Rainer Raupach

Normalized metal artifact reduction (NMAR) in computed tomography

PURPOSE While modern clinical CT scanners under normal circumstances produce high quality images, severe artifacts degrade the image quality and the diagnostic value if metal prostheses or other metal objects are present in the field of measurement. Standard methods for metal artifact reduction (MAR) replace those parts of the projection data that are affected by metal (the so-called metal trace or metal shadow) by interpolation. However, while sinogram interpolation methods efficiently remove metal artifacts, new artifacts are often introduced, as interpolation cannot completely recover the information from the metal trace. The purpose of this work is to introduce a generalized normalization technique for MAR, allowing for efficient reduction of metal artifacts while adding almost no new ones. The method presented is compared to a standard MAR method, as well as MAR using simple length normalization. METHODS In the first step, metal is segmented in the image domain by thresholding. A 3D forward projection identifies the metal trace in the original projections. Before interpolation, the projections are normalized based on a 3D forward projection of a prior image. This prior image is obtained, for example, by a multithreshold segmentation of the initial image. The original rawdata are divided by the projection data of the prior image and, after interpolation, denormalized again. Simulations and measurements are performed to compare normalized metal artifact reduction (NMAR) to standard MAR with linear interpolation and MAR based on simple length normalization. RESULTS Promising results for clinical spiral cone-beam data are presented in this work. Included are patients with hip prostheses, dental fillings, and spine fixation, which were scanned at pitch values ranging from 0.9 to 3.2. Image quality is improved considerably, particularly for metal implants within bone structures or in their proximity. The improvements are evaluated by comparing profiles through images and sinograms for the different methods and by inspecting ROIs. NMAR outperforms both other methods in all cases. It reduces metal artifacts to a minimum, even close to metal regions. Even for patients with dental fillings, which cause most severe artifacts, satisfactory results are obtained with NMAR. In contrast to other methods, NMAR prevents the usual blurring of structures close to metal implants if the metal artifacts are moderate. CONCLUSIONS NMAR clearly outperforms the other methods for both moderate and severe artifacts. The proposed method reliably reduces metal artifacts from simulated as well as from clinical CT data. Computationally efficient and inexpensive compared to iterative methods, NMAR can be used as an additional step in any conventional sinogram inpainting-based MAR method.

Automated attenuation-based tube potential selection for thoracoabdominal computed tomography angiography: improved dose effectiveness.

Purpose:To introduce a novel algorithm of automated attenuation-based tube potential selection and to assess its impact on image quality and radiation dose of body computed tomography angiography (CTA). Materials and Methods:In all, 40 patients (mean age 71 ± 11.8 years, body mass index (BMI) 25.7 ± 3.8 kg/m2, range 18.8–33.8 kg/m2) underwent 64-slice thoracoabdominal CTA (contrast material: 80 mL, 5 mL/s) using an automated tube potential selection algorithm (CAREkV), which optimizes tube-potential (70–140 kV) and tube-current (138.8 ± 18.6 effective mAs, range 106–177 mAs) based on the attenuation profile of the topogram and on the diagnostic task. Image quality was semiquantitatively assessed by 2 blinded and independent readers (scores 1: excellent to 5: nondiagnostic). Attenuation and noise were measured by another 2 blinded and independent readers. Contrast-to-noise ratio was calculated. The CT dose index (CTDIvol) was recorded and compared with the estimated CTDIvol of a standard 120 kV protocol without using the algorithm in each patient. Selected tube potentials were correlated with BMI and attenuation of the topogram. Results:Diagnostic image quality was obtained in all patients (excellent: 14; good: 21; moderate: 5; interreader agreement: &kgr; = 0.78). Mean attenuation, noise, and contrast-to-noise ratio were 260.8 ± 63.5 Hounsfield units, 15.5 ± 3.3 Hounsfield units, and 14 ± 4.2, respectively, with good to excellent agreement between readers (r = 0.50–0.99, P < 0.01 each). Automated attenuation-based tube potential selection resulted in a kV-reduction from 120 to 100 kV in 23 patients and to 80 kV in 1 patient, whereas tube potential increased to 140 kV in 1 patient. Automatically selected tube potential showed a significant correlation with both BMI (r = 0.427, P < 0.05) and attenuation of the topogram (r = 0.831, P < 0.001). CTDIvol (7.95 ± 2.6 mGy) was significantly lower when using the algorithm compared with the standard 120 kV protocol (10.59 ± 1.8 mGy, P < 0.001), corresponding to an overall dose reduction of 25.1%. Conclusion:Automated attenuation-based tube potential selection based on the attenuation profile of the topogram is feasible, provides a diagnostic image quality of body CTA, and reduces overall radiation dose by 25% as compared with a standard protocol with 120 kV.

Frequency split metal artifact reduction (FSMAR) in computed tomography.

PURPOSE The problem of metal artifact reduction (MAR) is almost as old as the clinical use of computed tomography itself. When metal implants are present in the field of measurement, severe artifacts degrade the image quality and the diagnostic value of CT images. Up to now, no generally accepted solution to this issue has been found. In this work, a method based on a new MAR concept is presented: frequency split metal artifact reduction (FSMAR). It ensures efficient reduction of metal artifacts at high image quality with enhanced preservation of details close to metal implants. METHODS FSMAR combines a raw data inpainting-based MAR method with an image-based frequency split approach. Many typical methods for metal artifact reduction are inpainting-based MAR methods and simply replace unreliable parts of the projection data, for example, by linear interpolation. Frequency split approaches were used in CT, for example, by combining two reconstruction methods in order to reduce cone-beam artifacts. FSMAR combines the high frequencies of an uncorrected image, where all available data were used for the reconstruction with the more reliable low frequencies of an image which was corrected with an inpainting-based MAR method. The algorithm is tested in combination with normalized metal artifact reduction (NMAR) and with a standard inpainting-based MAR approach. NMAR is a more sophisticated inpainting-based MAR method, which introduces less new artifacts which may result from interpolation errors. A quantitative evaluation was performed using the examples of a simulation of the XCAT phantom and a scan of a spine phantom. Further evaluation includes patients with different types of metal implants: hip prostheses, dental fillings, neurocoil, and spine fixation, which were scanned with a modern clinical dual source CT scanner. RESULTS FSMAR ensures sharp edges and a preservation of anatomical details which is in many cases better than after applying an inpainting-based MAR method only. In contrast to other MAR methods, FSMAR yields images without the usual blurring close to implants. CONCLUSIONS FSMAR should be used together with NMAR, a combination which ensures an accurate correction of both high and low frequencies. The algorithm is computationally inexpensive compared to iterative methods and methods with complex inpainting schemes. No parameters were chosen manually; it is ready for an application in clinical routine.

Ultralow-dose chest computed tomography for pulmonary nodule detection: first performance evaluation of single energy scanning with spectral shaping.

PurposeThe purpose of this study was to evaluate the image quality and sensitivity of ultralow radiation dose single-energy computed tomography (CT) with tin filtration for spectral shaping and iterative reconstructions for the detection of pulmonary nodules in a phantom setting. MethodsSingle-energy CT was performed using third-generation dual-source CT (SOMATOM Force; 2 × 192 slices) at 70 kVp, 100 kVp with tin filtration (100Sn kVp), and 150Sn kV with tube current-time product adjustments resulting in standard dose (CT volume dose index, 3.1 mGy/effective dose, 1.3 mSv at a scan length of 30 cm), 1/10th dose level (0.3 mGy/0.13 mSv), and 1/20th dose level (0.15 mGy/0.06 mSv). An anthropomorphic chest phantom simulating an intermediate-sized adult with randomly distributed solid pulmonary nodules of various sizes (2–10 mm; attenuation, 75 HU at 120 kVp) was used. Images were reconstructed with advanced model-based iterative reconstruction (ADMIRE; strength levels 3 and 5) and were compared with those acquired with second-generation dual-source CT at 120 kVp (reconstructed with filtered back projection) and sinogram-affirmed iterative reconstruction (strength level 3) at the lowest possible dose at 120 kVp (CT volume dose index, 0.28 mGy). One blinded reader measured image noise, and 2 blinded, independent readers determined overall image quality on a 5-grade scale (1 = nondiagnostic to 5 = excellent) and marked nodule localization with confidence rates on a 5-grade scale (1 = unsure to 5 = high confidence). The constructional drawing of the phantom served as reference standard for calculation of sensitivity. Two patients were included, for proof of concept, who were scanned with the 100Sn kVp protocol at the 1/10th and 1/20th dose level. ResultsImage noise was highest in the images acquired with second-generation dual-source CT and reconstructed with filtered back projection. At both the 1/10th and 1/20th dose levels, image noise at a tube voltage of 100Sn kVp was significantly lower than in the 70 kVp and 150Sn kV data sets (ADMIRE 3, P < 0.01; ADMIRE 5, P < 0.05). Sensitivity of nodule detection was lowest in images acquired with second-generation dual-source CT at 120 kVp and the lowest possible dose. Protocols at 100Sn kVp and ADMIRE 5 showed highest sensitivity at the 1/10th and 1/20th dose levels. Highest numbers of false-positives occurred in second-generation dual-source CT images (range, 12–15), whereas lowest numbers occurred in the 1/10th and 1/20th dose data sets acquired with third-generation dual-source CT at 100Sn kVp and reconstructed with ADMIRE strength levels 3 and 5 (total of 1 and 0 false-positives, respectively). Diagnostic confidence at 100Sn kVp was significantly higher than at 70 kVp or 150Sn kV (ADMIRE 3, P < 0.05; ADMIRE 5, P < 0.01) at both the 1/10th and 1/20th dose levels. Images of the 2 patients scanned with 100Sn kVp at the 1/10th and 1/20th dose levels were of diagnostic quality. ConclusionsOur study suggests that chest CT for the detection of pulmonary nodules can be performed with third-generation dual-source CT producing high image quality, sensitivity, and diagnostic confidence at a very low effective radiation dose of 0.06 mSv when using a single-energy protocol at 100 kVp with spectral shaping and when using advanced iterative reconstruction techniques.

Wavelet Based Noise Reduction in CT-Images Using Correlation Analysis

The projection data measured in computed tomography (CT) and, consequently, the slices reconstructed from these data are noisy. We present a new wavelet based structure-preserving method for noise reduction in CT-images that can be used in combination with different reconstruction methods. The approach is based on the assumption that data can be decomposed into information and temporally uncorrelated noise. In CT two spatially identical images can be generated by reconstructions from disjoint subsets of projections: using the latest generation dual source CT-scanners one image can be reconstructed from the projections acquired at the first, the other image from the projections acquired at the second detector. For standard CT-scanners the two images can be generated by splitting up the set of projections into even and odd numbered projections. The resulting images show the same information but differ with respect to image noise. The analysis of correlations between the wavelet representations of the input images allows separating information from noise down to a certain signal-to-noise level. Wavelet coefficients with small correlation are suppressed, while those with high correlations are assumed to represent structures and are preserved. The final noise-suppressed image is reconstructed from the averaged and weighted wavelet coefficients of the input images. The proposed method is robust, of low complexity and adapts itself to the noise in the images. The quantitative and qualitative evaluation based on phantom as well as real clinical data showed, that high noise reduction rates of around 40% can be achieved without noticeable loss of image resolution.

64- Versus 16-slice CT angiography for coronary artery stent assessment: in vitro experience.

Objectives:We sought to assess the visualization of different coronary artery stents and the delineation of in-stent stenoses using 64- and 16-slice multidector computed tomography (MDCT). Materials and Methods:A total of 15 different coronary stents with a simulated in-stent stenosis were placed in a vascular phantom and scanned with a 16-slice and a 64-slice MDCT at orientations of 0°, 45°, and 90° relative to the scanners z-axis. Visible lumen diameter and attenuation in the stented and the unstented segment of the phantom were measured. Three readers assessed stenosis delineation and visualization of the residual lumen using a 5-point scale. Results:Artificial lumen narrowing (ALN) was significantly reduced with 64-slice CT compared with 16-slice CT. At an angle of 0°, 45°, and 90° relative to the scanners z-axis, the ALN for 16-slice CT was 42.2%, 39.8%, and 44.0% using a slice-thickness of 1.0 mm and 40.9%, 40.4%, and 41.6% using a slice thickness of 0.75 mm, respectively. With 64-slice CT, the ALN was 39.1%, 37.3%, and 36.0% at the respective angles. The differences between attenuation values in the stented and unstented segment of the tube were significantly lower for 64-slice CT. Mean visibility scores were significantly higher for 64-slice CT. Conclusion:Use of the 64-slice CT results in superior visualization of the stent lumen and in-stent stenosis compared with 16-slice CT, especially when the stent is orientated parallel to the x-ray beam.

Iterative Reconstruction Algorithm for Abdominal Multidetector CT at Different Tube Voltages: Assessment of Diagnostic Accuracy, Image Quality, and Radiation Dose in a Phantom Study

PURPOSE To assess the diagnostic accuracy, image quality, and radiation dose of an iterative reconstruction algorithm compared with a filtered back projection (FBP) algorithm for abdominal computed tomography (CT) at different tube voltages. MATERIALS AND METHODS A custom liver phantom with 45 simulated hypovascular liver tumors (diameters of 5, 10, and 15 mm; tumor-to-liver contrast of 10, 25, and 50 HU) was placed in a cylindrical water container that mimicked an intermediate-sized patient. The phantom was scanned at 120, 100, and 80 kVp. The CT data sets were reconstructed with FBP and iterative reconstruction. The image noise was measured, and the contrast-to-noise ratio (CNR) of the tumors was calculated. The radiation dose was assessed with the volume CT dose index. Tumor detection was independently performed by three radiologists. Statistical analysis included analysis of variance. RESULTS Compared with the FBP data set at 120 kVp, the iterative reconstruction data set collected at 100 kVp demonstrated significantly lower mean image noise (20.9 and 16.7 HU, respectively; P < .001) and greater mean CNRs for the simulated tumors (P < .001). The iterative reconstruction data set collected at 120 kVp yielded the highest sensitivity for tumor detection, while the FBP data set at 80 kVp yielded the lowest. The sensitivity for the iterative reconstruction data set at 100 kVp was comparable with that for the FBP data set at 120 kVp (79.3% and 74.9%, respectively; P > .99). The volume CT dose index decreased by 39.8% between the 120-kVp protocol and the 100-kVp protocol and by 70.3% between the 120-kVp protocol and the 80-kVp protocol. CONCLUSION Results of this phantom study suggest that a 100-kVp abdominal CT protocol with an iterative reconstruction algorithm for simulated intermediate-sized patients increases the image quality and maintains the diagnostic accuracy at a reduced radiation dose when compared with a 120-kVp protocol with an FBP algorithm.

Analytical evaluation of the signal and noise propagation in x-ray differential phase-contrast computed tomography

We analyze the signal and noise propagation of differential phase-contrast computed tomography (PCT) compared with conventional attenuation-based computed tomography (CT) from a theoretical point of view. This work focuses on grating-based differential phase-contrast imaging. A mathematical framework is derived that is able to analytically predict the relative performance of both imaging techniques in the sense of the relative contrast-to-noise ratio for the contrast of any two materials. Two fundamentally different properties of PCT compared with CT are identified. First, the noise power spectra show qualitatively different characteristics implying a resolution-dependent performance ratio. The break-even point is derived analytically as a function of system parameters such as geometry and visibility. A superior performance of PCT compared with CT can only be achieved at a sufficiently high spatial resolution. Second, due to periodicity of phase information which is non-ambiguous only in a bounded interval statistical phase wrapping can occur. This effect causes a collapse of information propagation for low signals which limits the applicability of phase-contrast imaging at low dose.

Normalized metal artifact reduction in head and neck computed tomography.

ObjectiveArtifacts from dental hardware affect image quality and the visualization of lesions in the oral cavity and oropharynx in computed tomography (CT). Therefore, magnetic resonance imaging is considered the imaging modality of choice in this region. Standard methods for metal artifact reduction (MAR) in CT replace the metal-affected raw data by interpolation, which is prone to new artifacts. We developed a generalized normalization technique for MAR (NMAR) that aims to suppress algorithm-induced artifacts and validated the performance of this algorithm in a clinical trial. Material and MethodsA 3-dimensional forward projection identifies the metal-affected raw data in the original projections after metal is segmented in the image domain by thresholding. A prior image is used to normalize the projections before interpolation. The original raw data are divided pixel-wise by the projection data of the prior image and, after interpolation, are denormalized again. Data from 19 consecutive patients with metal artifacts from dental hardware were reconstructed with standard filtered backprojection (FBP), linear interpolation MAR (LIMAR), and NMAR. The image quality of slices containing metal was analyzed for the severity of artifacts and diagnostic value; magnetic resonance imaging performed the same day on a 3-T system served as a reference standard in all cases. ResultsA total of 260 slices containing metal dental hardware were analyzed. A total of 164 slices were nondiagnostic with FBP, 157 slices with LIMAR, and 87 slices with NMAR. The mean (SD) number of slices per patient with severe artifacts was 10.1 (3.7), 9.6 (4.6), and 5.4 (3.6) and the mean (SD) number of slices with artifacts affecting diagnostic confidence was 3.3 (1.7), 4.9 (2.9), and 3.7 (1.9) for FBP, LIMAR, and NMAR, respectively (P < 0.001). Pairwise comparison did not show significant differences between FBP and LIMAR (P = 0.40), but there were significant differences between FBP and NMAR as well as LIMAR and NMAR (both P < 0.001). Interobserver agreement was excellent (&kgr; = 0.974). Two malignant lesions were unmasked with NMAR image reconstructions. No algorithm-related artifacts were detected in regions that did not contain metal in NMAR images. ConclusionNormalized MAR has the potential to improve image quality in patients with artifacts from dental hardware and to improve the diagnostic accuracy of CT of the oral cavity and oropharynx.

Iterative Image Reconstruction Techniques for CT Coronary Artery Calcium Quantification: Comparison with Traditional Filtered Back Projection in Vitro and in Vivo

PURPOSE To investigate in vitro and in vivo the use of image-based and raw data-based iterative reconstruction algorithms for quantification of coronary artery calcium by using the Agatston score and subsequent cardiac risk stratification. MATERIALS AND METHODS In vitro data were obtained by using a moving anthropomorphic cardiac phantom containing calcium inserts of different concentrations and sizes. With institutional review board approval and HIPAA compliance, coronary calcium imaging data of 110 consecutive patients (mean age ± standard deviation, 58.2 years ± 9.8; 48 men) were reconstructed with filtered back projection (FBP), iterative reconstruction in image space (IRIS), and sinogram-affirmed iterative reconstruction (SAFIRE). Image noise was measured and the Agatston score was obtained for all reconstructions. Assignment to Agatston scores and percentile-based cardiac risk categories was compared. Statistical analysis included the Cohen κ coefficient and Friedman and Wilcoxon testing. RESULTS In vitro, mean Agatston scores ± standard deviation for FBP (638.9 ± 9.6), IRIS (622.7 ± 15.2), and SAFIRE (631.4 ± 17.6) were comparable (P = .30). The smallest phantom calcifications were more frequently detected when iterative reconstruction techniques were used. The Agatston scores in the patient cohort were not significantly different among FBP, IRIS, and SAFIRE in paired comparisons (median Agatston score [25th and 75th percentiles]: 76.0 [20.6, 243.9], 76.4 [22, 249.3], and 75.7 [21.5, 49.1], respectively; P = .20 each). Comparison of categorization based on Agatston score percentiles showed excellent agreement for both IRIS and SAFIRE with FBP (κ = 0.975 [0.942-1.00] and κ = 0.963 [0.922-1.00], respectively). The mean effective dose was 1.02 mSv ± 0.51. Mean image noise was significantly (P < .001) higher with FBP than that with iterative reconstructions. CONCLUSION In comparison with FBP, iterative reconstruction techniques do not have a profound effect on the reproducible quantification of coronary calcium according to Agatston score and subsequent cardiac risk classification, although risk reclassification may occur in a small subset of subjects.