Power Spectrum Analysis of Breast Parenchyma with Digital Breast Tomosynthesis Images in a Longitudinal Screening Cohort from Two Vendors.

Rationale and Objectives: To quantitatively compare breast parenchymal texture between two Digital Breast Tomosynthesis (DBT) vendors using images from the same patients.Materials and Methods: This retrospective study included consecutive patients who had normal screening DBT exams performed in Janu...

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Publicado en:Academic Radiology Vol. 29; no. 6; pp. 841 - 851
Autores principales: Yang, Kai, Abbey, Craig K, Chou, Shinn-Huey Shirley, Dontchos, Brian N, Li, Xinhua, Lehman, Constance D, Liu, Bob
Formato: research Journal Article
Publicado: Elsevier B.V. Jun2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2022
      vid: 29
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      pub: Elsevier B.V.
      place: New York, New York
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        156650619
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        156650619
        10.1016/j.acra.2021.08.014
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        156650619
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        atl: Power Spectrum Analysis of Breast Parenchyma with Digital Breast Tomosynthesis Images in a Longitudinal Screening Cohort from Two Vendors.
      aug:
        au:
          Yang, Kai
          Abbey, Craig K
          Chou, Shinn-Huey Shirley
          Dontchos, Brian N
          Li, Xinhua
          Lehman, Constance D
          Liu, Bob
        affil: Division of Diagnostic Imaging Physics, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
      sug:
        subj:
          Breast Neoplasms
          Mammography Methods
          Retrospective Design
          Spectrum Analysis
          Female
          Male
          Breast
          Health Screening
          Human
          Female
          Male
      ab: Rationale and Objectives: To quantitatively compare breast parenchymal texture between two Digital Breast Tomosynthesis (DBT) vendors using images from the same patients.Materials and Methods: This retrospective study included consecutive patients who had normal screening DBT exams performed in January 2018 from GE and normal screening DBT exams in adjacent years from Hologic. Power spectrum analysis was performed within the breast tissue region. The slope of a linear function between log-frequency and log-power, β, was derived as a quantitative measure of breast texture and compared within and across vendors along with secondary parameters (laterality, view, year, image format, and breast density) with correlation tests and t-tests.Results: A total of 24,339 DBT slices or synthetic 2D images from 85 exams in 25 women were analyzed. Strong power-law behavior was verified from all images. Values of β d did not differ significantly for laterality, view, or year. Significant differences of β were observed across vendors for DBT images (Hologic: 3.4±0.2 vs GE: 3.1±0.2, 95% CI on difference: 0.27 to 0.30) and synthetic 2D images (Hologic: 2.7±0.3 vs GE: 3.0±0.2, 95% CI on difference: -0.36 to -0.27), and density groups with each vendor: scattered (GE: 3.0±0.3, Hologic: 3.3±0.3) vs. heterogeneous (GE: 3.2±0.2, Hologic: 3.4±0.1), 95% CI (-0.27, -0.08) and (-0.21, -0.05), respectively.Conclusion: There are quantitative differences in the presentation of breast imaging texture between DBT vendors and across breast density categories. Our findings have relevance and importance for development and optimization of AI algorithms related to breast density assessment and cancer detection.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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