Nondestructive and three-dimensional visualization by identifying elements using synchrotron radiation microscale X-ray CT reveals microbial and cavity distributions in anaerobic granular sludge.

We developed a nondestructive three-dimensional microbial visualization method utilizing synchrotron radiation X-ray microscale computed tomography to better understand the relationship between microorganisms and their surrounding habitats. The method was tested and optimized using a mixture of axenic Escherichia coli and Comamonas testosteroni. The osmium-thiocarbohydrazide-osmium method was used to stain all the microbial cells, and gold in situ hybridization was used to detect specific phylogenetic microbial groups. The stained samples were embedded in epoxy resin for microtomographic analysis. Differences in X-ray absorbances were calculated by subtracting the pre-L3-edge images from the post-L3-edge images to visualize the osmium and gold signals. Although we successfully detected cells stained with osmium, those labeled with gold were not detected, probably because of the insufficient density of gold atoms in the microbial cells. We then applied the developed technique to anaerobic granules and visualized the distribution of microbial cells and extracellular polymeric substances. Empty spaces were highlighted to determine the cavity distribution in granules. Numerous independent cavities of different sizes were identified in the granules. The developed method can be applied to various environmental samples for deeper insights into microbial life in their habitats. IMPORTANCE: Microorganisms inhabit diverse environments and often form biofilms. One factor that affects their community structure is the surrounding physical environment. The arrangement of residential space within the formed biofilm plays a crucial role in the supply and transportation of substances, as well as the discharge of metabolites. Conventional approaches, such as scanning electron microscopy and confocal laser scanning microscopy combined with fluorescence in situ hybridization, have limitations as they provide information primarily from the biofilm surface and cross-sections. In this study, we developed a method for detecting microorganisms in biofilms using synchrotron radiation X-ray microscale computer tomography. The developed method allows nondestructive three-dimensional observation of biofilms at a single-cell resolution (voxel size of approximately 200 nm), facilitating an understanding of the relationship between microorganisms and their physical habitats.

Correlation Between Contrast-Detail Analysis and Clinical Image Quality Assessment of Intrapulmonary Lesions in Dual-Energy Subtraction Chest Radiography Using the Two-Shot Method: A Phantom Study.

RATIONALE AND OBJECTIVES: Dual-energy subtraction (DES) imaging constitutes a technique that has demonstrated efficacy in enhancing the detectability of pulmonary nodules on chest radiographs. However, a simple and quantitative methodology for evaluating the clinical image quality of DES images is currently lacking. The objective of this study was to investigate the applicability of contrast-detail (C-D) phantom analysis to the visual clinical image quality evaluation of chest DES images. MATERIALS AND METHODS: We employed a custom-made phantom incorporating the C-D phantom and a multipurpose anthropomorphic adult chest phantom. Two phantom sizes were utilized to simulate standard- and large-bodied adult patients for each phantom. The custom-made phantom images were scored automatically using dedicated software, yielding an inverse image quality figure (IQFinv) value. The multipurpose anthropomorphic adult chest phantom was employed in a visual grading analysis (VGA) study that was conducted by two experienced radiologists and five radiological technologists. Each nodule placed in the chest phantom image was rated on a 4-point Likert scale. RESULTS: A statistically significant correlation was observed between the VGA scores of the seven observers and the obtained IQFinv values. CONCLUSION: The findings of this study suggest that DES image analysis of the C-D phantom possesses the potential to be utilized for the evaluation of clinical DES image quality based on chest lesion detectability.

Effect of high- and low-energy entrance surface dose allocation ratio for two-shot dual-energy subtraction imaging on low-contrast resolution.

INTRODUCTION: Dual-energy subtraction (DES) imaging can obtain chest radiographs with high contrast between nodules and healthy lung tissue, and evaluating of chest radiography and evaluating exposure conditions is crucial to obtain a high-quality diagnostic image. This study aimed to investigate the effect of the dose allocation ratio of entrance surface dose (ESD) between high- and low-energy projection in low-contrast resolution of soft-tissue images for two-shot DES imaging in digital radiography using a contrast-detail phantom (CD phantom). METHODS: A custom-made phantom mimicking a human chest that combined a CD phantom, polymethylmethacrylate square plate, and an aluminum plate (1-3 mm) was used. The tube voltage was 120 kVp (high-energy) and 60 kVp (low-energy). The ESD was changed from 0.1 to 0.5 mGy in 0.1 mGy increments. Dose allocation ratio of ESD between 120 kVp and 60 kVp projection was set at 1:1, 1:2, 1:3, and 2:1. Inverse image quality figure (IQFinv) was calculated from the custom-made phantom images. RESULTS: When the total ESD and aluminum thickness were constant, no significant difference in IQFinv was observed under most conditions of varied dose allocation ratio. Similarly, when the total ESD and the dose allocation ratio were constant, there was no significant difference in IQFinv based on the aluminum plate thickness. CONCLUSION: Using IQFinv to evaluate the quality of the two-shot DES image suggested that dose allocation ratio did not have a significant effect on low-contrast resolution of soft-tissue images. IMPLICATIONS FOR PRACTICE: The present results provide useful information for determining exposure conditions for two-shot DES imaging.

Towards subtraction angiography using a multi-layered X-ray detector.

The feasibility of single-exposure dual-energy imaging (DEI) was investigated in pursuit of motion-artifact-free subtraction angiography. To acquire low- and high-energy images simultaneously from a single X-ray exposure, a sandwich-like multilayered detector was fabricated by configuring two phosphor-coupled photodiode array layers in tandem. A simple analytic model describing the signal in DE-reconstructed images was derived. For the feasibility test, two plastic phantoms with linear arrays of cylindrical holes were prepared to contain iodinated water. One consisted of the same-diameter cylinders with different iodine concentrations, whereas the other had the different-diameter cylinders with the same iodine concentration. The concentration and size discrimination capabilities of single-exposure DEI were evaluated by investigating the phantom images. While the image noise relative to the signal was almost independent of the mass thickness of iodine, the iodine detectability improved with the mass thickness. The detectability performance at a lower tube voltage (e.g. 60 kV) outperformed those at higher voltages, as expected from the model. The results obtained in this study demonstrate the potential applicability of the single-exposure approach to motion-artifact-free subtraction angiography.

Improved detection of solitary pulmonary nodules on radiographs compared with deep bone suppression imaging.

BACKGROUND: The present study aimed to investigate whether deep bone suppression imaging (BSI) could increase the diagnostic performance for solitary pulmonary nodule detection compared with digital tomosynthesis (DTS), dual-energy subtraction (DES) radiography, and conventional chest radiography (CCR). METHODS: A total of 256 patients (123 with a solitary pulmonary nodule, 133 with normal findings) were included in the study. The confidence score of 6 observers determined the presence or absence of pulmonary nodules in each patient. These were first analyzed using a CCR image, then with CCR plus deep BSI, then with CCR plus DES radiography, and finally with DTS images. Receiver-operating characteristic curves were used to evaluate the performance of the 6 observers in the detection of pulmonary nodules. RESULTS: For the 6 observers, the average area under the curve improved significantly from 0.717 with CCR to 0.848 with CCR plus deep BSI (P<0.01), 0.834 with CCR plus DES radiography (P<0.01), and 0.939 with DTS (P<0.01). Comparisons between CCR and CCR plus deep BSI found that the sensitivities of the assessments by the 3 residents increased from 53.2% to 69.5% (P=0.014) for nodules located in the upper lung field, from 30.6% to 44.6% (P=0.015) for nodules that were partially/completely obscured by the bone, and from 33.2% to 45.8% (P=0.006) for nodules <10 mm. CONCLUSIONS: The deep BSI technique can significantly increase the sensitivity of radiology residents for solitary pulmonary nodules compared with CCR. Increased detection was seen mainly for smaller nodules, nodules with partial/complete obscuration, and nodules located in the upper lung field.

Lung cancer screening by single-shot dual-energy subtraction using flat-panel detector.

PURPOSE: The purpose of this study was to evaluate the usefulness of single-shot dual-energy subtraction (DES) method using a flat-panel detector for lung cancer screening MATERIALS AND METHODS: The subjects were 13,315 residents (5801 males and 7514 females) aged 50 years or older (50-97 years, with an intermediate value of 68 years) who underwent lung cancer screening for a period of 1 year and 6 months from January 2019 to June 2020. We investigated whether the number of lung cancers detected, the detection rate, and the rate of required scrutiny changed, when DES images were added to the judgment based on conventional chest radiography. RESULTS: When DES images were added, the number and percentage of cancer detection increased from 16 (0.12%) to 23 (0.17%) (P < 0.05). Five of the newly detected 7 lung cancers were in the early stages of resectable cancer. The rate of participants requiring scrutiny increased slightly from 1.1 to 1.3%. CONCLUSION: DES method improved the detection of lung cancer in screening. The increase in the percentage of participants requiring scrutiny was negligible.

Radiomic Analysis of Contrast-Enhanced Mammography With Different Image Types: Classification of Breast Lesions.

Objective: A limited number of studies have focused on the radiomic analysis of contrast-enhanced mammography (CEM). We aimed to construct several radiomics-based models of CEM for classifying benign and malignant breast lesions. Materials and Methods: The retrospective, double-center study included women who underwent CEM between November 2013 and February 2020. Radiomic analysis was performed using high-energy (HE), low-energy (LE), and dual-energy subtraction (DES) images from CEM. Datasets were randomly divided into the training and testing sets at a ratio of 7:3. The maximum relevance minimum redundancy (mRMR) method and least absolute shrinkage and selection operator (LASSO) logistic regression were used to select the radiomic features and construct the best classification models. The performances of the models were assessed by the area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI). Leave-group-out cross-validation (LGOCV) for 100 rounds was performed to obtain the mean AUCs, which were compared by the Wilcoxon rank-sum test and the Kruskal-Wallis rank-sum test. Results: A total of 192 women with 226 breast lesions (101 benign; 125 malignant) were enrolled. The median age was 48 years (range, 22-70 years). For the classification of breast lesions, the AUCs of the best models were 0.931 (95% CI: 0.873-0.989) for HE, 0.897 (95% CI: 0.807-0.981) for LE, 0.882 (95% CI: 0.825-0.987) for DES images and 0.960 (95% CI: 0.910-0.998) for all of the CEM images in the testing set. According to LGOCV, the models constructed with the HE images and all of the CEM images showed the highest mean AUCs for the training (0.931 and 0.938, respectively; P < 0.05 for both) and testing sets (0.892 and 0.889, respectively; P = 0.55 for both), which were significantly higher than those of the two models constructed with the LE and DES images in the training (0.912 and 0.899, respectively; all P < 0.05) and testing sets (0.866 and 0.862, respectively; all P < 0.05). Conclusions: Radiomic analysis of CEM images was valuable for classifying benign and malignant breast lesions. The use of HE images or all three types of CEM images can achieve the best performance.

Dual energy imaging in cardiothoracic pathologies: A primer for radiologists and clinicians.

Recent advances in dual-energy imaging techniques, dual-energy subtraction radiography (DESR) and dual-energy CT (DECT), offer new and useful additional information to conventional imaging, thus improving assessment of cardiothoracic abnormalities. DESR facilitates detection and characterization of pulmonary nodules. Other advantages of DESR include better depiction of pleural, lung parenchymal, airway and chest wall abnormalities, detection of foreign bodies and indwelling devices, improved visualization of cardiac and coronary artery calcifications helping in risk stratification of coronary artery disease, and diagnosing conditions like constrictive pericarditis and valvular stenosis. Commercially available DECT approaches are classified into emission based (dual rotation/spin, dual source, rapid kilovoltage switching and split beam) and detector-based (dual layer) systems. DECT provide several specialized image reconstructions. Virtual non-contrast images (VNC) allow for radiation dose reduction by obviating need for true non contrast images, low energy virtual mono-energetic images (VMI) boost contrast enhancement and help in salvaging otherwise non-diagnostic vascular studies, high energy VMI reduce beam hardening artifacts from metallic hardware or dense contrast material, and iodine density images allow quantitative and qualitative assessment of enhancement/iodine distribution. The large amount of data generated by DECT can affect interpreting physician efficiency but also limit clinical adoption of the technology. Optimization of the existing workflow and streamlining the integration between post-processing software and picture archiving and communication system (PACS) is therefore warranted.

Efficiency and reporting confidence analysis of sequential dual-energy subtraction for thoracic x-ray examinations.

Rationale and objectives: We aimed to report and compare accuracy, reproducibility, and reporting confidence between thoracic dual-energy subtraction (DES) and routine posterior-anterior chest radiography (PA-CR) techniques. Materials (patients) and methods: We obtained DES (D1-D4) images from 96 patients using DES and a high-resolution dynamic flat-panel detector in combination. We compared the DES images of these patients with their PA-CR images. The maximum time interval between performing DES and PA-CR was nine weeks. Two radiologists evaluated abnormal findings on DES and PA-CR images using a three-point scale, and reporting confidence was scored using a four-point scale. The intra- and interobserver agreement values of the scores were analyzed. Further, the radiation exposure doses during PA-CR and DES acquisitions were calculated. Results: The intra- and interobserver agreement values of PA-CR and DES images were good. The reporting confidence scores for DES were generally higher than those for PA-CR. Between bone-subtracted (D3) and soft-tissue-subtracted (D4) images, the former was more successful and useful in the evaluation of bone structures, whereas the latter was better in the evaluation of consolidation and/or solitary nodules. Conclusions: DES has the potential to improve the accuracy, reproducibility, and reporting confidence of thoracic radiography. It also has the potential to provide a better diagnosis of chest pathologies using relatively low dose radiation.

A real-time, single-exposure, dual-energy subtraction mask for markerless tumor tracking in radiotherapy: Proof of concept.

INTRODUCTION: Bone density can interfere with fluoroscopy-guided tumor tracking in radiotherapy. To improve markerless tumor tracking accuracy, we developed a dual energy subtraction (DES) mechanical image mask to use with a single x-ray exposure. METHODS: The DES mask consists of 2-mm-thick stainless-steel with 128 pairs of slits (0.388 mm width and openings), designed to match the dynamic flat panel detector (DFPD) pixel size. This was set on the front of the DFPD. This results in a DFPD image with one containing the exposed pixels and one containing the masked pixels. The masked pixel columns were interpolated from adjacent pixels and a subtraction image was generated from the interpolated images to make a bone suppression (BS) image. A chest phantom was set on the commercially available moving table (CIRS DYNAMIC PLATFORM 008PL) and DFPD images were acquired. A reference BS image was generated by double-exposure DES with and without a 2-mm-thick stainless-steel plate. Image quality and markerless tumor tracking accuracy were then evaluated. RESULTS: The DES mask decreased most of the visible bone densities from the chest phantom image acquired with a single exposure for a peak-signal-to-noise-ratio/structural similarity index measure (PSNR/SSIM) of 25.3 db/0.685). The tracking positional error, originally 12.6 mm, was improved to 0.2 mm. CONCLUSIONS: The DES mask can aid in BS image on fluoroscopic imaging and may be useful in markerless tumor tracking.

Phantom-based study exploring the effects of different scatter correction approaches on the reconstructed images generated by contrast-enhanced stationary digital breast tomosynthesis.

Stationary digital breast tomosynthesis (sDBT) is an emerging technology in which the single rotating x-ray tube is replaced by a fixed array of multiple carbon nanotube-enabled sources, providing a higher spatial and temporal resolution. As such, sDBT offers a promising platform for contrast-enhanced (CE) imaging. However, given the minimal enhancement above background with standard operational tube settings and iodine dosing, CE breast imaging requires additional acquisition steps to isolate the iodine signal, using either temporal or dual energy subtraction (TS or DES) protocols. Also, correcting for factors that limit contrast is critical, and scatter and noise pose unique challenges during tomosynthesis. This phantom-based study of CE sDBT compared different postacquisition scatter correction approaches on the quality of the reconstructed image slices. Beam-pass collimation was used to sample scatter indirectly, from which an interpolated scatter map was obtained for each projection image. Scatter-corrected projections provided the information for reconstruction. Comparison between the application of different scatter maps demonstrated the significant effect that processing has on the contrast-to-noise ratio and feature detectability ([Formula: see text]) in the final displayed images and emphasized the critical importance of scatter correction during DES.

Optimization of contrast-enhanced breast imaging: Analysis using a cascaded linear system model.

PURPOSE: Contrast-enhanced (CE) breast imaging involves the injection contrast agents (i.e., iodine) to increase conspicuity of malignant lesions. CE imaging may be used in conjunction with digital mammography (DM) or digital breast tomosynthesis (DBT) and has shown promise in improving diagnostic specificity. Both CE-DM and CE-DBT techniques require optimization as clinical diagnostic tools. Physical factors including x-ray spectra, subtraction technique, and the signal from iodine contrast, must be considered to provide the greatest object detectability and image quality. We developed a cascaded linear system model (CLSM) for the optimization of CE-DM and CE-DBT employing dual energy (DE) subtraction or temporal (TE) subtraction. METHODS: We have previously developed a CLSM for DBT implemented with an a-Se flat panel imager (FPI) and filtered backprojection (FBP) reconstruction algorithm. The model is used to track image quality metrics - modulation transfer function (MTF) and noise power spectrum (NPS) - at each stage of the imaging chain. In this study, the CLSM is extended for CE breast imaging. The effect of x-ray spectrum (varied by changing tube potential and the filter) and DE and TE subtraction techniques on breast structural noise was measured was studied and included as a deterministic source of noise in the CLSM. From the two-dimensional (2D) and three-dimensional (3D) MTF and NPS, the ideal observer signal-to-noise ratio (SNR), also known as the detectability index (d'), may be calculated. Using d' as a FOM, we discuss the optimization of CE imaging for the task of iodinated contrast object detection within structured backgrounds. RESULTS: Increasing x-ray energy was determined to decrease the magnitude of structural noise and not its correlation. By performing DE subtraction, the magnitude of the structural noise was further reduced at the expense of increased stochastic (quantum and electronic) noise. TE subtraction exhibited essentially no residual structural noise at the expense of increased quantum noise, even over that of the DE case. For DE subtraction, optimization of dose weighting to the HE view (fh ) results in the minimization of quantum noise. Both subtraction weighting factor (wSub ) and the iodine contrast signal were dependent on the LE and HE x-ray spectra. To best detect a 5 mm Gaussian lesion with 5 mg/ml of iodine within a 4 cm thick breast, it was found that the high energy (HE) view should be acquired with a tube potential of 47 kVp (W/Ti spectrum) and the low energy (LE) view with a potential of 23 kVp (W/Rh spectrum). Due to the complete removal of structural noise, TE subtraction produced much higher d' than DE subtraction both as a function of mean glandular dose and iodine concentration. CONCLUSIONS: We have shown the effect of increasing x-ray energy as well as projection domain subtraction on breast structural noise. Further, we have exhibited the utility of the CLSM for DE and TE subtraction CE imaging in the optimization of imaging parameters such as x-ray energy, fh , and wSub as well as guiding the understanding of their effects on image contrast and noise.

Cascade of multi-scale convolutional neural networks for bone suppression of chest radiographs in gradient domain.

Suppression of bony structures in chest radiographs (CXRs) is potentially useful for radiologists and computer-aided diagnostic schemes. In this paper, we present an effective deep learning method for bone suppression in single conventional CXR using deep convolutional neural networks (ConvNets) as basic prediction units. The deep ConvNets were adapted to learn the mapping between the gradients of the CXRs and the corresponding bone images. We propose a cascade architecture of ConvNets (called CamsNet) to refine progressively the predicted bone gradients in which the ConvNets work at successively increased resolutions. The predicted bone gradients at different scales from the CamsNet are fused in a maximum-a-posteriori framework to produce the final estimation of a bone image. This estimation of a bone image is subtracted from the original CXR to produce a soft-tissue image in which the bone components are eliminated. Our method was evaluated on a dataset that consisted of 504 cases of real two-exposure dual-energy subtraction chest radiographs (404 cases for training and 100 cases for test). The results demonstrate that our method can produce high-quality and high-resolution bone and soft-tissue images. The average relative mean absolute error of the produced bone images and peak signal-to-noise ratio of the produced soft-tissue images were 3.83% and 38.7dB, respectively. The average bone suppression ratio of our method was 83.8% for the CXRs with pixel sizes of nearly 0.194mm. Furthermore, we apply the trained CamsNet model on the CXRs acquired by various types of X-ray machines, including scanned films, and our method can also produce visually appealing bone and soft-tissue images.

Color radiography in lung nodule detection and characterization: comparison with conventional gray scale radiography.

BACKGROUND: To compare the capability of lung nodule detection and characterization between dual-energy radiography with color-representation (DCR) and conventional gray scale chest radiography (GSR). METHODS: A total of 130 paired chest radiographs (DCR and GSR) obtained from 65 patients (14 with normal scans and 51 with pulmonary nodules) were evaluated. After analysis, 45 non-calcified and 21 calcified nodules were identified. DCR was obtained by adding color space within material-decomposed data (blue for high attenuation and red for low attenuation) and by compounding the manipulated data to one color image. Three radiologists marked suggested nodules on radiographic images and assessed the level of confidence of lesion presence and probability of nodule calcification by using a nine-point rating scale. The jackknife active free-response receiver operating characteristics (JAFROC) analysis was used to evaluate lesion detectability, and multi-reader multi-case receiver operating characteristics (MRMC ROC) analysis was used for the evaluation of the accuracy of nodule calcification prediction. RESULTS: Figures of merit (FOM) from JAFROC was 0.807 for DCR and 0.811 for GSR, respectively; nodule detectability was not significantly different between DCR and GSR (p = 0.93). Areas under curve (AUC) from MRMC ROC were 0.944 for DCR and 0.828 for GSR, respectively; performance of DCR in predicting lung nodule calcification was significantly higher than that of GSR (p = 0.04). CONCLUSIONS: DCR showed similar performance in terms of lung nodule detection compared with GSR. However, DCR does provide a significant benefit in predicting the presence of nodule calcification.

Comparison of dual energy subtraction chest radiography and traditional chest X-rays in the detection of pulmonary nodules.

BACKGROUND: Dual energy subtraction (DES) radiography is a powerful but underutilized technique which aims to improve the diagnostic value of an X-ray by separating soft tissue from bones, producing two different images. Compared to traditional chest X-rays, DES requires exposure to higher doses of radiation but may achieve higher accuracy. The objective of this study was to assess the clinical benefits of DES radiography by comparing the speed and accuracy of diagnosis of pulmonary nodules with DES versus traditional chest X-rays. METHODS: Five radiologists and five radiology residents read the DES and traditional chest X-rays of 51 patients, 34 with pulmonary nodules and 17 without. Their accuracy and speed in the detection of nodules were measured using specialized image display software. RESULTS: DES radiography reduced reading time from 13 to 10 sec (P<0.0001) in staff and from 21 to 15 sec in residents (P<0.0001). There was also a small increase in sensitivity 0.58 to 0.67 overall (P<0.10) with no change in specificity (0.85 overall). CONCLUSIONS: By eliminating rib shadows in soft tissue images, DES improved the speed and accuracy of radiologists in the diagnosis of pulmonary nodules.

Role of digital tomosynthesis and dual energy subtraction digital radiography in detection of parenchymal lesions in active pulmonary tuberculosis.

OBJECTIVE: To assess the role of digital tomosynthesis (DTS) and dual energy subtraction digital radiography (DES-DR) in detection of parenchymal lesions in active pulmonary tuberculosis (TB) and to compare them with digital radiography (DR). MATERIALS AND METHODS: This prospective study was approved by our institutional review committee. DTS and DES-DR were performed in 62 patients with active pulmonary TB within one week of multidetector computed tomography (MDCT) study. Findings of active pulmonary TB, that is consolidation, cavitation and nodules were noted on digital radiography (DR), DTS and DES-DR in all patients. Sensitivity, specificity, positive and negative predictive values of all 3 modalities was calculated with MDCT as reference standard. In addition presence of centrilobular nodules was also noted on DTS. RESULTS: Our study comprised of 62 patients (33 males, 29 females with age range 18-82 years). Sensitivity and specificity of DTS for detection of nodules and cavitation was better than DR and DES-DR. Sensitivity and specificity of DTS for detection of consolidation was comparable to DR and DES-DR. DES-DR performed better than DR in detection of nodules and cavitation. DTS was also able to detect centrilobular nodules with sensitivity and specificity of 57.4% and 86.5% respectively. CONCLUSION: DTS and DES-DR perform better than DR in detection of nodules, consolidation and cavitation in pulmonary TB. DTS gives better results than DES-DR, particularly in detection of cavitation and has moderate sensitivity for detection of centrilobular nodules. Thus DTS can be used for evaluation of patients of suspected pulmonary TB, thereby giving a more confident diagnosis of active disease and also in follow up.

Role of digital tomosynthesis and dual energy subtraction digital radiography in detecting pulmonary nodules.

OBJECTIVE: Digital tomosynthesis (DT) and dual-energy subtraction digital radiography (DES-DR) are known to perform better than conventional radiography in the detection of pulmonary nodules. Yet the comparative diagnostic performances of DT, DES-DR and digital radiography (DR) is not known. The present study compares the diagnostic performances of DT, DES-DR and DR in detecting pulmonary nodules. SUBJECTS AND METHODS: The institutional Review Board approved the study and informed written consent was obtained. Fifty-five patients (30 with pulmonary nodules, 25 with non-nodular focal chest pathology) were included in the study. DT and DES-DR were performed within 14 days of MDCT. Composite images acquired at high kVp as part of DES-DR were used as DR images. Images were analyzed for presence of nodules and calcification in nodules. Interpretations were assigned confidence levels from 1 to 5 according to Five-Point rating scale. Areas under the receiver operating characteristic curves were compared using Z test. RESULTS: A total of 110 (88 non-calcified, 22 calcified) nodules were identified on MDCT. For detection of nodules, DR showed cumulative sensitivity and specificity of 25.45% and 67.97%, respectively. DT showed a cumulative sensitivity and specificity of 60.9% and 85.07%, respectively. The performance was significantly better than DR (p<0.003). DES-DR showed sensitivity and specificity of 27.75% and 82.64%, not statistically different from those of DR (p-0.92). In detection of calcification, there was no statistically significant difference between DT, DES-DR and DR. CONCLUSIONS: DT performs significantly better than DES-DR and DR at the cost of moderate increase in radiation dose.

The technology feasibility studies and image quality evaluation of computed tomographic pulmonary angiography using dual-energy subtraction / 实用放射学杂志

Objective To assess quantitative and subjective image quality in computed tomography pulmonary angiography (CT-PA)with dual-energy subtraction methods,and to select the best dual-energy subtraction method.Methods 30 consecutive patients underwent CTPA using a single tube,fast voltage switching technique.One set of routine poly-chromatic images (RPI),two sets of monochromatic images with different optimal contrast-to-noise ratios (OCNR)and three sets of dual-energy subtraction images (DE-SI)were obtained by a dedicated workstation with dual-energy software (AW4.5 Advantage WS;GE Healthcare).For all the six sets of images,CNR and the score of global subjective image quality were calculated.Results DESI 3 got the highest CNR,and DESI 1 got the next high CNR.In global subjective image quality,DESI 1 got the highest score.However,when compared with DESI 2,no significant difference was found.Conclusion CTPA with dual-energy subtraction technique is feasible.DESI 1 affords the best bal-ance between quantitative analysis and subjective evaluation compared with other sets of images.

Comparison of chest dual-energy subtraction digital tomosynthesis and dual-energy subtraction radiography for detection of pulmonary nodules: initial evaluations in human clinical cases.

RATIONALE AND OBJECTIVES: To compare initial evaluations of chest dual-energy subtraction digital tomosynthesis (DES-DT) and dual-energy subtraction radiography (DES-R) for detection of pulmonary nodules. MATERIALS AND METHODS: DES-DT and DES-R systems with pulsed x-rays and rapid kV switching were used to evaluate pulmonary nodules (>4-6 mm, 2 nodules; >6-8 mm, 2 nodules; >8 mm, 32 nodules). Multidetector computed tomography was used as a reference. A filtered back-projection algorithm was used to reconstruct low-voltage (60 kVp), high-voltage (120 kVp), and soft-tissue or bone-subtracted tomograms of the desired layer thicknesses from the image data acquired during a single tomographic scan. DES-R images were processed from the low- and high-voltage images. To detect the pulmonary nodules, we used both systems to examine 36 patients with and 36 patients without pulmonary nodules. Two radiologists and three doctors of pulmonary medicine (average experience, 18 years) performed receiver operating characteristic (ROC) curve analysis to evaluate the results. RESULTS: The ROC analysis results suggested that the detection ability was significantly better for DES-DT than for DES-R (P < .0001; 95% confidence interval: DES-DT, 0.94 [0.83-0.99]; DES-R, 0.76 [0.68-0.85]; sensitivity: DES-DT, 87.7 ± 2.9%; DES-R, 53.8 ± 3.5%; specificity: DES-DT, 78.3 ± 5.6%; DES-R, 78.4 ± 3.4%; accuracy: DES-DT, 83.1 ± 3.8%, DES-R, 66.1 ± 2.0%). When the nodules were no longer superimposed over the normal structures, their characteristics and distribution could be observed much more clearly. CONCLUSION: Compared with DES-R, DES-DT provided greater sensitivity for detection of pulmonary nodules, particularly for the larger ones.

X-ray Digital Linear Tomosynthesis Imaging for Artificial Pulmonary Nodule Detection.

The purpose of this paper is to identify indications for volumetric X-ray digital linear tomosynthesis (DLT) with single- and dual-energy subtraction techniques for artificial pulmonary nodule detection and compare X-ray DLT, X-ray digital radiography, and computed tomography.