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Breast Density Analysis Using Digital Breast Tomosynthesis

We evaluated an automated percentage of breast density (BD) technique (PD(a)) with digital breast tomosynthesis (DBT) data. The approach is based on the wavelet expansion followed by analyzing signal dependent noise. Several measures were investigated as risk factors: normalized volumetric; total de...

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Autores principales: Heine, John, Fowler, Erin E.E., Weinfurtner, R. Jared, Hume, Emma, Tworoger, Shelley S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9948963/
https://www.ncbi.nlm.nih.gov/pubmed/36824710
http://dx.doi.org/10.1101/2023.02.10.527911
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author Heine, John
Fowler, Erin E.E.
Weinfurtner, R. Jared
Hume, Emma
Tworoger, Shelley S.
author_facet Heine, John
Fowler, Erin E.E.
Weinfurtner, R. Jared
Hume, Emma
Tworoger, Shelley S.
author_sort Heine, John
collection PubMed
description We evaluated an automated percentage of breast density (BD) technique (PD(a)) with digital breast tomosynthesis (DBT) data. The approach is based on the wavelet expansion followed by analyzing signal dependent noise. Several measures were investigated as risk factors: normalized volumetric; total dense volume; average of the DBT slices (slice-mean); a two-dimensional (2D) metric applied to the synthetic images; and the mean and standard deviations of the pixel values. Volumetric measures were derived theoretically, and PD(a) was modeled as a function of compressed breast thickness. An alternative method for constructing synthetic 2D mammograms was investigated using the volume results. A matched case-control study (n = 426 pairs) was analyzed. Conditional logistic regression modeling, controlling body mass index and ethnicity, was used to estimate odds ratios (ORs) for each measure with 95% confidence intervals provided parenthetically. There were several significant findings: volumetric measure [OR = 1.43 (1.18, 1.72)], which produced an identical OR as the slice-mean measure as predicted; [OR =1.44 (1.18, 1.75)] when applied to the synthetic images; and mean of the pixel values (volume or 2D synthetic) [ORs ~ 1.31 (1.09, 1.57)]. PD(a) was modeled as 2(nd) degree polynomial (concave-down): its maximum value occurred at 0.41×(compressed breast thickness), which was similar across case-control groups, and was significant from this position [OR = 1.47 (1.21, 1.78)]. A standardized 2D synthetic image was produced, where each pixel value represents the percentage of BD above its location. The significant findings indicate the validity of the technique. Derivations supported by empirical analyses produced a new synthetic 2D standardized image technique. Ancillary to the objectives, the results provide evidence for understanding the percentage of BD measure applied to 2D mammograms. Notwithstanding the findings, the study design provides a template for investigating other measures such as texture.
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spelling pubmed-99489632023-02-24 Breast Density Analysis Using Digital Breast Tomosynthesis Heine, John Fowler, Erin E.E. Weinfurtner, R. Jared Hume, Emma Tworoger, Shelley S. bioRxiv Article We evaluated an automated percentage of breast density (BD) technique (PD(a)) with digital breast tomosynthesis (DBT) data. The approach is based on the wavelet expansion followed by analyzing signal dependent noise. Several measures were investigated as risk factors: normalized volumetric; total dense volume; average of the DBT slices (slice-mean); a two-dimensional (2D) metric applied to the synthetic images; and the mean and standard deviations of the pixel values. Volumetric measures were derived theoretically, and PD(a) was modeled as a function of compressed breast thickness. An alternative method for constructing synthetic 2D mammograms was investigated using the volume results. A matched case-control study (n = 426 pairs) was analyzed. Conditional logistic regression modeling, controlling body mass index and ethnicity, was used to estimate odds ratios (ORs) for each measure with 95% confidence intervals provided parenthetically. There were several significant findings: volumetric measure [OR = 1.43 (1.18, 1.72)], which produced an identical OR as the slice-mean measure as predicted; [OR =1.44 (1.18, 1.75)] when applied to the synthetic images; and mean of the pixel values (volume or 2D synthetic) [ORs ~ 1.31 (1.09, 1.57)]. PD(a) was modeled as 2(nd) degree polynomial (concave-down): its maximum value occurred at 0.41×(compressed breast thickness), which was similar across case-control groups, and was significant from this position [OR = 1.47 (1.21, 1.78)]. A standardized 2D synthetic image was produced, where each pixel value represents the percentage of BD above its location. The significant findings indicate the validity of the technique. Derivations supported by empirical analyses produced a new synthetic 2D standardized image technique. Ancillary to the objectives, the results provide evidence for understanding the percentage of BD measure applied to 2D mammograms. Notwithstanding the findings, the study design provides a template for investigating other measures such as texture. Cold Spring Harbor Laboratory 2023-02-16 /pmc/articles/PMC9948963/ /pubmed/36824710 http://dx.doi.org/10.1101/2023.02.10.527911 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Heine, John
Fowler, Erin E.E.
Weinfurtner, R. Jared
Hume, Emma
Tworoger, Shelley S.
Breast Density Analysis Using Digital Breast Tomosynthesis
title Breast Density Analysis Using Digital Breast Tomosynthesis
title_full Breast Density Analysis Using Digital Breast Tomosynthesis
title_fullStr Breast Density Analysis Using Digital Breast Tomosynthesis
title_full_unstemmed Breast Density Analysis Using Digital Breast Tomosynthesis
title_short Breast Density Analysis Using Digital Breast Tomosynthesis
title_sort breast density analysis using digital breast tomosynthesis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9948963/
https://www.ncbi.nlm.nih.gov/pubmed/36824710
http://dx.doi.org/10.1101/2023.02.10.527911
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