Artifact reduction methods for truncated projections in iterative breast tomosynthesis reconstruction

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

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

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

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

Comparative evaluation of tomosynthesis, computed tomography, and magnetic resonance imaging findings for metacarpophalangeal joints from equine cadavers

OBJECTIVE

To describe the technique and assess the diagnostic potential and limitations of tomosynthesis for imaging of the metacarpophalangeal joint (MCPJ) of equine cadavers; compare the tomosynthesis appearance of pathological lesions with their conventional radiographic, CT, and MRI appearances; and evaluate all imaging findings with gross lesions of a given MCPJ.

SAMPLE

Distal portions of 4 forelimbs from 4 equine cadavers.

PROCEDURES

The MCPJs underwent radiography, tomosynthesis (with a purpose-built benchtop unit), CT, and MRI; thereafter, MCPJs were disarticulated and evaluated for the presence of gross lesions. The ability to identify pathological lesions on all images was assessed, followed by semiobjective scoring for quality of the overall image and appearance of the subchondral bone, articular cartilage, periarticular margins, and adjacent trabecular bone of the third metacarpal bone, proximal phalanx, and proximal sesamoid bones of each MCPJ.

RESULTS

Some pathological lesions in the subchondral bone of the third metacarpal bone were detectable with tomosynthesis but not with radiography. Overall, tomosynthesis was comparable to radiography, but volumetric imaging modalities were superior to tomosynthesis and radiography for imaging of subchondral bone, articular cartilage, periarticular margins, and adjacent bone.

CONCLUSIONS AND CLINICAL RELEVANCE

With regard to the diagnostic characterization of equine MCPJs, tomosynthesis may be more accurate than radiography for identification of lesions within subchondral bone because, in part, of its ability to reduce superimposition of regional anatomic features. Tomosynthesis may be useful as an adjunctive imaging technique, highlighting subtle lesions within bone, compared with standard radiographic findings.

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.

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.

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.

Segmented separable footprint projector for digital breast tomosynthesis and its application for subpixel reconstruction

PURPOSE

Digital forward and back projectors play a significant role in iterative image reconstruction. The accuracy of the projector affects the quality of the reconstructed images. Digital breast tomosynthesis (DBT) often uses the ray-tracing (RT) projector that ignores finite detector element size. This paper proposes a modified version of the separable footprint (SF) projector, called the segmented separable footprint (SG) projector, that calculates efficiently the Radon transform mean value over each detector element. The SG projector is specifically designed for DBT reconstruction because of the large height-to-width ratio of the voxels generally used in DBT. This study evaluates the effectiveness of the SG projector in reducing projection error and improving DBT reconstruction quality.

METHODS

We quantitatively compared the projection error of the RT and the SG projector at different locations and their performance in regular and subpixel DBT reconstruction. Subpixel reconstructions used finer voxels in the imaged volume than the detector pixel size. Subpixel reconstruction with RT projector uses interpolated projection views as input to provide adequate coverage of the finer voxel grid with the traced rays. Subpixel reconstruction with the SG projector, however, uses the measured projection views without interpolation. We simulated DBT projections of a test phantom using CatSim (GE Global Research, Niskayuna, NY) under idealized imaging conditions without noise and blur, to analyze the effects of the projectors and subpixel reconstruction without other image degrading factors. The phantom contained an array of horizontal and vertical line pair patterns (1 to 9.5 line pairs/mm) and pairs of closely spaced spheres (diameters 0.053 to 0.5 mm) embedded at the mid-plane of a 5-cm-thick breast tissue-equivalent uniform volume. The images were reconstructed with regular simultaneous algebraic reconstruction technique (SART) and subpixel SART using different projectors. The resolution and contrast of the test objects in the reconstructed images and the computation times were compared under different reconstruction conditions.

RESULTS

The SG projector reduced the projector error by 1 to 2 orders of magnitude at most locations. In the worst case, the SG projector still reduced the projection error by about 50%. In the DBT reconstructed slices parallel to the detector plane, the SG projector not only increased the contrast of the line pairs and spheres but also produced more smooth and continuous reconstructed images, whereas the discrete and sparse nature of the RT projector caused artifacts appearing as patterned noise. For subpixel reconstruction, the SG projector significantly increased object contrast and computation speed, especially for high subpixel ratios, compared with the RT projector implemented with accelerated Siddon's algorithm. The difference in the depth resolution among the projectors is negligible under the conditions studied. Our results also demonstrated that subpixel reconstruction can improve the spatial resolution of the reconstructed images, and can exceed the Nyquist limit of the detector under some conditions.

CONCLUSIONS

The SG projector was more accurate and faster than the RT projector. The SG projector also substantially reduced computation time and improved the image quality for the tomosynthesized images with and without subpixel reconstruction.

Comparison of FBP and Iterative Algorithms with Non-Uniform Angular Sampling

Some people may believe that the filtered backprojection (FBP) algorithm does not work if the projection data are measured non-uniformly. Some may also believe that iterative algorithms can automatically handle the non-uniformly sampled data in the projector/backprojector. This paper claims that the FBP algorithm can effectively handle the situation where the angular sampling is not uniform. This paper compares the images that are reconstructed by both the FBP and the iterative Landweber algorithms when the angular sampling is nonuniform. When the iteration number is low, the iterative algorithms do not handle the non-uniform sampling properly. A weighting strategy is then suggested and it makes the image resolution more isotropic. In few-view tomography, the FBP and iterative algorithms both perform poorly if no other prior information is used. We have made the following observations: 1) When using an iterative algorithm, one must use early solutions due to noise amplification. 2) An early solution can have anisotropic spatial resolution if the angular sampling is not uniform. 3) The anisotropic resolution problem can be solved by introducing angle dependent weighting, which is not noise dependent. 4) The weighting is not effective when the iteration number is large. The weighting only affects the early solutions, and does not affect the converged solution. 5) When the iteration number is large, the model-mismatch errors are amplified and cause artifacts in the image. 6) The FBP algorithm is not sensitive to the model-mismatch errors, and does not have the "early solution" problems. 7) In few-view tomography, both FBP and iterative algorithms perform poorly, while the FBP algorithm gives a sharper image than the iterative algorithm does.

A diffusion-based truncated projection artifact reduction method for iterative digital breast tomosynthesis reconstruction

Digital breast tomosynthesis (DBT) has strong promise to improve sensitivity for detecting breast cancer. DBT reconstruction estimates the breast tissue attenuation using projection views (PVs) acquired in a limited angular range. Because of the limited field of view (FOV) of the detector, the PVs may not completely cover the breast in the x-ray source motion direction at large projection angles. The voxels in the imaged volume cannot be updated when they are outside the FOV, thus causing a discontinuity in intensity across the FOV boundaries in the reconstructed slices, which we refer to as the truncated projection artifact (TPA). Most existing TPA reduction methods were developed for the filtered backprojection method in the context of computed tomography. In this study, we developed a new diffusion-based method to reduce TPAs during DBT reconstruction using the simultaneous algebraic reconstruction technique (SART). Our TPA reduction method compensates for the discontinuity in background intensity outside the FOV of the current PV after each PV updating in SART. The difference in voxel values across the FOV boundary is smoothly diffused to the region beyond the FOV of the current PV. Diffusion-based background intensity estimation is performed iteratively to avoid structured artifacts. The method is applicable to TPA in both the forward and backward directions of the PVs and for any number of iterations during reconstruction. The effectiveness of the new method was evaluated by comparing the visual quality of the reconstructed slices and the measured discontinuities across the TPA with and without artifact correction at various iterations. The results demonstrated that the diffusion-based intensity compensation method reduced the TPA while preserving the detailed tissue structures. The visibility of breast lesions obscured by the TPA was improved after artifact reduction.

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.

Digital breast tomosynthesis is comparable to mammographic spot views for mass characterization

PURPOSE

To determine if digital breast tomosynthesis (DBT) performs comparably to mammographic spot views (MSVs) in characterizing breast masses as benign or malignant.

MATERIALS AND METHODS

This IRB-approved, HIPAA-compliant reader study obtained informed consent from all subjects. Four blinded Mammography Quality Standards Act-certified academic radiologists individually evaluated DBT images and MSVs of 67 masses (30 malignant, 37 benign) in 67 women (age range, 34-88 years). Images were viewed in random order at separate counterbalanced sessions and were rated for visibility (10-point scale), likelihood of malignancy (12-point scale), and Breast Imaging Reporting and Data System (BI-RADS) classification. Differences in mass visibility were analyzed by using the Wilcoxon matched-pairs signed-ranks test. Reader performance was measured by calculating the area under the receiver operating characteristic curve (A(z)) and partial area index above a sensitivity threshold of 0.90 (A(z)(0.90)) by using likelihood of malignancy ratings. Masses categorized as BI-RADS 4 or 5 were compared with histopathologic analysis to determine true-positive results for each modality.

RESULTS

Mean mass visibility ratings were slightly better with DBT (range, 3.2-4.4) than with MSV (range, 3.8-4.8) for all four readers, with one reader's improvement achieving statistical significance (P = .001). The A(z) ranged 0.89-0.93 for DBT and 0.88-0.93 for MSV (P ≥ .23). The A(z)((0.90)) ranged 0.36-0.52 for DBT and 0.25-0.40 for MSV (P ≥ .20). The readers characterized seven additional malignant masses as BI-RADS 4 or 5 with DBT than with MSV, at a cost of five false-positive biopsy recommendations, with a mean of 1.8 true-positive (range, 0-3) and 1.3 false-positive (range, -1 to 4) assessments per reader.

CONCLUSION

In this small study, mass characterization in terms of visibility ratings, reader performance, and BI-RADS assessment with DBT was similar to that with MSVs. Preliminary findings suggest that MSV might not be necessary for mass characterization when performing DBT.

Selective-diffusion regularization for enhancement of microcalcifications in digital breast tomosynthesis reconstruction

PURPOSE

Digital breast tomosynthesis (DBT) has been shown to improve mass detection. Detection of microcalcifications is more challenging because of the large breast volume to be searched for subtle signals. The simultaneous algebraic reconstruction technique (SART) was found to provide good image quality for DBT, but the image noise is amplified with an increasing number of iterations. In this study, the authors developed a selective-diffusion (SD) method for noise regularization with SART to improve the contrast-to-noise ratio (CNR) of microcalcifications in the DBT slices for human or machine detection.

METHODS

The SD method regularizes SART reconstruction during updating with each projection view. Potential microcalcifications are differentiated from the noisy background by estimating the local gradient information. Different degrees of regularization are applied to the signal or noise classes, such that the microcalcifications will be enhanced while the noise is suppressed. The new SD method was compared to several current methods, including the quadratic Laplacian (QL) method, the total variation (TV) method, and the nonconvex total p-variation (TpV) method for noise regularization with SART. A GE GEN2 prototype DBT system with a stationary digital detector was used for the acquisition of DBT scans at 21 angles in 3 degrees increments over a +/-30 degrees range. The reconstruction image quality without regularization and that with the different regularization methods were compared using the DBT scans of an American College of Radiology phantom and a human subject. The CNR and the full width at half maximum (FWHM) of the line profiles of microcalcifications within the in-focus DBT slices were used as image quality measures.

RESULTS

For the comparison of large microcalcifications in the DBT data of the subject, the SD method resulted in comparable CNR to the nonconvex TpV method. Both of them performed better than the other two methods. For subtle microcalcifications, the SD method was superior to other methods in terms of CNR. In both the subject and phantom DBT data, for large microcalcifications, the FWHM of the SD method was comparable to that without regularization, which was wider than that of the TV type methods. For subtle microcalcifications, the SD method had comparable FWHM values to the TV type methods. All three regularization methods were superior to the QL method in terms of FWHM.

CONCLUSIONS

The SART regularized by the selective-diffusion method enhanced the CNR and preserved the sharpness of microcalcifications. In comparison with three existing regularization methods, the selective-diffusion regularization was superior to the other methods for subtle microcalcifications.