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...
| Publicado en: | Academic Radiology Vol. 29; no. 6; pp. 841 - 851 |
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| Autores principales: | , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Jun2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=156650619&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 156650619 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10766332 T4X jtl: Academic Radiology issn: 10766332 maglogo: N pubinfo: dt: Jun2022 vid: 29 iid: 6 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 156650619 156650619 NLM34563442 156650619 10.1016/j.acra.2021.08.014 NLM34563442 156650619 ppf: 841 ppct: 10 formats: tig: 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 refInfo: holdings: @attributes: islocal: N |
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