Rayleigh imaging in spectral mammography

Dual Energy (DE) imaging has been widely used in digital radiography and fluoroscopy, as has dual energy CT for various medical applications. In this study, the imaging performance of a dynamic dual-layer a-Si flat panel detector (FPD) prototype was characterized for dual energy imaging tasks. Dual energy cone beam CT (DE CBCT) scans were acquired and used to perform material decomposition in the projection domain, followed by reconstruction to generate material specific and virtual monoenergetic (VM) images. The dual-layer FPD prototype was built on a Varex XRD 4343RF detector by adding a 200 μm thick CsI scintillator and a-Si panel of 150 μm pixel size on top as a low energy detector. A 1 mm copper filter was added as a middle layer to increase energy separation with the bottom layer as a high energy detector. The imaging performance, such as Modulation Transfer Function (MTF), Conversion Factor (CF), and Detector Quantum Efficiency (DQE) of both the top and bottom detector layers were characterized and compared with those of the standard single layer XRD4343 RF detector. Several tissue equivalent cylinders (solid water, liquid water, bone, acrylic, polyethylene, etc.) were placed on a rotating stand, and two separate 450-projection CBCT scans were performed under continuous 120 kV and 80 kV X-ray beams. After an empirical material decomposition calibration, water and bone images were generated for each projection, and their respective volumes were reconstructed using Varex’s CBCT Software Tools (CST 2.0). A VM image, which maximized the contrast-to-noise ratio of water to polyethylene, was generated based on the water and bone images. The MTF at 1.0 lp/mm from the low energy detector was 32% and 22% higher than the high energy detector and the standard detector, respectively; the DQE of both high and low energy detectors is much lower than that of the standard XRD 4343RF detector. The CNR of water to polyethylene from the VM image improved by 50% over that from the low energy image alone at 120 kV, and by 80% at 80 kV. This study demonstrates the feasibility of using a dual-layer FPD in applications such as DE CBCT for contrast enhancement and material decomposition. Further evaluations are underway.

Purpose: To investigate the potential of spectral mammography to distinguish between type I calcifications, consisting of calcium oxalate dihydrate or weddellite compounds that are more often associated with benign lesions, and type II calcifications containing hydroxyapatite which are predominantly associated with malignant tumors. Methods: Using a ray tracing algorithm, we simulated the total number of x-ray photons recorded by the detector at one pixel from a single pencil-beam projection through a breast of 50/50 (adipose/glandular) tissues with inserted microcalcifications of different types and sizes. Material decomposition using two energy bins was then applied to characterize the simulated calcifications into hydroxyapatite and weddellite using maximumlikelihood estimation, taking into account the polychromatic source, the detector response function and the energy dependent attenuation. Results: Simulation tests were carried out for different doses and calcification sizes for multiple realizations. The results were summarized using receiver operating characteristic (ROC) analysis with the area under the curve (AUC) taken as an overall indicator of discrimination performance and showing high AUC values up to 0.99. Conclusion: Our simulation results obtained for a uniform breast imaging phantom indicate that spectral mammography using two energy bins has the potential to be used as a non-invasive method for discrimination between type I and type II microcalcifications to improve early breast cancer diagnosis and reduce the number of unnecessary breast biopsies.

Objective To assess the feasibility of characterizing pleural fluid on the basis of spectral imaging features utilizing spectral CT imaging. Methods Gemstone spectral imaging(GSI) was used to examine 20 pleural fluids filled tubes (11 exudates and 9 transudates ) following diagnostic thoracentesis. Effusions were classified as transudates or exudates using laboratory markers based on Light criteria. CT values on 140 kVp QC image were compared between two groups. Using GSI viewer, various CT spectral imaging parameters (CT values on different energy level, effective-Z, iodine-water concentration,calcium-water concentration and calcium-fat concentration ) were calculated and compared between two groups. The difference of these spectral characteristic parameters was evaluated statistically by independent-samples t test. Results According to Light criteria, the mean CT value on QC image of exudates [ ( 19. 56 ±4. 10) HU ] was higher than that of transudates [ ( 13.44 ±3.46) HU] (t =3.002,P =0. 010).Difference of CT value was found more obvious in the lower keV. On 40 keV images, the difference of CT value of two groups was the largest, the mean value of exudates [ (47.49 ± 14. 60) HU ] was significantly higher than that of transudates[ ( 19. 76 ± 6. 85) HU ] ( t = 5.520, P = 0. 000). While On 140 keV, the mean CT value were (9.76 ±4. 16)and (6.22 ±3. 17) HU and the difference of the two group has no statistically significant difference (t =2. 107,P =0. 050). The mean slope rates of exudates (0.51 ± 0.23)was significantly larger than that of transudates (0. 18 ± 0. 08 ) ( t= 4. 287, P = 0. 001 ). The effective-Z (7. 89 ± 0. 16), iodine-water concentration [ (5. 74 ± 1.28 ) g/L], calcium-water concentration[ (7. 89 ±1.78) g/L] and calcium-fat concentration [ (25.95 ± 1.74) g/L] of exudates were significantly higher than those of transudates [ 7.67 ± 0. 07, ( 1.70 ± 0. 95 ) g/L, (2. 53 ± 1.37 ) g/L, ( 20. 82 ± 1.40 ) g/L ] ( t = 4. 080,6. 998,6. 546,6. 301 ,P ＜ 0. 05 ). Conclusions The spectral curve and spectral imaging parameters of exudates is found to be different from transudates. The low energy spectral imaging plays an important role in the characterization of pleural fluid. Gemstone spectral CT imaging provides a new multiparameter method to differentiate transudates and exudates. Key words: Pleural effusion; Exudates and transudates; Tomography, X-ray computed

Spectral CT is attracting more and more attention in medicine, industrial nondestructive testing and security inspection field. Material decomposition is an important issue to a spectral CT to discriminate materials. Because of the spectrum overlap of energy channels, as well as the correlation of basis functions, it is well acknowledged that decomposition step in spectral CT imaging causes noise amplification and artifacts in component coefficient images. In this work, we propose materials decomposition via an optimization method to improve the quality of decomposed coefficient images. On the basis of general optimization problem, total variance minimization is constrained on coefficient images in our overall objective function with adjustable weights. We solve this constrained optimization problem under the framework of ADMM. Validation on both a numerical dental phantom in simulation and a real phantom of pig leg on a practical CT system using dual-energy imaging is executed. Both numerical and physical experiments give visually obvious better reconstructions than a general direct inverse method. SNR and SSIM are adopted to quantitatively evaluate the image quality of decomposed component coefficients. All results demonstrate that the TV-constrained decomposition method performs well in reducing noise without losing spatial resolution so that improving the image quality. The method can be easily incorporated into different types of spectral imaging modalities, as well as for cases with energy channels more than two.

The Value of Nonenhanced Single-Source Dual-Energy CT for Differentiating Metastases From Adenoma in Adrenal Glands

Purpose: Although bedside imaging is among the most common radiographic exams (e.g., line and catheter placement in the ICU), poor image quality often challenges even conspicuous tasks. We hypothesize that dual-energy (DE) imaging using a novel wireless detector (with form factor equivalent to a film cassette) improves the conspicuity of interventional devices through material decomposition. This work optimizes the system configuration, acquisition techniques, and decomposition techniques for this novel bedside imaging technology. Method and Materials: A mobile x-ray system was integrated with a wireless DR detector (DRX-1) to permit DE image acquisition. Preliminary experimentation involved a benchtop and phantoms simulating bedside imaging. The contrast-to-noise ratio (CNR) was evaluated in DE images for common ICU imaging tasks. Measurements were performed as a function of antiscatter grid ratio (from gridless to 12:1), kVp pair (kVpLow = 40–90 kVp and kVpHigh = 90–140 kVp), and added filtration. Image quality was further improved by implementing linear and nonlinear noise-reduction algorithms. Expert radiologists assessed DR and DE imaging task performance in anthropomorphic phantoms implanted with interventional tools. Results: DE imaging significantly boosted conspicuity of interventional devices in bedside imaging tasks. Antiscatter grids increased CNR by ∼50% without dose increase. Optimal kVp pair was [50/90] kVp, with lower techniques distinct from previous studies attributed to high x-ray scatter in bedside configurations. Optimal filters were identified, with ∼0.2 mm Ag or Sn found optimal for the fixed-filter scenario. Noise-reduction algorithms preserved CNR at reduced imaging dose and indicate distinct processing for soft-tissue and metal decomposition. Qualitative reader studies show a dramatic boost in conspicuity for DE imaging compared to DR. Conclusion: Advances in portable DR enable superior bedside imaging through advanced DE imaging functionality. Optimization of DE imaging and decomposition techniques render interventional tools conspicuous compared to DR without increasing patient dose. Research funded by Carestream Health

To demonstrate the value of optimizing non-contrast head imaging tasks by using the multiple virtual monochromatic spectral imaging (VMSI) sets in dual-energy spectral computed tomography (CT) and determine the optimal energy levels for various tasks in imaging head. This retrospective study includes 55 patients (29 women and 26 men, average age of 54.5±12.3years) who underwent non-contrast head CT in spectral imaging mode. For each patient, 21 VMSI sets from 40 to 140 keV at 5 keV intervals and 120 kVp-like image were reconstructed. Signal-to-noise ratio (SNR) for gray matter (GM) and white matter (WM), contrast-to-noise ratio (CNR) between GM and WM, subcalvarial artifact index (SAI) and posterior fossa artifact index (PFAI) were measured by placing regions-of-interest (ROIs) in nine areas of the brain. Two radiologists subjectively rated the image quality in terms of GM-WM differentiation, beam hardening artifacts in the subcalvarial space, and posterior fossa. The overall image noise was evaluated using a 5-point Likert scale. Measurement data were then statistically analyzed. The optimal energy level for viewing the supratentorial brain and reducing beam hardening artifacts in the subcalvarial space and posterior fossa was 65 keV and 75 keV, respectively. All corresponding measurements at these energy levels were significantly better than those measured at other energy levels (all P < 0.05). Dual-energy spectral CT imaging provides a set of virtual monochromatic spectral imaging and can be selected on-demand to optimize the imaging tasks in non-contrast head CT. VMSI reconstruction of dual-energy unenhanced head CT scans at 65-75 keV enables to maximize image quality.

Breast imaging technology is advancing on several fronts. In digital mammography, the major technological trend has been on optimization of approaches for performing combined mammography and tomosynthesis using the same system. In parallel, photon‐counting slot‐scan mammography is now in clinical use and more efforts are directed towards further development of this approach for spectral imaging. Spectral imaging refers to simultaneous acquisition of two or more energy‐windowed images. Depending on the detector and associated electronics, there are a number of ways this can be accomplished. Spectral mammography using photon‐counting detectors can suppress electronic noise and importantly, it enables decomposition of the image into various material compositions of interest facilitating quantitative imaging. Spectral imaging can be particularly important in intravenously injected contrast mammography and eventually tomosynthesis. The various approaches and applications of spectral mammography are discussed.Digital breast tomosynthesis relies on the mechanical movement of the x‐ray tube to acquire a number of projections in a predefined arc, typically from 9 to 25 projections over a scan angle of +/−7.5 to 25 degrees depending on the particular system. The mechanical x‐ray tube motion requires relatively long acquisition time, typically between 3.7 to 25 seconds depending on the system. Moreover, mechanical scanning may have an effect on the spatial resolution due to internal x‐ray filament or external mechanical vibrations. New x‐ray source arrays have been developed and they are aimed at replacing the scanned x‐ray tube for improved acquisition time and potentially for higher spatial resolution. The potential advantages and challenges of this approach are described.Combination of digital mammography and tomosynthesis in a single system places increased demands on certain functional aspects of the detector and overall performance, particularly in the tomosynthesis mode due to lower photon fluence per projection. This may require fast‐frame acquisition and symmetric or asymmetric pixel binning in some systems. Recent studies investigated the performance of increased conversion layer thickness for contrast‐enhanced imaging of the breast in dual‐energy acquisition mode. In other direct conversion detectors operating in the avalanche mode, sensitivities close to the single photon response are also explored for mammography and breast tomosynthesis. The potential advantages and challenges of this approach are described.Dedicated breast CT brings x‐ray imaging of the breast to true tomographic 3D imaging. It can eliminate the tissue superposition problem and does not require physical compression of the breast. Using cone beam geometry and a flat‐panel detector, several hundred projections are acquired and reconstructed to near isotropic voxels. Multiplanar reconstruction facilitates viewing the breast volume in any desired orientation. Ongoing clinical studies, the current state‐of‐the art, and research to advance the technology are described.Learning Objectives: To understand the ongoing developments in x‐ray imaging of the breast To understand the approaches and applications of spectral mammography To understand the potential advantages of distributed x‐ray source arrays for digital breast tomosynthesis To understand the ongoing developments in detector technology for digital mammography and breast tomosynthesis To understand the current state‐of‐the‐art for dedicated cone‐beam breast CT and research to advance the technology. Research collaboration with Koning Corporation.

Material decomposition allows the reconstruction of material-specific images in spectral X-ray imaging, which requires efficient decomposition models. Due to the presence of nonideal effects in X-ray imaging systems, it is difficult to explicitly estimate the imaging systems for material decomposition tasks. As an alternative to previous empirical material decomposition methods, we investigated material decomposition using ensemble learning methods in this paper. Three ensemble methods with two decision trees as the base learning algorithms were investigated to perform material decomposition in both simulation and experiment. The results were quantitatively evaluated for comparison studies. In general, the results demonstrate that the proposed ensemble learning methods often outperform their base learning algorithms, and rarely reduce performance. Compared to the reference methods and its base learning algorithm, the performance of the Boosting method using REPTree with regularization is improved by over 42% and 13%, respectively, in the noiseless simulated scenario of the XCAT phantom with cardiac and respiratory motion, and over 36% and 17%, respectively, in the noisy scenario. Simultaneously, the performance is improved by over 9% and 8%, respectively, in the original torso phantom scenario, and over 13% and 12%, respectively, in the denoising scenario. The results indicate that ensemble learning with gradient descent optimization algorithms is more appropriate for material decomposition tasks. Further studies are encouraged to facilitate future efforts toward clinical applications.

Contrast-enhanced (CE) dual-energy (DE) x-ray breast imaging uses a low- and high-energy x-ray spectral pair to eliminate soft-tissue signal variation and thereby increase the detectability of exogenous imaging agents. Currently, CEDE breast imaging is performed with iodinated contrast agents. These compounds are limited by several deficiencies, including rapid clearance and poor tumor targeting ability. The purpose of this work is to identify novel contrast materials whose contrast-to-noise ratio (CNR) is comparable or superior to that of iodine in the mammographic energy range. A monoenergetic DE subtraction framework was developed to calculate the DE signal intensity resulting from the logarithmic subtraction of the low- and high-energy signal intensities. A weighting factor is calculated to remove the dependence of the DE signal on the glandularity of the breast tissue. Using the DE signal intensity and weighting factor, the CNR for materials with atomic numbers (Z) ranging from 1 to 79 are computed for energy pairs between 10 and 50 keV.A group of materials with atomic numbers ranging from 42 to 63 were identified to exhibit the highest levels of CNR in the mammographic energy range. Several of these materials have been formulated as nanoparticles for various applications but none, apart from iodine, have been investigated as CEDE breast imaging agents. Within this group of materials, the necessary dose fraction to the LE image decreases as the atomic number increases. By reducing the dose to the LE image, the DE subtraction technique will not provide an anatomical image of sufficient quality to accompany the contrast information. Therefore, materials with Z from 42 to 52 provide nearly optimal values of CNR with energy pairs and dose fractions that provide good anatomical images. This work is intended to inspire further research into new materials for optimized CEDE breast functional imaging.

Objective To explore the quantitative characteristics of pancreatic ductal adenocarcinoma (PDAC) in single-source dual energy spectral CT imaging. Methods From January 2013 to December 2014, 113 patients underwent dual phase contrast-enhanced gemstone spectral imaging (GSI) on Discovery CT 750 HD. All diagnoses were pathologically confirmed by surgery or biopsy. The spectral HU curves of PDAC were observed, the monochromatic CT values, the effective atomic number (Zeff), the iodine concentration (IC), water concentration (WC), and the corresponding normalized values (normalized monochromatic CT values, normalized Zeff, normalized IC, normalized WC) of the lesion and the pancreatic parenchyma in late arterial phase (AP) and portal venous phase (PP) were recorded. The measurements were performed three times repeatedly. Paired t test (normal distribution) or Wilcoxon test (non-normal distribution) were used for analyzing the differences between the two phases and between PDAC and pancreatic parenchyma. Results The monochromatic CT values of PDAC in AP were lower than in PP at each energy level and the difference was more marked at lower energy. The normalized monochromatic CT values increased with the increase of energy level in both AP and PP and the difference was more distinct at lower energy. The Zeff, IC and normalized IC of PDAC all had significant differences (P<0.05), while the WC, normalized Zeff, and normalized WC had no difference between AP and PP. The Zeff and IC of pancreatic parenchyma had significant differences (P<0.05), while the WC had no difference between AP and PP. The differences of Zeff, IC, and WC between PDAC and pancreatic parenchyma were significant in both two phases (P<0.05). Conclusions Dual phase CT spectral imaging showed characteristic quantitative parameters of pancreatic ductal adenocarcinoma. The monochromatic CT values, Zeff, and iodine concentration of PDAC were lower than those of pancreatic parenchyma in both AP and PP. The monochromatic CT values, Zeff, and iodine concentration of PDAC in late arterial phase were lower than those in portal venous phase. The differences were all more distinct at lower energy. Key words: Pancreatic neoplasms; Tomography, X-ray computed; Comparative study

We present a novel method for characterizing mammographic findings using spectral imaging without the use of contrast agent. Within a statistical framework, suspicious findings are analyzed to determine if they are likely to be benign cystic lesions or malignant tissue. To evaluate the method, we have designed a phantom where combinations of different tissue types are realized by decomposition into the material bases aluminum and polyethylene. The results indicate that the lesion size limit for reliable characterization is below 10 mm diameter, when quantum noise is the only considered source of uncertainty. Furthermore, preliminary results using clinical images are encouraging, but allow no conclusions with significance.

Dual energy computed tomography (DECT) plays a significant role in medical application and public security. The accuracy of the decomposition relies much on the quality of the reconstructed images. Images reconstructed by traditional methods generally suffer from significant noise, leading to the low accuracy of the material decomposition and identification. In order to solve the above problem, the maximum a posteriori expectation maximization (MAP-EM) is employed to reconstruct the CT images for the material decomposition, and the performance of the material decomposition is evaluated. A dual source DECT system with 140/80 kVp are simulated by Geant4. The MAP-EM algorithm is used to reconstruct the images from the collected projection at two different tube voltages. And then the basis material decomposition coefficient images are obtained with the basis material decomposition coefficient equations. Comparing with the commonly used filtered back projection (FBP) algorithm, the MAP-EM algorithm reduced noise in polyethylene region on the reconstructed images at two tube voltages with 80 kVp and 140 kVp up to 33.23%, 26.43% respectively. The contrast-to-noise ratios (CNRs) of the aluminum images were improved by 54.13% and 41.02%, that of the HA images by 52.75% and 40.47%, and that of the salt water images by 52.84% and 40.22% at the above two tube voltages. Compared with DE-FBP, the decomposition error of DE-MAP was reduced by 95.94% to 99.09%. In conclusion, the result shows superior performance on material decomposition and identification with high CNRs and low decomposition errors with the DECT images reconstructed by MAP-EM algorithm.

To investigate the value of single-source dual-energy spectral CT imaging in improving the accuracy of preoperative diagnosis of lymph node metastasis of thyroid carcinoma. Thirty-four thyroid carcinoma patients were enrolled and received spectral CT scanning before thyroidectomy and cervical lymph node dissection surgery. Iodine-based material decomposition (MD) images and 101 sets of monochromatic images from 40 to 140 keV were reconstructed after CT scans. The iodine concentrations (IC) of lymph nodes were measured on the MD images and was normalized to that of common carotid artery to obtain the normalized iodine concentration (NIC). The CT number of lymph nodes as function of photon energy was measured on the 101 sets of images to generate a spectral HU curve and to calculate its slope λHU. The measurements between the metastatic and non-metastatic lymph nodes were statistically compared and receiver operating characteristic (ROC) curves were used to determine the optimal thresholds of these measurements for diagnosing lymph nodes metastasis. There were 136 lymph nodes that were pathologically confirmed. Among them, 102 (75%) were metastatic and 34 (25%) were non-metastatic. The IC, NIC and the slope λHU of the metastatic lymph nodes were 3.93±1.58 mg/mL, 0.70±0.55 and 4.63±1.91, respectively. These values were statistically higher than the respective values of 1.77±0.71 mg/mL, 0.29±0.16 and 2.19±0.91 for the non-metastatic lymph nodes (all P<0.001). ROC analysis determined the optimal diagnostic threshold for IC as 2.56 mg/mL, with the sensitivity, specificity and accuracy of 83.3%, 91.2% and 85.3%, respectively. The optimal threshold for NIC was 0.289, with the sensitivity, specificity and accuracy of 96.1%, 76.5% and 91.2%, respectively. The optimal threshold for the spectral curve slope λHU was 2.692, with the sensitivity, specificity and accuracy of 88.2%, 82.4% and 86.8%, respectively. The measurements obtained in dual-energy spectral CT improve the sensitivity and accuracy for preoperatively diagnosing lymph node metastasis in thyroid carcinoma.

Propagation-based imaging is an X-ray phase-contrast method that does not require any additional optical elements in the imaging system. Instead, phase-contrast effects are observed as measurable intensity variations after an incident X-ray wave field has propagated some distance between the object and plane of detection. Subsequent phase-retrieval processing of the recorded images is a necessary step in order to obtain quantitative information and can greatly increase the image signal-to-noise ratio, in particular in computed tomography. Most commonly this is done by approximating the object as a single material, which cannot always be justified. An example of this is the presence of bones and soft-tissues in biomedical imaging, which motivated the work presented here. We developed the combination of spectral X-ray imaging and propagation-based X-ray phasecontrast imaging to overcome the limitations of a single-material approximation. The addition of spectral data enables phase-retrieval on multi-material objects, as well as the use of processing methods well-known from conventional dual-energy imaging, such as material decomposition, virtual monochromatic images and effective atomic-number mapping. Here, we present first computed tomography results of spectral propagation-based phase-contrast. We discuss how the phase retrieval process can be interpreted as low- and high-pass filters. Lastly, we take a look at current and future technological challenges, and the potential application areas of spectral propagation-based phase-contrast imaging.