Needle artifact reduction during interventional CT procedures using a silver filter.

BACKGROUND: MAR algorithms have not been productized in interventional imaging because they are too time-consuming. Application of a beam hardening filter can mitigate metal artifacts and doesn't increase computational burden. We evaluate the ability to reduce metal artifacts of a 0.5 mm silver (Ag) additional filter in a Multidetector Computed Tomography (MDCT) scanner during CT-guided biopsy procedures. METHODS: A biopsy needle was positioned inside the lung field of an anthropomorphic phantom (Lungman, Kyoto Kagaku, Kyoto, Japan). CT acquisitions were performed with beam energies of 100 kV, 120 kV, 135 kV, and 120 kV with the Ag filter and reconstructed using a filtered back projection algorithm. For each measurement, the CTDIvol was kept constant at 1 mGy. Quantitative profiles placed in three regions of the artifact (needle, needle tip, and trajectory artifacts) were used to obtain metrics (FWHM, FWTM, width at - 100 HU, and absolute error in HU) to evaluate the blooming artifact, artifact width, change in CT number, and artifact range. An image quality analysis was carried out through image noise measurement. A one-way analysis of variance (ANOVA) test was used to find significant differences between the conventional CT beam energies and the Ag filtered 120 kV beam. RESULTS: The 120 kV-Ag is shown to have the shortest range of artifacts compared to the other beam energies. For needle tip and trajectory artifacts, a significant reduction of - 53.6% (p < 0.001) and - 48.7% (p < 0.001) in the drop of the CT number was found, respectively, in comparison with the reference beam of 120 kV as well as a significant decrease of up to - 34.7% in the artifact width (width at - 100 HU, p < 0.001). Also, a significant reduction in the blooming artifact of - 14.2% (FWHM, p < 0.001) and - 53.3% (FWTM, p < 0.001) was found in the needle artifact. No significant changes (p > 0.05) in image noise between the conventional energies and the 120 kV-Ag were found. CONCLUSIONS: A 0.5 mm Ag additional MDCT filter demonstrated consistent metal artifact reduction generated by the biopsy needle. This reduction may lead to a better depiction of the target and surrounding structures while maintaining image quality.

Development of a classification method for mild liver fibrosis using non-contrast CT image.

PURPOSE: Detection of early-stage liver fibrosis has direct clinical implications on patient management and treatment. The aim of this paper is to develop a non-invasive, cost-effective method for classifying liver disease between "non-fibrosis" (F0) and "fibrosis" (F1-F4), and to evaluate the classification performance quantitatively. METHODS: Image data from 75 patients who underwent a simultaneous liver biopsy and non-contrast CT examination were used for this study. Non-contrast CT image texture features such as wavelet-based features, standard deviation of variance filter, and mean CT number were calculated in volumes of interest (VOIs) positioned within the liver parenchyma. In addition, a combined feature was calculated using logistic regression with L2-norm regularization to further improve fibrosis detection. Based on the final pathology from the liver biopsy, the patients were labelled either as "non-fibrosis" or "fibrosis". Receiver-operating characteristic (ROC) curve, area under the ROC curve (AUROC), specificity, sensitivity, and accuracy were determined for the algorithm to differentiate between "non-fibrosis" and "fibrosis". RESULTS: The combined feature showed the highest classification performance with an AUROC of 0.86, compared to the wavelet-based feature (AUROC, 0.76), the standard deviation of variance filter (AUROC, 0.65), and mean CT number (AUROC, 0.84). The combined feature's specificity, sensitivity, and accuracy were 0.66, 0.88, and 0.76, respectively, showing the most promising results. CONCLUSION: A new non-invasive and cost-effective method was developed to classify liver diseases between "non-fibrosis" (F0) and "fibrosis" (F1-F4). The proposed method makes it possible to detect liver fibrosis in asymptomatic patients using non-contrast CT images for better patient management and treatment.

Standardizing CT lung density measure across scanner manufacturers.

PURPOSE: Computed Tomography (CT) imaging of the lung, reported in Hounsfield Units (HU), can be parameterized as a quantitative image biomarker for the diagnosis and monitoring of lung density changes due to emphysema, a type of chronic obstructive pulmonary disease (COPD). CT lung density metrics are global measurements based on lung CT number histograms, and are typically a quantity specifying either the percentage of voxels with CT numbers below a threshold, or a single CT number below which a fixed relative lung volume, nth percentile, falls. To reduce variability in the density metrics specified by CT attenuation, the Quantitative Imaging Biomarkers Alliance (QIBA) Lung Density Committee has organized efforts to conduct phantom studies in a variety of scanner models to establish a baseline for assessing the variations in patient studies that can be attributed to scanner calibration and measurement uncertainty. METHODS: Data were obtained from a phantom study on CT scanners from four manufacturers with several protocols at various tube potential voltage (kVp) and exposure settings. Free from biological variation, these phantom studies provide an assessment of the accuracy and precision of the density metrics across platforms solely due to machine calibration and uncertainty of the reference materials. The phantom used in this study has three foam density references in the lung density region, which, after calibration against a suite of Standard Reference Materials (SRM) foams with certified physical density, establishes a HU-electron density relationship for each machine-protocol. We devised a 5-step calibration procedure combined with a simplified physical model that enabled the standardization of the CT numbers reported across a total of 22 scanner-protocol settings to a single energy (chosen at 80 keV). A standard deviation was calculated for overall CT numbers for each density, as well as by scanner and other variables, as a measure of the variability, before and after the standardization. In addition, a linear mixed-effects model was used to assess the heterogeneity across scanners, and the 95% confidence interval of the mean CT number was evaluated before and after the standardization. RESULTS: We show that after applying the standardization procedures to the phantom data, the instrumental reproducibility of the CT density measurement of the reference foams improved by more than 65%, as measured by the standard deviation of the overall mean CT number. Using the lung foam that did not participate in the calibration as a test case, a mixed effects model analysis shows that the 95% confidence intervals are [-862.0 HU, -851.3 HU] before standardization, and [-859.0 HU, -853.7 HU] after standardization to 80 keV. This is in general agreement with the expected CT number value at 80 keV of -855.9 HU with 95% CI of [-857.4 HU, -854.5 HU] based on the calibration and the uncertainty in the SRM certified density. CONCLUSIONS: This study provides a quantitative assessment of the variations expected in CT lung density measures attributed to non-biological sources such as scanner calibration and scanner x-ray spectrum and filtration. By removing scanner-protocol dependence from the measured CT numbers, higher accuracy and reproducibility of quantitative CT measures were attainable. The standardization procedures developed in study may be explored for possible application in CT lung density clinical data.

How influential is the duration of contrast material bolus injection in perfusion CT? evaluation in a swine model.

PURPOSE: To analyze the effect of the duration of contrast material bolus injection on perfusion values in a swine model by using the maximum slope method. MATERIALS AND METHODS: This study was approved by the institutional animal care committee. Twenty pigs (weight range, 63-77 kg) underwent dynamic volume computed tomography (CT) of the kidneys during suspended respiration. Before the CT examination, a miniature cuff-shaped ultrasonographic flow probe encircling the right renal artery was surgically implanted in each pig to obtain true perfusion values. Two sequential perfusion CT series were performed in 30 seconds, each comprising 30 volumes with identical parameters (100 kV, 200 mAs, 0.5 sec rotation time). The duration of contrast material bolus (0.5 mL/kg of body weight) was 3.8 seconds in the first series (short bolus series) and 11.5 seconds in the second series (long bolus series), and the injection flow rate was adapted accordingly. In each pig, cortical kidney volume was determined by using the volume with the highest cortical enhancement. CT perfusion values were calculated for both series by using the maximum slope method and were statistically compared and correlated with the true perfusion values from the flow probe by using linear regression analysis. RESULTS: Mean true perfusion and CT perfusion values (in minutes(-1)) for the short bolus series were 1.95 and 2.03, respectively (P = .22), and for the long bolus series, they were 2.02 and 1.92, respectively (P = .12). CT perfusion showed very good correlation with true perfusion in both the short (slope, 1.01; 95% confidence interval: 0.91, 1.11) and long (slope, 0.92; 95% confidence interval: 0.78, 1.04) series. On the basis of the regression analysis, CT perfusion values in the short bolus series were overestimated by 1% and those in the long bolus series were underestimated by 8%. CONCLUSION: Duration of contrast material bolus injection does not influence CT perfusion values substantially. The longer, clinically preferred intravenous injection scheme is sufficiently accurate for CT perfusion.

CT angiography: current technology and clinical use.

Since 1958, catheter angiography has assumed the role of gold standard for vascular imaging, despite the invasive nature of the procedure. Less invasive techniques for vascular imaging, such as computed tomographic angiography (CTA), have been developed and have matured in conjunction with developments in catheter arteriography. In a few cases, such as imaging, the aorta and the pulmonary arteries, CTA has supplanted catheter angiography as the gold standard. The expanding role of CTA emphasizes the need for deep, broad-based understanding of physical principles. This review describes CT hardware and associated software for angiography. The fundamentals of CTA physics are complemented with several clinical examples.