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Conventional x-ray imaging provides little quantitative information due to scatter, beam hardening, and overlaying tissues. A single-shot quantitative x-ray imaging (SSQI) method was previously developed to quantify material-specific densities in x-ray imaging by combining the use of a primary modulator (PM) and dual-layer (DL) detector. The feasibility of this concept was demonstrated with simulations using an iterative patch-based method. In this work, we propose a new algorithm pipeline for SSQI that enables accurate quantification and high computational efficiency. The DL images contain four measurements that are obtained behind the unattenuated and partially attenuated regions of the PM of each layer. Using the low-frequency property of scatter and a pre-calibrated material decomposition (MD), four unknowns (i.e., two scatter images and two material-specific images) are jointly recovered by directly solving four equations given by the four measurements. We tested this algorithm in simulations and further demonstrated its efficacy on chest phantom experiments. Through simulation, we show that the new method for MD is robust against scatter. Its performance improves with smaller PM pitch size and smaller focal spot blur. The RMSE in material-specific images compared to ground truth reduces by 52%−84% versus without scatter correction. For our experimental study, we successfully separated soft tissue and bone. The computational time for processing each view was ~8 s without optimization. The reported results further strengthen the potential of SSQI for widespread adoption, leading to quantitative imaging not only for x-ray imaging but also for real-time image guidance or cone-beam CT.

Purpose Metal artifact remains a challenge in cone-beam CT images. Many image domain-based segmentation methods have been proposed for metal artifact reduction (MAR), which require two-pass reconstruction. Such methods first segment metal from a first-pass reconstruction and then forward-project the metal mask to identify them in projections. These methods work well in general but are limited when the metal is outside the scan field-of-view (FOV) or when the metal is moving during the scan. In the former, even reconstructing with a larger FOV does not guarantee a good estimate of metal location in the projections; and in the latter, the metal location in each projection is difficult to identify due to motion. Single-pass methods that detect metal in single-energy projections have also been developed, but often have imperfect metal detection that leads to residual artifacts. In this work, we develop a MAR method using a dual-layer (DL) flat panel detector, which improves performance for single-pass reconstruction. Methods In this work, we directly detect metal objects in projections using dual-energy (DE) imaging that generates material-specific images (e.g., soft tissue and bone), where the metal stands out in bone images when nonuniform soft tissue background is removed. Metal is detected via simple thresholding, and entropy filtration is further applied to remove false-positive detections. A DL detector provides DE images with superior temporal and spatial registration and was used to perform the task. Scatter correction was first performed on DE raw projections to improve the accuracy of material decomposition. One phantom mimicking a liver biopsy setup and a cadaver head were used to evaluate the metal reduction performance of the proposed method and compared with that of a standard two-pass reconstruction, a previously published sinogram-based method using a Markov random field (MRF) model, and a single-pass projection-domain method using single-energy imaging. The phantom has a liver steering setup placed in a hollow chest phantom, with embedded metal and a biopsy needle crossing the phantom boundary. The cadaver head has dental fillings and a metal tag attached to its surface. The identified metal regions in each projection were corrected by interpolation using surrounding pixels, and the images were reconstructed using filtered backprojection. Results Our current approach removes metal from the projections, which is robust to FOV truncation during imaging acquisition. In case of FOV truncation, the method outperformed the two-pass reconstruction method. The proposed method using DE renders better accuracy in metal segmentation than the MRF method and single-energy method, which were prone to false-positive errors that cause additional streaks. For the liver steering phantom, the average spatial nonuniformity was reduced from 0.127 in uncorrected images to 0.086 using a standard two-pass reconstruction and to 0.077 using the proposed method. For the cadaver head, the average standard deviation within selected soft tissue regions ( σ s ) was reduced from 209.1 HU in uncorrected images to 69.1 HU using a standard two-pass reconstruction and to 46.8 HU using our proposed method. The proposed method reduced the processing time by 31% as compared with the two-pass method. Conclusions We proposed a MAR method that directly detects metal in the projection domain using DE imaging, which is robust to truncation and superior to that of single-energy imaging. The method requires only a single-pass reconstruction that substantially reduces processing time compared with the standard two-pass metal reduction method.

Purpose: The focal spot size and shape of an x-ray system are critical factors to the spatial resolution. Conventional approaches to characterizing the focal spot use specialized tools that usually require careful calibration. We propose an alternative to characterize the x-ray source’s focal spot, simply using a rotating edge and flat-panel detector. Methods: An edge is moved to the beam axis, and an edge spread function (ESF) is obtained at a specific angle. Taking the derivative of the ESF provides the line spread function, which is the Radon transform of the focal spot in the direction parallel to the edge. By rotating the edge about the beam axis for 360 deg, we obtain a complete Radon transform, which is used for reconstructing the focal spot. We conducted a study on a clinical C-arm system with three focal spot sizes (0.3, 0.6, and 1.0 mm nominal size), then compared the focal spot imaged using the proposed method against the conventional pinhole approach. The full width at half maximum (FWHM) of the focal spots along the width and height of the focal spot were used for quantitative comparisons. Results: Using the pinhole method as ground truth, the proposed method accurately characterized the focal spot shapes and sizes. Quantitatively, the FWHM widths were 0.37, 0.65, and 1.14 mm for the pinhole method and 0.33, 0.60, and 1.15 mm for the proposed method for the 0.3, 0.6, and 1.0 mm nominal focal spots, respectively. Similar levels of agreement were found for the FWHM heights. Conclusions: The method uses a rotating edge to characterize the focal spot and could be automated in the future using a system’s built-in collimator. The method could be included as part of quality assurance tests of image quality and tube health.

BACKGROUND: High-resolution, low-noise detectors with minimal dead-space at chest-wall could improve posterior coverage and microcalcification visibility in dedicated cone-beam breast CT (CBBCT). However, their smaller field-of-view necessitates laterally-shifted detector geometry to enable optimizing the air-gap for x-ray scatter rejection. OBJECTIVE: To evaluate laterally-shifted detector geometry for CBBCT with clinical projection datasets that provide for anatomical structures and lesions. METHODS: CBBCT projection datasets (n=17 breasts) acquired with a 40×30-cm detector (1024×768-pixels, 0.388-mm pixels) were truncated along the fan-angle to emulate 20.3×30-cm, 22.2×30-cm and 24.1×30-cm detector formats and correspond to 20, 120, 220-pixels overlap in conjugate views, respectively. Feldkamp-Davis-Kress (FDK) algorithm with three different weighting schemes were used for reconstruction. Visual analysis for artifacts and quantitative analysis of root-mean-squared-error (RMSE), absolute difference between truncated and 40×30-cm reconstructions (Diff), and its power spectrum (PS(Diff)) were performed. RESULTS: Artifacts were observed for 20.3×30-cm, but not for other formats. The 24.1×30-cm provided the best quantitative results with RMSE and Diff (both in units of μ, cm(−1)) of 4.39×10(−3)±1.98×10(−3) and 4.95×10(−4)±1.34×10(−4), respectively. The PS(Diff)(>0.3 cycles/mm) was in the order of 10(−14)μ(2)mm(3) and was spatial-frequency independent. CONCLUSIONS: Laterally-shifted detector CBBCT with at least 220-pixels overlap in conjugate views (24.1×30-cm detector format), provides quantitatively accurate and artifact-free reconstruction.

Cone-beam CT (CBCT) is widely used in diagnostic imaging and image-guided procedures, leading to an increasing need for advanced CBCT techniques, such as dual energy (DE) imaging. Previous studies have shown that DE-CBCT can perform quantitative material decomposition, including quantification of contrast agents, electron density, and virtual monoenergetic images. Currently, most CBCT systems perform DE imaging using a kVp switching technique. However, the disadvantages of this method are spatial and temporal misregistration as well as total scan time increase, leading to errors in the material decomposition. DE-CBCT with a dual layer flat panel detector potentially overcomes these limitations by acquiring the dual energy images simultaneously. In this work, we investigate the DE imaging performance of a prototype dual layer detector by evaluating its material decomposition capability and comparing its performance to that of the kVp switching method. Two sets of x-ray spectra were used for kVp switching: 80/120 kVp and 80/120 kVp + 1 mm Cu filtration. Our results show the dual layer detector outperforms kVp switching at 80/120 kVp with matched dose. The performance of kVp switching was better by adding 1 mm copper filtration to the high energy images (80/120 kVp + 1 mm Cu), though the dual layer detector still provided comparable performance for material decomposition tasks. Overall, both the dual layer detector and kVp switching methods provided quantitative material decomposition images in DE-CBCT, with the dual layer detector having additional potential advantages.

Metal artifact remains a challenge in cone-beam CT images. Many two-pass metal artifact reduction methods have been proposed, which work fairly well, but are limited when the metal is outside the scan field-of-view (FOV) or when the metal is moving during the scan. In the former, even reconstructing with a larger FOV does not guarantee a good estimate of metal location in the projections; and in the latter, the metal location in each projection is difficult to identify due to motion. Furthermore, two-pass methods increase the total reconstruction time. In this study, a projection-based metal detection and correction method with a dual layer detector is investigated. The dual layer detector provides dual energy images with perfect temporal and spatial registration in each projection, which aid in the identification of metal. A simple phantom with metal wires (copper) and a needle (steel) is used to evaluate the projection-based metal artifact reduction method from a dual layer scan and compared with that of a single layer scan. Preliminary results showed enhanced ability to identify metal regions, leading to substantially reduced metal artifact in reconstructed images. In summary, an effective single-pass, projection-domain method using a dual layer detector has been demonstrated, and it is expected to be robust against truncation and motion.

The size and shape of an x-ray source’s focal spot is a critical factor in the imaging system’s overall spatial resolution. The conventional approach to imaging the focal spot uses a pinhole camera, but this requires careful, manual measurements. Instead, we propose a novel alternative, simply using the collimator available on many x-ray systems. After placing the edge of a collimator blade in the center of the beam, we can obtain an image of its edge spread function (ESF). Each ESF provides information about the focal spot distribution – specifically, the parallel projection of the focal spot in the direction parallel to the edge. If the edge is then rotated about the beam axis, each image provides a different parallel projection of the focal spot until a complete Radon transform of the focal spot distribution is obtained. The focal spot can then be reconstructed by the inverse Radon transform, or parallel-beam filtered backprojection. We conducted a study on a clinical C-arm system with 3 focal spot sizes (0.3, 0.6, 1.0 mm nominal size), comparing the focal spot obtained using the rotating edge method against the conventional pinhole approach. Our results demonstrate accurate characterization of the size and shape of the focal spot.

Purpose Dual-energy (DE) x-ray imaging has many clinical applications in radiography, fluoroscopy, and CT. This work characterizes a prototype dual-layer (DL) flat-panel detector (FPD) and investigates its DE imaging capabilities for applications in two-dimensional (2D) radiography/fluoroscopy and quantitative three-dimensional (3D) cone-beam CT. Unlike other DE methods like kV switching, a DL FPD obtains DE images from a single exposure, making it robust against patient and system motion. Methods The DL FPD consists of a top layer with a 200 µm-thick CsI scintillator coupled to an amorphous silicon (aSi) FPD of 150 µm pixel size and a bottom layer with a 550 µm thick CsI scintillator coupled to an identical aSi FPD. The two layers are separated by a 1-mm Cu filter to increase spectral separation. Images (43 × 43 cm2 active area) can be readout in 2 × 2 binning mode (300 µm pixels) at up to 15 frames per second. Detector performance was first characterized by measuring the MTF, NPS, and DQE for the top and bottom layers. For 2D applications, a qualitative study was conducted using an anthropomorphic thorax phantom containing a porcine heart with barium-filled coronary arteries (similar to iodine). Additionally, fluoroscopic lung tumor tracking was investigated by superimposing a moving tumor phantom on the thorax phantom. Tracking accuracies of single-energy (SE) and DE fluoroscopy were compared against the ground truth motion of the tumor. For 3D quantitative imaging, a phantom containing water, iodine, and calcium inserts was used to evaluate overall DE material decomposition capabilities. Virtual monoenergetic (VM) images ranging from 40 to 100 keV were generated, and the optimal VM image energy which achieved the highest image uniformity and maximum contrast-to-noise ratio (CNR) was determined. Results The spatial resolution of the top layer was substantially higher than that of the bottom layer (top layer 50% MTF = 2.2 mm-1 , bottom layer = 1.2 mm-1 ). A substantial increase in NNPS and reduction in DQE were observed for the bottom layer mainly due to photon loss within the top layer and Cu filter. For 2D radiographic and fluoroscopic applications, the DL FPD was capable of generating high-quality material-specific images separating soft tissue from bone and barium. For lung tumor tracking, DE fluoroscopy yielded more accurate results than SE fluoroscopy, with an average reduction in the root mean square error (RMSE) of over 10×. For the DE-CBCT studies, accurate basis material decompositions were obtained. The estimated material densities were 294.68 ± 17.41 and 92.14 ± 15.61 mg/ml for the 300 and 100 mg/ml calcium inserts, respectively, and 8.93 ± 1.45, 4.72 ± 1.44, and 2.11 ± 1.32 mg/ml for the 10, 5, and 2 mg/ml iodine inserts, respectively, with an average error of less than 5%. The optimal VM image energy was found to be 60 keV. Conclusions We characterized a prototype DL FPD and demonstrated its ability to perform accurate single-exposure DE radiography/fluoroscopy and DE-CBCT. The merits of the DL detector approach include superior spatial and temporal registration between its constituent images, and less complicated acquisition sequences.

In this work, five [Cu(dppp)(phen)]X complexes (X=BF4 ( 1 ), SO3CF3 ( 2 ), NO3 ( 3 ), SCN ( 4 ), I ( 5 )) have been synthesized from 1,10-phenanthroline (phen) and 1,3-bis(diphenylphosphino)propane (dppp) ligands, which show strong phosphorescence between 560–600 nm in the solid state at room temperature. Complexes 1 – 5 show a broad solid state emission in the green region of the spectrum. As commendable emitter, complex 5 exhibits extraordinary quantum yield ( Φ p) as high as 18% with lifetime ( τ p) of 10.1–11.2 μs at room temperature. Time-dependent density functional theory calculation (TD-DFT) was performed on complexes 1 ~ 5 to rationalize their experimental absorption and emission spectra. Complex 2 displays a favorable π - π stacking and can be simplified as two-dimensional topology.

Purpose The quality of dedicated cone-beam breast CT (CBBCT) imaging is fundamentally limited by x-ray scatter contamination due to the large irradiation volume. In this paper, we propose a scatter correction method for CBBCT using a novel forward-projection model with high correction efficacy and reliability. Method We first coarsely segment the uncorrected, first-pass, reconstructed CBBCT images into binary-object maps and assign the segmented fibroglandular and adipose tissue with the correct attenuation coefficients based on the mean x-ray energy. The modified CBBCT are treated as the prior images toward scatter correction. Primary signals are first estimated via forward projection on the modified CBBCT. To avoid errors caused by inaccurate segmentation, only sparse samples of estimated primary are selected for scatter estimation. A Fourier-Transform based algorithm, herein referred to as local filtration hereafter, is developed to efficiently estimate the global scatter distribution on the detector. The scatter-corrected images are obtained by removing the estimated scatter distribution from measured projection data. Results We evaluate the method performance on six patients with different breast sizes and shapes representing the general population. The results show that the proposed method effectively reduces the image spatial non-uniformity from 8.27 to 1.91% for coronal views and from 6.50 to 3.00% for sagittal views. The contrast-to-deviation ratio is improved by an average factor of 1.41. Comparisons on the image details reveal that the proposed scatter correction successfully preserves fine structures of fibroglandular tissues that are lost in the segmentation process. Conclusion We propose a highly practical and efficient scatter correction algorithm for CBBCT via a forward-projection model. The method is attractive in clinical CBBCT imaging as it is readily implementable on a clinical system without modifications in current imaging protocols or system hardware.

Quantitative short-scan cone beam CT (CBCT) is impeded by streaking and shading artifacts. Streaking artifacts can be caused by approximate handling of data redundancy in short-scan FDK with Parker’s weighting, while shading artifacts are caused by scatter and beam hardening effects. In this work, we improve the image quality of short-scan CBCT by removing the streaking artifacts using a previously proposed algorithm in a framework of filtered backprojection with shift-invariant filtering and equal weighting. An efficient image domain shading correction using sparse samples is subsequently applied to further improve the image uniformity. The improved image quality is shown for this approach, both in visual appearance and quantitative measurements of three clinical head scans.

The quantitative use of cone beam computed tomography (CBCT) in radiation therapy is limited by severe shading artifacts, even with system embedded correction. We recently proposed effective shading correction methods, using planning CT (pCT) as prior information to estimate low- frequency errors in either the projection domain or image domain. In this work, we further improve the clinical practicality of our previous methods by removing the requirement of prior pCT images. Clinical CBCT images are typically composed of a limited number of tissues. By utilizing the low frequency characteristic of shading distribution, we first generate a ‘shading-free’ template image by enforcing uniformity on CBCT voxels of the same tissue type via a technique named partitioned tissue classification. Only a small subset of voxels in the template image are used in the correction process to generate sparse samples of shading artifacts. Local filtration, a Fourier transform based algorithm, is employed to efficiently process the sparse errors to compute a full-field distribution of shading artifacts for CBCT correction. We evaluate the method’s performance using an anthropomorphic pelvis phantom and 6 pelvis patients. The proposed method improves the image quality of CBCT for both phantom and patients to a level matching that of pCT. On the pelvis phantom, the signal non-uniformity (SNU) is reduced from 12.11% to 3.11% and 8.40% to 2.21% on fat and muscle, respectively. The maximum CT number error is reduced from 70 to 10 HU and 73 to 11 HU on fat and muscle, respectively. On patients, the average SNU is reduced from 9.22% to 1.06% and 11.41% to 1.67% on fat and muscle, respectively. The maximum CT number error is reduced from 95 to 9 HU and 88 to 8 HU on fat and muscle, respectively. The typical processing time for one CBCT dataset is about 45 s on a standard PC.

Purpose: The image quality of dedicated cone beam breast CT (CBBCT) is limited by substantial scatter contamination, resulting in cupping artifacts and contrast-loss in reconstructed images. Such effects obscure the visibility of soft-tissue lesions and calcifications, which hinders breast cancer detection and diagnosis. In this work, we propose a library-based software approach to suppress scatter on CBBCT images with high efficiency, accuracy, and reliability. Methods: The authors precompute a scatter library on simplified breast models with different sizes using the geant4-based Monte Carlo (MC) toolkit. The breast is approximated as a semiellipsoid with homogeneous glandular/adipose tissue mixture. For scatter correction on real clinical data, the authors estimate the breast size from a first-pass breast CT reconstruction and then select the corresponding scatter distribution from the library. The selected scatter distribution from simplified breast models is spatially translated to match the projection data from the clinical scan and is subtracted from the measured projection for effective scatter correction. The method performance was evaluated using 15 sets of patient data, with a wide range of breast sizes representing about 95% of general population. Spatial nonuniformity (SNU) and contrast to signal deviation ratio (CDR) were used as metrics for evaluation. Results: Since the time-consuming MC simulation for library generation is precomputed, the authors’ method efficiently corrects for scatter with minimal processing time. Furthermore, the authors find that a scatter library on a simple breast model with only one input parameter, i.e., the breast diameter, sufficiently guarantees improvements in SNU and CDR. For the 15 clinical datasets, the authors’ method reduces the average SNU from 7.14% to 2.47% in coronal views and from 10.14% to 3.02% in sagittal views. On average, the CDR is improved by a factor of 1.49 in coronal views and 2.12 in sagittal views. Conclusions: The library-based scatter correction does not require increase in radiation dose or hardware modifications, and it improves over the existing methods on implementation simplicity and computational efficiency. As demonstrated through patient studies, the authors’ approach is effective and stable, and is therefore clinically attractive for CBBCT imaging.

Purpose: High-resolution, photon-counting, energy-resolved detector with fast-framing capability can facilitate simultaneous acquisition of precontrast and postcontrast images for subtraction angiography without pixel registration artifacts and can facilitate high-resolution real-time imaging during image-guided interventions. Hence, this study was conducted to determine the spatial resolution characteristics of a hexagonal pixel array photon-counting cadmium telluride (CdTe) detector. Methods: A 650 μm thick CdTe Schottky photon-counting detector capable of concurrently acquiring up to two energy-windowed images was operated in a single energy-window mode to include photons of 10 keV or higher. The detector had hexagonal pixels with apothem of 30 μm resulting in pixel pitch of 60 and 51.96 μm along the two orthogonal directions. The detector was characterized at IEC-RQA5 spectral conditions. Linear response of the detector was determined over the air kerma rate relevant to image-guided interventional procedures ranging from 1.3 nGy/frame to 91.4 μGy/frame. Presampled modulation transfer was determined using a tungsten edge test device. The edge-spread function and the finely sampled line spread function accounted for hexagonal sampling, from which the presampled modulation transfer function(MTF) was determined. Since detectors with hexagonal pixels require resampling to square pixels for distortion-free display, the optimal square pixel size was determined by minimizing the root-mean-squared-error of the aperture functions for the square and hexagonal pixels up to the Nyquist limit. Results: At Nyquist frequencies of 8.33 and 9.62 cycles/mm along the apothem and orthogonal to the apothem directions, the modulation factors were 0.397 and 0.228, respectively. For the corresponding axis, the limiting resolution defined as 10% MTF occurred at 13.3 and 12 cycles/mm, respectively. Evaluation of the aperture functions yielded an optimal square pixel size of 54 μm. After resampling to 54 μm square pixels using trilinear interpolation, the presampled MTF at Nyquist frequency of 9.26 cycles/mm was 0.29 and 0.24 along the orthogonal directions and the limiting resolution (10% MTF) occurred at approximately 12 cycles/mm. Visual analysis of a bar pattern image showed the ability to resolve close to 12 line-pairs/mm and qualitative evaluation of a neurovascular nitinol-stent showed the ability to visualize its struts at clinically relevant conditions. Conclusions: Hexagonal pixel array photon-counting CdTe detector provides high spatial resolution in single-photon counting mode. After resampling to optimal square pixel size for distortion-free display, the spatial resolution is preserved. The dual-energy capabilities of the detector could allow for artifact-free subtraction angiography and basis material decomposition. The proposed high-resolution photon-counting detector with energy-resolving capability can be of importance for several image-guided interventional procedures as well as for pediatric applications.

Dedicated breast computed tomography (BCT) is an emerging clinical modality that can eliminate tissue superposition and has the potential for improved sensitivity and specificity for breast cancer detection and diagnosis. It is performed without physical compression of the breast. Most of the dedicated BCT systems use large-area detectors operating in cone-beam geometry and are referred to as cone-beam breast CT (CBBCT) systems. The large-area detectors in CBBCT systems are energy-integrating, indirect-type detectors employing a scintillator that converts x-ray photons to light, followed by detection of optical photons. A key consideration that determines the image quality achieved by such CBBCT systems is the choice of scintillator and its performance characteristics. In this work, a framework for analyzing the impact of the scintillator on CBBCT performance and its use for task-specific optimization of CBBCT imaging performance is described.

Purpose Dedicated cone beam breast CT (CBBCT) suffers from x-ray scatter contamination. We aim to identify the source of the significant difference between the scatter distributions estimated by two recent methods proposed by our group and to investigate its effect on CBBCT image quality. Method We recently proposed two novel methods of scatter correction for CBBCT, using a library based (LB) technique and a forward projection (FP) model. Despite similar enhancement on CBBCT image qualities, these two methods obtain very different scatter distributions. We hypothesize that the off-focus radiation (OFR) is the contributor and results in nontrivial signals in x-ray projections, which is ignored in the scatter estimation via the LB method. Experiments using a thin wire test tool are designed to study the effect of OFR on CBBCT spatial resolution by measuring the point spread function (PSF) and the modulation transfer function (MTF). A narrow collimator setting is used to suppress the OFR-induced signals. In addition, "PSFs" and "MTFs" are measured on clinical CBBCT images obtained by the LB and FP methods using small calcifications as point sources. The improvement of spatial resolution achieved by suppressing OFR in the wire experiment as well as in the clinical study is quantified by the improvement ratios of PSFs and spatial frequencies at different MTF values. Our hypothesis that OFR causes the imaging difference between the FP and LB methods is verified if these ratios obtained from experimental and clinical data are consistent. Results In the wire experiment, the results show that suppression of OFR increases the maximum signal of the PSF by about 14% and reduces the full-width-at-half-maximum (FWHM) by about 12.0%. Similar improvement on spatial resolution is achieved by the FP method compared with the LB method in the patient study. The improvement ratios of spatial frequencies at different MTF values without OFR match very well in both studies at a level of around 16%, with an average root-mean-square difference of 0.47%. Conclusion The results of the wire experiment and the clinical study indicate that the main difference between the LB and FP methods is whether the OFR-induced signals are included after scatter correction. Our study further shows that OFR significantly affects the image spatial resolution of CBBCT, indicating that the visualization of micro-calcifications is susceptible to OFR contamination. Our finding is therefore important in further improvement of diagnostic performance of CBBCT.

This study retrospectively analyzed the mean glandular dose (MGD) to 133 breasts from 132 subjects, all women, who participated in a clinical trial evaluating dedicated breast CT in a diagnostic population. The clinical trial was conducted in adherence to a protocol approved by institutional review boards and the study participants provided written informed consent. Individual estimates of mean glandular dose to each breast from dedicated breast CT was obtained by combining x-ray beam characteristics with estimates of breast dimensions and fibroglandular fraction from volumetric breast CT images, and using normalized glandular dose coefficients. For each study participant and for the breast corresponding to that imaged with breast CT, an estimate of the MGD from diagnostic mammography (including supplemental views) was obtained from the DICOM image headers for comparison. This estimate uses normalized glandular dose coefficients corresponding to a breast with 50% fibroglandular weight fraction. The median fibroglandular weight fraction for the study cohort determined from volumetric breast CT images was 15%. Hence, the MGD from diagnostic mammography was corrected to be representative of the study cohort. Individualized estimates of MGD from breast CT ranged from 5.7 mGy to 27.8 mGy. Corresponding to the breasts imaged with breast CT, the MGD from diagnostic mammography ranged from 2.6 to 31.6 mGy. The mean (± inter-breast SD) and the median MGD (mGy) from dedicated breast CT exam were 13.9±4.6 and 12.6, respectively. For the corresponding breasts, the mean (± inter-breast SD) and the median MGD (mGy) from diagnostic mammography were 12.4±6.3 and 11.1, respectively. Statistical analysis indicated that at the 0.05 level, the distributions of MGD from dedicated breast CT and diagnostic mammography were significantly different (Wilcoxon signed ranks test, p = 0.007). While the interquartile range and the range (maximum-minimum) of MGD from dedicated breast CT was lower than diagnostic mammography, the median MGD from dedicated breast CT was approximately 13.5% higher than that from diagnostic mammography. The MGD for breast CT is based on a 1.45 mm skin layer and that for diagnostic mammography is based on a 4 mm skin layer; thus, favoring a lower estimate for MGD from diagnostic mammography. The median MGD from dedicated breast CT corresponds to the median MGD from 4 to 5 diagnostic mammography views. In comparison, for the same 133 breasts, the mean and the median number of views per breast during diagnostic mammography were 4.53 and 4, respectively. Paired analysis showed that there was approximately equal likelihood of receiving lower MGD from either breast CT or diagnostic mammography. Future work will investigate methods to reduce and optimize radiation dose from dedicated breast CT.

High-resolution, photon-counting, energy-resolved detector with fast-framing capability can facilitate simultaneous acquisition of precontrast and postcontrast images for subtraction angiography without pixel registration artifacts and can facilitate high-resolution real-time imaging during image-guided interventions. Hence, this study was conducted to determine the spatial resolution characteristics of a hexagonal pixel array photon-counting cadmium telluride (CdTe) detector.A 650 μm thick CdTe Schottky photon-counting detector capable of concurrently acquiring up to two energy-windowed images was operated in a single energy-window mode to include photons of 10 keV or higher. The detector had hexagonal pixels with apothem of 30 μm resulting in pixel pitch of 60 and 51.96 μm along the two orthogonal directions. The detector was characterized at IEC-RQA5 spectral conditions. Linear response of the detector was determined over the air kerma rate relevant to image-guided interventional procedures ranging from 1.3 nGy/frame to 91.4 μGy/frame. Presampled modulation transfer was determined using a tungsten edge test device. The edge-spread function and the finely sampled line spread function accounted for hexagonal sampling, from which the presampled modulation transfer function (MTF) was determined. Since detectors with hexagonal pixels require resampling to square pixels for distortion-free display, the optimal square pixel size was determined by minimizing the root-mean-squared-error of the aperture functions for the square and hexagonal pixels up to the Nyquist limit.At Nyquist frequencies of 8.33 and 9.62 cycles/mm along the apothem and orthogonal to the apothem directions, the modulation factors were 0.397 and 0.228, respectively. For the corresponding axis, the limiting resolution defined as 10% MTF occurred at 13.3 and 12 cycles/mm, respectively. Evaluation of the aperture functions yielded an optimal square pixel size of 54 μm. After resampling to 54 μm square pixels using trilinear interpolation, the presampled MTF at Nyquist frequency of 9.26 cycles/mm was 0.29 and 0.24 along the orthogonal directions and the limiting resolution (10% MTF) occurred at approximately 12 cycles/mm. Visual analysis of a bar pattern image showed the ability to resolve close to 12 line-pairs/mm and qualitative evaluation of a neurovascular nitinol-stent showed the ability to visualize its struts at clinically relevant conditions.Hexagonal pixel array photon-counting CdTe detector provides high spatial resolution in single-photon counting mode. After resampling to optimal square pixel size for distortion-free display, the spatial resolution is preserved. The dual-energy capabilities of the detector could allow for artifact-free subtraction angiography and basis material decomposition. The proposed high-resolution photon-counting detector with energy-resolving capability can be of importance for several image-guided interventional procedures as well as for pediatric applications.

Optically derived tissue properties across a range of breast densities and the effects of breast compression on estimates of hemoglobin, oxygen metabolism, and water and lipid concentrations were obtained from a coregistered imaging system that integrates near-infrared spectral tomography (NIRST) with digital breast tomosynthesis (DBT). Image data were analyzed from 27 women who underwent four IRB approved NIRST/DBT exams that included fully and mildly compressed breast acquisitions in two projections—craniocaudal (CC) and mediolateral-oblique (MLO)—and generated four data sets per patient (full and moderate compression in CC and MLO views). Breast density was correlated with HbT (r=0.64, p=0.001), water (r=0.62, p=0.003), and lipid concentrations (r=?0.74, p

A multimodality system combining a clinical prototype digital breast tomosynthesis with its imaging geometry modified to facilitate near-infrared spectroscopic imaging has been developed. The accuracy of parameters recovered from near-infrared spectroscopy is dependent on fibroglandular tissue content. Hence, in this study, volumetric estimates of fibroglandular tissue from tomosynthesis reconstructions were determined. A kernel-based fuzzy c-means algorithm was implemented to segment tomosynthesis reconstructed slices in order to estimate fibroglandular content and to provide anatomic priors for near-infrared spectroscopy. This algorithm was used to determine volumetric breast density (VBD), defined as the ratio of fibroglandular tissue volume to the total breast volume, expressed as percentage, from 62 tomosynthesis reconstructions of 34 study participants. For a subset of study participants who subsequently underwent mammography, VBD from mammography matched for subject, breast laterality and mammographic view was quantified using commercial software and statistically analyzed to determine if it differed from tomosynthesis. Summary statistics of the VBD from all study participants were compared with prior independent studies. The fibroglandular volume from tomosynthesis and mammography were not statistically different (p=0.211, paired t-test). After accounting for the compressed breast thickness, which were different between tomosynthesis and mammography, the VBD from tomosynthesis was correlated with (r =0.809, p0.99, paired t-test), and was linearly related to, the VBD from mammography. Summary statistics of the VBD from tomosynthesis were not statistically different from prior studies using high-resolution dedicated breast computed tomography. The observation of correlation and linear association in VBD between mammography and tomosynthesis suggests that breast density associated risk measures determined for mammography are translatable to tomosynthesis. Accounting for compressed breast thickness is important when it differs between the two modalities. The fibroglandular volume from tomosynthesis reconstructions is similar to mammography indicating suitability for use during near-infrared spectroscopy.

Purpose: To determine the mean and range of volumetric glandular fraction (VGF) of the breast in a diagnostic population using a high-resolution flat-panel cone-beam dedicated breast CT system. This information is important for Monte Carlo-based estimation of normalized glandular dose coefficients and for investigating the dependence of VGF on breast dimensions, race, and pathology. Methods: Image data from a clinical trial investigating the role of dedicated breast CT that enrolled 150 women were retrospectively analyzed to determine the VGF. The study was conducted in adherence to a protocol approved by the institutional human subjects review boards and written informed consent was obtained from all study participants. All participants in the study were assigned BI-RADS{sup Registered-Sign} 4 or 5 as per the American College of Radiology assessment categories after standard diagnostic work-up and underwent dedicated breast CT exam prior to biopsy. A Gaussian-kernel based fuzzy c-means algorithm was used to partition the breast CT images into adipose and fibroglandular tissue after segmenting the skin. Upon determination of the accuracy of the algorithm with a phantom, it was applied to 137 breast CT volumes from 136 women. VGF was determined for each breast and the mean and range were determined. Pathology resultsmore » with classification as benign, malignant, and hyperplasia were available for 132 women, and were used to investigate if the distributions of VGF varied with pathology. Results: The algorithm was accurate to within {+-}1.9% in determining the volume of an irregular shaped phantom. The study mean ({+-} inter-breast SD) for the VGF was 0.172 {+-} 0.142 (range: 0.012-0.719). VGF was found to be negatively correlated with age, breast dimensions (chest-wall to nipple length, pectoralis to nipple length, and effective diameter at chest-wall), and total breast volume, and positively correlated with fibroglandular volume. Based on pathology, pairwise statistical analysis (Mann-Whitney test) indicated that at the 0.05 significance level, there was no significant difference in distributions of VGF without adjustment for age between malignant and nonmalignant breasts (p= 0.41). Pairwise comparisons of the distributions of VGF in increasing order of mammographic breast density indicated all comparisons were statistically significant (p < 0.002). Conclusions: This study used a different clinical prototype breast CT system than that in previous studies to image subjects from a different geographical region, and used a different algorithm for analysis of image data. The mean VGF estimated from this study is within the range reported in previous studies, indicating that the choice of 50% glandular weight fraction to represent an average breast for Monte Carlo-based estimation of normalized glandular dose coefficients in mammography needs revising. In the study, the distributions of VGF did not differ significantly with pathology.« less

Purpose: Dedicated breast CT prototypes used in clinical investigations utilize single circular source trajectory and cone-beam geometry with flat-panel detectors that do not satisfy data-sufficiency conditions and could lead to cone beam artifacts. Hence, this work investigated the glandular dose characteristics of a circle-plus-line trajectory that fulfills data-sufficiency conditions for image reconstruction in dedicated breast CT. Methods: Monte Carlo-based computer simulations were performed using the GEANT4 toolkit and was validated with previously reported normalized glandular dose coefficients for one prototype breast CT system. Upon validation, Monte Carlo simulations were performed to determine the normalized glandular dose coefficients as a function of x-ray source position along the line scan. The source-to-axis of rotation distance and the source-to-detector distance were maintained constant at 65 and 100 cm, respectively, in all simulations. The ratio of the normalized glandular dose coefficient at each source position along the line scan to that for the circular scan, defined as relative normalized glandular dose coefficient (RD{sub g}N), was studied by varying the diameter of the breast at the chest wall, chest-wall to nipple distance, skin thickness, x-ray beam energy, and glandular fraction of the breast. Results: The RD{sub g}N metric when stated as a function of sourcemore » position along the line scan, relative to the maximum length of line scan needed for data sufficiency, was found to be minimally dependent on breast diameter, chest-wall to nipple distance, skin thickness, glandular fraction, and x-ray photon energy. This observation facilitates easy estimation of the average glandular dose of the line scan. Polynomial fit equations for computing the RD{sub g}N and hence the average glandular dose are provided. Conclusions: For a breast CT system that acquires 300-500 projections over 2{pi} for the circular scan, the addition of a line trajectory with equal source spacing and constant x-ray beam quality (kVp and HVL) and mAs matched to the circular scan, will result in less than 0.18% increase in average glandular dose to the breast per projection along the line scan.« less

Monte Carlo simulations were used to investigate large-angle x-ray scatter at design energy of 25 keV during small field of view (9.6 cm × 5 cm) differential phase contrast imaging of the breast using Talbot-Lau interferometry. Homogenous, adipose and fibroglandular breasts of uniform thickness ranging from 2 to 8 cm encompassing the field of view were modeled. Theoretically determined transmission efficiencies of the gratings were used to validate the Monte Carlo simulations, followed by simulations to determine the x-ray scatter reaching the detector. The recorded x-ray scatter was classified into x-ray photons that underwent at least one Compton interaction (incoherent scatter) and Rayleigh interaction alone (coherent scatter) for further analysis. Monte Carlo based estimates of transmission efficiencies showed good correspondence (r2 > 0.99) with theoretical estimates. Scatter-to-primary ratio increased with increasing breast thickness, ranging from 0.11 to 0.22 for 2 to 8 cm thick adipose breasts and from 0.12 to 0.28 for 2 to 8 cm thick fibroglandular breasts. The analyzer grating reduced incoherent scatter by ~18% for 2 cm thick adipose breast and by ~35% for 8 cm thick fibroglandular breast. Coherent scatter was the dominant contributor to the total scatter. Coherent-to-incoherent scatter ratio ranged from 2.2 to 3.1 for 2 to 8 cm thick adipose breasts and from 2.7 to 3.4 for 2 to 8 cm thick fibroglandular breasts.

Objectives: In this prospective pilot study, the feasibility of non-contrast dedicated breast computed tomography (bCT) to determine primary tumor volume and monitor its changes during neoadjuvant chemotherapy (NAC) treatment was investigated. Materials and Methods: Eleven women who underwent NAC were imaged with a clinical prototype dedicated bCT system at three time points – pre-, mid-, and post-treatment. The study radiologist marked the boundary of the primary tumor from which the tumor volume was quantified. An automated algorithm was developed to quantify the primary tumor volume for comparison with radiologist's segmentation. The correlation between pre-treatment tumor volumes from bCT and MRI, and the correlation and concordance in tumor size between post-treatment bCT and pathology were determined. Results: Tumor volumes from automated and radiologist's segmentations were correlated (Pearson's r = 0.935, P < 0.001) and were not different over all time points [P = 0.808, repeated measures analysis of variance (ANOVA)]. Pre-treatment tumor volumes from MRI and bCT were correlated (r = 0.905, P < 0.001). Tumor size from post-treatment bCT was correlated with pathology (r = 0.987, P = 0.002) for invasive ductal carcinoma larger than 5 mm and the maximum difference in tumor size was 0.57 cm. The presence of biopsy clip (3 mm) limited the ability to accurately measure tumors smaller than 5 mm. All study participants were pathologically assessed to be responders, with three subjects experiencing complete pathologic response for invasive cancer and the reminder experiencing partial response. Compared to pre-treatment tumor volume, there was a statistically significant (P = 0.0003, paired t-test) reduction in tumor volume at mid-treatment observed with bCT, with an average tumor volume reduction of 47%. Conclusions: This pilot study suggests that dedicated non-contrast bCT has the potential to serve as an expedient imaging tool for monitoring tumor volume changes during NAC. Larger studies are needed in future.

To determine the x-ray photon energy dependence of the anatomic power spectrum of the breast when imaged with dedicated breast computed tomography (CT).A theoretical framework for scaling the empirically determined anatomic power spectrum at one x-ray photon energy to that at any given x-ray photon energy when imaged with dedicated breast CT was developed. Theory predicted that when the anatomic power spectrum is fitted with a power curve of the form k f(-β), where k and β are fit coefficients and f is spatial frequency, the exponent β would be independent of x-ray photon energy (E), and the amplitude k scales with the square of the difference in energy-dependent linear attenuation coefficients of fibroglandular and adipose tissues. Twenty mastectomy specimens based numerical phantoms that were previously imaged with a benchtop flat-panel cone-beam CT system were converted to 3D distribution of glandular weight fraction (f(g)) and were used to verify the theoretical findings. The 3D power spectrum was computed in terms of f(g) and after converting to linear attenuation coefficients at monoenergetic x-ray photon energies of 20-80 keV in 5 keV intervals. The 1D power spectra along the axes were extracted and fitted with a power curve of the form k f(-β). The energy dependence of k and β were analyzed.For the 20 mastectomy specimen based numerical phantoms used in the study, the exponent β was found to be in the range of 2.34-2.42, depending on the axis of measurement. Numerical simulations agreed with the theoretical predictions that for a power-law anatomic spectrum of the form k f(-β), β was independent of E and k(E) = k(1)[μ(g)(E) - μ(a)(E)](2), where k(1) is a constant, and μ(g)(E) and μ(a)(E) represent the energy-dependent linear attenuation coefficients of fibroglandular and adipose tissues, respectively.Numerical simulations confirmed the theoretical predictions that in dedicated breast CT, the spatial frequency dependence of the anatomic power spectrum will be independent of x-ray photon energy, and the amplitude of the anatomic power spectrum scales by the square of difference in linear attenuation coefficients of fibroglandular and adipose tissues.

Digital breast tomosynthesis (DBT) is a limited-angle tomographic x-ray imaging technique that reduces the effect of tissue super position observed in planar mammography. An integrated imaging platform that combines DBT with near infrared spectroscopy (NIRS) to provide co-registered anatomical and functional imaging is under development. Incorporation of anatomic priors can benefit NIRS reconstruction. In this work, we provide a segmentation and classification method to extract potential lesions, as well as adipose, fibroglandular, muscle and skin tissue in reconstructed DBT images that serve as anatomic priors during NIRS reconstruction. The method may also be adaptable for estimating tumor volume, breast glandular content, and for extracting lesion features for potential application to computer aided detection and diagnosis.

Calibration of a three-dimensional multimodal digital breast tomosynthesis (DBT) x-ray and non-fiber based near infrared spectral tomography (NIRST) system is challenging but essential for clinical studies. Phantom imaging results yielded linear contrast recovery of total hemoglobin (HbT) concentration for cylindrical inclusions of 15 mm, 10 mm and 7 mm with a 3.5% decrease in the HbT estimate for each 1 cm increase in inclusion depth. A clinical exam of a patient's breast containing both benign and malignant lesions was successfully imaged, with greater HbT was found in the malignancy relative to the benign abnormality and fibroglandular regions (11 μM vs. 9.5 μM). Tools developed improved imaging system characterization and optimization of signal quality, which will ultimately improve patient selection and subsequent clinical trial results.

Purpose: To determine the mean and range of location-averaged breast skin thickness using high-resolution dedicated breast CT for use in Monte Carlo-based estimation of normalized glandular dose coefficients. Methods: This study retrospectively analyzed image data from a clinical study investigating dedicated breast CT. An algorithm similar to that described by Huang [“The effect of skin thickness determined using breast CT on mammographic dosimetry,” Med. Phys. 35(4), 1199–1206 (2008) doi: 10.1118/1.2841938.] was used to determine the skin thickness in 137 dedicated breast CT volumes from 136 women. The location-averaged mean breast skin thickness for each breast was estimated and the study population mean and range were determined. Pathology results were available for 132 women, and were used to investigate if the distribution of location-averaged mean breast skin thickness varied with pathology. The effect of surface fitting to account for breast curvature was also studied. Results: The study mean (± interbreast SD) for breast skin thickness was 1.44 ± 0.25 mm (range: 0.87–2.34 mm), which was in excellent agreement with Huang et al. Based on pathology, pair-wise statistical analysis (Mann-Whitney test) indicated that at the 0.05 significance level, there were no significant difference in the location-averaged mean breast skin thickness distributions between the groups: benign vs malignant (p = 0.223), benign vs hyperplasia (p = 0.651), hyperplasia vs malignant (p = 0.229), and malignant vs nonmalignant (p = 0.172). Conclusions: Considering this study used a different clinical prototype system, and the study participants were from a different geographical location, the observed agreement between the two studies suggests that the choice of 1.45 mm thick skin layer comprising the epidermis and the dermis for breast dosimetry is appropriate. While some benign and malignant conditions could cause skin thickening, in this study cohort the location-averaged mean breast skin thickness distributions did not differ significantly with pathology. The study also underscored the importance of considering breast curvature in estimating breast skin thickness.

Purpose To determine the x-ray photon energy dependence of the anatomic power spectrum of the breast when imaged with dedicated breast computed tomography (CT). Methods A theoretical framework for scaling the empirically determined anatomic power spectrum at one x-ray photon energy to that at any given x-ray photon energy when imaged with dedicated breast CT was developed. Theory predicted that when the anatomic power spectrum is fitted with a power curve of the form k f(-β), where k and β are fit coefficients and f is spatial frequency, the exponent β would be independent of x-ray photon energy (E), and the amplitude k scales with the square of the difference in energy-dependent linear attenuation coefficients of fibroglandular and adipose tissues. Twenty mastectomy specimens based numerical phantoms that were previously imaged with a benchtop flat-panel cone-beam CT system were converted to 3D distribution of glandular weight fraction (f(g)) and were used to verify the theoretical findings. The 3D power spectrum was computed in terms of f(g) and after converting to linear attenuation coefficients at monoenergetic x-ray photon energies of 20-80 keV in 5 keV intervals. The 1D power spectra along the axes were extracted and fitted with a power curve of the form k f(-β). The energy dependence of k and β were analyzed. Results For the 20 mastectomy specimen based numerical phantoms used in the study, the exponent β was found to be in the range of 2.34-2.42, depending on the axis of measurement. Numerical simulations agreed with the theoretical predictions that for a power-law anatomic spectrum of the form k f(-β), β was independent of E and k(E) = k(1)[μ(g)(E) - μ(a)(E)](2), where k(1) is a constant, and μ(g)(E) and μ(a)(E) represent the energy-dependent linear attenuation coefficients of fibroglandular and adipose tissues, respectively. Conclusions Numerical simulations confirmed the theoretical predictions that in dedicated breast CT, the spatial frequency dependence of the anatomic power spectrum will be independent of x-ray photon energy, and the amplitude of the anatomic power spectrum scales by the square of difference in linear attenuation coefficients of fibroglandular and adipose tissues.