Simple method for computing scattered radiation in breast tomosynthesis

Díaz, Oliver; Elangovan, Premkumar; Young, Kenneth C.; Wells, Kevin; Dance, David R.

doi:10.1002/mp.13760

Cited by 9 publications

(10 citation statements)

References 47 publications

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“…At this stage, the images did not include any scattered radiation. The scatter‐to‐primary ratio (SPR) was modeled using Monte Carlo techniques and was estimated to be 0.19 for 2D imaging and between 0.78 and 0.92 for DBT depending on the tube angle 44 . The same values were used for each breast glandularity.…”

Section: Methodsmentioning

confidence: 99%

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Effect of glandularity on the detection of simulated cancers in planar, tomosynthesis, and synthetic 2D imaging of the breast using a hybrid virtual clinical trial

et al. 2021

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The purpose of this study was to measure the threshold diameter of calcifications and masses for 2D imaging, digital breast tomosynthesis (DBT), and synthetic 2D images, for a range of breast glandularities. This study shows the limits of detection for each of the technologies and the strengths and weaknesses of each in terms of visualizing the radiological features of small cancers. Methods: Mathematical voxel breast phantoms with glandularities by volume of 9%,18%,and 30% with a thickness of 53 mm were created.Simulated ill-defined masses and calcification clusters with a range of diameters were inserted into some of these breast models. The imaging characteristics of a Siemens Inspiration X-ray system were measured for a 29 kV, tungsten/rhodium anode/filter combination. Ray tracing through the breast models was undertaken to create simulated 2D and DBT projection images. These were then modified to adjust the image sharpness, and to add scatter and noise. The mean glandular doses for the images were 1.43, 1.47, and 1.47 mGy for 2D and 1.92, 1.97, and 1.98 mGy for DBT for the three glandularities. The resultant images were processed to create 2D, DBT planes and synthetic 2D images. Patches of the images with or without a simulated lesion were extracted, and used in a four-alternative forced choice study to measure the threshold diameters for each imaging mode, lesion type, and glandularity. The study was undertaken by six physicists. Results: The threshold diameters of the lesions were 6.2, 4.9, and 6.7 mm (masses) and 225, 370, and 399 µm, (calcifications) for 2D, DBT, and synthetic 2D, respectively, for a breast glandularity of 18%. The threshold diameter of illdefined masses is significantly smaller for DBT than for both 2D (p≤0.006) and synthetic 2D (p≤0.012) for all glandularities. Glandularity has a significant effect on the threshold diameter of masses, even for DBT where there is reduced background structure in the images. The calcification threshold diameters for 2D images were significantly smaller than for DBT and synthetic 2D for all glandularities. There were few significant differences for the threshold diameter of calcifications between glandularities, indicating that the background structure has little effect on the detection of calcifications. We measured larger but nonsignificant differences in the threshold diameters for synthetic 2D imaging than for 2D imaging for masses in the 9% (p = 0.059) and 18% (p = 0.19) glandularities. The threshold diameters for synthetic 2D imaging were larger than for 2D imaging for calcifications (p < 0.001) for all glandularities.

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Section: Methodsmentioning

confidence: 99%

“…The scatter-to-primary ratio (SPR) was modeled using Monte Carlo techniques and was estimated to be 0.19 for 2D imaging and between 0.78 and 0.92 for DBT depending on the tube angle. 44 The same values were used for each breast glandularity. A uniform signal was added to each projection image to simulate scattered radiation.…”

Section: Image Simulationmentioning

confidence: 99%

Effect of glandularity on the detection of simulated cancers in planar, tomosynthesis, and synthetic 2D imaging of the breast using a hybrid virtual clinical trial

et al. 2021

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“…Scatter radiation from the breast compression plate and the support plate also affects the scatter distribution inside the breast. 18,21 Monte Carlo-based scatter estimations have high accuracy, at the cost of long computational time. 18,19,22 Feng et al proposed a model-based method to reduce computational time for patient-specific scatter estimation.…”

Section: Introductionmentioning

confidence: 99%

Deep-learning convolutional neural network-based scatter correction for contrast enhanced digital breast tomosynthesis in both cranio-caudal and mediolateral-oblique views

et al. 2023

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Purpose: Scatter radiation in contrast-enhanced digital breast tomosynthesis (CEDBT) reduces the image quality and iodinated lesion contrast. Monte Carlo simulation can provide accurate scatter estimation at the cost of computational burden. A model-based convolutional method trades off accuracy for processing speed. The purpose of this study is to develop a fast and robust deep-learning (DL) convolutional neural network (CNN)-based scatter correction method for CEDBT.Approach: Projection images and scatter maps of digital anthropomorphic breast phantoms were generated using Monte Carlo simulations. Experiments were conducted to validate the simulated scatter-to-primary ratio (SPR) at different locations of a breast phantom. Simulated projection images were used for CNN training and testing. Two separate U-Nets [low-energy (LE)-CNN and high-energy (HE)-CNN] were trained for LE and HE spectrum, respectively. CNN-based scatter correction was applied to a clinical case with a malignant iodinated mass to evaluate the influence on the lesion detection. Results:The average and standard deviation of mean absolute percentage error of LE-CNN and HE-CNN estimated scatter map are 2% AE 0.4% and 2.4% AE 0.8%, respectively. For clinical cases, the lesion signal difference to noise ratio average improvement was 190% after CNNbased scatter correction. To conduct scatter correction on clinical CEDBT images, the whole process of loading CNNs parameters and scatter correction for LE and HE images took <4 s, with 9 GB GPU computational cost. The SPR variation across the breast agrees between experimental measurements and Monte Carlo simulations. Conclusions:We developed a CNN-based scatter correction method for CEDBT in both CC view and mediolateral-oblique view with high accuracy and fast speed.

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“…In spectral CEDBT, scatter is more severe due to the increase in x-ray energies 2 . To mitigate the effects of scattered radiation, many scatter correction methods have been developed using Monte Carlo (MC) simulation, kernel-based convolution, empirical interpolation, deep learning, and primary modulators [3][4][5][6][7][8][9][10][11] .…”

Section: Introductionmentioning

confidence: 99%

A scatter correction method for contrast-enhanced digital breast tomosynthesis with a dual-layer detector

Duan

Huang

et al. 2023

Medical Imaging 2023: Physics of Medical Imaging

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Contrast-enhanced digital breast tomosynthesis (CEDBT) utilizes iodinated contrast agents and spectral imaging techniques to highlight breast tumors with neo-angiogenesis. Conventional dual-shot (DS) CEDBT suffers from motion artifacts due to patient motion between two separate x-ray exposures for the sequential acquisitions of high- and low-energy (HE and LE) images. To mitigate motion artifacts, a new CEDBT system was designed with a direct-indirect dual-layer (DL) detector. It enables simultaneous acquisition of HE and LE images with a single exposure. Our previous study has demonstrated the feasibility of the DL detector to cancel normal breast tissue and provide lesion contrast comparable to DS. Due to the absence of anti-scatter grids, both DS- and DL-CEDBT suffer image quality degradation from scattered radiation, which introduces cupping artifacts and reduces lesion contrast. In this study, we are proposing a hybrid scatter correction method, which combines the straightforward kernel-based iterative convolution method and the empirical interpolation method. The hybrid method was applied to Monte Carlo (MC) simulated DL-DBT projection images of anthropomorphic digital breast phantoms of varying glandularity and compressed thickness. Results showed that the hybrid method improves scatter estimation accuracy compared to the single-kernel iterative convolution method. The hybrid method was applied to a clinical DS-CEDBT case for scatter correction. The results showed reduced cupping artifacts and improved lesion contrast.

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Simple method for computing scattered radiation in breast tomosynthesis

Cited by 9 publications

References 47 publications

Effect of glandularity on the detection of simulated cancers in planar, tomosynthesis, and synthetic 2D imaging of the breast using a hybrid virtual clinical trial

Effect of glandularity on the detection of simulated cancers in planar, tomosynthesis, and synthetic 2D imaging of the breast using a hybrid virtual clinical trial

Deep-learning convolutional neural network-based scatter correction for contrast enhanced digital breast tomosynthesis in both cranio-caudal and mediolateral-oblique views

A scatter correction method for contrast-enhanced digital breast tomosynthesis with a dual-layer detector

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