| 1. |
- Bjerkén, Anna, et al.
(författare)
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Dose evaluation of simultaneous breast radiography and mechanical imaging
- 2023
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Ingår i: Medical Imaging 2023 : Physics of Medical Imaging - Physics of Medical Imaging. ; 12463
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Konferensbidrag (refereegranskat)abstract
- This study investigates the impact in terms of radiation dose when performing simultaneous digital breast tomosynthesis(DBT) and mechanical imaging (MI) – DBTMI. DBTMI has demonstrated the potential to increase specificity of cancerdetection, and reduce unnecessary biopsies, as compared to digital mammography (DM) screening. The presence of theMI sensor during simultaneous image acquisition may increase the radiation dose when automatic exposure control is used.In this project, a radiation dose study was conducted on clinically available breast imaging systems with and without theMI sensor. We have investigated three approaches to analyse the dose increase in DBTMI, using (i) the estimates of averageglandular dose (AGD) reported in DICOM headers of radiography images; (ii) AGD measured by a conventionaldosemeter; and (iii) AGD measured by optically stimulated luminescence using NaCl pellets. The relative increase in AGDestimated from DICOM headers when using the MI sensor was on average 10.7% and 12.4%, for DM and DBTmeasurements, respectively. The relative increase in AGD using the conventional dosemeter was 11.2% in DM mode and12.2% in DBT mode. The relative increase in AGD using NaCl pellets was 14.6% in DM mode. Our measurements suggestthat the use of simultaneous breast radiography and MI increases the AGD by 13% on average. The increase in dose is stillbelow the acceptable values in mammography screening recommended by the European Guidelines.
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| 2. |
- Costa, Arthur C., et al.
(författare)
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Assessment of projection interpolation to compensate for the increased radiation dose in DBTMI
- 2023
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Ingår i: Medical Imaging 2023 : Physics of Medical Imaging - Physics of Medical Imaging. - 1605-7422. - 9781510660311 ; 12463
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Konferensbidrag (refereegranskat)abstract
- The combination of digital breast tomosynthesis (DBT) with other imaging modalities has been investigated in order to improve the detection and diagnosis of breast cancer. Mechanical Imaging (MI) measures the stress over the surface of the compressed breast, using a pressure sensor, during radiographic examination and its response has shown a correlation with the presence of malignant lesions. Thus, the combination of DBT and MI (DBTMI) has shown potential to reduce false positive results in breast cancer screening. However, compared to the conventional DBT exam, the presence of the MI sensor during mammographic image acquisition may cause a slight increase in the radiation dose. This work presents a proposal to reduce the radiation dose in DBTMI exams by removing some projections from the original set and replacing them with synthetic projections generated by a video frame interpolation (VFI) neural network. We compared several DBTMI acquisition arrangements, considering the removal of 16% of the original projections, using a deformable physical breast phantom, and evaluated the quality of the reconstructed images based on the Normalized Root Mean Squared Error (NRMSE). The results showed that, for some arrangements, the slices reconstructed with the addition of synthetic DBTMI projections presented better quality than when they were reconstructed with the reduced set of projections. Further studies must be carried out to optimize the interpolation approach.
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| 3. |
- Dustler, Magnus, et al.
(författare)
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Realism of mammography tissue patches simulated using perlin noise : A forced choice reading study
- 2021
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Ingår i: Medical Imaging 2021 : Physics of Medical Imaging - Physics of Medical Imaging. - : SPIE. - 1605-7422. - 9781510640191 ; 11595
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Konferensbidrag (refereegranskat)abstract
- Software breast phantoms are central to the optimization of breast imaging, where in many cases the use of real images would be inefficient - or impossible. Establishing the realism of such phantoms is critical. For this study, patches of simulated breast tissue with different composition - fatty, scattered, heterogenous and dense tissue - were generated using a method based on Perlin noise. The composition of the patches is controlled by numerical parameters derived from input by radiologists and medical physicists with experience of breast imaging. Separate Perlin noise-based methods were used to simulate skin pores, high-frequency noise (representing quantum and electronic noise) and ligaments and vascular structures. In a forced choice reading study, the realism of the simulated tissue patches compared to patches from real mammograms was determined. Patches of 200-500 pixels were extracted from radiolucent, linear, nodular or homogenous (10 per category) mammograms randomly selected from a previously acquired dataset. Eighteen simulated patches in the same size range were added. Four readers, two radiologists and two medical physicists were shown the images in random order and asked to rate them as real or simulated. All readers accepted a substantial fraction of simulated images as real, ranging from 22% to 72%. Only two readers showed a significant difference in the number of images rated real in the real and simulated groups, 22% vs 73% (P=.0003) and 33% vs 63% (P=.04), respectively. These results suggest that the method employed can create images that are almost indistinguishable from patches of real mammograms.
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| 4. |
- Petersson, Hannie, et al.
(författare)
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VALIDATION OF A SIMULATION PROCEDURE FOR GENERATING BREAST TOMOSYNTHESIS PROJECTION IMAGES.
- 2016
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Ingår i: Radiation Protection Dosimetry. - : Oxford University Press (OUP). - 1742-3406 .- 0144-8420.
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Tidskriftsartikel (refereegranskat)abstract
- In order to achieve optimal diagnostic performance in breast tomosynthesis (BT) imaging, the parameters of the imaging chain should be evaluated. For the purpose of such evaluations, a simulation procedure based on the Monte Carlo code system Penelope and the geometry of a Siemens BT system has been developed to generate BT projection images. In this work, the simulation procedure is validated by comparing contrast and sharpness in simulated images with contrast and sharpness in real images acquired with the BT system. The results of the study showed a good agreement of sharpness in real and simulated reconstructed image planes, but the contrast was shown to be higher in the simulated compared with the real projection images. The developed simulation procedure could be used to generate BT images, but it is of interest to further investigate how the procedure could be modified to generate more realistic image noise and contrast.
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| 5. |
- Rodriguez-Ruiz, Alejandro, et al.
(författare)
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One-view digital breast tomosynthesis as a stand-alone modality for breast cancer detection : do we need more?
- 2018
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Ingår i: European Radiology. - : Springer Science and Business Media LLC. - 0938-7994 .- 1432-1084. ; 28:5, s. 1938-1948
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To compare the performance of one-view digital breast tomosynthesis (1v-DBT) to that of three other protocols combining DBT and mammography (DM) for breast cancer detection. Materials and methods: Six radiologists, three experienced with 1v-DBT in screening, retrospectively reviewed 181 cases (76 malignant, 50 benign, 55 normal) in two sessions. First, they scored sequentially: 1v-DBT (medio-lateral oblique, MLO), 1v-DBT (MLO) + 1v-DM (cranio-caudal, CC) and two-view DM + DBT (2v-DM+2v-DBT). The second session involved only 2v-DM. Lesions were scored using BI-RADS® and level of suspiciousness (1–10). Sensitivity, specificity, receiver operating characteristic (ROC) and jack-knife alternative free-response ROC (JAFROC) were computed. Results: On average, 1v-DBT was non-inferior to any of the other protocols in terms of JAFROC figure-of-merit, area under ROC curve, sensitivity or specificity (p>0.391). While readers inexperienced with 1v-DBT screening improved their sensitivity when adding more images (69–79 %, p=0.019), experienced readers showed similar sensitivity (76 %) and specificity (70 %) between 1v-DBT and 2v-DM+2v-DBT (p=0.482). Subanalysis by lesion type and breast density showed no difference among modalities. Conclusion: Detection performance with 1v-DBT is not statistically inferior to 2v-DM or to 2v-DM+2v-DBT; its use as a stand-alone modality might be sufficient for readers experienced with this protocol. Key points: • One-view breast tomosynthesis is not inferior to two-view digital mammography.• One-view DBT is not inferior to 2-view DM plus 2-view DBT.• Training may lead to 1v-DBT being sufficient for screening.
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| 6. |
- Teixeira, Joao P.V., et al.
(författare)
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Novel Perlin-based phantoms using 3D models of compressed breast shapes and fractal noise
- 2022
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Ingår i: Medical Imaging 2022 : Physics of Medical Imaging - Physics of Medical Imaging. - : SPIE. - 1605-7422. - 9781510649378 ; 12031
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Konferensbidrag (refereegranskat)abstract
- Virtual clinical trials (VCTs) have been used widely to evaluate digital breast tomosynthesis (DBT) systems. VCTs require realistic simulations of the breast anatomy (phantoms) to characterize lesions and to estimate risk of masking cancers. This study introduces the use of Perlin-based phantoms to optimize the acquisition geometry of a novel DBT prototype. These phantoms were developed using a GPU implementation of a novel library called Perlin-CuPy. The breast anatomy is simulated using 3D models under mammography cranio-caudal compression. In total, 240 phantoms were created using compressed breast thickness, chest-wall to nipple distance, and skin thickness that varied in a {[35, 75], [59, 130), [1.0, 2.0]} mm interval, respectively. DBT projections and reconstructions of the phantoms were simulated using two acquisition geometries of our DBT prototype. The performance of both acquisition geometries was compared using breast volume segmentations of the Perlin phantoms. Results show that breast volume estimates are improved with the introduction of posterior-anterior motion of the x-ray source in DBT acquisitions. The breast volume is overestimated in DBT, varying substantially with the acquisition geometry; segmentation errors are more evident for thicker and larger breasts. These results provide additional evidence and suggest that custom acquisition geometries can improve the performance and accuracy in DBT. Perlin phantoms help to identify limitations in acquisition geometries and to optimize the performance of the DBT prototypes.
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| 7. |
- Tomic, Hanna, et al.
(författare)
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Using simulated breast lesions based on Perlin noise for evaluation of lesion segmentation
- 2024
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Ingår i: Medical Imaging 2024 : Physics of Medical Imaging - Physics of Medical Imaging. - : SPIE-Intl Soc Optical Eng. - 1605-7422. - 9781510671546 ; 12925
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Konferensbidrag (refereegranskat)abstract
- Segmentation of diagnostic radiography images using deep learning is progressively expanding, which sets demands on the accessibility, availability, and accuracy of the software tools used. This study aimed at evaluating the performance of a segmentation model for digital breast tomosynthesis (DBT), with the use of computer-simulated breast anatomy. We have simulated breast anatomy and soft tissue breast lesions, by utilizing a model approach based on the Perlin noise algorithm. The obtained breast phantoms were projected and reconstructed into DBT slices using a publicly available open-source reconstruction method. Each lesion was then segmented using two approaches: 1. the Segment Anything Model (SAM), a publicly available AI-based method for image segmentation and 2. manually by three human observers. The lesion area in each slice was compared to the ground truth area, derived from the binary mask of the lesion model. We found similar performance between SAM and manual segmentation. Both SAM and the observers performed comparably in the central slice (mean absolute relative error compared to the ground truth and standard deviation SAM: 4 ± 3 %, observers: 3 ± 3 %). Similarly, both SAM and the observers overestimated the lesion area in the peripheral reconstructed slices (mean absolute relative error and standard deviation SAM: 277 ± 190 %, observers: 295 ± 182 %). We showed that 3D voxel phantoms can be used for evaluating different segmentation methods. In preliminary comparison, tumor segmentation in simulated DBT images using SAM open-source method showed a similar performance as manual tumor segmentation.
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| 8. |
- Torlegård, B., et al.
(författare)
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Identifying and modelling clinical subpopulations from the Malmö breast tomosynthesis screening trial
- 2020
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Ingår i: 15th International Workshop on Breast Imaging, IWBI 2020. - : SPIE. - 0277-786X .- 1996-756X. - 9781510638310 ; 11513
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Konferensbidrag (refereegranskat)abstract
- Virtual Clinical Trials (VCT) are an effective tool to evaluate the performance of novel imaging systems using computer simulations. VCT results depend on the selection of virtual patient populations. In the case of breast imaging, virtual patients should be matched to a desired clinical population in terms of selected anatomical or demographic descriptors. We are developing a virtual population of women who participated in the Malmö Breast Tomosynthesis Screening Trial (MBTST). We have used clinical values of the compressed breast thickness and volumetric breast density to develop a multidimensional distribution of women in MBTST. Breast density and thickness values were obtained from anonymized, previously collected tomosynthesis images of 14,746 women. In this paper, we compare several approaches to identify clinical subpopulations and select virtual patients that represent various groups of clinical subjects. We performed two methods to identify clinical subpopulations by clustering clinical data using the K-means algorithm or woman's age. The obtained clusters have been explored and compared using the silhouette mean. The K-means algorithm yielded grouping of MBTST data into two clusters; however, that grouping was, shown to be suboptimal by the silhouette analysis. The agebased clustering showed significant overlap in terms of breast thickness and density. We also compared two approaches to select sets of representative phantoms. Our analysis has emphasized benefits and limitations of different clustering methods. The preferred method depends on the specific task that should be addressed using VCTs. Simulation of representative phantoms is ongoing. Potential correlations with pathological findings and/or parenchymal properties will be investigated.
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