Voting strategy for artifact reduction in digital breast tomosynthesis

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.

The Tomosynthesis Broken Halo Sign: Diagnostic Utility for the Classification of Newly Diagnosed Breast Tumors

BACKGROUND

Compared to conventional 2D mammography, digital breast tomosynthesis (DBT) offers greater breast lesion detection rates. Ring-like hypodense artifacts surrounding dense lesions are a common byproduct of DBT. This study's purpose was to assess whether minuscule changes spanning this halo-termed the "broken halo sign"-could improve lesion classification.

METHODS

This retrospective study was approved by the local ethics review board. After screening 288 consecutive patients, DBT studies of 191 female participants referred for routine mammography with a subsequent histologically verified finding of the breast were assessed. Examined variables included patient age, histological diagnosis, architectural distortion, maximum size, maximum halo depth, conspicuous margins, irregular shape and broken halo sign.

RESULTS

While a higher halo strength was indicative of malignancy in general (p = 0.031), the broken halo sign was strongly associated with malignancy (p < 0.0001, odds ratio (OR) 6.33), alongside architectural distortion (p = 0.012, OR 3.49) and a diffuse margin (p = 0.006, OR 5.49). This was especially true for denser breasts (ACR C/D), where the broken halo sign was the only factor predicting malignancy (p = 0.03, 5.22 OR).

CONCLUSION

DBT-associated halo artifacts warrant thorough investigation in newly found breast lesions as they are associated with malignant tumors. The "broken halo sign"-the presence of small lines of variable diameter spanning the peritumoral areas of hypodensity-is a strong indicator of malignancy, especially in dense breasts, where architectural distortion may be obfuscated due to the surrounding tissue.

A new projection correction based voting strategy for breast calcification artifact reduction

Objective.Digital Breast Tomosynthesis (DBT) is an imaging technique that combines traditional tomography with image processing and reconstruction techniques. In screening for breast cancer, high attenuation lesion will cause calcification hardening artifacts, which reduces the reconstructed image quality and limits diagnostic accuracy. We focus on the reconstruction artifacts that are caused by high-attenuation features in DBT, and aim to propose an efficient and accurate method to remove calcification artifacts and retain calcification information.Approach.The proposed method first introduces a new segmentation method, which can segment breast calcification accurately and effectively. Then an interpolation method is used to eliminate both the calcified area and artifact area in the projection images which are then used to reconstruct the image without artifacts and calcifications. Finally, the interpolated reconstructed image and the unprocessed reconstructed image are fused under the proposed voting strategy to obtain the DBT image with calcification artifacts removal.Main results.18 groups of simulated projection data and 10 groups of real projection data collected by us are used to evaluate the proposed method. Experimental results show that our algorithm can effectively reduce the calcification artifact and preserve the effective information in the image as well.Significance.The proposed method utilizes a novel projection correction based voting fusion strategy for image fusion, and is advanced in reducing breast calcification artifacts compared with other state-of-the-art methods. Our work paves the way for more efficient and precise DBT breast cancer screening.

Improved digital chest tomosynthesis image quality by use of a projection-based dual-energy virtual monochromatic convolutional neural network with super resolution

We developed a novel dual-energy (DE) virtual monochromatic (VM) very-deep super-resolution (VDSR) method with an unsharp masking reconstruction algorithm (DE–VM–VDSR) that uses projection data to improve the nodule contrast and reduce ripple artifacts during chest digital tomosynthesis (DT). For estimating the residual errors from high-resolution and multiscale VM images from the projection space, the DE–VM–VDSR algorithm employs a training network (mini-batch stochastic gradient-descent algorithm with momentum) and a hybrid super-resolution (SR) image [simultaneous algebraic reconstruction technique (SART) total-variation (TV) first-iterative shrinkage–thresholding algorithm (FISTA); SART–TV–FISTA] that involves subjective reconstruction with bilateral filtering (BF) [DE–VM–VDSR with BF]. DE-DT imaging was accomplished by pulsed X-ray exposures rapidly switched between low (60 kV, 37 projection) and high (120 kV, 37 projection) tube-potential kVp by employing a 40° swing angle. This was followed by comparison of images obtained employing the conventional polychromatic filtered backprojection (FBP), SART, SART–TV–FISTA, and DE–VM–SART–TV–FISTA algorithms. The improvements in contrast, ripple artifacts, and resolution were compared using the signal-difference-to-noise ratio (SDNR), Gumbel distribution of the largest variations, radial modulation transfer function (radial MTF) for a chest phantom with simulated ground-glass opacity (GGO) nodules, and noise power spectrum (NPS) for uniform water phantom. The novel DE–VM–VDSR with BF improved the overall performance in terms of SDNR (DE–VM–VDSR with BF: 0.1603, without BF: 0.1517; FBP: 0.0521; SART: 0.0645; SART–TV–FISTA: 0.0984; and DE–VM–SART–TV–FISTA: 0.1004), obtained a Gumbel distribution that yielded good images showing the type of simulated GGO nodules used in the chest phantom, and reduced the ripple artifacts. The NPS of DE–VM–VDSR with BF showed the lowest noise characteristics in the high-frequency region (~0.8 cycles/mm). The DE–VM–VDSR without BF yielded an improved resolution relative to that of the conventional reconstruction algorithms for radial MTF analysis (0.2–0.3 cycles/mm). Finally, based on the overall image quality, DE–VM–VDSR with BF improved the contrast and reduced the high-frequency ripple artifacts and noise.

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.

Digital Breast Tomosynthesis: Technique and Common Artifacts

Image optimization at digital breast tomosynthesis (DBT) involves a series of trade-offs between multiple variables. Wider sweep angles provide better separation of overlapping tissues, but they result in decreased in-plane resolution as well as increased scan times that may be prone to patient motion. Techniques to reduce scan time, such as continuous tube motion and pixel binning during detector readout, reduce the chances of patient motion but may degrade the in-plane resolution. Image artifacts are inherent to DBT because of the limited angular range of the acquisition. Iterative reconstruction algorithms have been shown to reduce various DBT artifacts.

A synthesizing method for signal-enhanced and artifact-reduced mammogram from digital breast tomosynthesis

In this paper, we propose a method for compositing a synthetic mammogram (SM) from digital breast tomosynthesis (DBT) slice images. The method consists of four parts. The first part is image reconstruction of DBT from the acquired projection data by use of backprojection-filtration (BPF) algorithm with a low-frequency boosting scheme and a high-density object reduction technique embedded. Also, a few expectation-maximization (EM) iterations have been additively implemented on top of the BPF algorithm to prepare a separate volume image. The second is generating three kinds of intermediate SMs. A forward projection image and a linear structure weighted forward projection image were computed. A maximum intensity projection of the BPF reconstructed volume image was also generated. The third part is integrating three intermediate SMs. The last is the post-processing of the SM. We scanned two physical phantoms in a prototype DBT scanner, and we have evaluated the performance of the proposed method. We also performed a clinical data study by use of 30 patient data who went through both DBT and digital mammography (DM) scans. Three experienced radiologists have read the SMs generated by several component techniques and also read the DM of each patient, and evaluated the generated SMs. The experimental phantom study and the clinical reader study consistently demonstrated the usefulness of the proposed method.

High-attenuation artifact reduction in breast tomosynthesis using a novel reconstruction algorithm

PURPOSE

To assess the effect on reducing the out-of-plane artifacts from metal objects in breast tomosynthesis (BT) using a novel artifact-reducing reconstruction algorithm in specimen radiography.

METHODS AND MATERIALS

The study was approved by the Regional Ethical Review Board. BT images of 18 partial- and whole mastectomy specimens from women with breast cancer were acquired before and after a needle was inserted close to the lesion. The images were reconstructed using both a standard reconstruction algorithm, and a novel algorithm; the latter uses pre-segmentation to remove highly attenuating artifact-inducing objects from projection images before reconstruction. Images were separately reconstructed with and without segmentation, and combined into an artifact-reduced reconstruction. Standard and artifact-reduced BT-algorithms were compared visually and quantitatively using clinical images of mastectomy specimens and a physical anthropomorphic phantom. Six readers independently assessed the visibility of the lesion with and without artifact-reduction in a side-by-side comparison. A quantitative analysis was performed, comparing the signal-difference to background ratio (SDBR) and artifact spread function (ASF) between the two reconstruction methods.

RESULTS

The magnitude of out-of-plane artifacts was clearly reduced with the novel reconstruction compared to BT-images without artifact reduction. Lesion masking by artifacts was largely averted; tumour visibility was comparable to standard BT images without a needle. In 76 ± 8% (standard deviation) of cases overall, readers could confidently state needle location. The same figure was 94 ± 6% for whole mastectomy cases, compared to 62 ± 17% for partial mastectomies. With metal artifact reduction, SDBR increased by 97% in the phantom, and by 69% in the mastectomies. The artifact spread function was substantially narrower.

CONCLUSION

Artifact reduction in BT using a novel reconstruction method enables qualitatively and quantitatively improved clinical use of BT when metal artifacts can be a limiting factor such as in tomosynthesis-guided biopsy.

Backprojection Filtration Image Reconstruction Approach for Reducing High-Density Object Artifacts in Digital Breast Tomosynthesis

While an accurate image reconstruction of digital breast tomosynthesis (DBT) is fundamentally impossible due to its limited data, the DBT is increasingly used in clinics for its rich image information at a relatively low dose. One of the dominant image artifacts in DBT that hinders a faithful diagnosis is high-density object artifact in conjunction with a limited angle problem. In this paper, we developed a very efficient method for reconstructing DBT images with much reduced high-density object artifacts. The method is based on backprojection filtration reconstruction algorithm, voting strategy, and image blending. Data derivatives were backprojected with appropriate weights to reduce ripple artifacts by use of the voting strategy. We generated another differentiated backprojection volume, where the edges of high-density objects are replaced by the background. After Hilbert transform, we blended the two images to reduce undershoot artifacts. Physical phantoms were scanned and we compared conventional filtered backprojection, filtered backprojection with weighted backprojection, and our proposed method. Ripple artifacts were dramatically suppressed and undershoot artifacts were also greatly suppressed in the proposed method.

Digital breast tomosynthesis: Image acquisition principles and artifacts

Digital breast tomosynthesis (DBT) is a new technology that is being used more frequently for both breast cancer screening and diagnostic purposes and its utilization is likely to continue to increase over time. The major benefit of tomosynthesis over 2D-mammography is that it allows radiologists to view breast tissue using a three-dimensional dataset and improves diagnostic accuracy by facilitating differentiation of potentially malignant lesions from overlap of normal tissue. In addition, image processing techniques allow reconstruction of two dimensional synthesized mammograms (SM) from DBT data, which eliminates the need for acquiring two dimensional full field digital mammography (FFDM) in addition to tomosynthesis and thereby reduces the radiation dose. DBT systems incorporate a moveable x-ray tube, which moves in a prescribed way over a limited angular range to obtain three-dimensional data of patients' breasts, and utilize reconstruction algorithms. The limited angular range for DBT leads to incomplete sampling of the object, and a movable x-ray tube prolongs the imaging time, both of which make DBT and SM susceptible to artifacts. Understanding the etiology of these artifacts should help radiologists in reducing the number of artifacts and in differentiating a true finding from one related to an artifact, thus potentially decreasing recall rates and false positive rates. This is becoming especially important with increased incorporation of DBT in practices around the world. The goal of this article is to review the physics principles behind DBT systems and use these principles to explain the origin of artifacts that can limit diagnostic evaluation.

Improving image quality for digital breast tomosynthesis: an automated detection and diffusion-based method for metal artifact reduction

In digital breast tomosynthesis (DBT), the high-attenuation metallic clips marking a previous biopsy site in the breast cause errors in the estimation of attenuation along the ray paths intersecting the markers during reconstruction, which result in interplane and inplane artifacts obscuring the visibility of subtle lesions. We proposed a new metal artifact reduction (MAR) method to improve image quality. Our method uses automatic detection and segmentation to generate a marker location map for each projection (PV). A voting technique based on the geometric correlation among different PVs is designed to reduce false positives (FPs) and to label the pixels on the PVs and the voxels in the imaged volume that represent the location and shape of the markers. An iterative diffusion method replaces the labeled pixels on the PVs with estimated tissue intensity from the neighboring regions while preserving the original pixel values in the neighboring regions. The inpainted PVs are then used for DBT reconstruction. The markers are repainted on the reconstructed DBT slices for radiologists' information. The MAR method is independent of reconstruction techniques or acquisition geometry. For the training set, the method achieved 100% success rate with one FP in 19 views. For the test set, the success rate by view was 97.2% for core biopsy microclips and 66.7% for clusters of large post-lumpectomy markers with a total of 10 FPs in 58 views. All FPs were large dense benign calcifications that also generated artifacts if they were not corrected by MAR. For the views with successful detection, the metal artifacts were reduced to a level that was not visually apparent in the reconstructed slices. The visibility of breast lesions obscured by the reconstruction artifacts from the metallic markers was restored.

Technical Note: Robust measurement of the slice-sensitivity profile in breast tomosynthesis

PURPOSE

The purpose of this work is to improve the repeatability of the measurement of the slice-sensitivity profile (SSP) in reconstructed breast tomosynthesis volumes.

METHODS

A grid of aluminum ball-bearings (BBs) within a PMMA phantom was imaged on breast tomosynthesis systems from three different manufacturers. The full-width half-maximum (FWHM) values were measured for the SSPs of the BBs in the reconstructed volumes. The effect of transforming the volumes from a Cartesian coordinate system (CCS) to a cone-beam coordinate system (CBCS) on the variability in the FWHM values was assessed.

RESULTS

Transforming the volumes from a CCS to a CBCS before measuring the SSPs reduced the coefficient of variation (COV) in the measurements of FWHM in repeated measurements by 56% and reduced the dependence of the FWHM values on the location of the BBs within the reconstructed volume by 76%.

CONCLUSIONS

Measuring the SSP in the volumes in a CBCS improves the robustness of the measurement.

Improved digital breast tomosynthesis images using automated ultrasound

PURPOSE

Digital breast tomosynthesis (DBT) offers poor image quality along the depth direction. This paper presents a new method that improves the image quality of DBT considerably through the a priori information from automated ultrasound (AUS) images.

METHODS

DBT and AUS images of a complex breast-mimicking phantom are acquired by a DBT/AUS dual-modality system. The AUS images are taken in the same geometry as the DBT images and the gradient information of the in-slice AUS images is adopted into the new loss functional during the DBT reconstruction process. The additional data allow for new iterative equations through solving the optimization problem utilizing the gradient descent method. Both visual comparison and quantitative analysis are employed to evaluate the improvement on DBT images. Normalized line profiles of lesions are obtained to compare the edges of the DBT and AUS-corrected DBT images. Additionally, image quality metrics such as signal difference to noise ratio (SDNR) and artifact spread function (ASF) are calculated to quantify the effectiveness of the proposed method.

RESULTS

In traditional DBT image reconstructions, serious artifacts can be found along the depth direction (Z direction), resulting in the blurring of lesion edges in the off-focus planes parallel to the detector. However, by applying the proposed method, the quality of the reconstructed DBT images is greatly improved. Visually, the AUS-corrected DBT images have much clearer borders in both in-focus and off-focus planes, fewer Z direction artifacts and reduced overlapping effect compared to the conventional DBT images. Quantitatively, the corrected DBT images have better ASF, indicating a great reduction in Z direction artifacts as well as better Z resolution. The sharper line profiles along the Y direction show enhancement on the edges. Besides, noise is also reduced, evidenced by the obviously improved SDNR values.

CONCLUSIONS

The proposed method provides great improvement on the quality of DBT images. This improvement makes it easier to locate and to distinguish a lesion, which may help improve the accuracy of the diagnosis using DBT imaging.

Breast mass detection using slice conspicuity in 3D reconstructed digital breast volumes

In digital breast tomosynthesis, the three dimensional (3D) reconstructed volumes only provide quasi-3D structure information with limited resolution along the depth direction due to insufficient sampling in depth direction and the limited angular range. The limitation could seriously hamper the conventional 3D image analysis techniques for detecting masses because the limited number of projection views causes blurring in the out-of-focus planes. In this paper, we propose a novel mass detection approach using slice conspicuity in the 3D reconstructed digital breast volumes to overcome the above limitation. First, to overcome the limited resolution along the depth direction, we detect regions of interest (ROIs) on each reconstructed slice and separately utilize the depth directional information to combine the ROIs effectively. Furthermore, we measure the blurriness of each slice for resolving the degradation of performance caused by the blur in the out-of-focus plane. Finally, mass features are extracted from the selected in focus slices and analyzed by a support vector machine classifier to reduce the false positives. Comparative experiments have been conducted on a clinical data set. Experimental results demonstrate that the proposed approach outperforms the conventional 3D approach by achieving a high sensitivity with a small number of false positives.

Characterization of a constrained paired-view technique in iterative reconstruction for breast tomosynthesis

PURPOSE

The order in which the projection views are employed in the reconstruction of tomosynthesis by iterative algorithms, such as simultaneous algebraic reconstruction technique and maximum likelihood, has a strong effect on the rate of convergence, accuracy, and the edge-blurring artifacts in the reconstructed image. The purpose of this investigation was to characterize and evaluate the effects of ordering schemes on image quality for breast tomosynthesis reconstruction and to explore a new constrained paired-view technique that could provide reduction of reconstruction artifacts. In this work, the authors compared several different ordering schemes and characterized the image quality and the formation of out-of-plane artifacts. Furthermore, a new normalization method is presented. It produces more accurate reconstructions with reduced artifacts comparing to the standard method of sequential ordering.

METHODS

In addition to visual assessment of image quality, several indices such as the signal-difference-to-noise ratio, the artifact-spread function, and the lesion detectability (d(')) were computed to quantitatively evaluate the effect of ordering scheme. The sets of breast tomosynthesis projection images were simulated for reconstruction; one set had uniform background (white noise only) and the other two contained both anatomic background and quantum noise. Clinical breast images were also studied for comparison.

RESULTS

The authors have quantified the image quality in reconstructed slices for a range of tumor sizes. The authors' proposed method provides better performance for all of the metrics tested (contrast, d('), and the level of artifacts) both for the uniform phantom case and in the presence of anatomical structure.

CONCLUSIONS

The paired projection normalization provides better performance in the image quality of the reconstructed slices, and results in a lower level of artifacts in the Z direction. This implies that even a relatively simple method like the "side-to-side" sequence, which pairs two symmetrical projections with equal angular distance from the central projection, would achieve better reconstructed image quality than the conventional "step-by-step" method, which uses sequential projections one after another.

Weighted simultaneous algebraic reconstruction technique for tomosynthesis imaging of objects with high-attenuation features

PURPOSE

This paper introduces a nonlinear weighting scheme into the backprojection operation within the simultaneous algebraic reconstruction technique (SART). It is designed for tomosynthesis imaging of objects with high-attenuation features in order to reduce limited angle artifacts.

METHODS

The algorithm estimates which projections potentially produce artifacts in a voxel. The contribution of those projections into the updating term is reduced. In order to identify those projections automatically, a four-dimensional backprojected space representation is used. Weighting coefficients are calculated based on a dissimilarity measure, evaluated in this space. For each combination of an angular view direction and a voxel position an individual weighting coefficient for the updating term is calculated.

RESULTS

The feasibility of the proposed approach is shown based on reconstructions of the following real three-dimensional tomosynthesis datasets: a mammography quality phantom, an apple with metal needles, a dried finger bone in water, and a human hand. Datasets have been acquired with a Siemens Mammomat Inspiration tomosynthesis device and reconstructed using SART with and without suggested weighting. Out-of-focus artifacts are described using line profiles and measured using standard deviation (STD) in the plane and below the plane which contains artifact-causing features. Artifacts distribution in axial direction is measured using an artifact spread function (ASF). The volumes reconstructed with the weighting scheme demonstrate the reduction of out-of-focus artifacts, lower STD (meaning reduction of artifacts), and narrower ASF compared to nonweighted SART reconstruction. It is achieved successfully for different kinds of structures: point-like structures such as phantom features, long structures such as metal needles, and fine structures such as trabecular bone structures.

CONCLUSIONS

Results indicate the feasibility of the proposed algorithm to reduce typical tomosynthesis artifacts produced by high-attenuation features. The proposed algorithm assigns weighting coefficients automatically and no segmentation or tissue-classification steps are required. The algorithm can be included into various iterative reconstruction algorithms with an additive updating strategy. It can also be extended to computed tomography case with the complete set of angular data.

A review of breast tomosynthesis. Part II. Image reconstruction, processing and analysis, and advanced applications

Many important post-acquisition aspects of breast tomosynthesis imaging can impact its clinical performance. Chief among them is the reconstruction algorithm that generates the representation of the three-dimensional breast volume from the acquired projections. But even after reconstruction, additional processes, such as artifact reduction algorithms, computer aided detection and diagnosis, among others, can also impact the performance of breast tomosynthesis in the clinical realm. In this two part paper, a review of breast tomosynthesis research is performed, with an emphasis on its medical physics aspects. In the companion paper, the first part of this review, the research performed relevant to the image acquisition process is examined. This second part will review the research on the post-acquisition aspects, including reconstruction, image processing, and analysis, as well as the advanced applications being investigated for breast tomosynthesis.

Comparison of algorithms for out-of-plane artifacts removal in digital tomosynthesis reconstructions

Digital tomosynthesis is a method of limited angle reconstruction of tomographic images produced at variable heights, on the basis of a set of angular projections taken in an arc around human anatomy. Reconstructed tomograms from unprocessed original projection images, however, are invariably affected by tomographic noise such as blurred images of objects lying outside the plane of interest and superimposed on the focused image of the fulcrum plane. The present work investigates the performance of two approaches for generation of tomograms with a reduced noise: a generalised post-processing method, based on constructing a noise mask from all planes in the reconstructed volume, and its subsequent subtraction from the in-focus plane and a filtered Multiple Projection Algorithm. The comparison between the two algorithms shows that the first method provides reconstructions with very good quality in case of high contrast features, especially for those embedded into a heterogeneous background.

Dependence of image quality on geometric factors in breast tomosynthesis

PURPOSE

Accurate and precise knowledge of the geometric relationships between the physical components (x-ray source, pivot point, and elements of the x-ray detector) critically influences the quality of reconstructed images in digital breast tomosynthesis (DBT). The sensitivity of image reconstruction to geometric inaccuracies is investigated by simulation of image formation and reconstruction for a DBT system.

METHODS

A mathematical simulation of a partial isocentric system is described. A block "phantom" containing small calcific particles is used to evaluate the effect of three linear and three angular parameters on localization of structures within the reconstructed image and on lesion contrast. Two types of geometric errors are studied: fixed offset inaccuracies and random interprojection inaccuracies in the context of a filtered back projection reconstruction algorithm.

RESULTS

It is shown that, in general, fixed offset errors lead to little degradation of image quality. However, a lack of precision in interprojection geometric parameters can cause a loss in lesion contrast and introduce artifacts. For example, projection mismatches of the gantry angle of 0.14 degrees (standard deviation) can reduce reconstructed lesion intensity by 20%. Reconstruction is particularly sensitive to detector yaw angle mismatches; even small fixed offset errors (0.31 degrees) in detector yaw can reduce lesion intensity by 20%. Interprojection variations in geometric parameters can also cause localization errors. For example, if detector yaw variations between projections occur and these are not accounted for, a standard deviation of 0.34 degrees can be expected to induce 1 mm root-mean-square error shift in lesion location.

CONCLUSIONS

In a simulation of image acquisition in DBT, the sensitivities in image quality to six geometric parameters were evaluated. Image reconstructions are relatively tolerant of fixed offset errors except for detector yaw. However, uncorrected variations in interprojection geometric parameters induce losses in lesion contrast and localization. Lesion contrast is affected more strongly by these errors compared to lesion localization in tomosynthesis.

Analysis of parenchymal texture with digital breast tomosynthesis: comparison with digital mammography and implications for cancer risk assessment

PURPOSE

To correlate the parenchymal texture features at digital breast tomosynthesis (DBT) and digital mammography with breast percent density (PD), an established breast cancer risk factor, in a screening population of women.

MATERIALS AND METHODS

This HIPAA-compliant study was approved by the institutional review board. Bilateral DBT images and digital mammograms from 71 women (mean age, 54 years; age range, 34-75 years) with negative or benign findings at screening mammography were retrospectively collected from a separate institutional review board-approved DBT screening trial (performed from July 2007 to March 2008) in which all women had given written informed consent. Parenchymal texture features of skewness, coarseness, contrast, energy, homogeneity, and fractal dimension were computed from the retroareolar region. Principal component analysis (PCA) was applied to obtain orthogonal texture components. Mammographic PD was estimated with software. Correlation analysis and multiple linear regression with generalized estimating equations were performed to determine the association between texture features and breast PD. Regression was adjusted for age to determine the independent association of texture to breast PD when age was also considered as a predictor variable.

RESULTS

Texture feature correlations to breast PD were stronger with DBT than with digital mammography. Statistically significant correlations (P < .001) were observed for contrast (r = 0.48), energy (r = -0.47), and homogeneity (r = -0.56) at DBT and for contrast (r = 0.26), energy (r = -0.26), and homogeneity (r = -0.33) at digital mammography. Multiple linear regression analysis of PCA texture components as predictors of PD also demonstrated significantly stronger associations with DBT. The association was strongest when age was also considered as a predictor of PD (R² = 0.41 for DBT and 0.28 for digital mammography; P < .001).

CONCLUSION

Parenchymal texture features are more strongly correlated to breast PD in DBT than in digital mammography. The authors' long-term hypothesis is that parenchymal texture analysis with DBT will result in quantitative imaging biomarkers that can improve the estimation of breast cancer risk.

Contrast detail phantom comparison on a commercially available unit. Digital breast tomosynthesis (DBT) versus full-field digital mammography (FFDM)

The performance of a commercial digital mammographic system working in 2D planar versus tomosynthesis mode was evaluated in terms of the image signal difference to noise ratio (SDNR). A contrast detail phantom was obtained embedding 1 cm Plexiglas, including 49 holes of different diameter and depth, between two layers containing a breast-simulating material. The phantom was exposed with the details plane perpendicular to the X-ray beam using the manufacturer's standard clinical breast acquisition parameters. SDNR in the digital breast tomosynthesis (DBT) images was higher than that of the full-field digital mammography (FFDM) for 38 out of 49 details in complex background conditions. These differences (p < 0.05) are statistically significant for 19 details out of 38. The relative SDNR results for DBT and FFDM images showed a dependence on the diameter of the details considered. This paper proposes an initial framework for a global image quality evaluation for commercial systems that can operate with different image acquisition modality using the same detector.

Digital mammography imaging: breast tomosynthesis and advanced applications

This article discusses recent developments in advanced derivative technologies associated with digital mammography. Digital breast tomosynthesis, its principles, development, and early clinical trials, are reviewed. Contrast-enhanced digital mammography and combined imaging systems with digital mammography and ultrasound are also discussed. Although all these methods are currently research programs, they hold promise for improving cancer detection and characterization if early results are confirmed by clinical trials.

Optimized image acquisition for breast tomosynthesis in projection and reconstruction space

Breast tomosynthesis has been an exciting new development in the field of breast imaging. While the diagnostic improvement via tomosynthesis is notable, the full potential of tomosynthesis has not yet been realized. This may be attributed to the dependency of the diagnostic quality of tomosynthesis on multiple variables, each of which needs to be optimized. Those include dose, number of angular projections, and the total angular span of those projections. In this study, the authors investigated the effects of these acquisition parameters on the overall diagnostic image quality of breast tomosynthesis in both the projection and reconstruction space. Five mastectomy specimens were imaged using a prototype tomosynthesis system. 25 angular projections of each specimen were acquired at 6.2 times typical single-view clinical dose level. Images at lower dose levels were then simulated using a noise modification routine. Each projection image was supplemented with 84 simulated 3 mm 3D lesions embedded at the center of 84 nonoverlapping ROIs. The projection images were then reconstructed using a filtered backprojection algorithm at different combinations of acquisition parameters to investigate which of the many possible combinations maximizes the performance. Performance was evaluated in terms of a Laguerre-Gauss channelized Hotelling observer model-based measure of lesion detectability. The analysis was also performed without reconstruction by combining the model results from projection images using Bayesian decision fusion algorithm. The effect of acquisition parameters on projection images and reconstructed slices were then compared to derive an optimization rule for tomosynthesis. The results indicated that projection images yield comparable but higher performance than reconstructed images. Both modes, however, offered similar trends: Performance improved with an increase in the total acquisition dose level and the angular span. Using a constant dose level and angular span, the performance rolled off beyond a certain number of projections, indicating that simply increasing the number of projections in tomosynthesis may not necessarily improve its performance. The best performance for both projection images and tomosynthesis slices was obtained for 15-17 projections spanning an angular are of approximately 45 degrees--the maximum tested in our study, and for an acquisition dose equal to single-view mammography. The optimization framework developed in this framework is applicable to other reconstruction techniques and other multiprojection systems.

Digital breast tomosynthesis versus digital mammography: a clinical performance study

OBJECTIVE

To compare the clinical performance of digital breast tomosynthesis (DBT) with that of full-field digital mammography (FFDM) in a diagnostic population.

METHODS

The study enrolled 200 consenting women who had at least one breast lesion discovered by mammography and/or ultrasound classified as doubtful or suspicious or probably malignant. They underwent tomosynthesis in one view [mediolateral oblique (MLO)] of both breasts at a dose comparable to that of standard screen-film mammography in two views [craniocaudal (CC) and MLO]. Images were rated by six breast radiologists using the BIRADS score. Ratings were compared with the truth established according to the standard of care and a multiple-reader multiple-case (MRMC) receiver-operating characteristic (ROC) analysis was performed. Clinical performance of DBT compared with that of FFDM was evaluated in terms of the difference between areas under ROC curves (AUCs) for BIRADS scores.

RESULTS

Overall clinical performance with DBT and FFDM for malignant versus all other cases was not significantly different (AUCs 0.851 vs 0.836, p = 0.645). The lower limit of the 95% CI or the difference between DBT and FFDM AUCs was -4.9%.

CONCLUSION

Clinical performance of tomosynthesis in one view at the same total dose as standard screen-film mammography is not inferior to digital mammography in two views.

Tomosynthesis imaging: at a translational crossroads

Tomosynthesis is a decades-old technique for section imaging that has seen a recent upsurge in interest due to its promise to provide three-dimensional information at lower dose and potentially lower cost than CT in certain clinical imaging situations. This renewed interest in tomosynthesis began in the late 1990s as a new generation of flat-panel detectors became available; these detectors were the one missing piece of the picture that had kept tomosynthesis from enjoying significant utilization earlier. In the past decade, tomosynthesis imaging has been investigated in a variety of clinical imaging situations, but the two most prominent have been in breast and chest imaging. Tomosynthesis has the potential to substantially change the way in which breast cancer and pulmonary nodules are detected and managed. Commercial tomosynthesis devices are now available or on the horizon. Many of the remaining research activities with tomosynthesis will be translational in nature and will involve physicist and clinician alike. This overview article provides a forward-looking assessment of the translational questions facing tomosynthesis imaging and anticipates some of the likely research and clinical activities in the next five years.

Towards optimized acquisition scheme for multiprojection correlation imaging of breast cancer

RATIONALE AND OBJECTIVES

Correlation imaging (CI) is a form of multiprojection imaging in which multiple images of a patient are acquired from slightly different angles. Information from these images is combined to make the final diagnosis. A critical factor affecting the performance of CI is its data acquisition scheme, because nonoptimized acquisition may distort pathologic indicators. The authors describe a computer-aided detection (CADe) methodology to optimize the acquisition scheme of CI for superior diagnostic accuracy.

MATERIALS AND METHODS

Images from 106 subjects were used. For each subject, 25 angular projections of a single breast were acquired. Projection images were supplemented with a simulated 3-mm three-dimensional lesion. Each projection was then processed using a traditional CADe algorithm at high sensitivity, followed by the reduction of false-positives by combining the geometric correlation information available from the multiple images. The performance of the CI system was determined in terms of free-response receiver-operating characteristic curves and the areas under receiver-operating characteristic curves. For optimization, the components of acquisition, such as the number of projections and their angular span, were systematically changed to investigate which of the many possible combinations maximized the obtainable CADe sensitivity and specificity.

RESULTS

The performance of the CI system was improved by increasing the angular span. Increasing the number of angular projections beyond a certain number did not improve performance. Maximum performance was obtained between 7 and 10 projections spanning a maximum angular arc of 45 degrees .

CONCLUSION

The findings suggest the existence of an optimum acquisition scheme for CI of the breast. CADe results confirmed earlier predictions on the basis of observer models. An optimized CI system may be an important diagnostic tool for improved breast cancer detection.

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

Digital breast tomosynthesis (DBT) is a three-dimensional (3D) x-ray imaging modality that reconstructs image slices parallel to the detector plane. Image acquisition is performed using a limited angular range (less than 50 degrees) and a limited number of projection views (less than 50 views). Due to incomplete data sampling, image artifacts are unavoidable in DBT. In this preliminary study, the image artifacts in DBT were investigated systematically using a linear system approximation. A cascaded linear system model of DBT was developed to calculate the 3D presampling modulation transfer function (MTF) with different image acquisition geometries and reconstruction filters using a filtered backprojection (FBP) algorithm. A thin, slanted tungsten (W) wire was used to measure the presampling MTF of the DBT system in the cross-sectional plane defined by the thickness (z-) and tube travel (x-) directions. The measurement was in excellent agreement with the calculation using the model. A small steel bead was used to calculate the artifact spread function (ASF) of the DBT system. The ASF was correlated with the convolution of the two-dimensional (2D) point spread function (PSF) of the system and the object function of the bead. The results showed that the cascaded linear system model can be used to predict the magnitude of image artifacts of small, high-contrast objects with different image acquisition geometry and reconstruction filters.

Design and Development of a New Multi-Projection X-Ray System for Chest Imaging

Overlapping anatomical structures may confound the detection of abnormal pathology, including lung nodules, in conventional single-projection chest radiography. To minimize this fundamental limiting factor, a dedicated digital multi-projection system for chest imaging was recently developed at the Radiology Department of Duke University. We are reporting the design of the multi-projection imaging system and its initial performance in an ongoing clinical trial. The system is capable of acquiring multiple full-field projections of the same patient along both the horizontal and vertical axes at variable speeds and acquisition frame rates. These images acquired in rapid succession from slightly different angles about the posterior-anterior (PA) orientation can be correlated to minimize the influence of overlying anatomy. The developed system has been tested for repeatability and motion blur artifacts to investigate its robustness for clinical trials. Excellent geometrical consistency was found in the tube motion, with positional errors for clinical settings within 1%. The effect of tube-motion on the image quality measured in terms of impact on the Modulation Transfer Function (MTF) was found to be minimal. The system was deemed clinic-ready and a clinical trial was subsequently launched. The flexibility of image acquisition built into the system provides a unique opportunity to easily modify it for different clinical applications, including tomosynthesis, correlation imaging (CI), and stereoscopic imaging.

Breast cancer imaging: a perspective for the next decade

Breast imaging is largely indicated for detection, diagnosis, and clinical management of breast cancer and for evaluation of the integrity of breast implants. In this work, a prospective view of techniques for breast cancer detection and diagnosis is provided based on an assessment of current trends. The potential role of emerging techniques that are under various stages of research and development is also addressed. It appears that the primary imaging tool for breast cancer screening in the next decade will be high-resolution, high-contrast, anatomical x-ray imaging with or without depth information. MRI and ultrasonography will have an increasingly important adjunctive role for imaging high-risk patients and women with dense breasts. Pilot studies with dedicated breast CT have demonstrated high-resolution three-dimensional imaging capabilities, but several technological barriers must be overcome before clinical adoption. Radionuclide based imaging techniques and x-ray imaging with intravenously injected contrast offer substantial potential as a diagnostic tools and for evaluation of suspicious lesions. Developing optical and electromagnetic imaging techniques hold significant potential for physiologic information and they are likely to be of most value when integrated with or adjunctively used with techniques that provide anatomic information. Experimental studies with breast specimens suggest that phase-sensitive x-ray imaging techniques can provide edge enhancement and contrast improvement but more research is needed to evaluate their potential role in clinical breast imaging. From the technological perspective, in addition to improvements within each modality, there is likely to be a trend towards multi-modality systems that combine anatomic with physiologic information. We are also likely to transition from a standardized screening, where all women undergo the same imaging exam (mammography), to selection of a screening modality or modalities based an individual-risk or other classification.

Imaging performance of an amorphous selenium digital mammography detector in a breast tomosynthesis system

In breast tomosynthesis a rapid sequence of N images is acquired when the x-ray tube sweeps through different angular views with respect to the breast. Since the total dose to the breast is kept the same as that in regular mammography, the exposure used for each image of tomosynthesis is 1/N. The low dose and high frame rate pose a tremendous challenge to the imaging performance of digital mammography detectors. The purpose of the present work is to investigate the detector performance in different operational modes designed for tomosynthesis acquisition, e.g., binning or full resolution readout, the range of view angles, and the number of views N. A prototype breast tomosynthesis system with a nominal angular range of +/-25 degrees was used in our investigation. The system was equipped with an amorphous selenium (a-Se) full field digital mammography detector with pixel size of 85 microm. The detector can be read out in full resolution or 2 x 1 binning (binning in the tube travel direction). The focal spot blur due to continuous tube travel was measured for different acquisition geometries, and it was found that pixel binning, instead of focal spot blur, dominates the detector modulation transfer function (MTF). The noise power spectrum (NPS) and detective quantum efficiency (DQE) of the detector were measured with the exposure range of 0.4-6 mR, which is relevant to the low dose used in tomosynthesis. It was found that DQE at 0.4 mR is only 20% less than that at highest exposure for both detector readout modes. The detector temporal performance was categorized as lag and ghosting, both of which were measured as a function of x-ray exposure. The first frame lags were 8% and 4%, respectively, for binning and full resolution mode. Ghosting is negligible and independent of the frame rate. The results showed that the detector performance is x-ray quantum noise limited at the low exposures used in each view of tomosynthesis, and the temporal performance at high frame rate (up to 2 frames per second) is adequate for tomosynthesis.

A mathematical model platform for optimizing a multiprojection breast imaging system

Multiprojection imaging is a technique in which a plurality of digital radiographic images of the same patient are acquired within a short interval of time from slightly different angles. Information from each image is combined to determine the final diagnosis. Projection data are either reconstructed into slices as in the case of tomosynthesis or analyzed directly as in the case of multiprojection correlation imaging technique, thereby avoiding reconstruction artifacts. In this study, the authors investigated the optimum geometry of acquisitions of a multiprojection breast correlation imaging system in terms of the number of projections and their total angular span that yield maximum performance in a task that models clinical decision. Twenty-five angular projections of each breast from 82 human subjects in our breast tomosynthesis database were each supplemented with a simulated 3 mm mass. An approach based on Laguerre-Gauss channelized Hotelling observer was developed to assess the detectability of the mass in terms of receiver operating characteristic (ROC) curves. Two methodologies were developed to integrate results from individual projections into one combined ROC curve as the overall figure of merit. To optimize the acquisition geometry, different components of acquisitions were changed to investigate which one of the many possible configurations maximized the area under the combined ROC curve. Optimization was investigated under two acquisition dose conditions corresponding to a fixed total dose delivered to the patient and a variable dose condition, based on the number of projections used. In either case, the detectability was dependent on the number of projections used, the total angular span of those projections, and the acquisition dose level. In the first case, the detectability approximately followed a bell curve as a function of the number of projections with the maximum between 8 and 16 projections spanning angular arcs of about 23 degrees-45 degrees, respectively. In the second case, the detectability increased with the number of projections approaching an asymptote at 11-17 projections for an angular span of about 45 degrees. These results indicate the inherent information content of the multi-projection image data reflecting the relative role of quantum and anatomical noise in multiprojection breast imaging. The optimization scheme presented here may be applied to any multiprojection imaging modalities and may be extended by including reconstruction in the case of digital breast tomosynthesis and breast computed tomography.

Automated detection of microcalcification clusters for digital breast tomosynthesis using projection data only: a preliminary study

Digital breast tomosynthesis (DBT) is a promising modality for breast imaging in which an anisotropic volume image of the breast is obtained. We present an algorithm for computerized detection of microcalcification clusters (MCCs) for DBT. This algorithm operates on the projection views only. Therefore it does not depend on reconstruction, and is computationally efficient. The algorithm was developed using a database of 30 image sets with microcalcifications, and a control group of 30 image sets without visible findings. The patient data were acquired on the first DBT prototype at Massachusetts General Hospital. Algorithm sensitivity was estimated to be 0.86 at 1.3 false positive clusters, which is below that of current MCC detection algorithms for full-field digital mammography. Because of the small number of patient cases, algorithm parameters were not optimized and one linear classifier was used. An actual limitation of our approach may be that the signal-to-noise ratio in the projection images is too low for microcalcification detection. Furthermore, the database consisted of predominantly small MCC. This may be related to the image quality obtained with this first prototype.

Breast tomosynthesis: present considerations and future applications

Mammography is an effective imaging tool for detecting breast cancer at an early stage and is the only screening modality proved to reduce mortality from breast cancer. However, the overlap of tissues depicted on mammograms may create significant obstacles to the detection and diagnosis of abnormalities. Diagnostic testing initiated because of a questionable result at screening mammography frequently causes patients unnecessary anxiety and incurs increased medical costs. Breast tomosynthesis, a new tool that is based on the acquisition of three-dimensional digital image data, could help solve the problem of interpreting mammographic features produced by tissue overlap. Although the technology has not yet been approved by the Food and Drug Administration, breast tomosynthesis has the potential to help reduce recall rates, improve the selection of patients for biopsy, and increase cancer detection rates, especially in patients with dense breasts. Supplemental material available at radiographics.rsnajnls.org/cgi/content/full/27/S231/DC1.

Application of boundary detection information in breast tomosynthesis reconstruction

Digital tomosynthesis mammography (DTM) is one of the most promising techniques that can potentially improve early detection of breast cancers. DTM can provide three-dimensional (3D) structural information by reconstructing the whole imaged volume from a sequence of projection-view (PV) mammograms that are acquired at a small number of projection angles over a limited angular range. Our previous study showed that simultaneous algebraic reconstruction technique (SART) can produce satisfactory tomosynthesized image quality compared to maximum likelihood-type algorithms. To improve the efficiency of DTM reconstruction and address the problem of boundary artifacts, we have developed methods to incorporate both two-dimensional (2D) and 3D breast boundary information within the SART reconstruction algorithm in this study. A second generation GE prototype tomosynthesis mammography system with a stationary digital detector was used for PV image acquisition from 21 angles in 3 degrees increments over a +/- 30 degrees angular range. The 2D breast boundary curves on all PV images were obtained by automated segmentation and were used to restrict the SART reconstruction to be performed only within the breast volume. The computation time of SART reconstruction was reduced by 76.3% and 69.9% for cranio-caudal and mediolateral oblique views, respectively, for the chosen example. In addition, a 3D conical trimming method was developed in which the 2D breast boundary curves from all PVs were back projected to generate the 3D breast surface. This 3D surface was then used to eliminate the multiple breast shadows outside the breast volume due to reconstruction by setting these voxels to a constant background value. Our study demonstrates that, by using the 2D and 3D breast boundary information, all breast boundary and most detector boundary artifacts can be effectively removed on all tomosynthesized slices.

Tomosynthesis and contrast-enhanced digital mammography: recent advances in digital mammography

Digital mammography is more and more replacing conventional mammography. Initial concerns about an inferior image quality of digital mammography have been largely overcome and recent studies even show digital mammography to be superior in women with dense breasts, while at the same time reducing radiation exposure. Nevertheless, an important limitation of digital mammography remains: namely, the fact that summation may obscure lesions in dense breast tissue. However, digital mammography offers the option of so-called advanced applications, and two of these, contrast-enhanced mammography and tomosynthesis, are promising candidates for improving the detection of breast lesions otherwise obscured by the summation of dense tissue. Two techniques of contrast-enhanced mammography are available: temporal subtraction of images acquired before and after contrast administration and the so-called dual-energy technique, which means that pairs of low/high-energy images acquired after contrast administration are subtracted. Tomosynthesis on the other hand provides three-dimensional information on the breast. The images are acquired with different angulations of the X-ray tube while the object or detector is static. Various reconstruction algorithms can then be applied to the set of typically nine to 28 source images to reconstruct 1-mm slices with a reduced risk of obscuring pathology. Combinations of both advanced applications have only been investigated in individual experimental studies; more advanced software algorithms and CAD systems are still in their infancy and have only undergone preliminary clinical evaluation.