Dual-energy Subtraction Research Articles

Soft Tissue/Bone Decomposition of Conventional Chest Radiographs Using Nonparametric Image Priors

Background and Objective When radiologists diagnose lung diseases in chest radiography, they can miss some lung nodules overlapped with ribs or clavicles. Dual-energy subtraction (DES) imaging performs well because it can produce soft tissue images, in which the bone components in chest radiography were almost suppressed but the visibility of nodules and lung vessels was still maintained. However, most routinely available X-ray machines do not possess the DES function. Thus, we presented a data-driven decomposition model to perform virtual DES function for decomposing a single conventional chest radiograph into soft tissue and bone images. Methods For a given chest radiograph, similar chest radiographs with corresponding DES soft tissue and bone images are selected from the training database as exemplars for decomposition. The corresponding fields between the observed chest radiograph and the exemplars are solved by a hierarchically dense matching algorithm. Then, nonparametric priors of soft tissue and bone components are constructed by sampling image patches from the selected soft tissue and bone images according to the corresponding fields. Finally, these nonparametric priors are integrated into our decomposition model, the energy function of which is efficiently optimized by an iteratively reweighted least-squares scheme (IRLS). Results The decomposition method is evaluated on a data set of posterior-anterior DES radiography (503 cases), as well as on the JSRT data set. The proposed method can produce soft tissue and bone images similar to those produced by the actual DES system. Conclusions The proposed method can markedly reduce the visibility of bony structures in chest radiographs and shows potential to enhance diagnosis.

Assessment of radiation effective dose from lung cancer screening pilot project in Institut Kanser Negara: A preliminary finding

The aim of this study is to evaluate effective dose received by participants from Lung Cancer Screening program in Institut Kanser Negara (IKN), Putrajaya. This retrospective study was performed between April 2016 - December 2016 where all scanning acquisition protocols and dose information from forty (40) participants were recorded and investigated. The screening process involves two types of imaging technique, the Dual Energy Subtraction (DES) Chest Xray and Low-Dose Computed Tomography (LDCT) imaging technique. Participant’s effective dose (ED) from DES and MSCT were analysed by using PCXMC (Version 2.0, Finland) and CT-EXPO (Version 2.3, Germany) software, respectively. It was observed that the mean ( ± SD) value for DES (at 60 kV), DES (at 120 kV) and MSCT examinations were 0.006 ± 0.005 mSv, 0.018 ± 0.005 mSv and 1.558 ± 0.129 mSv, respectively. In a whole, the total cumulative ED values for participants were ranged from 1.376 mSv to 1.986 mSv. It was summarized that both optimized techniques were useful for screening needs and the ED value from this study were lower when compared to other established reference.

Markerless tumor tracking using fast-kV switching dual-energy fluoroscopy on a benchtop system.

To evaluate markerless tumor tracking (MTT) using fast-kV switching dual-energy (DE) fluoroscopy on a bench top system. Fast-kV switching DE fluoroscopy was implemented on a bench top which includes a turntable stand, flat panel detector, and x-ray tube. The customized generator firmware enables consecutive x-ray pulses that alternate between programmed high and low energies (e.g., 60 and 120kVp) with a maximum frame rate of 15Hz. In-house software was implemented to perform weighted DE subtraction of consecutive images to create an image sequence that removes bone and enhances soft tissues. The weighting factor was optimized based on gantry angle. To characterize this system, a phantom was used that simulates the chest anatomy and tumor motion in the lung. Five clinically relevant tumor sizes (5-25mm diameter) were considered. The targets were programmed to move in the inferior-superior direction of the phantom, perpendicular to the x-ray beam, using a cos4 waveform to mimic respiratory motion. Target inserts were then tracked with MTT software using a template matching method. The optimal computed tomography (CT) slice thickness for template generation was also evaluated. Tracking success rate and accuracy were calculated in regions of the phantom where the target overlapped ribs vs spine, to compare the performance of single energy (SE) and DE imaging methods. For the 5mm target, a CT slice thickness of 0.75mm resulted in the lowest tracking error. For the larger targets (≥10mm) a CT slice thickness ≤2mm resulted in comparable tracking errors for SE and DE images. Overall DE imaging improved MTT accuracy, relative to SE imaging, for all tumor targets in a rotational acquisition. Compared to SE, DE imaging increased tracking success rate of small target inserts (5 and 10mm). For fast motion tracking, success rates improved from 23% to 64% and 74% to 90% for 5 and 10mm targets inserts overlapping ribs, respectively. For slow moving targets success rates improved from 19% to 59% and 59% to 91% in 5 and 10mm targets overlapping the ribs, respectively. Similar results were observed when the targets overlapped the spine. For larger targets (≥15mm) tracking success rates were comparable using SE and DE imaging. This work presents the first results of MTT using fast-kV switching DE fluoroscopy. Using DE imaging has improved the tracking accuracy of MTT, especially for small targets. The results of this study will guide the future implementation of fast-kV switching DE imaging using the on-board imager of a linear accelerator.

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

IntroductionBone 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. MethodsThe 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. ResultsThe 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. ConclusionsThe DES mask can aid in BS image on fluoroscopic imaging and may be useful in markerless tumor tracking.

Diagnostic performance of dual-energy CT and subtraction CT for renal lesion detection and characterization.

To compare the effect of dual-energy CT (DECT) material density datasets on diagnostic performance, readers' confidence, and interpretation time for renal lesion detection and characterization in comparison to subtraction CT (SCT). One hundred fourteen patients (69/45 = M/F, mean age=67years) who underwent contrast-enhanced DECT between January 2015 and February 2018 for suspected renal mass were included retrospectively. For each patient, three radiologists assessed three image datasets: group A, material density iodine (MDI) + material density water (MDW); group B, SCT only; and group C, SCT + true unenhanced phase + virtual monochromatic images at 65keV. Readers evaluated image quality (4-point scale), the number of lesions, and likely diagnosis. Reading times were recorded. Quantitatively, iodine concentration (IC from MDI) and delta Hounsfield units (ΔHU) for all lesions were measured. Diagnostic accuracy was compared using the area under the receiver operating characteristic curve (AUC). Image quality and interpretation time were compared with Kruskal-Wallis and t tests. Study cohort (230 lesions; mean size=23.63mm (5-116mm)) consisted of 60 enhancing, 158 non-enhancing, and 12 lipid-dominant angiomyolipoma lesions. Significantly higher image quality was demonstrated for MDI compared to SCT (mean score=3.82 vs. 3; p< 0.05). Comparable diagnostic accuracy was observed for group A (AUC=0.88) and group C (AUC=0.87) and was higher compared to that for group B (AUC=0.75). Group A was read faster than group C (41.49s vs. 71.45s per exam; p< 0.05). Both IC and ΔHU values had high accuracy (AUC=0.97) for differentiating enhancing vs. non-enhancing lesions; however, IC enabled differentiation of clear cell renal cell carcinoma from other enhancing lesions with moderate accuracy (AUC=0.73). MDI images increase readers' confidence for renal lesion detection and characterization while providing a more efficient radiologist workflow, irrespective of readers' experience. • Material density iodine (MDI) images enable faster interpretation due to high image quality and potentially reduced need for quantitation. • MDI images increase diagnostic confidence of readers, irrespective of radiologists' experience. • High accuracy with dual-energy CT (DECT) can potentially reduce healthcare costs by eliminating the need for additional investigations.

Iodine Maps from Subtraction CT or Dual-Energy CT to Detect Pulmonary Emboli with CT Angiography: A Multiple-Observer Study.

Background Dual-energy CT iodine maps are used to detect pulmonary embolism (PE) with CT angiography but require dedicated hardware. Subtraction CT, a software-only solution, results in iodine maps with high contrast-to-noise ratios. Purpose To compare the use of subtraction CT versus dual-energy CT iodine maps to CT angiography for PE detection. Materials and Methods In this prospective study ( https://clinicaltrials.gov , NCT02890706), 274 participants suspected of having PE underwent precontrast CT followed by contrast material-enhanced dual-energy CT angiography between July 2016 and April 2017. Iodine maps from dual-energy CT were derived. Subtraction maps (contrast-enhanced CT minus precontrast CT) were calculated after motion correction. Truth was established by expert consensus. A total of 75 randomly selected participants with and without PE (1:1 ratio) were evaluated by three radiologists and six radiology residents (blinded to final diagnosis) for the presence of PE using three types of CT: CT angiography alone, dual-energy CT, and subtraction CT. The partial area under the receiver operating characteristic curve (AUC) for the clinically relevant specificity region (maximum partial AUC, 0.11) was compared by using multireader multicase variance. A P value less than or equal to .025 was considered indicative of a significant difference due to multiple comparisons. Results There were 35 men and 40 women in the reader study (mean age, 63 years ± 12 [standard deviation]). The pooled sensitivities were not different (P ≥ .31 among techniques) (95% confidence intervals [CIs]: 67%, 89% for CT angiography; 72%, 91% for dual-energy CT; 70%, 91% for subtraction CT). However, pooled specificity was higher for subtraction CT (95% CI: 100%, 100%) than for CT angiography (95% CI: 89%, 97%) or dual-energy CT (95% CI: 89%, 98%) (P < .001). Partial AUCs for the average observer improved equally when adding iodine maps (subtraction CT [0.093] vs CT angiography [0.088], P = .03; dual-energy CT [0.094] vs CT angiography, P = .01; dual-energy CT vs subtraction CT, P = .68). Average reading times were equivalent (range, 97-101 seconds; P ≥ .41) among techniques. Conclusion Subtraction CT iodine maps had greater specificity than CT angiography alone in pulmonary embolism detection. Subtraction CT had comparable diagnostic performance to that of dual-energy CT, without the need for dedicated hardware. © RSNA, 2019 Online supplemental material is available for this article.

Prototype system for interventional dual-energy subtraction angiography.

Dual-energy subtraction angiography (DESA) using fast kV switching has received attention for its potential to reduce misregistration artifacts in thoracic and abdominal imaging where patient motion is difficult to control; however, commercial interventional solutions are not currently available. The purpose of this work was to adapt an x-ray angiography system for 2D and 3D DESA. The platform for the dual-energy prototype was a commercially available x-ray angiography system with a flat panel detector and an 80 kW x-ray tube. Fast kV switching was implemented using custom x-ray tube control software that follows a user-defined switching program during a rotational acquisition. Measurements made with a high temporal resolution kV meter were used to calibrate the relationship between the requested and achieved kV and pulse width. To enable practical 2D and 3D imaging experiments, an automatic exposure control algorithm was developed to estimate patient thickness and select a dual-energy switching technique (kV and ms switching) that delivers a user-specified task CNR at the minimum air kerma to the interventional reference point. An XCAT-based simulation study conducted to evaluate low and high energy image registration for the scenario of 30-60 frame/s pulmonary angiography with respiratory motion found normalized RMSE values ranging from 0.16% to 1.06% in tissue-subtracted DESA images, depending on respiratory phase and frame rate. Initial imaging in a porcine model with a 60 kV, 10 ms, 325 mA / 120 kV, 3.2 ms, 325 mA switching technique demonstrated an ability to form tissue-subtracted images from a single contrast-enhanced acquisition.

Micro-CT myelography using contrast-enhanced digital subtraction: feasibility and initial results in healthy rats.

The spinal subarachnoid space (SSAS) is vital for neural performance. Although models of spinal diseases and trauma are used frequently, no methods exist to obtain high-resolution myelograms in rodents. Thereby, our aim was to explore the feasibility of obtaining high-resolution micro-CT myelograms of rats by contrast-enhanced dual-energy (DE) and single-energy (SE) digital subtraction. Micro-CT contrast-enhanced DE and SE imaging protocols were implemented with live adult rats (total of 18 animals). For each protocol, contrast agents based on iodine (Iomeron® 400 and Fenestra® VC) and gold nanoparticles (AuroVist™ 15nm) were tested. For DE, images at low- and high-energy settings were acquired after contrast injection; for SE, one image was acquired before and the other after contrast injection. Post-processing consisted of region of interest selection, image registration, weighted subtraction, and longitudinal alignment. High-resolution myelograms were obtained with contrast-enhanced digital subtraction protocols. After qualitative and quantitative (contrast-to-noise ratio) analyses, we found that the SE acquisition protocol with Iomeron® 400 provides the best images. 3D contour renderings allowed visualization of SSAS and identification of some anatomical structures within it. This in vivo study shows the potential of SE contrast-enhanced myelography for imaging SSAS in rat. This approach yields high-resolution 3D images without interference from adjacent anatomical structures, providing an innovative tool for further assessment of studies involving rat SSAS.

Bone Suppression of Chest Radiographs With Cascaded Convolutional Networks in Wavelet Domain

Bone suppression of chest radiographs (CXRs) is potentially useful for diagnosing lung diseases for radiologists and computer–aided diagnosis. This paper presents a cascaded convolutional network model in wavelet domain (Wavelet-CCN) for bone suppression in single conventional CXR. Wavelet coefficients are sparse and suitable as the output of convolutional network. The convolutional networks are trained to predict the wavelet coefficients of bone images from the wavelet coefficients of CXRs, using real two-exposure dual energy subtraction (DES) CXRs as training data. By combining the multi-level wavelet decomposition and a cascaded refinement framework, the Wavelet-CCN model can work automatically with a multi-scale approach and progressively refine the prediction in terms of accuracy and spatial resolution. Compared with previous work of CamsNet model which preforms bone prediction in gradient domain, the Wavelet-CCN model predicts the wavelet coefficients to reconstruct bone images and can avoid the inconsistent background intensity caused by 2D integration of gradients. The predicted bone image is subtracted from the original CXR to produce a soft-tissue image. The Wavelet-CCN model and its variants with different wavelet basis are evaluated on a dataset that consists of 504 cases of real two-exposure DES CXRs (404 cases for training and 100 cases for test). Experimental results show that among all the variants and different wavelet bases, the Wavelet-CCN model with Haar wavelet performs best. The average peak signal-to-noise ratio and structural similarity index of the soft-tissue images produced by the proposed Wavelet-CCN model are both higher than those of the previous CamsNet model in gradient domain, reaching values of 39.4 (±0.94) dB and 0.977 (±0.004), respectively. The results also demonstrate that the Wavelet-CCN model can process the CXRs acquired by four types of X-ray machines.

P053] Contrast-enhanced digital mammography on commercial systems: an optimization study

Purpose We introduce a novel algorithm for dual energy (DE) subtraction proposed in [1] , [2] , based on an iterative procedure for taking into account the intrinsic polychromaticity of conventional X-ray tubes. The result is an improvement of background cancellation with respect to the currently available DE systems. The algorithm was applied to a set of DE radiographs of a dedicated anthropomorphic phantom embedding small agglomerates of contrast medium (iodine), acquired with a commercial mammography system. Methods The employed anthropomorphic phantom, specifically designed for DE applications, is a polymethyl methacrylate (PMMA) box of parallelepipedal shape. It contains a large number of PMMA spheres of different diameters, embedded in paraffin wax. Moreover, it embeds a system of cavities that can be filled with iodine solutions of various concentrations. The phantom was imaged with X-ray beams of low energy (29 ± 2 kV) and high energy (47 ± 2 kV), generated by a commercial mammography unit with a tungsten anode and additional filtrations of rhodium (low energy) and copper (high energy). Results We achieved an almost complete cancellation of the background texture, resulting in an enhanced visibility of the iodine details. Such result was achieved with lower exposures than the values typical of diagnostic practice. We noticed no significant dependence of the image quality on the particular choice of beam energies. Conclusions The implementation of the novel subtraction algorithm on a commercial unit allowed an effective background cancellation with a reduced amount of delivered dose. Such result was largely independent of the imaging parameters, which is an indication of robustness of the algorithm. In conclusion, the proposed algorithm paves the way to an improvement of the diagnostic effectiveness of DE imaging.

Large-scale MV CT for cargo imaging: A feasibility study

Computed tomography (CT) has a major advantage over radiography in that it provides 3D imaging and resolves the structural overlap problem inherent to radiography. Since the early 1970s, CT evolved in parallel with radiography in many areas. As megavoltage (MV) cargo radiography is now in use, it is of interest to evaluate the feasibility of corresponding MV cargo CT. A feasibility study of MV cargo CT has been performed in this work. The MV cargo CT system has an imaging field of view of 3.25 m in diameter. The system design includes a compact X-ray source and detectors that are already used in existing MV cargo radiography systems. Although compact X-ray sources provide limited X-ray output, it is shown that this output is sufficient to perform CT imaging of large cluttered cargo contents for which MV radiography may be inconclusive. The scan time is 60 s at the X-ray dose levels lower than the permitted limit of 5 mGy. A steel tank phantom with 2 m diameter including different materials was used. The MV CT images were generated at 3.5 MV, 6 MV, and 9 MV beam energies. The materials were separated based on their CT numbers as well as using dual energy subtraction method. The materials with close densities and X-ray attenuations such as W and U were reliably separated and quantified based on their measured CT numbers. The boundary conditions for the system design were determined, including scan time, radiation dose, maximum object thicknesses, and spatial resolution. Based on the findings of this feasibility study, it is concluded that the MV cargo CT system with large field of view can be developed based on existing technology already used in MV cargo radiography. Such a CT system can be extremely useful when used adjunct to existing MV radiography on resolving the special cases that cannot be resolved conclusively with radiography alone.

Comparing dual energy CT and subtraction CT on a phantom: which one provides the best contrast in iodine maps for sub-centimetre details?

ObjectivesTo compare contrast-to-noise ratios (CNRs) and iodine discrimination thresholds on iodine maps derived from dual energy CT (DECT) and subtraction CT (SCT).MethodsA contrast-detail phantom experiment was performed with 2 to 15 mm diameter tubes containing water or iodinated contrast concentrations ranging from 0.5 mg/mL to 20 mg/mL. DECT scans were acquired at 100 kVp and at 140 kVp+Sn filtration. SCT scans were acquired at 100 kVp. Iodine maps were created by material decomposition (DECT) or by subtraction of water scans from iodine scans (SCT). Matched exposure levels varied from 8 to 15 mGy. Iodine discrimination thresholds (Cr) and response times were determined by eight observers.ResultsThe adjusted mean CNR was 1.9 times higher for SCT than for DECT. Exposure level had no effect on CNR. All observers discriminated all details ≥10 mm at 12 and 15 mGy. For sub-centimetre details, the lowest calculated Cr was ≤ 0.50 mg/mL for SCT and 0.64 mg/mL for DECT. The smallest detail was discriminated at ≥4.4 mg/mL with SCT and at ≥7.4 mg/mL with DECT. Response times were lower for SCT than DECT.ConclusionsSCT results in higher CNR and reduced iodine discrimination thresholds compared to DECT for sub-centimetre details.Key Points• Subtraction CT iodine maps exhibit higher CNR than dual-energy iodine maps• Lower iodine concentrations can be discriminated for sub-cm details with SCT• Response times are lower using SCT compared to dual-energy CT

Classification of Breast Masses Using a Computer-Aided Diagnosis Scheme of Contrast Enhanced Digital Mammograms.

Contrast-enhanced digital mammography (CEDM) is a promising imaging modality in breast cancer diagnosis. This study aims to investigate how to optimally develop a computer-aided diagnosis (CAD) scheme of CEDM images to classify breast masses. A CEDM dataset of 111 patients was assembled, which includes 33 benign and 78 malignant cases. Each CEDM includes two types of images namely, low energy (LE) and dual-energy subtracted (DES) images. A CAD scheme was applied to segment mass regions depicting on LE and DES images separately. Optimal segmentation results generated from DES images were also mapped to LE images or vice versa. After computing image features, multilayer perceptron based machine learning classifiers that integrate with a correlation-based feature subset evaluator and leave-one-case-out cross-validation method were built to classify mass regions. When applying CAD to DES and LE images with original segmentation, areas under ROC curves (AUC) were 0.759 ± 0.053 and 0.753 ± 0.047, respectively. After mapping the mass regions optimally segmented on DES images to LE images, AUC significantly increased to 0.848 ± 0.038 (p < 0.01). Study demonstrated that DES images eliminated overlapping effect of dense breast tissue, which helps improve mass segmentation accuracy. The study demonstrated that applying a novel approach to optimally map mass region segmented from DES images to LE images enabled CAD to yield significantly improved performance.

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.

Dual Energy Fluoroscopy Improves the Accuracy of Template-Based Tracking in Lung Cancer Patients Receiving Stereotactic Body Radiation Therapy

Template-based matching algorithms are currently being considered for markerless motion tracking (MMT) of lung tumors using fluoroscopy. The accuracy of this match is quantified through a metric known as peak-to-side lobe ratio (PSR). A previous study has shown that template matches with PSR≥3 are significantly more accurate than those with PSR<3. The goal of this study is to evaluate the fraction of single energy (SE) fluoroscopic images, obtained in SBRT lung cancer patients, that have PSR≥3, and if the addition of dual energy (DE) subtraction fluoroscopy can increase the PSR value. Moreover, radiomic parameters from CT images are evaluated to determine if any are predictive of PSR. In this prospective study, a total of 2,448 fluoroscopy frames were acquired, at multiple imaging angles, from 8 SBRT patients with Stage IA - IIA lung cancer. Sequential 60 kVp and 120 kVp fluoroscopic sequences were acquired and aligned based on respiratory signal. DE fluoroscopic sequences were created using a frame-by-frame weighted logarithmic subtraction. Separately, a template was derived from the contoured gross tumor volume (GTV) on the CT simulation scan. A template-based matching algorithm was used to track tumor motion throughout the DE and SE (120 kVp) fluoroscopy sequences. This algorithm shifts the template across the image and calculates the normalized cross correlation (NCC) between the template and image, resulting in a match score surface. The offset at which the NCC has the maximum value (i.e., the position of the peak of the surface) represents the potential target position. The strength of this peak relative to NCC values away from the peak, called side lobe values, is quantified by the PSR. Radiomic parameters using the GTV from the planning CT scans were examined to determine correlation with the PSR values. Approximately 68% of the SE fluoroscopic images had PSR ≥3. Of the SE images with PSR <3, 79.5% were obtained at an oblique imaging angle, while the remaining were obtained at an anterior imaging angle. By adding DE fluoroscopy, over 86% of the images obtained PSR ≥3 (P < 0.001). Of the 23 unique imaging sessions, SE imaging alone allowed for tracking in over 80% of the images in 12/23 (52%) sessions vs. 18/23 (78%) when combined with DE fluoroscopy (P = 0.12). In those cases where DE imaging increased the PSR to ≥3, the change in template positioning was 1.14 +/- 0.61 mm. Of the 200 unique radiomic parameters analyzed, “energy” was predictive of PSR value, having a Pearson’s correlation coefficient = 0.846 and 0.841 for SE and DE, respectively. The PSR value provides an independent metric for assessing the accuracy of a template match when used in conjunction with MMT. The addition of DE imaging to SE fluoroscopy increases the fraction of images with PSR >3, thus improving the overall accuracy of template matching.

Dual-energy wave subtraction imaging for evaluation of barely visible impact damage with an ultrasonic propagation imaging system

Barely visible impact damage from low-velocity impacts have been studied as critical design factors of composite structures. In this article, a dual-energy wave subtraction algorithm using an ultrasonic propagation imaging system is proposed to evaluate barely visible impact damage as a strategy of fast in situ nondestructive evaluation or structural health monitoring (SHM). The ultrasonic propagation imaging system is a type of nondestructive evaluation or SHM system and is based on scanning laser-induced guided ultrasound and fixed sensors. The amplitude of ultrasonic signals generated by the ultrasonic propagation imaging system increases with the increasing energy of the laser beam. Two ultrasonic signals generated by different excitation energies of the laser beam can be equalized by multiplying a constant factor to one of them. Therefore, the residuals after subtraction of two signals may be close to zero. However, the two different energy induced signals in the damaged area will be nonzero due to the change in material conditions regarding the laser ultrasonic generation mechanism. The dual-energy wave subtraction algorithm eliminates most of the incident ultrasonic waves and amplifies anomalous waves. A composite wing skin including two barely visible impact damages as well as a composite sandwich panel, including a single barely visible impact damage, were inspected to validate the proposed algorithm.

Quantitative contrast-enhanced spectral mammography based on photon-counting detectors: A feasibility study.

To investigate the feasibility of accurate quantification of iodine mass thickness in contrast-enhanced spectral mammography. A computer simulation model was developed to evaluate the performance of a photon-counting spectral mammography system in the application of contrast-enhanced spectral mammography. A figure-of-merit (FOM), which was defined as the decomposed iodine signal-to-noise ratio (SNR) with respect to the square root of the mean glandular dose (MGD), was chosen to optimize the imaging parameters, in terms of beam energy, splitting energy, and prefiltrations for breasts of various thicknesses and densities. Experimental phantom studies were also performed using a beam energy of 40 kVp and a splitting energy of 34 keV with 3 mm Al prefiltration. A two-step calibration method was investigated to quantify the iodine mass thickness, and was validated using phantoms composed of a mixture of glandular and adipose materials, for various breast thicknesses and densities. Finally, the traditional dual-energy log-weighted subtraction method was also studied as a comparison. The measured iodine signal from both methods was compared to the known value to characterize the quantification accuracy and precision. The optimal imaging parameters, which lead to the highest FOM, were found at a beam energy between 42 and 46 kVp with a splitting energy at 34 keV. The optimal tube voltage decreased as the breast thickness or the Al prefiltration increased. The proposed quantification method was able to measure iodine mass thickness on phantoms of various thicknesses and densities with high accuracy. The root-mean-square (RMS) error for cm-scale lesion phantoms was estimated to be 0.20 mg/cm2 . The precision of the technique, characterized by the standard deviation of the measurements, was estimated to be 0.18 mg/cm2 . The traditional weighted subtraction method also predicted a linear correlation between the measured signal and the known iodine mass thickness. However, the correlation slope and offset values were strongly dependent on the total breast thickness and density. The results of this study suggest that iodine mass thickness for cm-scale lesions can be accurately quantified with contrast-enhanced spectral mammography. The quantitative information can potentially improve the differential power for malignancy.

The advantage of digital tomosynthesis for pulmonary nodule detection concerning influence of nodule location and size: a phantom study

To investigate the advantage of digital tomosynthesis (DTS) over chest radiography (CXR) and dual-energy subtraction radiography (DES) for pulmonary nodule detection according to the location and size of solid simulated pulmonary nodules (SPNs). Ninety-six SPNs of variable sizes were inserted into eight different regions of a lung phantom. These regions were further classified into two groups of danger and non-danger zones based on anatomical location influencing the detection of pulmonary nodules. The 96 cases with inserted SPNs and an additional nodule-free 96 control cases all underwent CXR, DES, and DTS examinations. Three observers independently reviewed all the images. The jackknife alternative free-response receiver operating characteristic was used to analyse diagnostic performance for each technique. DTS was superior to CXR and DES for detection of smaller SPNs, except in the retrodiaphragmatic and apical regions. DTS outperformed CXR and DES for detection of larger SPNs in the paramediastinal region. For 5- and 8-mm SPNs, DTS was superior to CXR and DES in the apical, paramediastinal and lateral pulmonary regions. In the retrodiaphragmatic region, the three techniques showed similar diagnostic performance regardless of the SPN size. DES was similar to DTS for detection of 8-mm SPN in the apical region. For 10- and 12-mm SPNs, CXR and DES showed similar diagnostic performance to DTS in the apical and lateral pulmonary regions; however, DTS was superior to CXR and DES in the paramediastinal region. DTS significantly improved the capability to detect synthetic pulmonary nodules compared with CXR and DES, for detection of smaller nodules in the apical, paramediastinal, and lateral pulmonary regions, and larger nodules located in the paramediastinal region in a thoracic phantom.

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

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. 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. 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. 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.

Dual energy subtraction method for breast calcification imaging

The aim of this work was to present an experimental dual energy (DE) method for the visualization of microcalcifications (μCs). A modified radiographic X-ray tube combined with a high resolution complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) X-ray detector was used. A 40/70kV spectral combination was filtered with 100 μm cadmium (Cd) and 1000 μm copper (Cu) for the low/high-energy combination. Homogenous and inhomogeneous breast phantoms and two calcification phantoms were constructed with various calcification thicknesses, ranging from 16 to 152 μm. Contrast-to-noise ratio (CNR) was calculated from the DE subtracted images for various entrance surface doses. A calcification thickness of 152 μm was visible, with mean glandular doses (MGD) in the acceptable levels (below 3mGy). Additional post-processing on the DE images of the inhomogeneous breast phantom resulted in a minimum visible calcification thickness of 93 μm (MGD=1.62mGy). The proposed DE method could potentially improve calcification visibility in DE breast calcification imaging.