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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.

Chest radiography (CXR) plays an important role in triage, management, and monitoring of patients with COVID-19. In this work, we use a dual-layer (DL) flat-panel detector to perform artifact-free single-exposure DE CXR for COVID-19 detection. A simulation study was performed to generate DE CXRs from CT volumes of 13 patients diagnosed with COVID-19, which were compared with simulated conventional CXR by two chest radiologists. A phantom study was also conducted using an anthropomorphic chest phantom with synthetic opacifications. Improved visualization of opacities was observed for DE CXRs in both studies, indicating that the proposed DL detector could be a powerful new tool for COVID-19 diagnosis and patient management.

Multiple factors contribute to anemia in patients with Hepatitis B virus (HBV)related acute-on-chronic liver failure (ACLF); however, the mechanism is unclear. The purpose of this study was to evaluate the clinical significance of the direct antiglobulin test (DAT) in patients with HBV related ACLF.DAT was used to detect immunoglobulins and/or complement proteins on the surface of erythrocytes.We recruited 78 HBV-associated ACLF patients, 30 chronic hepatitis B(CHB)patients and 40 healthy people between October 2015 and May 2016. In HBV related ACLF patients, the hemoglobin concentration, number of erythrocytes, and hematocrit value were significantly lower, while the erythrocyte distribution width was significantly higher, compared to patients with CHB and healthy controls (HCs) (P0.001). The rates of DAT positivity in HBV related ACLF patients, CHB patients, and HCs were 62.8 %, 13.3 %, and 0%, respectively. DAT-positive ACLF patients exhibited lower Hb levels, older average age, as well as higher total bilirubin, alanine aminotransferase, and complement component 3 levels compared to DAT-negative patients.HBV related ACLF patients showed significant alterations in erythrocyte parameters, possibly reflecting disease development and severity. The high presence of erythrocyte autoantibodies suggested that immunologic clearance of erythrocytes contributed to multifactorial anemia in HBV related ACLF patients.

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.

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.

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.

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.

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.

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.

Purpose: Scatter errors are detrimental to cone-beam breast CT (CBBCT) accuracy and obscure the visibility of calcifications and soft-tissue lesions. In this work, we propose practical yet effective scatter correction for CBBCT using a library-based method and investigate its feasibility via small-group patient studies. Method: Based on a simplified breast model with varying breast sizes, we generate a scatter library using Monte-Carlo (MC) simulation. Breasts are approximated as semi-ellipsoids with homogeneous glandular/adipose tissue mixture. On each patient CBBCT projection dataset, an initial estimate of scatter distribution is selected from the pre-computed scatter library by measuring the corresponding breast size on raw projections and the glandular fraction on a first-pass CBBCT reconstruction. Then the selected scatter distribution is modified by estimating the spatial translation of the breast between MC simulation and the clinical scan. Scatter correction is finally performed by subtracting the estimated scatter from raw projections. Results: On two sets of clinical patient CBBCT data with different breast sizes, the proposed method effectively reduces cupping artifact and improves the image contrast by an average factor of 2, with an efficient processing time of 200ms per conebeam projection. Conclusion: Compared with existing scatter correction approaches on CBBCT, the proposed library-based method is clinically advantageous in that it requires no additional scans or hardware modifications. As the MC simulations are pre-computed, our method achieves a high computational efficiency on each patient dataset. The library-based method has shown great promise as a practical tool for effective scatter correction on clinical CBBCT.

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.

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide with high prevalence and lethality. Hepatitis B virus (HBV) and Hepatitis C virus (HCV) infection are the major risk factors for HCC. Long noncoding RNAs (lncRNAs) are involved in diverse biological processes, and aberrant lncRNA expression is relevant to many human diseases including HCC. Although many researches on HCC have been reported and lncRNAs roles in carcinogenesis have been highlighted recently, reports on roles of lncRNAs in HBV/HCV-induced HCC are limited. In this review, we concentrate on recent progress regarding the functional roles of lncRNAs in HCC and HBV/HCV-related HCC.

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

A cohort of 34 normal, benign and malignant breasts were imaged using a combined NIR tomography and breast tomosynthesis unit with two views and compression levels, recovering region based estimates of hemoglobin, oxygen saturation, water and lipids.

Purpose: Several commercial and non-commercial software and techniques are available for determining breast density from mammograms. However, where mandated by law the breast density information communicated to the subject/patient is based on radiologist's interpretation of breast density from mammograms. Several studies have reported on the concordance among radiologists in interpreting mammographic breast density. In this work, we investigated the accuracy of radiologist's interpretation of breast density. Methods: Volumetric breast density (VBD) determined from 134 unilateral dedicated breast CT scans from 134 subjects was considered the truth. An MQSA-qualified study radiologist with more than 20 years of breast imaging experience reviewed the DICOM “for presentation” standard 2-view mammograms of the corresponding breasts and assigned BIRADS breast density categories. For statistical analysis, the breast density categories were dichotomized in two ways; fatty vs. dense breasts where “fatty” corresponds to BIRADS breast density categories A/B, and “dense” corresponds to BIRADS breast density categories C/D, and extremely dense vs. fatty to heterogeneously dense breasts, where extremely dense corresponds to BIRADS breast density category D and BIRADS breast density categories A through C were grouped as fatty to heterogeneously dense breasts. Logistic regression models (SAS 9.3) were used to determine the association between radiologist's interpretation of breast density and VBD from breast CT, from which the area under the ROC (AUC) was determined. Results: Both logistic regression models were statistically significant (Likelihood Ratio test, p

Purpose: The image quality of dedicated cone-beam breast CT (CBBCT) is fundamentally limited by substantial x-ray 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 to suppress x-ray scatter in CBBCT images using a deterministic forward projection model. Method: We first use the 1st-pass FDK-reconstructed CBBCT images to segment fibroglandular and adipose tissue. Attenuation coefficients are assigned to the two tissues based on the x-ray spectrum used for imaging acquisition, and is forward projected to simulate scatter-free primary projections. We estimate the scatter by subtracting the simulated primary projection from the measured projection, and then the resultant scatter map is further refined by a Fourier-domain fitting algorithm after discarding untrusted scatter information. The final scatter estimate is subtracted from the measured projection for effective scatter correction. In our implementation, the proposed scatter correction takes 0.5 seconds for each projection. The method was evaluated using the overall image spatial non-uniformity (SNU) metric and the contrast-to-noise ratio (CNR) with 5 clinical datasets of BI-RADS 4/5 subjects. Results: For the 5 clinical datasets, our method reduced the SNU from 7.79% to 1.68% in coronal view and from 6.71% to 3.20% in sagittal view. The average CNR is improved by a factor of 1.38 in coronal view and 1.26 in sagittal view. Conclusion: The proposed scatter correction approach requires no additional scans or prior images and uses a deterministic model for efficient calculation. Evaluation with clinical datasets demonstrates the feasibility and stability of the method. These features are attractive for clinical CBBCT and make our method distinct from other approaches. Supported partly by NIH R21EB019597, R21CA134128 and R01CA195512.The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Purpose: Scatter contamination is detrimental to image quality in dedicated cone-beam breast CT (CBBCT), resulting in cupping artifacts and loss of contrast in reconstructed images. Such effects impede visualization of breast lesions and the quantitative accuracy. Previously, we proposed a library-based software approach to suppress scatter on CBBCT images. In this work, we quantify the efficacy and stability of this approach using datasets from 15 human subjects. Methods: A pre-computed scatter library is generated using Monte Carlo simulations for semi-ellipsoid breast models and homogeneous fibroglandular/adipose tissue mixture encompassing the range reported in literature. Projection datasets from 15 human subjects that cover 95 percentile of breast dimensions and fibroglandular volume fraction were included in the analysis. Our investigations indicate that it is sufficient to consider the breast dimensions alone and variation in fibroglandular fraction does not significantly affect the scatter-to-primary ratio. The breast diameter is measured from a first-pass reconstruction; the appropriate scatter distribution is selected from the library; and, deformed by considering the discrepancy in total projection intensity between the clinical dataset and the simulated semi-ellipsoidal breast. The deformed scatter-distribution is subtracted from the measured projections for scatter correction. Spatial non-uniformity (SNU) and contrast-to-noise ratio (CNR) were used as quantitative metrics to evaluate the results. Results: On the 15 patient cases, our method reduced the overall image spatial non-uniformity (SNU) from 7.14%±2.94% (mean ± standard deviation) to 2.47%±0.68% in coronal view and from 10.14%±4.1% to 3.02% ±1.26% in sagittal view. The average contrast to noise ratio (CNR) improved by a factor of 1.49±0.40 in coronal view and by 2.12±1.54 in sagittal view. Conclusion: We demonstrate the robustness and effectiveness of a library-based scatter correction method using patient datasets with large variability in breast dimensions and composition. The high computational efficiency and simplicity in implementation make this attractive for clinical implementation. Supported partly by NIH R21EB019597, R21CA134128 and R01CA195512.The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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.

Studies of cardiovascular system and cardiac assistance devices are key research direction in our laboratory, a challenging project requires conducting physiological experiments on animal constantly. In an operation, It is significant to detect small changes in important physiological parameters for ensuring the integrity of animal. As a result, in order to detect and acquire accurate parameter variation, a simple monitoring module is quite required as an adjunct to experiments. Directing the widely applied invasive blood pressure monitoring system, a typical block of it is introduced here. Sensor of this system applied has been used in present medical field whose superiorities embody in its continuity, high sensitivity and hygiene. A simulated experiment was established to functionally calibrate the performance of this module to ensure signals can be recorded by the data acquisition system. The result showed a high linear correlationship between pressure and output. That the serial output can be used to interface to a computer for further analysis serves a function as continuous monitor during experiment.

Miniature axial flow pump (M-AFP) is a ventricular assist device that supports the failing ventricle in advanced stage heart failure. In the past several years, we have developed two types of M-AFP aiming for children. In this paper, mechanical performance of them are tested and analyzed in order to help us find out their differences in nature. A simulative circulative apparatus is designed that can be used to quantitatively predict the mechanical characteristic parameters of the pumps and their relationship. Under the condition of load pressure invariance, we mainly test the change of blood flow with these two pumps respectively. The type A has a volume of 47ml; with external diameter of 26mm and length of 72mm. The simulative cardiac flow attains 3–4L/min under the pressure of 100mmHg, which is enough to assist the left ventricular of children. In all the two pumps, rotate speed of impeller and flow rate of blood present positive mutuality with pressure invariance. Besides, comparing with type A, the type B has smaller volume, and it is much easier for type B to increase rotate speed of the pump and comparably reduce energy consumption. Apart from the characters of smaller volume and simpler configuration, the output of miniature axial blood pump has achieved required pressure and blood flow. We still have the possibility to improve the blood pump by reducing energy consumption and increasing efficiency. The performance test and comparison in simulative circulation apparatus that is out of body is very important for improvement of blood pump. It can accelerate the development of mechanical assistant therapy and increase the cure rate of heart failure for children.

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 investigate the radiation dose reduction and the effect of weighting schemes on image quality in cone‐beam dedicated breast CT acquired with coronal truncated projections that is similar in concept as extended field‐of‐view imaging with laterally‐shifted flat‐panel detectors. Methods: Three pre‐weighting schemes were implemented in conjunction with filtered backprojection (FBP) reconstruction to study the effect of coronal truncation in dedicated breast CT. If the fan‐angle of the non‐truncated projections is represented as 2f (24‐degrees), then coronal truncations corresponding to f+0.25, f+1.5, and f+2.7‐degrees were investigated. Monte Carlo simulations using the GEANT4 toolkit were used to determine the radiation dose reduction at the aforementioned truncations. Projection images of a numerical phantom with dimensions representative of an average pendant breast containing six spherical signal objects in a homogenous background were reconstructed without and with truncation. Cone‐beam projections from a diagnostic dedicated breast CT exam acquired with fan‐angle of 2f were truncated at the aforementioned fan‐angles and reconstructed. Phantom and clinical images were analyzed for artifacts and the visibility of signal features. Results: For an average 14‐cm diameter, 15% fibroglandular breast, the estimated dose reduction at fan‐angles of f+0.25, f+1.5, and f+2.7‐degrees were 47%, 34% and 21%, respectively. The severity of artifacts increased with decreasing fan‐angle. The choice of weighting scheme does not appear to have a substantial effect on mitigating artifacts. At fan‐angles of f+1.5 and above, shading artifacts were subtle and could not be easily discerned. The signal objects in the phantom and the microcalcification in the clinical images were discernible. For 10, 14 and 18 cm diameter, 15% fibroglandular breasts, the radiation dose reduction at fan‐angle of f+1.5‐degrees were 27%, 34% and 37%, respectively. Conclusion: There exists a potential to reduce radiation dose by approximately 30% from cone‐beam dedicated breast CT acquired with coronal truncated projections. Supported in part by the National Institutes of Health (NIH) grants R01 CA128906 and R21 CA134128. The contents are solely the responsibility of the authors and do not represent the official views of the NIH or the NCI.

Purpose: To measure the volumetric breast density (VBD) from digital breast tomosynthesis (DBT) reconstructions and compare with estimates from mammography. Methods: A kernel-based fuzzy c-means algorithm developed to segment DBT reconstructed slices to provide anatomic priors for near-infrared spectroscopy (NIRS) in a multimodality NIRS/DBT clinical-prototype imaging system was used to quantitate VBD. The VBD was determined from 17 DBT reconstructions of 11 breasts from 9 subjects (6 subjects—unilateral 2-view, 1 subject—unilateral craniocaudal (CC) view, 2 subjects—bilateral CC view) who underwent multimodality NIRS/DBT imaging. VBD from mammography (Quantra, Hologic Inc.) matched for subject, breast laterality and view was used for comparison. To account for differences in compressed breast thickness (T) between the modalities, the metric normalized VBD (nVBD = VBD/T) was considered. Results: All data satisfied normality assumption (Shapiro-Wilks, p>0.06). Pearson's correlation (r) and paired t-tests were used for analysis. The normalized VBD (nVBD) was statistically correlated (r=0.66, p

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.