Image artifacts in digital breast tomosynthesis: investigation of the effects of system geometry and reconstruction parameters using a linear system approach

In-silico study of the impact of system design parameters on microcalcification detection in wide-angle digital breast tomosynthesis

Purpose

Accurate detection of microcalcifications ( μ Calcs ) is crucial for the early detection of breast cancer. Some clinical studies have indicated that digital breast tomosynthesis (DBT) systems with a wide angular range have inferior μ Calc detectability compared with those with a narrow angular range. This study aims to (1) provide guidance for optimizing wide-angle (WA) DBT for improving μ Calcs detectability and (2) prioritize key optimization factors.

Approach

An in-silico DBT pipeline was constructed to evaluate μ Calc detectability of a WA DBT system under various imaging conditions: focal spot motion (FSM), angular dose distribution (ADS), detector pixel pitch, and detector electronic noise (EN). Images were simulated using a digital anthropomorphic breast phantom inserted with 120   μ m μ Calc clusters. Evaluation metrics included the signal-to-noise ratio (SNR) of the filtered channel observer and the area under the receiver operator curve (AUC) of multiple-reader multiple-case analysis.

Results

Results showed that FSM degraded μ Calcs sharpness and decreased the SNR and AUC by 5.2% and 1.8%, respectively. Non-uniform ADS increased the SNR by 62.8% and the AUC by 10.2% for filtered backprojection reconstruction with a typical clinical filter setting. When EN decreased from 2000 to 200 electrons, the SNR and AUC increased by 21.6% and 5.0%, respectively. Decreasing the detector pixel pitch from 85 to 50    μ m improved the SNR and AUC by 55.6% and 7.5%, respectively. The combined improvement of a 50   μ m pixel pitch and EN200 was 89.2% in the SNR and 12.8% in the AUC.

Conclusions

Based on the magnitude of impact, the priority for enhancing μ Calc detectability in WA DBT is as follows: (1) utilizing detectors with a small pixel pitch and low EN level, (2) allocating a higher dose to central projections, and (3) reducing FSM. The results from this study can potentially provide guidance for DBT system optimization in the future.

Optimizing angular range in digital breast tomosynthesis: A phantom study investigating lesion detection across varied breast density and thickness

PURPOSE

To determine the optimal angular range (AR) for digital breast tomosynthesis (DBT) systems that provides highest lesion visibility across various breast densities and thicknesses.

METHOD

A modular DBT phantom, consisting of tissue-equivalent adipose and glandular modules, along with a module embedded with test objects (speckles, masses, fibers), was used to create combinations simulating different breast thicknesses, densities, and lesion locations. A prototype DBT system operated at four ARs (AR±7.5°, AR±12.5°, AR±19°, and AR±25°) to acquire 11 projection images for each combination, with separate fixed doses for thin and thick combinations. Three blinded radiologists independently assessed lesion visibility in reconstructed images; assessments were averaged and compared using linear mixed models.

RESULTS

Speckle visibility was highest with AR±7.5° or AR±12.5°, decreasing with wider ARs in all density and thickness combinations. The difference between AR±7.5° and AR±12.5° was not statistically significant, except for the tube-side speckles in thin-fatty combinations (5.83 [AR±7.5°] vs. 5.39 [AR±12.5°], P = 0.019). Mass visibility was not affected by AR in thick combinations, while AR±12.5° exhibited the highest mass visibility for both thin-fatty and thin-dense combinations (P = 0.032 and 0.007, respectively). Different ARs provided highest fiber visibility for different combinations; however, AR±12.5° consistently provided highest or comparable visibility. AR±12.5° showed highest overall lesion visibility for all density and thickness combinations.

CONCLUSIONS

AR±12.5° exhibited the highest overall lesion visibility across various phantom thicknesses and densities using a projection number of 11.

Full 3-D modulation transfer function estimation of tomosynthesis system using modified Richardson-Lucy deconvolution

BACKGROUND

Tomosynthesis systems are three-dimensional (3-D) medical imaging devices that operate over limited acquisition angles using low radiation dosages. To measure the spatial resolution performance of a tomosynthesis system, the modulation transfer function (MTF) is widely used as a quantitative evaluation metric.

PURPOSE

We previously introduced a method to estimate the full 3-D MTF of a cone-beam computed tomography system using two-dimensional (2-D) Richardson-Lucy (RL) deconvolution with Tikhonov-Miller regularization. However, this method can not be applied directly to estimate the 3-D MTF of a tomosynthesis system, since the unique artifacts (i.e., shadow artifacts, spreading tails, directional blurring, and high-level noise) of the system produce several errors that lower the estimation performance. Varying positions of the negative pixels due to shadow artifacts and spreading tails cause inconsistent deconvolution performances at each of the directional projections, and the severe noise in the reconstructed images cause noise amplification during estimation. This work proposes several modifications to the previous method to resolve the inconsistent performance and noise amplification errors to increase the full 3-D MTF estimation accuracy.

METHODS

Three modifications were introduced to the 2-D RL deconvolution to prevent estimation errors and improve MTF estimation performance: non-negativity relaxation function, cost function to terminate the iterative process of RL deconvolution, and regularization strength for noise control. To validate the effectiveness of the proposed modifications, we reconstructed sphere phantoms from simulation and experimental tomosynthesis studies in the iso-center and offset-center positions as well as estimated the full 3-D MTFs using the previous and proposed methods. We compared the 3-D render images, central plane images, and center profiles of the estimated 3-D MTFs and calculated the full widths at half and tenth maximum for quantitative evaluation.

RESULTS

The previous method cannot estimate the full 3-D MTF of a tomosynthesis system; its inaccurate negative pixel relaxation produces circular-shaped errors, and the mean squared error based simple cost function for termination causes inconsistent estimation at each directional projection to diminish the clear edges of the low-frequency drop and missing sample regions. Noise amplification from lack of noise regularization is also seen in the previous method results. Compared to the previous method, the proposed method shows superior estimation performance at reducing errors in both the simulation and experimental studies regardless of object position. The proposed method preserves the low-frequency drop, missing sample regions from the limited acquisition angles, and missing cone region from the offset-center position; the estimated MTFs also show FWHM and FWTM values close to those of the ideal MTFs than with the previous method.

CONCLUSIONS

This work presents a method to estimate the full 3-D MTF of a tomosynthesis system. The proposed modifications prevent circular-shaped errors and noise amplification due to the geometry for limited acquisition angles and high noise levels. Compared to our previous method, the proposed scheme show better performance for estimating the 3-D MTF of the tomosynthesis system.

Typical values of z-resolution for different Digital Breast Tomosynthesis systems evaluated in a multicenter study

PURPOSE

The aim of the present study, conducted by a working group of the Italian Association of Medical Physics (AIFM), was to define typical z-resolution values for different digital breast tomosynthesis (DBT) models to be used as a reference for quality control (QC). Currently, there are no typical values published in internationally agreed QC protocols.

METHODS

To characterize the z-resolution of the DBT models, the full width at half maximum (FWHM) of the artifact spread function (ASF), a technical parameter that quantifies the signal intensity of a detail along reconstructed planes, was analyzed. Five different commercial phantoms, CIRS Model 011, CIRS Model 015, Modular DBT phantom, Pixmam 3-D, and Tomophan, were evaluated on reconstructed DBT images and 82 DBT systems (6 vendors, 9 models) in use at 39 centers in Italy were involved.

RESULTS

The ASF was found to be dependent on the detail size, the DBT angular acquisition range, the reconstruction algorithm and applied image processing. In particular, a progressively greater signal spread was observed as the detail size increased and the acquisition angle decreased. However, a clear correlation between signal spread and angular range width was not observed due to the different signal reconstruction and image processing strategies implemented in the algorithms developed by the vendors studied.

CONCLUSIONS

The analysis led to the identification of typical z-resolution values for different DBT model-phantom configurations that could be used as a reference during a QC program.

Task-based detectability in anatomical background in digital mammography, digital breast tomosynthesis and synthetic mammography

Objective.Determining the detectability of targets for the different imaging modalities in mammography in the presence of anatomical background noise is challenging. This work proposes a method to compare the image quality and detectability of targets in digital mammography (DM), digital breast tomosynthesis (DBT) and synthetic mammography.Approach. The low-frequency structured noise produced by a water phantom with acrylic spheres was used to simulate anatomical background noise for the different types of images. A method was developed to apply the non-prewhitening observer model with eye filter (NPWE) in these conditions. A homogeneous poly(methyl) methacrylate phantom with a 0.2 mm thick aluminium disc was used to calculate 2D in-plane modulation transfer function (MTF), noise power spectrum (NPS), noise equivalent quanta, and system detective quantum efficiency for 30, 50 and 70 mm thicknesses. The in-depth MTFs of DBT volumes were determined using a thin tungsten wire. The MTF, system NPS and anatomical NPS were used in the NPWE model to calculate the threshold gold thickness of the gold discs contained in the CDMAM phantom, which was taken as reference. Main results.The correspondence between the NPWE model and the CDMAM phantom (linear Pearson correlation 0.980) yielded a threshold detectability index that was used to determine the threshold diameter of spherical microcalcifications and masses. DBT imaging improved the detection of masses, which depended mostly on the reduction of anatomical background noise. Conversely, DM images yielded the best detection of microcalcifications.Significance.The method presented in this study was able to quantify image quality and object detectability for the different imaging modalities and levels of anatomical background noise.

Chest tomosynthesis deblurring using CNN with deconvolution layer for vertebrae segmentation

BACKGROUND

Limited scan angles cause severe distortions and artifacts in reconstructed tomosynthesis images when the Feldkamp-Davis-Kress (FDK) algorithm is used for the purpose, which degrades clinical diagnostic performance. These blurring artifacts are fatal in chest tomosynthesis images because precise vertebrae segmentation is crucial for various diagnostic analyses, such as early diagnosis, surgical planning, and injury detection. Moreover, because most spinal pathologies are related to vertebral conditions, the development of methods for accurate and objective vertebrae segmentation in medical images is an important and challenging research area.

PURPOSE

The existing point-spread-function-(PSF)-based deblurring methods use the same PSF in all sub-volumes without considering the spatially varying property of tomosynthesis images. This increases the PSF estimation error, thus further degrading the deblurring performance. However, the proposed method estimates the PSF more accurately by using sub-CNNs that contain a deconvolution layer for each sub-system, which improves the deblurring performance.

METHODS

To minimize the effect of the spatially varying property, the proposed deblurring network architecture comprises four modules: (1) block division module, (2) partial PSF module, (3) deblurring block module, and (4) assembling block module. We compared the proposed DL-based method with the FDK algorithm, total-variation iterative reconstruction with GP-BB (TV-IR), 3D U-Net, FBPConvNet, and two-phase deblurring method. To investigate the deblurring performance of the proposed method, we evaluated its vertebrae segmentation performance by comparing the pixel accuracy (PA), intersection-over-union (IoU), and F-score values of reference images to those of the deblurred images. Also, pixel-based evaluations of the reference and deblurred images were performed by comparing their root mean squared error (RMSE) and visual information fidelity (VIF) values. In addition, 2D analysis of the deblurred images were performed by artifact spread function (ASF) and full width half maximum (FWHM) of the ASF curve.

RESULTS

The proposed method was able to recover the original structure significantly, thereby further improving the image quality. The proposed method yielded the best deblurring performance in terms of vertebrae segmentation and similarity. The IoU, F-score, and VIF values of the chest tomosynthesis images reconstructed using the proposed SV method were 53.5%, 28.7%, and 63.2% higher, respectively, than those of the images reconstructed using the FDK method, and the RMSE value was 80.3% lower. These quantitative results indicate that the proposed method can effectively restore both the vertebrae and the surrounding soft tissue.

CONCLUSIONS

We proposed a chest tomosynthesis deblurring technique for vertebrae segmentation by considering the spatially varying property of tomosynthesis systems. The results of quantitative evaluations indicated that the vertebrae segmentation performance of the proposed method was better than those of the existing deblurring methods.

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.

Visual adaptation to medical images: a comparison of digital mammography and tomosynthesis

Purpose

Radiologists and other image readers spend prolonged periods inspecting medical images. The visual system can rapidly adapt or adjust sensitivity to the images that an observer is currently viewing, and previous studies have demonstrated that this can lead to pronounced changes in the perception of mammogram images. We compared these adaptation effects for images from different imaging modalities to explore both general and modality-specific consequences of adaptation in medical image perception.

Approach

We measured perceptual changes induced by adaptation to images acquired by digital mammography (DM) or digital breast tomosynthesis (DBT), which have both similar and distinct textural properties. Participants (nonradiologists) adapted to images from the same patient acquired from each modality or for different patients with American College of Radiology-Breast Imaging Reporting and Data System (BI-RADS) classification of dense or fatty tissue. The participants then judged the appearance of composite images formed by blending the two adapting images (i.e., DM versus DBT or dense versus fatty in each modality).

Results

Adaptation to either modality produced similar significant shifts in the perception of dense and fatty textures, reducing the salience of the adapted component in the test images. In side-by-side judgments, a modality-specific adaptation effect was not observed. However, when the images were directly fixated during adaptation and testing, so that the textural differences between the modalities were more visible, significantly different changes in the sensitivity to the noise in the images were observed.

Conclusions

These results confirm that observers can readily adapt to the visual properties or spatial textures of medical images in ways that can bias their perception of the images, and that adaptation can also be selective for the distinctive visual features of images acquired by different modalities.

Comparison of lesion detection and conspicuity between narrow-angle and wide-angle digital breast tomosynthesis for dense and non-dense breasts

Digital breast tomosynthesis (DBT) has been shown to improve both sensitivity and specificity for breast cancer detection compared to full-field digital mammography. However, its performance could be limited for patients with dense breasts. Clinical DBT systems vary in their system designs, one of which is the acquisition angular range (AR), which leads to varied performance for different imaging tasks. In this study, we aim to compare DBT systems with different AR. We used a previously validated cascaded linear system model to investigate the dependence of in-plane breast structural noise (BSN) and detectability of masses on AR. We conducted a pilot clinical study to compare the lesion conspicuity between clinical DBT systems with the narrowest and the widest AR. Patients called back for diagnostic imaging on suspicious findings were imaged with both narrow-angle (NA) and wide-angle (WA) DBT. We analyzed the BSN for clinical images using noise power spectrum (NPS) analysis. A 5-point Likert scale was used in the reader study to compare the lesion conspicuity. Our theoretical calculation results show that increasing AR leads to reduced BSN and improved mass detectability. The NPS analysis on clinical images shows the lowest BSN for WA DBT. The WA DBT provides better lesion conspicuity for masses and asymmetries and shows a greater advantage for non-microcalcification lesions in dense breasts. The NA DBT provides better characterizations for microcalcifications. The WA DBT can downgrade false-positive findings seen on NA DBT. In conclusion, WA DBT could improve the detection of masses and asymmetries for patients with dense breasts.

Performance evaluation of digital breast tomosynthesis systems: physical methods and experimental data

Digital breast tomosynthesis (DBT) has become a well-established breast imaging technique, whose performance has been investigated in many clinical studies, including a number of prospective clinical trials. Results from these studies generally point to non-inferiority in terms of microcalcification detection and superior mass-lesion detection for DBT imaging compared to digital mammography (DM). This modality has become an essential tool in the clinic for assessment and ad-hoc screening but is not yet implemented in most breast screening programmes at a state or national level. While evidence on the clinical utility of DBT has been accumulating, there has also been progress in the development of methods for technical performance assessment and quality control of these imaging systems. DBT is a relatively complicated ‘pseudo-3D’ modality whose technical assessment poses a number of difficulties. This paper reviews methods for the technical performance assessment of DBT devices, starting at the component level in part one and leading up to discussion of system evaluation with physical test objects in part two. We provide some historical and basic theoretical perspective, often starting from methods developed for DM imaging. Data from a multi-vendor comparison are also included, acquired under the medical physics quality control protocol developed by EUREF and currently being consolidated by a European Federation of Organisations for Medical Physics working group. These data and associated methods can serve as a reference for the development of reference data and provide some context for clinical studies.

Variation in digital breast tomosynthesis image quality at differing heights above the detector

INTRODUCTION

The aim of this preliminary work was to determine if image quality in digital breast tomosynthesis (DBT) changes when tomosynthesis image slices were obtained at differing heights above the detector and in differing breast thicknesses.

METHODS

A CIRS Model 020 BR3D breast imaging phantom was used to obtain the DBT images. The images were also acquired at different tube voltages, and each exposure was determined by the automatic exposure control system. Contrast-to-noise ratio (CNR) and figure-of-merit (FOM) values were obtained and compared.

RESULTS

At a phantom thickness of 5 cm or greater, there was a significant reduction (P ≤ 0.05) of image CNR values obtained from the images near the top of the phantom to those obtained near the bottom of the phantom. When the phantom thickness was 4 cm, there was no significant difference in CNR values between DBT images acquired at any height in the phantom. FOM values generally showed no difference when images were obtained at differing heights above the detector.

CONCLUSION

Image quality, as measured by the CNR, was reduced when tomosynthesis slice image heights were at the top of the phantom and when the thickness of the phantom was more than 4 cm. From this preliminary work, clinicians need to be aware that DBT images obtained near the top of the breast, when breast thickness is greater than 4 cm, may have reduced image quality. Further work is needed to fully assess any DBT image quality changes when images are obtained near the top of the breast.

The impact on lesion detection via a multi-vendor study: A phantom-based comparison of digital mammography, digital breast tomosynthesis, and synthetic mammography

PURPOSE

The aim of this study is to perform a test object-based comparison of the imaging performance of digital mammography (DM), digital breast tomosynthesis (DBT), and synthetic mammography (SM).

METHODS

Two test objects were used, the CDMAM and the L1-structured phantom. Small-detail detectability was assessed using CDMAM and the microcalcification simulating specks in the L1-structured background. Detection of spiculated and non-spiculated mass-like objects was assessed using the L1 phantom. Six different systems were included: Amulet Innovality (Fujifilm), Senographe Pristina (GEHC), 3Dimensions (Hologic), Giotto Class (IMS), Clarity 2D/3D (Planmed), and Mammomat Revelation (Siemens). Images were acquired under automatic exposure control (AEC) and at adjusted levels of AEC/2 and 2 × AEC level. Threshold gold thickness (T_tr ) was established for the 0.13-mm-diameter CDMAM discs. Threshold diameters for the calcifications (d_{tr_c} ), the spiculated masses (d_{tr_sm} ), and for the non-spiculated masses (d_{tr_nsm} ) were established. The threshold condition was defined as the thickness or diameter for a 62.5% correct score.

RESULTS

T_tr for DM was generally superior to DBT, which in turn was superior to SM, but for most systems, these differences between modes were not significant. For L1, no significant differences in d_{tr_c} were found between DM and DBT. The increase in d_{tr_c} from DM to SM at AEC dose was 1%, 19%, 11%, 14%, 46%, and 27% for the Fujifilm, GEHC, Hologic, IMS, Planmed, and Siemens, respectively, indicating significantly poorer performance for all vendors except for Fujifilm, Hologic, and IMS. For both mass types, DBT performed better than SM, while SM showed no significant difference with DM (except for Fujifilm spiculated masses). The dose had an impact on small-detail detectability for both phantoms but did not influence the detection of either mass type.

CONCLUSIONS

Both phantoms indicated potentially reduced small-detail detectability for SM versus DM and DBT and should therefore not be used in stand-alone mode. The L1 phantom demonstrated no significant difference in microcalcification detection between DM and DBT and also demonstrated the superiority of DBT, compared to DM for mass detection, for all six systems.

[Assessment of imaging performance of digital breast tomosynthesis based on systematic simulation]

OBJECTIVE

To assess the imaging performance of digital breast tomography (DBT) based on systematic simulation.

OBJECTIVE

The raw measurements of physical phantoms at a variety of radiation dose levels and clinical patients at the normal radiation dose were acquired from a clinical DBT system for low-dose simulation and reconstruction using 3 reconstruction algorithms, namely Feldkamp-Davis-Kress (FDK), simultaneous algebraic reconstruction technique (SART) and adaptive steepest-descent projection onto convex sets with total-variation constraint (ASDPOCS-TV) algorithms. The image quality was compared across different radiation dose levels and reconstruction algorithms in terms of signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), noise-power spectrum (NPS), artifact spread function (ASF) and full width at half maximum (FWHM) of ASF indexes.

OBJECTIVE

The reliability of low-dose DBT simulation strategy was verified by the experiment. Within a suitable range of dose levels, increasing the doses resulted in reduced high-frequency noise component and significantly increased SNR (P < 0.05). But when the value of exposure was below 40 mAs, the images acquired at different dose levels had similar representation. The performance of the 3 reconstruction algorithms varied for different anatomical structures, and the image quality of ASDPOCS-TV algorithm was generally superior to SART and FDK algorithms with less through-plane artifacts and noise.

OBJECTIVE

The quality of DBT images is significantly affected by both radiation dose and reconstruction algorithms. A tradeoff of the parameters, the overall image quality and the clinical needs for diagnostic purposes should be considered to achieve the optimal imaging performance on a given clinical task.

Digital Breast Tomosynthesis: an Overview

Breast cancer is emerging as the most common malignancy in Indian women. Mammography is one of the few screening modalities available to the modern world that has proved itself of much use by aiding early detection and treatment of non-palpable, node-negative breast cancers. However, due to its two-dimensional nature, many cases of malignancies are still missed, to be detected at a later date or by an alternate modality. In 2011, FDA approved the supplemental use of digital breast tomosynthesis (DBT) in screening and diagnostic set ups. The acquisition of multiple low-dose projection images of the compressed parenchyma provided a 'third' dimension to the mammogram whereby the breast tissue could be seen layer by layer on the workstation. It improves cancer detection rate, and reduces recall rate and false-positive findings by improving lesion characterization. The current review discusses the principle of DBT with a comprehensive study of the literature.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13193-021-01310-y.

An Enhanced Visualization of DBT Imaging Using Blind Deconvolution and Total Variation Minimization Regularization

Digital Breast Tomosynthesis (DBT) presents out-of-plane artifacts caused by features of high intensity. Given observed data and knowledge about the point spread function (PSF), deconvolution techniques recover data from a blurred version. However, a correct PSF is difficult to achieve and these methods amplify noise. When no information is available about the PSF, blind deconvolution can be used. Additionally, Total Variation (TV) minimization algorithms have achieved great success due to its virtue of preserving edges while reducing image noise. This work presents a novel approach in DBT through the study of out-of-plane artifacts using blind deconvolution and noise regularization based on TV minimization. Gradient information was also included. The methodology was tested using real phantom data and one clinical data set. The results were investigated using conventional 2D slice-by-slice visualization and 3D volume rendering. For the 2D analysis, the artifact spread function (ASF) and Full Width at Half Maximum (FWHMM_ASF) of the ASF were considered. The 3D quantitative analysis was based on the FWHM of disks profiles at 90°, noise and signal to noise ratio (SNR) at 0° and 90°. A marked visual decrease of the artifact with reductions of FWHM_ASF (2D) and FWHM_90° (volume rendering) of 23.8% and 23.6%, respectively, was observed. Although there was an expected increase in noise level, SNR values were preserved after deconvolution. Regardless of the methodology and visualization approach, the objective of reducing the out-of-plane artifact was accomplished. Both for the phantom and clinical case, the artifact reduction in the z was markedly visible.

APRICOT: Advanced Platform for Reproducible Infrastructures in the Cloud via Open Tools

Background  Scientific publications are meant to exchange knowledge among researchers but the inability to properly reproduce computational experiments limits the quality of scientific research. Furthermore, bibliography shows that irreproducible preclinical research exceeds 50%, which produces a huge waste of resources on nonprofitable research at Life Sciences field. As a consequence, scientific reproducibility is being fostered to promote Open Science through open databases and software tools that are typically deployed on existing computational resources. However, some computational experiments require complex virtual infrastructures, such as elastic clusters of PCs, that can be dynamically provided from multiple clouds. Obtaining these infrastructures requires not only an infrastructure provider, but also advanced knowledge in the cloud computing field.

Objectives  The main aim of this paper is to improve reproducibility in life sciences to produce better and more cost-effective research. For that purpose, our intention is to simplify the infrastructure usage and deployment for researchers.

Methods  This paper introduces Advanced Platform for Reproducible Infrastructures in the Cloud via Open Tools (APRICOT), an open source extension for Jupyter to deploy deterministic virtual infrastructures across multiclouds for reproducible scientific computational experiments. To exemplify its utilization and how APRICOT can improve the reproduction of experiments with complex computation requirements, two examples in the field of life sciences are provided. All requirements to reproduce both experiments are disclosed within APRICOT and, therefore, can be reproduced by the users.

Results  To show the capabilities of APRICOT, we have processed a real magnetic resonance image to accurately characterize a prostate cancer using a Message Passing Interface cluster deployed automatically with APRICOT. In addition, the second example shows how APRICOT scales the deployed infrastructure, according to the workload, using a batch cluster. This example consists of a multiparametric study of a positron emission tomography image reconstruction.

Conclusion  APRICOT's benefits are the integration of specific infrastructure deployment, the management and usage for Open Science, making experiments that involve specific computational infrastructures reproducible. All the experiment steps and details can be documented at the same Jupyter notebook which includes infrastructure specifications, data storage, experimentation execution, results gathering, and infrastructure termination. Thus, distributing the experimentation notebook and needed data should be enough to reproduce the experiment.

GPU acceleration of a model-based iterative method for Digital Breast Tomosynthesis

Digital Breast Tomosynthesis (DBT) is a modern 3D Computed Tomography X-ray technique for the early detection of breast tumors, which is receiving growing interest in the medical and scientific community. Since DBT performs incomplete sampling of data, the image reconstruction approaches based on iterative methods are preferable to the classical analytic techniques, such as the Filtered Back Projection algorithm, providing fewer artifacts. In this work, we consider a Model-Based Iterative Reconstruction (MBIR) method well suited to describe the DBT data acquisition process and to include prior information on the reconstructed image. We propose a gradient-based solver named Scaled Gradient Projection (SGP) for the solution of the constrained optimization problem arising in the considered MBIR method. Even if the SGP algorithm exhibits fast convergence, the time required on a serial computer for the reconstruction of a real DBT data set is too long for the clinical needs. In this paper we propose a parallel SGP version designed to perform the most expensive computations of each iteration on Graphics Processing Unit (GPU). We apply the proposed parallel approach on three different GPU boards, with computational performance comparable with that of the boards usually installed in commercial DBT systems. The numerical results show that the proposed GPU-based MBIR method provides accurate reconstructions in a time suitable for clinical trials.

A collection input based support tensor machine for lesion malignancy classification in digital breast tomosynthesis

Digital breast tomosynthesis (DBT) with improved lesion conspicuity and characterization has been adopted in screening practice. DBT-based diagnosis strongly depends on physicians' experience, so an automatic lesion malignancy classification model using DBT could improve the consistency of diagnosis among different physicians. Tensor-based approaches that use the original imaging data as input have shown promising results for many classification tasks. However, DBT data are pseudo-3D volumetric imaging as the slice spacing of DBT is much coarser than that of the in-plane resolution. Thus, directly constructing DBT as the third-order tensor in a conventional tensor-based classifier with introducing additional information to the original DBT data along the slice-spacing dimension will lead to inconsistency across all three dimensions. To avoid such inconsistency, we introduce a collection input based support tensor machine (CISTM)-based classifier that uses the tensor collection as input for classifying lesion malignancy in DBT. In CISTM, instead of introducing the third dimension directly into the geometry construction, the third-dimension structural relationship is related by weight parameters in the decision function, which is dynamically and automatically constructed during the classifier training process and is more consistent with the pseudo-3D nature of DBT. We tested our method on a DBT dataset of 926 images among which 262 were malignant and 664 were benign. We compared our method with the latest tensor-based method, KSTM (kernelled support tensor machine), which does not consider the unique non-uniform resolution property of DBT. Experimental results illustrate that the CISTM-based classifier is effective for classifying breast lesion malignancy in DBT and that it outperforms the KSTM-based classifier.

Svahn T. Evaluation of a new image reconstruction method for digital breast tomosynthesis: effects on the visibility of breast lesions and breast density

OBJECTIVE

To compare image quality and breast density of two reconstruction methods, the widely-used filtered-back projection (FBP) reconstruction and the iterative heuristic Bayesian inference reconstruction (Bayesian inference reconstruction plus the method of total variation applied, HBI).

METHODS

Thirty-two clinical DBT data sets with malignant and benign findings, n = 27 and 17, respectively, were reconstructed using FBP and HBI. Three experienced radiologists evaluated the images independently using a 5-point visual grading scale and classified breast density according to the American College of Radiology Breast Imaging-Reporting And Data System Atlas, fifth edition. Image quality metrics included lesion conspicuity, clarity of lesion borders and spicules, noise level, artifacts surrounding the lesion, visibility of parenchyma and breast density.

RESULTS

For masses, the image quality of HBI reconstructions was superior to that of FBP in terms of conspicuity,clarity of lesion borders and spicules (p < 0.01). HBI and FBP were not significantly different in calcification conspicuity. Overall, HBI reduced noise and supressed artifacts surrounding the lesions better (p < 0.01). The visibility of fibroglandular parenchyma increased using the HBI method (p < 0.01). On average, five cases per radiologist were downgraded from BI-RADS breast density category C/D to A/B.

CONCLUSION

HBI significantly improves lesion visibility compared to FBP. HBI-visibility of breast parenchyma increased, leading to a lower breast density rating. Applying the HBIR algorithm should improve the diagnostic performance of DBT and decrease the need for additional imaging in patients with dense breasts.

ADVANCES IN KNOWLEDGE

Iterative heuristic Bayesian inference (HBI) image reconstruction substantially improves the image quality of breast tomosynthesis leading to a better visibility of breast carcinomas and reduction of the perceived breast density compared to the widely-used filtered-back projection (FPB) reconstruction. Applying HBI should improve the accuracy of breast tomosynthesis and reduce the number of unnecessary breast biopsies. It may also reduce the radiation dose for the patients, which is especially important in the screening context.

Effect of source blur on digital breast tomosynthesis reconstruction

PURPOSE

Most digital breast tomosynthesis (DBT) reconstruction methods neglect the blurring of the projection views caused by the finite size or motion of the x-ray focal spot. This paper studies the effect of source blur on the spatial resolution of reconstructed DBT using analytical calculation and simulation, and compares the influence of source blur over a range of blurred source sizes.

METHODS

Mathematically derived formulas describe the point spread function (PSF) of source blur on the detector plane as a function of the spatial locations of the finite-sized source and the object. By using the available technical parameters of some clinical DBT systems, we estimated the effective source sizes over a range of exposure time and DBT scan geometries. We used the CatSim simulation tool (GE Global Research, NY) to generate digital phantoms containing line pairs and beads at different locations and imaged with sources of four different sizes covering the range of potential source blur. By analyzing the relative contrasts of the test objects in the reconstructed images, we studied the effect of the source blur on the spatial resolution of DBT. Furthermore, we simulated a detector that rotated in synchrony with the source about the rotation center and calculated the spatial distribution of the blurring distance in the imaged volume to estimate its influence on source blur.

RESULTS

Calculations demonstrate that the PSF is highly shift-variant, making it challenging to accurately implement during reconstruction. The results of the simulated phantoms demonstrated that a typical finite-sized focal spot (~0.3 mm) will not affect the reconstructed image resolution if the x-ray tube is stationary during data acquisition. If the x-ray tube moves during exposure, the extra blur due to the source motion may degrade image resolution, depending on the effective size of the source along the direction of the motion. A detector that rotates in synchrony with the source does not reduce the influence of source blur substantially.

CONCLUSIONS

This study demonstrates that the extra source blur due to the motion of the x-ray tube during image acquisition substantially degrades the reconstructed image resolution. This effect cannot be alleviated by rotating the detector in synchrony with the source. The simulation results suggest that there are potential benefits of modeling the source blur in image reconstruction for DBT systems using continuous-motion acquisition mode.

A phantom study comparing technical image quality of five breast tomosynthesis systems

BACKGROUND

Digital breast tomosynthesis (DBT) is a three-dimensional breast imaging method. DBT vendors employ various approaches in both image acquisition and data processing, which may affect image quality and radiation exposure to patients.

OBJECTIVE

This study aimed to evaluate the performance of five DBT systems: Fujifilm Amulet Innovality (using both a standard mode and high-resolution mode), GE Senographe Essential, Hologic Selenia Dimensions, Planmed Clarity 3D, and Siemens Mammomat Inspiration.

MATERIALS AND METHODS

The performance of each device and imaging technique was evaluated and compared by phantom measurements performed with four quality assurance phantoms. Technical image quality assessments consisted of measuring artefact extent, in-plane resolution, relative noise power spectrum, and geometric accuracy.

RESULTS

Artefact spreading varied remarkably between the devices, and the full width at half maximum values of artefact spread functions varied from 3.5 mm to 10.7 mm. Noticeable in-plane resolution anisotropy, determined using modulation transfer function (MTF) analysis, was typically observed between tube travel direction and chest wall-nipple direction. The MTF₅₀ varied from 1.1 mm^-1 to 1.6 mm^-1 and from 1.5 mm^-1 to 4.1 mm^-1 in the tube travel and chest wall-nipple directions, respectively. Moreover, distinctly different noise power spectra were observed between the systems. The geometric accuracy in every system was within 0.5%.

CONCLUSION

Technical image quality assessments with image quality phantoms revealed remarkable differences in artefact spread, in-plane resolution, and noise properties between the DBT systems and imaging methods.

Digital Breast Tomosynthesis: Physics, Artifacts, and Quality Control Considerations

As digital breast tomosynthesis (DBT) becomes widely used, radiologists must understand the basic principles of (a) image acquisition, (b) artifacts, and (c) quality control (QC) that are specific to DBT. Standard acquisition parameters common to both full-field digital mammography (FFDM) and DBT are combinations of x-ray tube voltage, current exposure time, and anode target and filter combinations. Image acquisition parameters specific to DBT include tube motion, sweep angle, and number of projections. Continuous tube motion or x-ray emission decreases imaging time but leads to focal spot blurring when compared with step-and-shoot techniques. The sweep angle and number of projections determines resolution. Wider sweep angles allow greater out-of-plane (z-axis) resolution, improving visualization of masses and architecture distortion. A greater number of projections increases in-plane or x-y axis resolution, improving visualization of microcalcifications. Artifacts related to DBT include blurring-ripple, truncation, and loss of skin and superficial tissue resolution. Motion artifacts are difficult to recognize because of inherent out-of-plane blurring. To maintain optimal image quality and an "as low as reasonably achievable" (ALARA) radiation dose, regular QC must be performed. DBT is considered a new imaging modality; therefore, breast imaging facilities are required to obtain a separate certification in addition to that in FFDM, and all personnel (radiologists, technologists, and medical physicists) are mandated to complete initial DBT training and maintain appropriate continuing medical education credits. ^©RSNA, 2019.

Imaging of fiber-like structures in digital breast tomosynthesis

Fiber-like features are an important aspect of breast imaging. Vessels and ducts are present in all breast images, and spiculations radiating from a mass can indicate malignancy. Accordingly, fiber objects are one of the three types of signals used in the American College of Radiology digital mammography (ACR-DM) accreditation phantom. Our work focuses on the image properties of fiber-like structures in digital breast tomosynthesis (DBT) and how image reconstruction can affect their appearance. The impact of DBT image reconstruction algorithm and regularization strength on the conspicuity of fiber-like signals of various orientations is investigated in simulation. A metric is developed to characterize this orientation dependence and allow for quantitative comparison of algorithms and associated parameters in the context of imaging fiber signals. The imaging properties of fibers, characterized in simulation, are then demonstrated in detail with physical DBT data of the ACR-DM phantom. The characterization of imaging of fiber signals is used to explain features of an actual clinical DBT case. For the algorithms investigated, at low regularization setting, the results show a striking variation in conspicuity as a function of orientation in the viewing plane. In particular, the conspicuity of fibers nearly aligned with the plane of the x-ray source trajectory is decreased relative to more obliquely oriented fibers. Increasing regularization strength mitigates this orientation dependence at the cost of increasing depth blur of these structures.

The threshold detectable mass diameter for 2D-mammography and digital breast tomosynthesis

Digital breast tomosynthesis (DBT) is currently under consideration for replacement of, or combined use with 2D-mammography in national breast screening programmes. To investigate the potential benefits that DBT can bring to screening, the threshold detectable lesion diameters were measured for different forms of DBT in comparison to 2D-mammography. The aim of this study was to compare the threshold detectable mass diameters obtained with narrow angle (15°/15 projections) and wide angle (50°/25 projections) DBT in comparison to 2D-mammography. Simulated images of 60 mm thick compressed breasts were produced with and without masses using a set of validated image modelling tools for 2D-mammography and DBT. Image processing and reconstruction were performed using commercial software. A series of 4-alternative forced choice (4AFC) experiments was conducted for signal detection with the masses as targets. The threshold detectable mass diameter was found for each imaging modality with a mean glandular dose of 2.5 mGy. The resulting values of the threshold diameter for 2D-mammography (10.2 ± 1.4 mm) were found to be larger (p < 0.001) than those for narrow angle DBT (6.0 ± 1.1 mm) and wide angle DBT (5.6 ± 1.2 mm). There was no significant difference between the threshold diameters for wide and narrow angle DBT. Implications for the introduction of DBT alone or in combination with 2D-mammography in breast cancer screening are discussed.

PHYSICAL CHARACTERISATION OF FOUR DIFFERENT COMMERCIAL DIGITAL BREAST TOMOSYNTHESIS SYSTEMS

The aim of this article was to characterise the performance of four different digital breast tomosynthesis (DBT) systems in terms of dose and image quality parameters. One of them, GE Pristina, has never been tested before. Average glandular doses were measured both in DBT and 2D full field digital mammography mode. Several phantoms were employed to perform signal difference to noise ratio, slice sensitivity profile, slice to slice incrementation, chest wall offset, z-axis geometry, artefact spread function, low contrast detectability, contrast detail evaluations, image uniformity and in-plane MTF in chest wall-nipple and in tube-travel directions. There are many differences in DBT systems explored: the angular range, detector type, reconstruction algorithms, and the presence or not of the grid. Even if it is not simple to calculate a global figure of merit, the analysis of all the collected data can be useful in a contest of a quality assurance program to define a set of values that could be used as benchmarks.

Variations in slice sensitivity profile for various height settings in tomosynthesis imaging: Phantom study

Understanding the properties of slice sensitivity profile (SSP), or slice thickness, is crucial for an accurate and highly reproducible diagnosis using tomosynthesis imaging. The objectives of the present study are therefore to quantitatively evaluate how the SSP with the use of a small metal bead is affected by different settings of the height from the table and the height of the center of rotation (COR) in tomosynthesis imaging except for the digital breast tomosynthesis, and visually verify the effects on tomosynthesis images. The reconstruction filters used were three types of filtered back-projection and iterative reconstructions. The SSP was measured from the full width at half maximum (FWHM-SSP) of the profile curve of the bead in the perpendicular direction (z direction) relative to the table. Two types of anthropomorphic phantoms simulating the human body, with bones and soft tissues, were used to study the effects of different settings for the COR height. In all reconstruction filters, the FWHM-SSP changed as the height of the bead varied when the bead and COR were set to the same height from the table. If the bead and the COR were set to different heights, the FWHM-SSP increased (decreased) when the height of the bead was set to be greater (less) than the height of the COR. These changes were also confirmed on the anthropomorphic phantom images of the bones and soft tissues.

Investigating simulation-based metrics for characterizing linear iterative reconstruction in digital breast tomosynthesis

PURPOSE

Simulation-based image quality metrics are adapted and investigated for characterizing the parameter dependences of linear iterative image reconstruction for DBT.

METHODS

Three metrics based on a 2D DBT simulation are investigated: (1) a root-mean-square-error (RMSE) between the test phantom and reconstructed image, (2) a gradient RMSE where the comparison is made after taking a spatial gradient of both image and phantom, and (3) a region-of-interest (ROI) Hotelling observer (HO) for signal-known-exactly/background-known-exactly (SKE/BKE) and signal-known-exactly/background-known-statistically (SKE/BKS) detection tasks. Two simulation studies are performed using the aforementioned metrics, varying voxel aspect ratio, and regularization strength for two types of Tikhonov-regularized least-squares optimization. The RMSE metrics are applied to a 2D test phantom with resolution bar patterns at varying angles, and the ROI-HO metric is applied to two tasks relevant to DBT: lesion detection, modeled by use of a large, low-contrast signal, and microcalcification detection, modeled by use of a small, high-contrast signal. The RMSE metric trends are compared with visual assessment of the reconstructed bar-pattern phantom. The ROI-HO metric trends are compared with 3D reconstructed images from ACR phantom data acquired with a Hologic Selenia Dimensions DBT system.

RESULTS

Sensitivity of the image RMSE to mean pixel value is found to limit its applicability to the assessment of DBT image reconstruction. The image gradient RMSE is insensitive to mean pixel value and appears to track better with subjective visualization of the reconstructed bar-pattern phantom. The ROI-HO metric shows an increasing trend with regularization strength for both forms of Tikhonov-regularized least-squares; however, this metric saturates at intermediate regularization strength indicating a point of diminishing returns for signal detection. Visualization with the reconstructed ACR phantom images appear to show a similar dependence with regularization strength.

CONCLUSIONS

From the limited studies presented it appears that image gradient RMSE trends correspond with visual assessment better than image RMSE for DBT image reconstruction. The ROI-HO metric for both detection tasks also appears to reflect visual trends in the ACR phantom reconstructions as a function of regularization strength. We point out, however, that the true utility of these metrics can only be assessed after amassing more data.

Physics considerations in MV-CBCT multi-layer imager design

Megavoltage (MV) cone-beam computed tomography (CBCT) using an electronic portal imaging (EPID) offers advantageous features, including 3D mapping, treatment beam registration, high-z artifact suppression, and direct radiation dose calculation. Adoption has been slowed by image quality limitations and concerns about imaging dose. Developments in imager design, including pixelated scintillators, structured phosphors, inexpensive scintillation materials, and multi-layer imager (MLI) architecture have been explored to improve EPID image quality and reduce imaging dose. The present study employs a hybrid Monte Carlo and linear systems model to determine the effect of detector design elements, such as multi-layer architecture and scintillation materials. We follow metrics of image quality including modulation transfer function (MTF) and noise power spectrum (NPS) from projection images to 3D reconstructions to in-plane slices and apply a task based figure-of-merit, the ideal observer signal-to-noise ratio (d') to determine the effect of detector design on object detectability. Generally, detectability was limited by detector noise performance. Deploying an MLI imager with a single scintillation material for all layers yields improvement in noise performance and d' linear with the number of layers. In general, improving x-ray absorption using thicker scintillators results in improved DQE(0). However, if light yield is low, performance will be affected by electronic noise at relatively high doses, resulting in rapid image quality degradation. Maximizing image quality in a heterogenous MLI detector (i.e. multiple different scintillation materials) is most affected by limiting total noise. However, while a second-order effect, maximizing total spatial resolution of the MLI detector is a balance between the intensity contribution of each layer against its individual MTF. So, while a thinner scintillator may yield a maximal individual-layer MTF, its quantum efficiency will be relatively low in comparison to a thicker scintillator and thus, intensity contribution may be insufficient to noticeably improve the total detector MTF.

Accuracy of Digital Tomosynthesis With Metal Artifact Reduction for Detecting Osteointegration in Cementless Hip Arthroplasty

BACKGROUND

Cementless hip arthroplasty is increasingly gaining popularity worldwide. Radiologic identification of osteointegration is key to confirming biologic fixation. We conducted the study reported here to determine the sensitivity and specificity of digital tomosynthesis with metal artifact reduction (TMAR), radiography, and conventional computed tomography in detecting osteointegration in cementless hip arthroplasty.

METHODS

We prospectively included data for 24 patients who underwent revision hip arthroplasty in our hospital, with 13 femoral and 14 acetabular cementless components retrieved that contained solid evidence of biologic fixation. All patients underwent 3 examinations before surgery, and evidence of osteointegration on retrieved prostheses was used as the reference standard. Seven orthopedic surgeons evaluated these images independently using uniform criteria.

RESULTS

On the femoral side, the sensitivity and specificity of detecting osteointegration were 73.8% ± 4.6% and 94.3% ± 1.5%, respectively, for TMAR; 50.4% ± 5.3% and 87.8% ± 2.1%, respectively, for radiography; and 36.4% ± 5.1% and 90.9% ± 1.9%, respectively, for CT. On the cup side, the corresponding values were 60.2% ± 8.3% and 86.4% ± 5.7%, respectively, for TMAR; 45.9% ± 8.5% and 66.4% ± 7.8%, respectively, for radiography; and 45.1% ± 8.5% and 73.5% ± 7.3%, respectively, by computed tomography.

CONCLUSION

TMAR significantly improved the accuracy osteointegration detection in cementless hip arthroplasty (P < .017).

Reduced anatomical clutter in digital breast tomosynthesis with statistical iterative reconstruction

PURPOSE

Digital breast tomosynthesis (DBT) has been shown to somewhat alleviate the breast tissue overlapping issues of two-dimensional (2D) mammography. However, the improvement in current DBT systems over mammography is still limited. Statistical image reconstruction (SIR) methods have the potential to reduce through-plane artifacts in DBT, and thus may be used to further reduce anatomical clutter. The purpose of this work was to study the impact of SIR on anatomical clutter in the reconstructed DBT image volumes.

METHODS

An SIR with a slice-wise total variation (TV) regularizer was implemented to reconstruct DBT images which were compared with the clinical reconstruction method (filtered backprojection). The artifact spread function (ASF) was measured to quantify the reduction of the through-plane artifacts level in phantom studies and microcalcifications in clinical cases. The anatomical clutter was quantified by the anatomical noise power spectrum with a power law fitting model: NPSa ( f) = α f-β . The β values were measured from the reconstructed image slices when the two reconstruction methods were applied to a cohort of clinical breast exams (N = 101) acquired using Hologic Selenia Dimensions DBT systems.

RESULTS

The full width half maximum (FWHM) of the measured ASF was reduced from 8.7 ± 0.1 mm for clinical reconstruction to 6.5 ± 0.1 mm for SIR which yields a 25% reduction in FWHM in phantom studies and the same amount of ASF reduction was also found in clinical measurements from microcalcifications. The measured β values for the two reconstruction methods were 3.17 ± 0.36 and 2.14 ± 0.39 for the clinical reconstruction method and the SIR method, respectively. This difference was statistically significant (P << 0.001). The dependence of β on slice location using either method was negligible.

CONCLUSIONS

Statistical image reconstruction enabled a significant reduction of both the through-plane artifacts level and anatomical clutter in the DBT reconstructions. The β value was found to be β≈2.14 with the SIR method. This value stays in the middle between the β≈1.8 for cone beam CT and β≈3.2 for mammography. In contrast, the measured β value in the clinical reconstructions (β≈3.17) remains close to that of mammography.

Design and development of a phantom for tomosynthesis with potential for automated analysis via the cloud

This paper describes Development of a Phantom for Tomosynthesis with Potential for Automated Analysis via the Cloud. Several studies are underway to investigate the effectiveness of Tomosynthesis Mammographic Image Screening, including the large TMIST project as funded by the National Cancer Institute https://www.cancer.gov/about-cancer/treatment/clinical-trials/nci-supported/tmist. The development of the phantom described in this paper follows initiatives from the FDA, the AAPM TG245 task group, and European Reference Organization (EUREF) for Quality Assured Breast Screening and Diagnostic Services Committee report noting, that no formal endorsement nor recommendation for use has been sought, or granted by any of these groups. This paper reports on the possibility of using this newly developed Tomosynthesis Phantom for Quality Assurance, field testing of image performance, including remote monitoring of DBT system performance, e.g., via transmission over the cloud. The phantom includes tests for: phantom positioning and alignment (important for remote analysis), scan geometry (x and y), chest wall offset, scan slice width and Slice Sensitivity Profile (SSP(z)) slice geometry (slice width), scan slice incrementation (z), z axis geometry bead, low contrast detectability using low contrast spheres, spatial resolution via Point Spread Function (PSF), Image uniformity, Signal to Noise Ratio (SNR), and Contrast to Noise Ratio (CNR) via readings over an Aluminum square. The phantom is designed for use with automated analysis via transmission of images over the cloud and the analysis package includes test of positioning accuracy (roll, pitch, and yaw). Data are shown from several commercial Tomosynthesis Scanners including Fuji, GE, Hologic, IMS‐Giotti, and Siemens; however, the focus of this paper is on phantom design, and not in general aimed at direct commercial comparisons, and wherever possible the identity of the data is anonymized. Results of automated analysis of the phantom are shown, and it is demonstrated that reliable analysis of such a phantom can be achieved remotely, including transmission of data through the cloud.

Leveraging multi-layer imager detector design to improve low-dose performance for megavoltage cone-beam computed tomography

While megavoltage cone-beam computed tomography (CBCT) using an electronic portal imaging device (EPID) provides many advantages over kilovoltage (kV) CBCT, clinical adoption is limited by its high doses. Multi-layer imager (MLI) EPIDs increase DQE(0) while maintaining high resolution. However, even well-designed, high-performance MLIs suffer from increased electronic noise from each readout, degrading low-dose image quality. To improve low-dose performance, shift-and-bin addition (ShiBA) imaging is proposed, leveraging the unique architecture of the MLI. ShiBA combines hardware readout-binning and super-resolution concepts, reducing electronic noise while maintaining native image sampling. The imaging performance of full-resolution (FR); standard, aligned binned (BIN); and ShiBA images in terms of noise power spectrum (NPS), electronic NPS, modulation transfer function (MTF), and the ideal observer signal-to-noise ratio (SNR)-the detectability index (d')-are compared. The FR 4-layer readout of the prototype MLI exhibits an electronic NPS magnitude 6-times higher than a state-of-the-art single layer (SLI) EPID. Although the MLI is built on the same readout platform as the SLI, with each layer exhibiting equivalent electronic noise, the multi-stage readout of the MLI results in electronic noise 50% higher than simple summation. Electronic noise is mitigated in both BIN and ShiBA imaging, reducing its total by ~12 times. ShiBA further reduces the NPS, effectively upsampling the image, resulting in a multiplication by a sinc² function. Normalized NPS show that neither ShiBA nor BIN otherwise affects image noise. The LSF shows that ShiBA removes the pixilation artifact of BIN images and mitigates the effect of detector shift, but does not quantifiably improve the MTF. ShiBA provides a pre-sampled representation of the images, mitigating phase dependence. Hardware binning strategies lower the quantum noise floor, with 2  ×  2 implementation reducing the dose at which DQE(0) degrades by 10% from 0.01 MU to 0.004 MU, representing 20% improvement in d'.

Virtual assessment of stereoscopic viewing of digital breast tomosynthesis projection images

Digital breast tomosynthesis (DBT) acquires a series of projection images from different angles as an x-ray source rotates around the breast. Such imaging geometry lends DBT naturally to stereoscopic viewing as two projection images with a reasonable separation angle can easily form a stereo pair. This simulation study assessed the efficacy of stereo viewing of DBT projection images. Three-dimensional computational breast phantoms with realistically shaped synthetic lesions were scanned by three simulated DBT systems. The projection images were combined into a sequence of stereo pairs and presented to a stereomatching-based model observer for deciding lesion presence. Signal-to-noise ratio was estimated, and the detection performance with stack viewing of reconstructed slices was the benchmark. We have shown that: (1) stereo viewing of projection images may underperform stack viewing of reconstructed slices for current DBT geometries; (2) DBT geometries may impact the efficacy of the two viewing modes differently: narrow-arc and wide-arc geometries may be better for stereo viewing and stack viewing, respectively; (3) the efficacy of stereo viewing may be more robust than stack viewing to reductions in dose. While in principle stereo viewing is potentially effective for visualizing DBT data, effective stereo viewing may require specifically optimized DBT image acquisition.

Detector Blur and Correlated Noise Modeling for Digital Breast Tomosynthesis Reconstruction

This paper describes a new image reconstruction method for digital breast tomosynthesis (DBT). The new method incorporates detector blur into the forward model. The detector blur in DBT causes correlation in the measurement noise. By making a few approximations that are reasonable for breast imaging, we formulated a regularized quadratic optimization problem with a data-fit term that incorporates models for detector blur and correlated noise (DBCN). We derived a computationally efficient separable quadratic surrogate (SQS) algorithm to solve the optimization problem that has a non-diagonal noise covariance matrix. We evaluated the SQS-DBCN method by reconstructing DBT scans of breast phantoms and human subjects. The contrast-to-noise ratio and sharpness of microcalcifications were analyzed and compared with those by the simultaneous algebraic reconstruction technique. The quality of soft tissue lesions and parenchymal patterns was examined. The results demonstrate the potential to improve the image quality of reconstructed DBT images by incorporating the system physics model. This paper is a first step toward model-based iterative reconstruction for DBT.

Second generation stationary digital breast tomosynthesis system with faster scan time and wider angular span

PURPOSE

The aim of this study was to characterize a new generation stationary digital breast tomosynthesis system with higher tube flux and increased angular span over a first generation system.

METHODS

The linear CNT x-ray source was designed, built, and evaluated to determine its performance parameters. The second generation system was then constructed using the CNT x-ray source and a Hologic gantry. Upon construction, test objects and phantoms were used to characterize system resolution as measured by the modulation transfer function (MTF), and artifact spread function (ASF).

RESULTS

The results indicated that the linear CNT x-ray source was capable of stable operation at a tube potential of 49 kVp, and measured focal spot sizes showed source-to-source consistency with a nominal focal spot size of 1.1 mm. After construction, the second generation (Gen 2) system exhibited entrance surface air kerma rates two times greater the previous s-DBT system. System in-plane resolution as measured by the MTF is 7.7 cycles/mm, compared to 6.7 cycles/mm for the Gen 1 system. As expected, an increase in the z-axis depth resolution was observed, with a decrease in the ASF from 4.30 mm to 2.35 mm moving from the Gen 1 system to the Gen 2 system as result of an increased angular span.

CONCLUSIONS

The results indicate that the Gen 2 stationary digital breast tomosynthesis system, which has a larger angular span, increased entrance surface air kerma, and faster image acquisition time over the Gen 1 s-DBT system, results in higher resolution images. With the detector operating at full resolution, the Gen 2 s-DBT system can achieve an in-plane resolution of 7.7 cycles per mm, which is better than the current commercial DBT systems today, and may potentially result in better patient diagnosis.

The effect of system geometry and dose on the threshold detectable calcification diameter in 2D-mammography and digital breast tomosynthesis

Digital breast tomosynthesis (DBT) is under consideration to replace or to be used in combination with 2D-mammography in breast screening. The aim of this study was the comparison of the detection of microcalcification clusters by human observers in simulated breast images using 2D-mammography, narrow angle (15°/15 projections) and wide angle (50°/25 projections) DBT. The effects of the cluster height in the breast and the dose to the breast on calcification detection were also tested. Simulated images of 6 cm thick compressed breasts were produced with and without microcalcification clusters inserted, using a set of image modelling tools for 2D-mammography and DBT. Image processing and reconstruction were performed using commercial software. A series of 4-alternative forced choice (4AFC) experiments was conducted for signal detection with the microcalcification clusters as targets. Threshold detectable calcification diameter was found for each imaging modality with standard dose: 2D-mammography: 2D-mammography (165  ±  9 µm), narrow angle DBT (211  ±  11 µm) and wide angle DBT (257  ±  14 µm). Statistically significant differences were found when using different doses, but different geometries had a greater effect. No differences were found between the threshold detectable calcification diameters at different heights in the breast. Calcification clusters may have a lower detectability using DBT than 2D imaging.

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

PURPOSE

Contrast-enhanced (CE) breast imaging involves the injection contrast agents (i.e., iodine) to increase conspicuity of malignant lesions. CE imaging may be used in conjunction with digital mammography (DM) or digital breast tomosynthesis (DBT) and has shown promise in improving diagnostic specificity. Both CE-DM and CE-DBT techniques require optimization as clinical diagnostic tools. Physical factors including x-ray spectra, subtraction technique, and the signal from iodine contrast, must be considered to provide the greatest object detectability and image quality. We developed a cascaded linear system model (CLSM) for the optimization of CE-DM and CE-DBT employing dual energy (DE) subtraction or temporal (TE) subtraction.

METHODS

We have previously developed a CLSM for DBT implemented with an a-Se flat panel imager (FPI) and filtered backprojection (FBP) reconstruction algorithm. The model is used to track image quality metrics - modulation transfer function (MTF) and noise power spectrum (NPS) - at each stage of the imaging chain. In this study, the CLSM is extended for CE breast imaging. The effect of x-ray spectrum (varied by changing tube potential and the filter) and DE and TE subtraction techniques on breast structural noise was measured was studied and included as a deterministic source of noise in the CLSM. From the two-dimensional (2D) and three-dimensional (3D) MTF and NPS, the ideal observer signal-to-noise ratio (SNR), also known as the detectability index (d'), may be calculated. Using d' as a FOM, we discuss the optimization of CE imaging for the task of iodinated contrast object detection within structured backgrounds.

RESULTS

Increasing x-ray energy was determined to decrease the magnitude of structural noise and not its correlation. By performing DE subtraction, the magnitude of the structural noise was further reduced at the expense of increased stochastic (quantum and electronic) noise. TE subtraction exhibited essentially no residual structural noise at the expense of increased quantum noise, even over that of the DE case. For DE subtraction, optimization of dose weighting to the HE view (f_h ) results in the minimization of quantum noise. Both subtraction weighting factor (w_Sub ) and the iodine contrast signal were dependent on the LE and HE x-ray spectra. To best detect a 5 mm Gaussian lesion with 5 mg/ml of iodine within a 4 cm thick breast, it was found that the high energy (HE) view should be acquired with a tube potential of 47 kVp (W/Ti spectrum) and the low energy (LE) view with a potential of 23 kVp (W/Rh spectrum). Due to the complete removal of structural noise, TE subtraction produced much higher d' than DE subtraction both as a function of mean glandular dose and iodine concentration.

CONCLUSIONS

We have shown the effect of increasing x-ray energy as well as projection domain subtraction on breast structural noise. Further, we have exhibited the utility of the CLSM for DE and TE subtraction CE imaging in the optimization of imaging parameters such as x-ray energy, f_h , and w_Sub as well as guiding the understanding of their effects on image contrast and noise.

Digital breast tomosynthesis: Dose and image quality assessment

The aim of this work was to evaluate how different acquisition geometries and reconstruction parameters affect the performance of four digital breast tomosynthesis (DBT) systems (Senographe Essential - GE, Mammomat Inspiration - Siemens, Selenia Dimensions - Hologic and Amulet Innovality - Fujifilm) on the basis of a physical characterization. Average Glandular Dose (AGD) and image quality parameters such as in-plane/in-depth resolution, signal difference to noise ratio (SDNR) and artefact spread function (ASF) were examined. Measured AGD values resulted below EUREF limits for 2D imaging. A large variability was recorded among the investigated systems: the mean dose ratio DBT/2D ranged between 1.1 and 1.9. In-plane resolution was in the range: 2.2mm^-1-3.8mm^-1 in chest wall-nipple direction. A worse resolution was found for all devices in tube travel direction. In-depth resolution improved with increasing scan angle but was also affected by the choice of reconstruction and post-processing algorithms. The highest z-resolution was provided by Siemens (50°, FWHM=2.3mm) followed by GE (25°, FWHM=2.8mm), while the Fujifilm HR showed the lowest one, despite its wide scan angle (40°, FWHM=4.1mm). The ASF was dependent on scan angle: smaller range systems showed wider ASF curves; however a clear relationship was not found between scan angle and ASF, due to the different post processing and reconstruction algorithms. SDNR analysis, performed on Fujifilm system, demonstrated that pixel binning improves detectability for a fixed dose/projection. In conclusion, we provide a performance comparison among four DBT systems under a clinical acquisition mode.

VOLUMETRIC LOCALISATION OF DENSE BREAST TISSUE USING BREAST TOMOSYNTHESIS DATA

This study attempted to use combined data from reconstructed digital breast tomosynthesis (DBT) volumes and density estimation of projection images to localise dense tissue inside the breast, using the assumption that the breast can be treated as consisting of only two types of tissue: fibroglandular (dense) and adipose (fatty). To be able to verify results, software breast phantoms generated using fractal Perlin noise were employed. Projection images were created using the PENELOPE Monte Carlo package. Dense tissue volume was estimated from the central projection image. The density image was used to determine the number of dense voxels at each pixel location, which were then placed using the DBT image as a template. The method proved capable of accurately determining the composition of 75±5 % of voxels.

Digital Breast Tomosynthesis: State of the Art

This topical review on digital breast tomosynthesis (DBT) is provided with the intent of describing the state of the art in terms of technology, results from recent clinical studies, advanced applications, and ongoing efforts to develop multimodality imaging systems that include DBT. Particular emphasis is placed on clinical studies. The observations of increase in cancer detection rates, particularly for invasive cancers, and the reduction in false-positive rates with DBT in prospective trials indicate its benefit for breast cancer screening. Retrospective multireader multicase studies show either noninferiority or superiority of DBT compared with mammography. Methods to curtail radiation dose are of importance. (©) RSNA, 2015.

A Sphere Phantom Approach to Measure Directional Modulation Transfer Functions for Tomosynthesis Imaging Systems

We propose a sphere phantom approach to measure spatially varying directional modulation transfer functions (MTFs) for tomosynthesis imaging systems. Since the reconstructed tomosynthesis images contain significant artifacts, traditional background detrending techniques may not be effective to estimate the background trends accurately, which is essential to acquire sphere only data. A background detrending technique optimized for local volumes with different cone angles is presented. To measure directional MTFs, we calculate plane integrals of ideal sphere phantom and sphere only data. To minimize the effects of the high level of noise in tomosynthesis images, Richardson-Lucy deconvolution with Tikhonov-Miller is used to estimate directional plane spread function (PlSF). Then, directional MTFs are calculated by taking the modulus of the Fourier transform of the directional PlSFs. The measured directional MTFs are compared with the ideal directional MTFs calculated from a simulated point object. Our results show that the proposed method reliably measures directional MTFs along any desired directions, especially near low frequency regions.