Pre-clinical evaluation and optimization of image quality for a next generation tomosynthesis prototype

Vent, Trevor L.; Acciavatti, Raymond J.; Choi, Chloe J.; Barufaldi, Bruno; Krishnamoorthy, S.; Borges, Lucas R.; Kuo, Johnny; Ringer, Peter; Ng, Susan; Surti, Suleman; Maidment, Andrew D. A.

doi:10.1117/12.2608811

Cited by 3 publications

(5 citation statements)

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“…Image acquisition, processing, and reconstruction techniques can be personalized and would potentially benefit from customized scanning motions; advanced and custom-tailored reconstruction techniques can be developed to improve the image quality with reduced outof-plane artifacts in DBT. Our previous work has demonstrated the benefits of customized acquisitions for: improved visibility of finer and small structures in mastectomy images [28], reduced cone beam artifacts with a superior breast outline demarcation [12,17,44], and improved fibroglandular-adipose tissue contrast with reduced out-of-plane artifacts [15,16]. Our colleagues' work [21] also emphasized the additional clinical benefits with more accurate information of breast tissue and the convex hull such as improved volumetric tissue estimation and registration [45][46][47] and improved models for 3D printing of phantoms [48].…”

Section: Discussionmentioning

confidence: 99%

“…The conventional geometry ( Table 2 .I) encompassed 15 projections with source motion in the left–right (LR) direction. The “T” geometry ( Table 2 .II) incorporated seven projections with source motion in the PA direction and eight projections with source motion in the LR direction (i.e., LR) [ 28 ]. Finally, we simulated a hypothetical acquisition geometry ( Table 2 .III, extra-wide angular range or XWR), since previous work had demonstrated that wide-range scanning offers the most accurate segmentation of the 3D breast outline or “convex hull” [ 24 ].…”

Section: Methodsmentioning

confidence: 99%

“…Clinical DBT systems use a limited angle acquisition with a small number of low-dose projections that can result in out-of-plane artifacts of breast tissue in the DBT reconstructions [ 24 , 27 ]. The accurate estimate of breast density using DBT images is challenging because of the presence of out-of-plane artifacts and the superposition of breast tissue [ 28 ]. Fully automated systems have been developed to quantify fibroglandular tissue in DBT images [ 29 , 30 ].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

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Section: Introductionmentioning

confidence: 99%

“…The University of Pennsylvania has developed a prototype next-generation tomosynthesis (NGT) system with more complex scanning motions than current clinical DBT systems [4][5][6][7]. The NGT system is capable of scanning with an additional component of source motion in the posteroanterior direction (perpendicular to the conventional motion), reducing out-of-focus structures [7]. Our ultimate goal is to incorporate scanning motions into the NGT system that are customized around suspicious areas (e.g., breast cancers, parenchyma distortions, and dense clusters), as well as areas prone to cancer masking, for improved breast screening and diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Multiclass Segmentation of Breast Tissue and Suspicious Findings: A Simulation-Based Study for the Development of Self-Steering Tomosynthesis

Barufaldi,

da Nobrega,

Carvalhal

et al. 2023

Tomography

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In breast tomosynthesis, multiple low-dose projections are acquired in a single scanning direction over a limited angular range to produce cross-sectional planes through the breast for three-dimensional imaging interpretation. We built a next-generation tomosynthesis system capable of multidirectional source motion with the intent to customize scanning motions around “suspicious findings”. Customized acquisitions can improve the image quality in areas that require increased scrutiny, such as breast cancers, architectural distortions, and dense clusters. In this paper, virtual clinical trial techniques were used to analyze whether a finding or area at high risk of masking cancers can be detected in a single low-dose projection and thus be used for motion planning. This represents a step towards customizing the subsequent low-dose projection acquisitions autonomously, guided by the first low-dose projection; we call this technique “self-steering tomosynthesis.” A U-Net was used to classify the low-dose projections into “risk classes” in simulated breasts with soft-tissue lesions; class probabilities were modified using post hoc Dirichlet calibration (DC). DC improved the multiclass segmentation (Dice = 0.43 vs. 0.28 before DC) and significantly reduced false positives (FPs) from the class of the highest risk of masking (sensitivity = 81.3% at 2 FPs per image vs. 76.0%). This simulation-based study demonstrated the feasibility of identifying suspicious areas using a single low-dose projection for self-steering tomosynthesis.

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

Marshall¹,

Bosmans²

2022

Phys. Med. Biol.

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

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Pre-clinical evaluation and optimization of image quality for a next generation tomosynthesis prototype

Cited by 3 publications

References 14 publications

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

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

Multiclass Segmentation of Breast Tissue and Suspicious Findings: A Simulation-Based Study for the Development of Self-Steering Tomosynthesis

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

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