Line-based iterative geometric calibration method for a tomosynthesis system

BACKGROUND

A next generation tomosynthesis (NGT) system, capable of two-dimensional source motion, detector motion in the perpendicular direction, and magnification tomosynthesis, was constructed to investigate different acquisition geometries. Existing position-based geometric calibration methods proved ineffective when applied to the NGT geometries.

PURPOSE

A line-based iterative calibration method is developed to perform accurate geometric calibration for the NGT system.

METHODS

The proposed method calculates the system geometry through virtual line segments created by pairs of fiducials within a calibration phantom, by minimizing the error between the line equations computed from the true and estimated fiducial projection pairs. It further attempts to correct the 3D fiducial locations based on the initial geometric calibration. The method's performance was assessed via simulation and experimental setups with four distinct NGT geometries: X, T, XZ, and TZ. The X geometry resembles a conventional DBT acquisition along the chest wall. The T geometry forms a "T"-shaped source path in mediolateral (ML) and posteroanterior (PA) directions. A descending detector motion is added to both X and T geometries to form the XZ and TZ geometries, respectively. Simulation studies were conducted to assess the robustness of the method to geometric perturbations and inaccuracies in fiducial locations. Experimental studies were performed to assess the impact of phantom magnification and the performance of the proposed method for various geometries, compared to the traditional position-based method. Star patterns were evaluated for both qualitative and quantitative analyses; the Fourier spectral distortions (FSDs) graphs and the contrast transfer function (CTF) were extracted. The limit of spatial resolution (LSR) was measured at 5% modulation of the CTF.

RESULTS

The proposed method presented is highly robust to geometric perturbation and fiducial inaccuracies. After the line-based iterative method, the mean distance between the true and estimated fiducial projections was [X, T, XZ, TZ]: [0.01, 0.01, 0.02, 0.01] mm. The impact of phantom magnification was observed; a contact-mode acquisition of a calibration phantom successfully provided an accurate geometry for 1.85× magnification images of a star pattern, with the X geometry. The FSD graphs for the contact-mode T geometry acquisition presented evidence of super-resolution, with the LSR of [0°-quadrant: 8.57, 90°-quadrant: 8.47] lp/mm. Finally, a contact-mode XZ geometry acquisition and a 1.50× magnification TZ geometry acquisition were reconstructed with three calibration methods-position-based, line-based, and iterative line-based. As more advanced methods are applied, the CTF becomes more isotropic, the FSD graphs demonstrate less spectral leakage as super-resolution is achieved, and the degree of blurring artifacts reduces significantly.

CONCLUSIONS

This study introduces a robust calibration method tailored to the unique requirements of advanced tomosynthesis systems. By employing virtual line segments and iterative techniques, we ensure accurate geometric calibration while mitigating the limitations posed by the complex acquisition geometries of the NGT system. Our method's ability to handle various NGT configurations and its tolerance to fiducial misalignment make it a superior choice compared to traditional calibration techniques.

Impact of super-resolution and image acquisition on the detection of calcifications in digital breast tomosynthesis

OBJECTIVES

A virtual clinical trial (VCT) method is proposed to determine the limit of calcification detection in tomosynthesis.

METHODS

Breast anatomy, focal findings, image acquisition, and interpretation (n = 14 readers) were simulated using screening data (n = 660 patients). Calcifications (0.2-0.4 mm3) were inserted into virtual breast phantoms. Digital breast tomosynthesis (DBT) acquisitions were simulated assuming various acquisition geometries: source motion (continuous and step-and-shoot), detector element size (140 and 70 µm), and reconstructed voxel size (35-140 µm). VCT results were estimated using multiple-reader multiple-case analyses and d' statistics. Signal-to-noise (SNR) analyses were also performed using BR3D phantoms.

RESULTS

Source motion and reconstructed voxel size demonstrated significant changes in the performance of imaging systems. Acquisition geometries that use 70 µm reconstruction voxel size and step-and-shoot motion significantly improved calcification detection. Comparing 70 with 100 µm reconstructed voxel size for step-and-shoot, the ΔAUC was 0.0558 (0.0647) and d' ratio was 1.27 (1.29) for 140 µm (70 µm) detector element size. Comparing step-and-shoot with a continuous motion for a 70 µm reconstructed voxel size, the ΔAUC was 0.0863 (0.0434) and the d' ratio was 1.40 (1.19) for 140 µm (70 µm) detector element. Small detector element sizes (e.g., 70 µm) did not significantly improve detection. The SNR results with the BR3D phantom show that calcification detection is dependent upon reconstructed voxel size and detector element size, supporting VCT results with comparable agreement (ratios: d' = 1.16 ± 0.11, SNR = 1.34 ± 0.13).

CONCLUSION

DBT acquisition geometries that use super-resolution (smaller reconstructed voxels than the detector element size) combined with step-and-shoot motion have the potential to improve the detection of calcifications.

CLINICAL RELEVANCE

Calcifications may not always be discernable in tomosynthesis because of differences in acquisition and reconstruction methods. VCTs can identify strategies to optimize acquisition and reconstruction parameters for calcification detection in tomosynthesis, most notably through super-resolution in the reconstruction.

KEY POINTS

• Super-resolution improves calcification detection and SNR in tomosynthesis; specifically, with the use of smaller reconstruction voxels. • Calcification detection using step-and-shoot motion is superior to that using continuous tube motion. • A detector element size of 70 µm does not provide better detection than 140 µm for small calcifications at the threshold of detectability.

Non-Isocentric Geometry for Next-Generation Tomosynthesis With Super-Resolution

Our lab at the University of Pennsylvania (UPenn) is investigating novel designs for digital breast tomosynthesis. We built a next-generation tomosynthesis system with a non-isocentric geometry (superior-to-inferior detector motion). This paper examines four metrics of image quality affected by this design. First, aliasing was analyzed in reconstructions prepared with smaller pixelation than the detector. Aliasing was assessed with a theoretical model of r -factor, a metric calculating amplitudes of alias signal relative to input signal in the Fourier transform of the reconstruction of a sinusoidal object. Aliasing was also assessed experimentally with a bar pattern (illustrating spatial variations in aliasing) and 360°-star pattern (illustrating directional anisotropies in aliasing). Second, the point spread function (PSF) was modeled in the direction perpendicular to the detector to assess out-of-plane blurring. Third, power spectra were analyzed in an anthropomorphic phantom developed by UPenn and manufactured by Computerized Imaging Reference Systems (CIRS), Inc. (Norfolk, VA). Finally, calcifications were analyzed in the CIRS Model 020 BR3D Breast Imaging Phantom in terms of signal-to-noise ratio (SNR); i.e., mean calcification signal relative to background-tissue noise. Image quality was generally superior in the non-isocentric geometry: Aliasing artifacts were suppressed in both theoretical and experimental reconstructions prepared with smaller pixelation than the detector. PSF width was also reduced at most positions. Anatomic noise was reduced. Finally, SNR in calcification detection was improved. (A potential trade-off of smaller-pixel reconstructions was reduced SNR; however, SNR was still improved by the detector-motion acquisition.) In conclusion, the non-isocentric geometry improved image quality in several ways.

Impact of Tomosynthesis Acquisition on 3D Segmentations of Breast Outline and Adipose/Dense Tissue with AI: A Simulation-Based Study

Digital breast tomosynthesis (DBT) reconstructions introduce out-of-plane artifacts and false-tissue boundaries impacting the dense/adipose and breast outline (convex hull) segmentations. A virtual clinical trial method was proposed to segment both the breast tissues and the breast outline in DBT reconstructions. The DBT images of a representative population were simulated using three acquisition geometries: a left-right scan (conventional, I), a two-directional scan in the shape of a "T" (II), and an extra-wide range (XWR, III) left-right scan at a six-times higher dose than I. The nnU-Net was modified including two losses for segmentation: (1) tissues and (2) breast outline. The impact of loss (1) and the combination of loss (1) and (2) was evaluated using models trained with data simulating geometry I. The impact of the geometry was evaluated using the combined loss (1&2). The loss (1&2) improved the convex hull estimates, resolving 22.2% of the false classification of air voxels. Geometry II was superior to I and III, resolving 99.1% and 96.8% of the false classification of air voxels. Geometry III (Dice = (0.98, 0.94)) was superior to I (0.92, 0.78) and II (0.93, 0.74) for the tissue segmentation (adipose, dense, respectively). Thus, the loss (1&2) provided better segmentation, and geometries T and XWR improved the dense/adipose and breast outline segmentations relative to the conventional scan.

Multiclass Segmentation of Breast Tissue and Suspicious Findings: A Simulation-Based Study for the Development of Self-Steering Tomosynthesis

In breast tomosynthesis, multiple low-dose projections are acquired in a single scanning direction over a limited angular range to produce cross-sectional planes through the breast for three-dimensional imaging interpretation. We built a next-generation tomosynthesis system capable of multidirectional source motion with the intent to customize scanning motions around "suspicious findings". Customized acquisitions can improve the image quality in areas that require increased scrutiny, such as breast cancers, architectural distortions, and dense clusters. In this paper, virtual clinical trial techniques were used to analyze whether a finding or area at high risk of masking cancers can be detected in a single low-dose projection and thus be used for motion planning. This represents a step towards customizing the subsequent low-dose projection acquisitions autonomously, guided by the first low-dose projection; we call this technique "self-steering tomosynthesis." A U-Net was used to classify the low-dose projections into "risk classes" in simulated breasts with soft-tissue lesions; class probabilities were modified using post hoc Dirichlet calibration (DC). DC improved the multiclass segmentation (Dice = 0.43 vs. 0.28 before DC) and significantly reduced false positives (FPs) from the class of the highest risk of masking (sensitivity = 81.3% at 2 FPs per image vs. 76.0%). This simulation-based study demonstrated the feasibility of identifying suspicious areas using a single low-dose projection for self-steering tomosynthesis.

Spatial dependency of multiplanar reconstruction in digital breast tomosynthesis

Tomosynthesis acquires projections over a limited angular range, resulting in anisotropic sampling in the Fourier domain. The volume of the sampled space is therefore spatially dependent; different Fourier components are sampled for the same object, depending upon where the object is located relative to the system origin. A next-generation tomosynthesis (NGT) system was developed at the University of Pennsylvania to increase the spatial isotropy in DBT, by incorporating additional system motions. In this work, we investigate the spatial dependency of image quality in tomosynthesis and compare conventional and NGT tomosynthesis in terms of multiplanar reconstruction (MPR). Two test objects, a high-frequency star pattern and a low-frequency octagon phantom, were placed throughout the detector field of view at various obliquities to analyze the anisotropic nature of tomosynthesis. Reconstructions of the star pattern were analyzed both qualitatively and quantitatively using the Fourier distortion metric (FSD). Reconstructions of the octagon phantom were analyzed qualitatively. In a separate experiment, a container filled with water and acrylic beads of various diameters were imaged at various locations to simulate low-contrast objects mimicking breast tissue. We show that the spatial dependency of MPR is unique to the tilt angle, orientation, and frequency of the input. The NGT geometry benefitted the visualization of objects by reducing the out-of-plane artifacts in MPR.

Renally Excretable Silver Telluride Nanoparticles as Contrast Agents for X-ray Imaging

The use of nanoparticles in the biomedical field has gained much attention due to their applications in biomedical imaging, drug delivery, and therapeutics. Silver telluride nanoparticles (Ag₂Te NPs) have been recently shown to be highly effective computed tomography (CT) and dual-energy mammography contrast agents with good stability and biocompatibility, as well as to have potential for many other biomedical purposes. Despite their numerous advantageous properties for diagnosis and treatment of disease, the clinical translation of Ag₂Te NPs is dependent on achieving high levels of excretion, a limitation for many nanoparticle types. In this work, we have synthesized and characterized a library of Ag₂Te NPs and identified conditions that led to 3 nm core size and were renally excretable. We found that these nanoparticles have good biocompatibility, strong X-ray contrast generation, and rapid renal clearance. Our CT data suggest that renal elimination of nanoparticles occurred within 2 h of administration. Moreover, biodistribution data indicate that 93% of the injected dose (%ID) has been excreted from the main organs in 24 h, 95% ID in 7 days, and 97% ID in 28 days with no signs of acute toxicity in the tissues studied under histological analysis. To our knowledge, this renal clearance is the best reported for Ag₂Te NP, while being comparable to the highest renal clearance reported for any type of nanoparticle. Together, the results herein presented suggest the use of GSH-Ag₂Te NPs as an X-ray contrast agent with the potential to be clinically translated in the future.

MaasPenn Radiomics Reproducibility Score: A Novel Quantitative Measure for Evaluating the Reproducibility of CT-Based Handcrafted Radiomic Features

Simple Summary

The reproducibility of handcrafted radiomic features (HRFs) has been reported to be affected by variations in imaging acquisition and reconstruction parameters. However, to date, these effects have not been understood or quantified. In this study, we analyzed a significantly large number of scenarios in an effort to quantify the effects of variations on the reproducibility of HRFs. In addition, we assessed the performance of ComBat harmonization in each of the 31,375 investigated scenarios. We developed a novel score that can be considered the first attempt to objectively assess the number of reproducible HRFs in different scenario. Following further validation, the score could be used to decide on the inclusion of data acquired differently, as well as the assessment of the generalizability of developed radiomic signatures.

Abstract

The reproducibility of handcrafted radiomic features (HRFs) has been reported to be affected by variations in imaging parameters, which significantly affect the generalizability of developed signatures and translation to clinical practice. However, the collective effect of the variations in imaging parameters on the reproducibility of HRFs remains unclear, with no objective measure to assess it in the absence of reproducibility analysis. We assessed these effects of variations in a large number of scenarios and developed the first quantitative score to assess the reproducibility of CT-based HRFs without the need for phantom or reproducibility studies. We further assessed the potential of image resampling and ComBat harmonization for removing these effects. Our findings suggest a need for radiomics-specific harmonization methods. Our developed score should be considered as a first attempt to introduce comprehensive metrics to quantify the reproducibility of CT-based handcrafted radiomic features. More research is warranted to demonstrate its validity in clinical contexts and to further improve it, possibly by the incorporation of more realistic situations, which better reflect real patients’ situations.

Computer Simulations of Case Difficulty in Digital Breast Tomosynthesis Using Virtual Clinical Trials

PURPOSE

Virtual clinical trials (VCTs) require computer simulations of representative patients and images to evaluate and compare changes in performance of imaging technologies. The simulated images are usually interpreted by model observers whose performance depends upon the selection of imaging cases used in training evaluation models. This work proposes an efficient method to simulate and calibrate soft tissue lesions, which matches the detectability threshold of virtual and human readings.

METHODS

Anthropomorphic breast phantoms were used to evaluate the simulation of four mass models (I-IV) that vary in shape and composition of soft tissue. Ellipsoidal (I) and spiculated (II-IV) masses were simulated using composite voxels with partial volumes. Digital breast tomosynthesis projections and reconstructions of a clinical system were simulated. Channelized Hotelling observers (CHOs) were evaluated using reconstructed slices of masses that varied in shape, composition, and density of surrounded tissue. The detectability threshold of each mass model was evaluated using receiver operating characteristic (ROC) curves calculated with the CHO's scores.

RESULTS

The area under the curve (AUC) of each calibrated mass model were within the 95% confidence interval (mean AUC [95% CI]) reported in a previous reader study (0.93 [0.89, 0.97]). The mean AUC [95% CI] obtained were 0.94 [0.93, 0.96], 0.92 [0.90, 0.93], 0.92 [0.90, 0.94], 0.93 [0.92, 0.95] for models I to IV, respectively. The mean AUC results varied substantially as a function of shape, composition, and density of surrounded tissue.

CONCLUSIONS

For successful VCTs, lesions composed of soft tissue should be calibrated to simulate imaging cases that match the case difficulty predicted by human readers. Lesion composition, shape, and size are parameters that should be carefully selected to calibrate VCTs. This article is protected by copyright. All rights reserved.

Achieving Isotropic Super-Resolution with a Non-Isocentric Acquisition Geometry in a Next-Generation Tomosynthesis System

We have constructed a prototype next-generation tomosynthesis (NGT) system that supports a non-isocentric acquisition geometry for digital breast tomosynthesis (DBT). In this geometry, the detector gradually descends in the superior-to-inferior direction. The aim of this work is to demonstrate that this geometry offers isotropic super-resolution (SR), unlike clinical DBT systems which are characterized by anisotropies in SR. To this end, a theoretical model of a sinusoidal test object was developed with frequency exceeding the alias frequency of the detector. We simulated two geometries: (1) a conventional geometry with a stationary detector, and (2) a non-isocentric geometry. The input frequency was varied over the full 360° range of angles in the plane of the object. To investigate whether SR was achieved, we calculated the Fourier transform of the reconstruction. The amplitude of the tallest peak below the alias frequency was measured relative to the peak at the input frequency. This ratio (termed the r-factor) should approach zero to achieve high-quality SR. In the conventional geometry, the r-factor was minimized (approaching zero) if the orientation of the frequency was parallel with the source motion, yet exceeded unity (prohibiting SR) in the orientation perpendicular to the source motion. However, in the non-isocentric geometry, the r-factor was minimized (approaching zero) for all orientations of the frequency, meaning SR was achieved isotropically. In summary, isotropic SR in DBT can be achieved using the non-isocentric acquisition geometry supported by the NGT system.

Effect of Nanoparticle Synthetic Conditions on Ligand Coating Integrity and Subsequent Nano-Biointeractions

Most current nanoparticle formulations have relatively low clearance efficiency, which may hamper their likelihood for clinical translation. Herein, we sought to compare the clearance and cellular distribution profiles between sub-5 nm, renally-excretable silver sulfide nanoparticles (Ag₂S-NPs) synthesized via either a bulk, high temperature, or a microfluidic, room temperature approach. We found that the thermolysis approach led to significant ligand degradation, but the surface coating shell was unaffected by the microfluidic synthesis. We demonstrated that the clearance was improved for Ag₂S-NPs with intact ligands, with less uptake in the liver. Moreover, differential distribution in hepatic cells was observed, where Ag₂S-NPs with degraded coatings tend to accumulate in Kupffer cells and those with intact coatings are more frequently found in hepatocytes. Therefore, understanding the impact of synthetic processes on ligand integrity and subsequent nano-biointeractions will aid in designing nanoparticle platforms with enhanced clearance and desired distribution profiles.

Silver chalcogenide nanoparticles: a review of their biomedical applications

Silver chalcogenide (Ag2X, where X = S, Se, or Te) nanoparticles have been extensively investigated for their applications in electronics but have only recently been explored for biomedical applications. In the past 10 years, Ag2X, primarily silver sulfides at first, have become of great importance as quantum dots, since they not only possess excellent deep tissue imaging properties in the near-infrared regions I and II, but also have low toxicities. Their appealing properties have led to numerous recent developments of Ag2X for biomedical applications. Furthermore, Ag2X have been discovered in the past 2-3 years to be potent X-ray contrast agents, adding to the numerous biomedical uses of these nanoparticles. In this review, we discuss the most recent advances in silver chalcogenide nanoparticle use in areas such as bio-imaging, theranostics, and biosensors. Moreover, we examine the advances in synthetic approaches for these nanoparticles, which include aqueous and organic syntheses routes. Finally, we discuss the advantages and current limitations in the use of silver chalcogenides for different biomedical applications and their potential for advancement and expansions in use.

Computational Breast Anatomy Simulation Using Multi-Scale Perlin Noise

Virtual clinical trials (VCTs) of medical imaging require realistic models of human anatomy. For VCTs in breast imaging, a multi-scale Perlin noise method is proposed to simulate anatomical structures of breast tissue in the context of an ongoing breast phantom development effort. Four Perlin noise distributions were used to replace voxels representing the tissue compartments and Cooper's ligaments in the breast phantoms. Digital mammography and tomosynthesis projections were simulated using a clinical DBT system configuration. Power-spectrum analyses and higher-order statistics properties using Laplacian fractional entropy (LFE) of the parenchymal texture are presented. These objective measures were calculated in phantom and patient images using a sample of 140 clinical mammograms and 500 phantom images. Power-law exponents were calculated using the slope of the curve fitted in the low frequency [0.1, 1.0] mm-1 region of the power spectrum. The results show that the images simulated with our prior and proposed Perlin method have similar power-law spectra when compared with clinical mammograms. The power-law exponents calculated are -3.10, -3.55, and -3.46, for the log-power spectra of patient, prior phantom and proposed phantom images, respectively. The results also indicate an improved agreement between the mean LFE estimates of Perlin-noise based phantoms and patients than our prior phantoms and patients. Thus, the proposed method improved the simulation of anatomic noise substantially compared to our prior method, showing close agreement with breast parenchyma measures.

Incorporating Robustness to Imaging Physics into Radiomic Feature Selection for Breast Cancer Risk Estimation

Digital mammography has seen an explosion in the number of radiomic features used for risk-assessment modeling. However, having more features is not necessarily beneficial, as some features may be overly sensitive to imaging physics (contrast, noise, and image sharpness). To measure the effects of imaging physics, we analyzed the feature variation across imaging acquisition settings (kV, mAs) using an anthropomorphic phantom. We also analyzed the intra-woman variation (IWV), a measure of how much a feature varies between breasts with similar parenchymal patterns-a woman's left and right breasts. From 341 features, we identified "robust" features that minimized the effects of imaging physics and IWV. We also investigated whether robust features offered better case-control classification in an independent data set of 575 images, all with an overall BI-RADS® assessment of 1 (negative) or 2 (benign); 115 images (cases) were of women who developed cancer at least one year after that screening image, matched to 460 controls. We modeled cancer occurrence via logistic regression, using cross-validated area under the receiver-operating-characteristic curve (AUC) to measure model performance. Models using features from the most-robust quartile of features yielded an AUC = 0.59, versus 0.54 for the least-robust, with p < 0.005 for the difference among the quartiles.

VIRTUAL CLINICAL TRIALS IN MEDICAL IMAGING SYSTEM EVALUATION AND OPTIMISATION

Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs are based on computer simulations of human anatomy, imaging modalities and image interpretation. OpenVCT is an open-source framework for conducting VCTs of medical imaging, with a particular focus on breast imaging. The aim of this paper was to evaluate the OpenVCT framework in two tasks involving digital breast tomosynthesis (DBT). First, VCTs were used to perform a detailed comparison of virtual and clinical reading studies for the detection of lesions in digital mammography and DBT. Then, the framework was expanded to include mechanical imaging (MI) and was used to optimise the novel combination of simultaneous DBT and MI. The first experiments showed close agreement between the clinical and the virtual study, confirming that VCTs can predict changes in performance of DBT accurately. Work in simultaneous DBT and MI system has demonstrated that the system can be optimised in terms of the DBT image quality. We are currently working to expand the OpenVCT software to simulate MI acquisition more accurately and to include models of tumour growth. Based on our experience to date, we envision a future in which VCTs have an important role in medical imaging, including support for more imaging modalities, use with rare diseases and a role in training and testing artificial intelligence (AI) systems.

Fully Automated Volumetric Breast Density Estimation from Digital Breast Tomosynthesis

Background While digital breast tomosynthesis (DBT) is rapidly replacing digital mammography (DM) in breast cancer screening, the potential of DBT density measures for breast cancer risk assessment remains largely unexplored. Purpose To compare associations of breast density estimates from DBT and DM with breast cancer. Materials and Methods This retrospective case-control study used contralateral DM/DBT studies from women with unilateral breast cancer and age- and ethnicity-matched controls (September 19, 2011-January 6, 2015). Volumetric percent density (VPD%) was estimated from DBT using previously validated software. For comparison, the publicly available Laboratory for Individualized Breast Radiodensity Assessment software package, or LIBRA, was used to estimate area-based percent density (APD%) from raw and processed DM images. The commercial Quantra and Volpara software packages were applied to raw DM images to estimate VPD% with use of physics-based models. Density measures were compared by using Spearman correlation coefficients (r), and conditional logistic regression was performed to examine density associations (odds ratios [OR]) with breast cancer, adjusting for age and body mass index. Results A total of 132 women diagnosed with breast cancer (mean age ± standard deviation [SD], 60 years ± 11) and 528 controls (mean age, 60 years ± 11) were included. Moderate correlations between DBT and DM density measures (r = 0.32-0.75; all P < .001) were observed. Volumetric density estimates calculated from DBT (OR, 2.3 [95% CI: 1.6, 3.4] per SD for VPD%_DBT) were more strongly associated with breast cancer than DM-derived density for both APD% (OR, 1.3 [95% CI: 0.9, 1.9] [P < .001] and 1.7 [95% CI: 1.2, 2.3] [P = .004] per SD for LIBRA raw and processed data, respectively) and VPD% (OR, 1.6 [95% CI: 1.1, 2.4] [P = .01] and 1.7 [95% CI: 1.2, 2.6] [P = .04] per SD for Volpara and Quantra, respectively). Conclusion The associations between quantitative breast density estimates and breast cancer risk are stronger for digital breast tomosynthesis compared with digital mammography. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Yaffe in this issue.

Quantitative analysis of speckle-based X-ray dark-field imaging using numerical wave-optics simulations

The dark-field signal measures the small-angle scattering strength and provides complementary diagnostic information. This is of particular interest for lung imaging due to the pronounced small-angle scatter from the alveolar microstructure. However, most dark-field imaging techniques are relatively complex, dose-inefficient, and require sophisticated optics and highly coherent X-ray sources. Speckle-based imaging promises to overcome these limitations due to its simple and versatile setup, only requiring the addition of a random phase modulator to conventional X-ray equipment. We investigated quantitatively the influence of sample structure, setup geometry, and source energy on the dark-field signal in speckle-based X-ray imaging with wave-optics simulations for ensembles of micro-spheres. We show that the dark-field signal is accurately predicted via a model originally derived for grating interferometry when using the mean frequency of the speckle pattern power spectral density as the characteristic speckle size. The size directly reflects the correlation length of the diffuser surface and did not change with energy or propagation distance within the near-field. The dark-field signal had a distinct dependence on sample structure and setup geometry but was also affected by beam hardening-induced modifications of the visibility spectrum. This study quantitatively demonstrates the behavior of the dark-field signal in speckle-based X-ray imaging.

The application of a workflow integrating the variable reproducibility and harmonizability of radiomic features on a phantom dataset

Radiomics–the high throughput extraction of quantitative features from medical images and their correlation with clinical and biological endpoints- is the subject of active and extensive research. Although the field shows promise, the generalizability of radiomic signatures is affected significantly by differences in scan acquisition and reconstruction settings. Previous studies reported on the sensitivity of radiomic features (RFs) to test-retest variability, inter-observer segmentation variability, and intra-scanner variability. A framework involving robust radiomics analysis and the application of a post-reconstruction feature harmonization method using ComBat was recently proposed to address these challenges. In this study, we investigated the reproducibility of RFs across different scanners and scanning parameters using this framework. We analysed thirteen scans of a ten-layer phantom that were acquired differently. Each layer was subdivided into sixteen regions of interest (ROIs), and the scans were compared in a pairwise manner, resulting in seventy-eight different scenarios. Ninety-one RFs were extracted from each ROI. As hypothesized, we demonstrate that the reproducibility of a given RF is not a constant but is dependent on the heterogeneity found in the data under analysis. The number (%) of reproducible RFs varied across the pairwise scenarios investigated, having a wide range between 8 (8.8%) and 78 (85.7%) RFs. Furthermore, in contrast to what has been previously reported, and as hypothesized in the robust radiomics analysis framework, our results demonstrate that ComBat cannot be applied to all RFs but rather on a percentage of those–the “ComBatable” RFs–which differed depending on the data being harmonized. The number (%) of reproducible RFs following ComBat harmonization varied across the pairwise scenarios investigated, ranging from 14 (15.4%) to 80 (87.9%) RFs, and was found to depend on the heterogeneity in the data. We conclude that the standardization of image acquisition protocols remains the cornerstone for improving the reproducibility of RFs, and the generalizability of the signatures developed. Our proposed approach helps identify the reproducible RFs across different datasets.

The Effects of In-Plane Spatial Resolution on CT-Based Radiomic Features' Stability with and without ComBat Harmonization

Simple Summary

Handcrafted radiomic features (HRFs) are quantitative features extracted from medical images, and they are mined for associations with different clinical endpoints. While many studies reported on the potential of HRFs to unravel clinical endpoints, the sensitivity of HRFs to variations in scanning parameters is affecting the inclusion of radiomic signatures in clinical decision-making. In this study, we investigated the effects of variations in the in-plane resolution of scans, while all other scanning parameters were fixed. Moreover, we investigated the effects of ten different image resampling methods and ComBat harmonization on the reproducibility of HRFs. Our results show that the majority of HRFs are significantly and variably affected by the differences in in-plane resolution. The majority of image resampling methods resulted in a higher number of reproducible HRFs compared to ComBat harmonization. Our developed framework guides identifying the reproducible and harmonizable HRFs in different scenarios.

Abstract

While handcrafted radiomic features (HRFs) have shown promise in the field of personalized medicine, many hurdles hinder its incorporation into clinical practice, including but not limited to their sensitivity to differences in acquisition and reconstruction parameters. In this study, we evaluated the effects of differences in in-plane spatial resolution (IPR) on HRFs, using a phantom dataset (n = 14) acquired on two scanner models. Furthermore, we assessed the effects of interpolation methods (IMs), the choice of a new unified in-plane resolution (NUIR), and ComBat harmonization on the reproducibility of HRFs. The reproducibility of HRFs was significantly affected by variations in IPR, with pairwise concordant HRFs, as measured by the concordance correlation coefficient (CCC), ranging from 42% to 95%. The number of concordant HRFs (CCC > 0.9) after resampling varied depending on (i) the scanner model, (ii) the IM, and (iii) the NUIR. The number of concordant HRFs after ComBat harmonization depended on the variations between the batches harmonized. The majority of IMs resulted in a higher number of concordant HRFs compared to ComBat harmonization, and the combination of IMs and ComBat harmonization did not yield a significant benefit. Our developed framework can be used to assess the reproducibility and harmonizability of RFs.

Under-exploration of Three-Dimensional Images Leads to Search Errors for Small Salient Targets

Advances in 3D imaging technology are transforming how radiologists search for cancer1,2 and how security officers scrutinize baggage for dangerous objects.3 These new 3D technologies often improve search over 2D images4,5 but vastly increase the image data. Here, we investigate 3D search for targets of various sizes in filtered noise and digital breast phantoms. For a Bayesian ideal observer optimally processing the filtered noise and a convolutional neural network processing the digital breast phantoms, search with 3D image stacks increases target information and improves accuracy over search with 2D images. In contrast, 3D search by humans leads to high miss rates for small targets easily detected in 2D search, but not for larger targets more visible in the visual periphery. Analyses of human eye movements, perceptual judgments, and a computational model with a foveated visual system suggest that human errors can be explained by interaction among a target's peripheral visibility, eye movement under-exploration of the 3D images, and a perceived overestimation of the explored area. Instructing observers to extend the search reduces 75% of the small target misses without increasing false positives. Results with twelve radiologists confirm that even medical professionals reading realistic breast phantoms have high miss rates for small targets in 3D search. Thus, under-exploration represents a fundamental limitation to the efficacy with which humans search in 3D image stacks and miss targets with these prevalent image technologies.

Development and Evaluation of the Fourier Spectral Distortion Metric

A spatial resolution metric is presented for tomosynthesis. The Fourier spectral distortion metric (FSD) was developed to evaluate specific resolution properties of different imaging techniques for digital tomosynthesis using a star pattern image to plot modulation in the frequency domain. The FSD samples the spatial resolution of a star-pattern image tangentially over an acute angle and for a range of spatial frequencies in a 2D image or 3D image reconstruction slice. The FSD graph portrays all frequencies present in a star pattern quadrant. In addition to the fundamental input frequency of the star pattern, the FSD graph shows spectral leakage, square wave harmonics, and residual noise. The contrast transfer function (CTF) is obtained using the FSD graph. The CTF is analogous to the modulation transfer function (MTF), but it is not normalized to unity at zero spatial frequency. Unlike the MTF, this metric separates the fundamental input-frequency from the other signals in the Fourier domain. This metric helps determine optimal image reconstruction parameters, the in-plane limit of spatial resolution with respect to aliased signals, and a threshold criterion for an image to support super resolution and reduce aliasing artifacts. Various sampling parameters were evaluated to optimize this metric and ascertain measurement accuracy. The FSD adequately compares resolution properties of 2D images and 3D image reconstruction slices for various x ray imaging modes without suppressing aliased signals.

Development of Magnification Tomosynthesis for Superior Resolution in Diagnostic Mammography

Our previous work showed that digital breast tomosynthesis (DBT) supports super-resolution (SR). Clinical systems are not yet designed to optimize SR; this can be demonstrated with a high-frequency line-resolution pattern. SR is achieved if frequencies are oriented laterally, but not if frequencies are oriented in the perpendicular direction; i.e., the posteroanterior (PA) direction. We are developing a next-generation tomosynthesis (NGT) prototype with new trajectories for the x-ray source. This system is being designed to optimize SR not just for screening, but also for diagnostic mammography; specifically, for magnification DBT (M-DBT). SR is not achieved clinically in magnification mammography, since the acquisition is 2D. The aim of this study is to investigate SR in M-DBT, and analyze how anisotropies differ from screening DBT (S-DBT). We have a theoretical model of a high-frequency sinusoidal test object. First, a conventional scanning motion (directed laterally) was simulated. In the PA direction, SR was not achieved in either S-DBT or M-DBT. Next, the scanning motion was angled relative to the lateral direction. This motion introduces submillimeter offsets in source positions in the PA direction. Theoretical modeling demonstrated that SR was achieved in M-DBT, but not in S-DBT, in the PA direction. This work shows that, with the use of magnification, anisotropies in SR are more sensitive to small offsets in the source motion, leading to insights into how to design M-DBT systems.

Silver telluride nanoparticles as biocompatible and enhanced contrast agents for X-ray imaging: an in vivo breast cancer screening study

Silver sulfide nanoparticles (Ag2S NPs) have gained considerable interest in the biomedical field due to their photothermal ablation enhancement, near-infrared fluorescence properties, low toxicity levels, and multi-imaging capabilities. Silver telluride nanoparticles (Ag2Te NPs) have similar properties to Ag2S NPs, should also be stable due to an extremely low solubility product and should generate greater X-ray contrast since tellurium is significantly more attenuating than sulfur at diagnostic X-ray energies. Despite these attractive properties, Ag2Te NPs have only been studied in vivo once and at a low dose (2 mg Ag per kg). Herein, for the first time, Ag2Te NPs' properties and their application in the biomedical field were studied in vivo in the setting requiring the highest nanoparticle doses of all biomedical applications, i.e. X-ray imaging. Ag2Te NPs were shown to be stable, biocompatible (no acute toxicity observed in the cell lines studied or in vivo), and generated higher contrast, compared to controls, in the two X-ray imaging techniques studied: computed tomography (CT) and dual-energy mammography (DEM). In summary, this is the first study where Ag2Te NPs were explored in vivo at a high dose. Our findings suggest that Ag2Te NPs provide strong X-ray contrast while exhibiting excellent biocompatibility. These results highlight the potential use of Ag2Te NPs in the biomedical field and as X-ray contrast agents for breast cancer screening.

Evaluating attenuation correction strategies in a dedicated, single-gantry breast PET-tomosynthesis scanner

We are developing a dedicated, combined breast positron emission tomography (PET)-tomosynthesis scanner. Both the PET and digital breast tomosynthesis (DBT) scanners are integrated in a single gantry to provide spatially co-registered 3D PET-tomosynthesis images. The DBT image will be used to identify the breast boundary and breast density to improve the quantitative accuracy of the PET image. This paper explores PET attenuation correction (AC) strategies that can be performed with the combined breast PET-DBT scanner to obtain more accurate, quantitative high-resolution 3D PET images. The PET detector is comprised of a 32 × 32 array of 1.5 × 1.5 × 15 mm3 LYSO crystals. The PET scanner utilizes two detector heads separated by either 9 or 11 cm, with each detector head having a 4 × 2 arrangement of PET detectors. GEANT4 Application for Tomographic Emission simulations were performed using an anthropomorphic breast phantom with heterogeneous attenuation under clinical DBT-compression. FDG-avid lesions, each 5 mm in diameter with 8:1 uptake, were simulated at four locations within the breast. Simulations were performed with a scan time of 2 min. PET AC was performed using the actual breast simulation model as well as DBT reconstructed volumetric images to derive the breast outline. In addition to using the known breast density as defined by the breast model, we also modeled it as uniform patient-independent soft-tissue, and as a uniform patient-specific material derived from breast tissue composition. Measured absolute lesion uptake was used to evaluate the quantitative accuracy of performing AC using the various strategies. This study demonstrates that AC is necessary to obtain a closer estimate of the true lesion uptake and background activity in the breast. The DBT image dataset assists in measuring lesion uptake with low bias by facilitating accurate breast delineation as well as providing accurate information related to the breast tissue composition. While both the uniform soft-tissue and patient-specific material approaches provides a close estimate to the ground truth, <5% bias can be achieved by using a uniform patient-specific material to define the attenuation map.

Calculation of Radiomic Features to Validate the Textural Realism of Physical Anthropomorphic Phantoms for Digital Mammography

In this paper, radiomic features are used to validate the textural realism of two anthropomorphic phantoms for digital mammography. One phantom was based off a computational breast model; it was 3D printed by CIRS (Computerized Imaging Reference Systems, Inc., Norfolk, VA) under license from the University of Pennsylvania. We investigate how the textural realism of this phantom compares against a phantom derived from an actual patient's mammogram ("Rachel", Gammex 169, Madison, WI). Images of each phantom were acquired at three kV in 1 kV increments using auto-time technique settings. Acquisitions at each technique setting were repeated twice, resulting in six images per phantom. In the raw ("FOR PROCESSING") images, 341 features were calculated; i.e., gray-level histogram, co-occurrence, run length, fractal dimension, Gabor Wavelet, local binary pattern, Laws, and co-occurrence Laws features. Features were also calculated in a negative screening population. For each feature, the middle 95% of the clinical distribution was used to evaluate the textural realism of each phantom. A feature was considered realistic if all six measurements in the phantom were within the middle 95% of the clinical distribution. Otherwise, a feature was considered unrealistic. More features were actually found to be realistic by this definition in the CIRS phantom (305 out of 341 features or 89.44%) than in the phantom derived from a specific patient's mammogram (261 out of 341 features or 76.54%). We conclude that the texture is realistic overall in both phantoms.

Super-Resolution in Digital Breast Tomosynthesis: Limitations of the Conventional System Design and Strategies for Optimization

Our previous work explored the use of super-resolution as a way to improve the visibility of calcifications in digital breast tomosynthesis. This paper demonstrates that there are anisotropies in super-resolution throughout the reconstruction, and investigates new motion paths for the x-ray tube to suppress these anisotropies. We used a theoretical model of a sinusoidal test object to demonstrate the existence of the anisotropies. In addition, high-frequency test objects were simulated with virtual clinical trial (VCT) software developed for breast imaging. The simulated objects include a lead bar pattern phantom as well as punctate calcifications in a breast-like background. In a conventional acquisition geometry in which the source motion is directed laterally, we found that super-resolution is not achievable if the frequency is oriented in the perpendicular direction (posteroanteriorly). Also, there are positions, corresponding to various slices above the breast support, at which super-resolution is inherently not achievable. The existence of these anisotropies was validated with VCT simulations. At locations predicted by theoretical modeling, the bar pattern phantom showed aliasing, and the spacing between individual calcifications was not properly resolved. To show that super-resolution can be optimized by re-designing the acquisition geometry, we applied our theoretical model to the analysis of new motion paths for the x-ray tube; specifically, motions with more degrees of freedom and with more rapid pulsing (submillimeter spacing) between source positions. These two strategies can be used in combination to suppress the anisotropies in super-resolution.

Proposing Rapid Source Pulsing for Improved Super-Resolution in Digital Breast Tomosynthesis

Our previous work showed that digital breast tomosynthesis (DBT) systems are capable of super-resolution, or subpixel resolution relative to the detector. Using a bar pattern phantom, it is possible to demonstrate that there are anisotropies in super-resolution throughout the reconstruction. These anisotropies are lessened in acquisition geometries with narrow spacing between source positions. This paper demonstrates that by re-arranging the source positions in the scan, the anisotropies can be minimized even further. To this end, a theoretical model of the reconstruction of a high-frequency sinusoidal test object was developed from first principles. We modeled the effect of clustering additional source positions around each conventional source position in fine increments (submillimeter). This design can be implemented by rapidly pulsing the source during a continuous sweep of the x-ray tube. It is shown that it is not possible to eliminate the anisotropies in a conventional DBT system with uniformly-spaced source positions, even if the increments of spacing are narrower than those used clinically. However, super-resolution can be achieved everywhere if the source positions are re-arranged in clusters with submillimeter spacing. Our previous work investigated a different approach for optimizing super-resolution through the use of detector motion perpendicular to the breast support. The advantage of introducing rapid source pulsing is that detector motion is no longer required; this mitigates the need for a thick detector housing, which may be cumbersome for patient positioning.

Robust Radiomic Feature Selection in Digital Mammography: Understanding the Effect of Imaging Acquisition Physics Using Phantom and Clinical Data Analysis

Studies have shown that combining calculations of radiomic features with estimates of mammographic density results in an even better assessment of breast cancer risk than density alone. However, to ensure that risk assessment calculations are consistent across different imaging acquisition settings, it is important to identify features that are not overly sensitive to changes in these settings. In this study, digital mammography (DM) images of an anthropomorphic phantom ("Rachel", Gammex 169, Madison, WI) were acquired at various technique settings. We varied kV and mAs, which control contrast and noise, respectively. DM images in women with negative screening exams were also analyzed. Radiomic features were calculated in the raw ("FOR PROCESSING") DM images; i.e., grey-level histogram, co-occurrence, run length, fractal dimension, Gabor Wavelet, local binary pattern, Laws, and co-occurrence Laws features. For each feature, the range of variation across technique settings in phantom images was calculated. This range was scaled against the range of variation in the clinical distribution (specifically, the range corresponding to the middle 90% of the distribution). In order for a radiomic feature to be considered robust, this metric of imaging acquisition variation (IAV) should be as small as possible (approaching zero). An IAV threshold of 0.25 was proposed for the purpose of this study. Out of 341 features, 284 features (83%) met the threshold IAV ≤ 0.25. In conclusion, we have developed a method to identify robust radiomic features in DM.

Renally Excretable and Size-Tunable Silver Sulfide Nanoparticles for Dual-Energy Mammography or Computed Tomography

Significant effort has been focused on developing renally-clearable nanoparticle agents since efficient renal clearance is important for eventual clinical translation. Silver sulfide nanoparticles (Ag₂S-NP) have recently been identified as contrast agents for dual energy mammography, computed tomography (CT) and fluorescence imaging and probes for drug delivery and photothermal therapy with good biocompatibility. However, most Ag₂S-NP reported to date are not renally excretable and are observed in vivo to accumulate and remain in the reticuloendothelial system (RES) organs, i.e. liver and spleen, for a long time, which could negatively impact their likelihood for translation. Herein, we present renally-clearable, 3.1 nm Ag₂S-NP with 85% of the injected dose (ID) being excreted within 24 hours of intravenous injection, which is amongst the best clearance of similarly sized nanoparticles reported thus far (mostly between 20-75% of ID). The urinary excretion and low RES accumulation of these nanoparticles in mice were indicated by in vivo CT imaging and biodistribution analysis. In summary, these ultrasmall Ag₂S-NP can be effectively eliminated via urine and have high translational potential for various biomedical applications.

Technical Note: Noise models for virtual clinical trials of digital breast tomosynthesis

PURPOSE

To investigate the use of an affine-variance noise model, with correlated quantum noise and spatially dependent quantum gain, for the simulation of noise in virtual clinical trials (VCT) of digital breast tomosynthesis (DBT).

METHODS

Two distinct technologies were considered: an amorphous-selenium (a-Se) detector with direct conversion and a thallium-doped cesium iodide (CsI(Tl)) detector with indirect conversion. A VCT framework was used to generate noise-free projections of a uniform three-dimensional simulated phantom, whose geometry and absorption match those of a polymethyl methacrylate (PMMA) uniform physical phantom. The noise model was then used to generate noisy observations from the simulated noise-free data, while two clinically available DBT units were used to acquire projections of the PMMA physical phantom. Real and simulated projections were then compared using the signal-to-noise ratio (SNR) and normalized noise power spectrum (NNPS).

RESULTS

Simulated images reported errors smaller than 4.4% and 7.0% in terms of SNR and NNPS, respectively. These errors are within the expected variation between two clinical units of the same model. The errors increase to 65.8% if uncorrelated models are adopted for the simulation of systems featuring indirect detection. The assumption of spatially independent quantum gain generates errors of 11.2%.

CONCLUSIONS

The investigated noise model can be used to accurately reproduce the noise found in clinical DBT. The assumption of uncorrelated noise may be adopted if the system features a direct detector with minimal pixel crosstalk.

Evaluation of non-Gaussian statistical properties in virtual breast phantoms

Images derived from a "virtual phantom" can be useful in characterizing the performance of imaging systems. This has driven the development of virtual breast phantoms implemented in simulation environments. In breast imaging, several such phantoms have been proposed. We analyze the non-Gaussian statistical properties from three classes of virtual breast phantoms and compare them to similar statistics from a database of breast images. These include clustered-blob lumpy backgrounds (CBLBs), truncated binary textures, and the UPenn virtual breast phantoms. We use Laplacian fractional entropy (LFE) as a measure of the non-Gaussian statistical properties of each simulation procedure. Our results show that, despite similar power spectra, the simulation approaches differ considerably in LFE with very low scores for the CBLB to high values for the UPenn phantom at certain frequencies. These results suggest that LFE may have value in developing and tuning virtual phantom simulation procedures.

Design and implementation of a radiation dose tracking and reporting system for mammography and digital breast tomosynthesis

A tracking system has been implemented to monitor radiation dose for digital mammography (DM) and digital breast tomosynthesis (DBT). This system communicates with a PACS through DICOM messages that allow the image metadata to be stored in a relational database. The tracking system accepts X-ray breast images, maps the image metadata into a SQL database, and allows a client-side application to report the data using a business intelligence framework. The database contains the DICOM information of 54,244 studies (235,225 images) acquired from four Selenia Dimensions systems. The average time to receive the images, and then extract and write the metadata into the database is 2.28 s for a DM and 3.84 s for a DBT image. Using the stored metadata, physics reports are generated based on chosen criteria (i.e., system model, mammography unit, breast data, acquisition techniques, physician, etc.). Our results show that the mean average glandular dose (AGD) varies significantly with compressed breast thickness and age. We observed an overall dose increase of 25.6% between DM and DBT (1.76 vs 2.21 mGy).

Personalization of X-Ray Tube Motion in Digital Breast Tomosynthesis Using Virtual Defrise Phantoms

In digital breast tomosynthesis (DBT), projection images are acquired as the x-ray tube rotates in the plane of the chest wall. We constructed a prototype next-generation tomosynthesis (NGT) system that has an additional component of tube motion in the perpendicular direction (i.e., posteroanterior motion). Our previous work demonstrated the advantages of the NGT system using the Defrise phantom. The reconstruction shows higher contrast and fewer blurring artifacts. To expand upon that work, this paper analyzes how image quality can be further improved by customizing the motion path of the x-ray tube based on the object being imaged. In simulations, phantoms are created with realistic 3D breast outlines based on an established model of the breast under compression. The phantoms are given an internal structure similar to a Defrise phantom. Two tissue types (fibroglandular and adipose) are arranged in a square-wave pattern. The reconstruction is analyzed as a binary classification task using thresholding to segment the two tissue types. At various thresholds, the classification of each voxel in the reconstruction is compared against the phantom, and receiver operating characteristic (ROC) curves are calculated. It is shown that the area under the ROC curve (AUC) is dependent on the x-ray tube trajectory. The trajectory that maximizes AUC differs between phantoms. In conclusion, this paper demonstrates that the acquisition geometry in DBT should be personalized to the object being imaged in order to optimize the image quality.

Nonstationary model of oblique x-ray incidence in amorphous selenium detectors: II. Transfer functions

PURPOSE

One limitation of experimental techniques for quantifying resolution and noise in detectors is that the measurement is made in a region-of-interest (ROI). With theoretical modeling, these properties can be measured at a point, allowing for quantification of spatial anisotropy. This paper calculates nonstationary transfer functions for amorphous selenium (a-Se) detectors in breast imaging. We use this model to demonstrate the performance advantage of a "next-generation" tomosynthesis (NGT) system, which is capable of x-ray source motion with more degrees of freedom than a clinical tomosynthesis system.

METHODS

Using Swank's formulation, the optical transfer function (OTF) and presampled noise power spectra (NPS) are determined based on the point spread function derived in Part 1. The modulation transfer function (MTF) is found from the normalized modulus of the OTF. To take into account the presence of digitization, the presampled NPS is convolved with a two-dimensional comb function, for which the period along each direction is the reciprocal of the detector element size. The detective quantum efficiency (DQE) is then determined from combined knowledge of the OTF and NPS.

RESULTS

First, the model is used to demonstrate the loss of image quality due to oblique x-ray incidence. The MTF is calculated along various polar angles, corresponding to different orientations of the input frequency. The MTF is independent of the incidence angle if the polar angle is perpendicular to the ray incidence direction. However, along other polar angles, oblique incidence results in MTF degradation at high frequencies. The MTF degradation is most substantial along the ray incidence direction. Unlike the MTF, the normalized NPS (NNPS) is independent of the incidence angle. To measure the relative signal-to-noise, the DQE is also calculated. Oblique incidence yields high-frequency DQE degradation, which is more pronounced than the MTF degradation. This arises because the DQE is proportionate with the square of the MTF. Ultimately, this model is used to evaluate how the image quality varies over the detector area. For various projection images, we calculate the variation in the incidence angle over this area. With the NGT system, the source can be positioned in such a way that this variation is minimized, and hence the DQE exhibits less anisotropy. To achieve this improvement in the image quality, the source needs to have a component of motion in the posteroanterior (PA) direction, which is perpendicular to the conventional direction of source motion in tomosynthesis.

CONCLUSIONS

In a-Se detectors, the DQE at high frequencies is degraded due to oblique incidence. The DQE degradation is more pronounced than the MTF degradation. This model is used to quantify the spatial variation in DQE over the detector area. The use of PA source motion is a strategy for minimizing this variation and thus improving the image quality.

Non-stationary model of oblique x-ray incidence in amorphous selenium detectors: I. Point spread function

PURPOSE

In previous work, a theoretical model of the point spread function (PSF) for oblique x-ray incidence in amorphous selenium (a-Se) detectors was proposed. The purpose of this paper is to develop a complementary model that includes two additional features. First, the incidence angle and the directionality of ray incidence are calculated at each position, assuming a divergent x-ray beam geometry. This approach allows the non-stationarity of the PSF to be modeled. Second, this paper develops a framework that is applicable to a digital system, unlike previous work which did not model the presence of a thin-film transistor (TFT) array.

METHODS

At each point on the detector, the incidence angle and the ray incidence direction are determined using ray tracing. Based on these calculations, an existing model for the PSF of the x-ray converter (Med Phys. 1995;22:365-374) is generalized to a non-stationary model. The PSF is convolved with the product of two rectangle functions, which model the sampling of the TFT array. The rectangle functions match the detector element (del) size in two dimensions.

RESULTS

It is shown that the PSF can be calculated in closed form. This solution is used to simulate a digital mammography (DM) system at two x-ray energies (20 and 40 keV). Based on the divergence of the x-ray beam, the direction of ray incidence varies with position. Along this direction, the PSF is broader than the reference rect function matching the del size. The broadening is more pronounced with increasing obliquity. At high energy, the PSF deviates more strongly from the reference rect function, indicating that there is more blurring. In addition, the PSF is calculated along the polar angle perpendicular to the ray incidence direction. For this polar angle, the shape of the PSF is dependent upon whether the ray incidence direction is parallel with the sides of the detector. If the ray incidence direction is parallel with either dimension, the PSF is a perfect rectangle function, matching the del size. However, if the ray incidence direction is at an oblique angle relative to the sides of the detector, the PSF is not rectangular. These results illustrate the non-stationarity of the PSF.

CONCLUSIONS

This paper demonstrates that an existing model of the PSF of a-Se detectors can be generalized to include the effects of non-stationarity and digitization. The PSF is determined in closed form. This solution offers the advantage of shorter computation time relative to approaches that use numerical methods. This model is a tool for simulating a-Se detectors in future work, such as in virtual clinical trials with computational phantoms.

An all-in-one nanoparticle (AION) contrast agent for breast cancer screening with DEM-CT-MRI-NIRF imaging

Conventional X-ray mammography has low diagnostic sensitivity for women with dense breasts. As a result, alternative contrast-enhanced screening tools such as dual energy mammography (DEM), computed tomography (CT), magnetic resonance imaging (MRI), and near-infrared fluorescence (NIRF) imaging are being used or investigated for these women. However, currently available contrast agents are non-ideal, have safety issues, and each imaging technique requires a different contrast agent. We therefore sought to develop a multimodal contrast agent that is functional for each breast imaging modality to simplify the diagnosis process and address the issues of existing contrast agents. Herein, we present a novel "all-in-one" nanoparticle (AION) multimodal imaging probe that has potent DEM, CT, MRI, and NIRF contrast properties and improved biocompatibility. AION were formed by co-encapsulation of a near-infrared fluorophore (DiR), silver sulfide nanoparticles (Ag2S-NP), and iron oxide nanoparticles (IO-NP) in PEGylated micelles. AION showed negligible cytotoxicity, which was in agreement with its minimal silver ion release profiles. AION generated strong contrast with all imaging modalities as demonstrated in phantom imaging. AION allowed in vivo tumor imaging as evidenced by the increase in contrast after injection. This study indicates the potential of AION as an effective multimodal contrast agent for breast cancer diagnosis with a range of imaging methods.

Validation of the Textural Realism of a 3D Anthropomorphic Phantom for Digital Breast Tomosynthesis

In this paper, texture calculations are used to validate the realism of a physical anthropomorphic phantom for digital breast tomosynthesis. The texture features were compared against clinical mammography data. Three groups of features (grey-level histogram, co-occurrence, and run-length) were considered. The features were analyzed over a broad range of technique settings (kV and mAs). These calculations were done in the central slice of the reconstruction as well as the synthetic 2D mammogram. For each feature, the clinical data were binned into strata based on the compressed breast thickness. It was demonstrated that the clinical features vary by thickness. To evaluate the realism of the phantom, each feature was compared against clinical data in the same thickness stratum. For the purpose of this paper, a feature was considered to be realistic if it was within the middle 95% of the statistical distribution of clinical values. In the reconstruction, most features were found to exhibit realism; specifically, all 12 grey-level histogram features, four out of seven co-occurrence features, and three out of seven run-length features. The realism of most features was robust to changes in the technique settings. However, in the synthetic 2D mammogram, fewer features were found to exhibit realism. In conclusion, this paper provides a validation of the textural realism of the phantom in the reconstruction, and shows that there is less realism in the synthetic 2D mammogram. We identify the features that should be considered to refine the design of the phantom in future work.

Analysis of Volume Overestimation Artifacts in the Breast Outline Segmentation in Tomosynthesis

In digital breast tomosynthesis (DBT), the reconstruction is calculated from x-ray projection images acquired over a small range of angles. One step in the reconstruction process is to identify the pixels that fall outside the shadow of the breast, to segment the breast from the background (air). In each projection, rays are back-projected from these pixels to the focal spot. All voxels along these rays are identified as air. By combining these results over all projections, a breast outline can be determined for the reconstruction. This paper quantifies the accuracy of this breast segmentation strategy in DBT. In this study, a physical phantom modeling a breast under compression was analyzed with a prototype next-generation tomosynthesis (NGT) system described in previous work. Multiple wires were wrapped around the phantom. Since the wires are thin and high contrast, their exact location can be determined from the reconstruction. Breast parenchyma was portrayed outside the outline defined by the wires. Specifically, the size of the phantom was overestimated along the posteroanterior (PA) direction; i.e., perpendicular to the plane of conventional source motion. To analyze how the acquisition geometry affects the accuracy of the breast outline segmentation, a computational phantom was also simulated. The simulation identified two ways to improve the segmentation accuracy; either by increasing the angular range of source motion laterally or by increasing the range in the PA direction. The latter approach is a unique feature of the NGT design; the advantage of this approach was validated with our prototype system.

Method for simulating dose reduction in digital mammography using the Anscombe transformation

PURPOSE

This work proposes an accurate method for simulating dose reduction in digital mammography starting from a clinical image acquired with a standard dose.

METHODS

The method developed in this work consists of scaling a mammogram acquired at the standard radiation dose and adding signal-dependent noise. The algorithm accounts for specific issues relevant in digital mammography images, such as anisotropic noise, spatial variations in pixel gain, and the effect of dose reduction on the detective quantum efficiency. The scaling process takes into account the linearity of the system and the offset of the detector elements. The inserted noise is obtained by acquiring images of a flat-field phantom at the standard radiation dose and at the simulated dose. Using the Anscombe transformation, a relationship is created between the calculated noise mask and the scaled image, resulting in a clinical mammogram with the same noise and gray level characteristics as an image acquired at the lower-radiation dose.

RESULTS

The performance of the proposed algorithm was validated using real images acquired with an anthropomorphic breast phantom at four different doses, with five exposures for each dose and 256 nonoverlapping ROIs extracted from each image and with uniform images. The authors simulated lower-dose images and compared these with the real images. The authors evaluated the similarity between the normalized noise power spectrum (NNPS) and power spectrum (PS) of simulated images and real images acquired with the same dose. The maximum relative error was less than 2.5% for every ROI. The added noise was also evaluated by measuring the local variance in the real and simulated images. The relative average error for the local variance was smaller than 1%.

CONCLUSIONS

A new method is proposed for simulating dose reduction in clinical mammograms. In this method, the dependency between image noise and image signal is addressed using a novel application of the Anscombe transformation. NNPS, PS, and local noise metrics confirm that this method is capable of precisely simulating various dose reductions.

Development of silica-encapsulated silver nanoparticles as contrast agents intended for dual-energy mammography

OBJECTIVE

Dual-energy (DE) mammography has recently entered the clinic. Previous theoretical and phantom studies demonstrated that silver provides greater contrast than iodine for this technique. Our objective was to characterize and evaluate in vivo a prototype silver contrast agent ultimately intended for DE mammography.

METHODS

The prototype silver contrast agent was synthesized using a three-step process: synthesis of a silver core, silica encapsulation and PEG coating. The nanoparticles were then injected into mice to determine their accumulation in various organs, blood half-life and dual-energy contrast. All animal procedures were approved by the institutional animal care and use committee.

RESULTS

The final diameter of the nanoparticles was measured to be 102 (±9) nm. The particles were removed from the vascular circulation with a half-life of 15 min, and accumulated in macrophage-rich organs such as the liver, spleen and lymph nodes. Dual-energy subtraction techniques increased the signal difference-to-noise ratio of the particles by as much as a factor of 15.2 compared to the single-energy images. These nanoparticles produced no adverse effects in mice.

CONCLUSION

Silver nanoparticles are an effective contrast agent for dual-energy x-ray imaging. With further design improvements, silver nanoparticles may prove valuable in breast cancer screening and diagnosis.

KEY POINTS

• Silver has potential as a contrast agent for DE mammography. • Silica-coated silver nanoparticles are biocompatible and suited for in vivo use. • Silver nanoparticles produce strong contrast in vivo using DE mammography imaging systems.

Implementation of Synthesized Two-dimensional Mammography in a Population-based Digital Breast Tomosynthesis Screening Program

Purpose To evaluate the early implementation of synthesized two-dimensional (s2D) mammography in a population screened entirely with s2D and digital breast tomosynthesis (DBT) (referred to as s2D/DBT) and compare recall rates and cancer detection rates to historic outcomes of digital mammography combined with DBT (referred to as digital mammography/DBT) screening. Materials and Methods This was an institutional review board-approved and HIPAA-compliant retrospective interpretation of prospectively acquired data with waiver of informed consent. Compared were recall rates, biopsy rates, cancer detection rates, and radiation dose for 15 571 women screened with digital mammography/DBT from October 1, 2011, to February 28, 2013, and 5366 women screened with s2D/DBT from January 7, 2015, to June 30, 2015. Two-sample z tests of equal proportions were used to determine statistical significance. Results Recall rate for s2D/DBT versus digital mammography/DBT was 7.1% versus 8.8%, respectively (P < .001). Biopsy rate for s2D/DBT versus digital mammography/DBT decreased (1.3% vs 2.0%, respectively; P = .001). There was no significant difference in cancer detection rate for s2D/DBT versus digital mammography/DBT (5.03 of 1000 vs 5.45 of 1000, respectively; P = .72). The average glandular dose was 39% lower in s2D/DBT versus digital mammography/DBT (4.88 mGy vs 7.97 mGy, respectively; P < .001). Conclusion Screening with s2D/DBT in a large urban practice resulted in similar outcomes compared with digital mammography/DBT imaging. Screening with s2D/DBT allowed for the benefits of DBT with a decrease in radiation dose compared with digital mammography/DBT. ^© RSNA, 2016 An earlier incorrect version of this article appeared online. This article was corrected on August 11, 2016.

Gold silver alloy nanoparticles (GSAN): an imaging probe for breast cancer screening with dual-energy mammography or computed tomography

Earlier detection of breast cancer reduces mortality from this disease. As a result, the development of better screening techniques is a topic of intense interest. Contrast-enhanced dual-energy mammography (DEM) is a novel technique that has improved sensitivity for cancer detection. However, the development of contrast agents for this technique is in its infancy. We herein report gold-silver alloy nanoparticles (GSAN) that have potent DEM contrast properties and improved biocompatibility. GSAN formulations containing a range of gold : silver ratios and capped with m-PEG were synthesized and characterized using various analytical methods. DEM and computed tomography (CT) phantom imaging showed that GSAN produced robust contrast that was comparable to silver alone. Cell viability, reactive oxygen species generation and DNA damage results revealed that the formulations with 30% or higher gold content are cytocompatible to Hep G2 and J774A.1 cells. In vivo imaging was performed in mice with and without breast tumors. The results showed that GSAN produce strong DEM and CT contrast and accumulated in tumors. Furthermore, both in vivo imaging and ex vivo analysis indicated the excretion of GSAN via both urine and feces. In summary, GSAN produce strong DEM and CT contrast, and has potential for both blood pool imaging and for breast cancer screening.

Digital breast tomosynthesis: lessons learned from early clinical implementation

The limitations of mammography are well known and are partly related to the fact that with conventional imaging, the three-dimensional volume of the breast is imaged and presented in a two-dimensional format. Because normal breast tissue is similar in x-ray attenuation to some breast cancers, clinically relevant malignancies may be obscured by normal overlapping tissue. In addition, complex areas of normal tissue may be perceived as suspicious. The limitations of two-dimensional breast imaging lead to low sensitivity in detecting some cancers and high false-positive recall rates. Although mammographic screening has been shown to reduce breast cancer deaths by approximately 30%, controversy exists over when and how often screening mammography should occur. Digital breast tomosynthesis (DBT) is rapidly being implemented in breast imaging clinics around the world as early clinical data demonstrate that it may address some of the limitations of conventional mammography. With DBT, multiple low-dose x-ray images are acquired in an arc and reconstructed to create a three-dimensional image, thus minimizing the impact of overlapping breast tissue and improving lesion conspicuity. Early studies of screening DBT have shown decreased false-positive callback rates and increased rates of cancer detection (particularly for invasive cancers), resulting in increased sensitivity and specificity. In our clinical practice, we have completed more than 2 years of using two-view digital mammography combined with two-view DBT for all screening and select diagnostic imaging examinations (over 25,000 patients). Our experience, combined with previously published data, demonstrates that the combined use of DBT and digital mammography is associated with improved outcomes for screening and diagnostic imaging. Online supplemental material is available for this article.

Description and characterization of a novel method for partial volume simulation in software breast phantoms

A modification to our previous simulation of breast anatomy is proposed to improve the quality of simulated x-ray projections images. The image quality is affected by the voxel size of the simulation. Large voxels can cause notable spatial quantization artifacts; small voxels extend the generation time and increase the memory requirements. An improvement in image quality is achievable without reducing voxel size by the simulation of partial volume averaging in which voxels containing more than one simulated tissue type are allowed. The linear x-ray attenuation coefficient of voxels is, thus, the sum of the linear attenuation coefficients weighted by the voxel subvolume occupied by each tissue type. A local planar approximation of the boundary surface is employed. In the two-material case, the partial volume in each voxel is computed by decomposition into up to four simple geometric shapes. In the three-material case, by application of the Gauss-Ostrogradsky theorem, the 3D partial volume problem is converted into one of a few simpler 2D surface area problems. We illustrate the benefits of the proposed methodology on simulated x-ray projections. An efficient encoding scheme is proposed for the type and proportion of simulated tissues in each voxel. Monte Carlo simulation was used to evaluate the quantitative error of our approximation algorithms.

Radiation dosimetry in digital breast tomosynthesis: report of AAPM Tomosynthesis Subcommittee Task Group 223

The radiation dose involved in any medical imaging modality that uses ionizing radiation needs to be well understood by the medical physics and clinical community. This is especially true of screening modalities. Digital breast tomosynthesis (DBT) has recently been introduced into the clinic and is being used for screening for breast cancer in the general population. Therefore, it is important that the medical physics community have the required information to be able to understand, estimate, and communicate the radiation dose levels involved in breast tomosynthesis imaging. For this purpose, the American Association of Physicists in Medicine Task Group 223 on Dosimetry in Tomosynthesis Imaging has prepared this report that discusses dosimetry in breast imaging in general, and describes a methodology and provides the data necessary to estimate mean breast glandular dose from a tomosynthesis acquisition. In an effort to maximize familiarity with the procedures and data provided in this Report, the methodology to perform the dose estimation in DBT is based as much as possible on that used in mammography dose estimation.

Parenchymal texture analysis in digital mammography: robust texture feature identification and equivalence across devices

An analytical framework is presented for evaluating the equivalence of parenchymal texture features across different full-field digital mammography (FFDM) systems using a physical breast phantom. Phantom images (FOR PROCESSING) are acquired from three FFDM systems using their automated exposure control setting. A panel of texture features, including gray-level histogram, co-occurrence, run length, and structural descriptors, are extracted. To identify features that are robust across imaging systems, a series of equivalence tests are performed on the feature distributions, in which the extent of their intersystem variation is compared to their intrasystem variation via the Hodges-Lehmann test statistic. Overall, histogram and structural features tend to be most robust across all systems, and certain features, such as edge enhancement, tend to be more robust to intergenerational differences between detectors of a single vendor than to intervendor differences. Texture features extracted from larger regions of interest (i.e., [Formula: see text]) and with a larger offset length (i.e., [Formula: see text]), when applicable, also appear to be more robust across imaging systems. This framework and observations from our experiments may benefit applications utilizing mammographic texture analysis on images acquired in multivendor settings, such as in multicenter studies of computer-aided detection and breast cancer risk assessment.