p=0.019-0.043). CONCLUSION: Dual-phase DE-CT with iodine uptake quantification is a feasible method with potential benefit in advanced assessment of anti-EGFR therapy response. We demonstrated a decrease in vascularization in the responding primary tumours and non-significant variable development of vascularization in non-responding tumours. KEY POINTS: • Dual-phase DE-CT is feasible for vascularization assessment of NSCLC with anti-EGFR therapy. • There was a significant decrease of iodine uptake in responding tumours. • There was a non-significant and variable development in non-responding tumours. • There was significant difference of AEF percentage change between responders and non-responders.