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数字乳腺断层合成的乳腺密度分析。

Breast density analysis of digital breast tomosynthesis.

机构信息

Cancer Epidemiology Department, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA.

Diagnostic Imaging and Interventional Radiology, Moffitt Cancer Center and Research Institute, 12902 Bruce B. Downs Blvd, Tampa, FL, 33612, USA.

出版信息

Sci Rep. 2023 Oct 31;13(1):18760. doi: 10.1038/s41598-023-45402-x.

DOI:10.1038/s41598-023-45402-x
PMID:37907569
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10618274/
Abstract

Mammography shifted to digital breast tomosynthesis (DBT) in the US. An automated percentage of breast density (PD) technique designed for two-dimensional (2D) applications was evaluated with DBT using several breast cancer risk prediction measures: normalized-volumetric; dense volume; applied to the volume slices and averaged (slice-mean); and applied to synthetic 2D images. Volumetric measures were derived theoretically. PD was modeled as a function of compressed breast thickness (CBT). The mean and standard deviation of the pixel values were investigated. A matched case-control (CC) study (n = 426 pairs) was evaluated. Odd ratios (ORs) were estimated with 95% confidence intervals. ORs were significant for PD: identical for volumetric and slice-mean measures [OR = 1.43 (1.18, 1.72)] and [OR = 1.44 (1.18, 1.75)] for synthetic images. A 2nd degree polynomial (concave-down) was used to model PD as a function of CBT: location of the maximum PD value was similar across CCs, occurring at 0.41 × CBT, and PD was significant [OR = 1.47 (1.21, 1.78)]. The means from the volume and synthetic images were also significant [ORs ~ 1.31 (1.09, 1.57)]. An alternative standardized 2D synthetic image was constructed, where each pixel value represents the percentage of breast density above its location. Several measures were significant and an alternative method for constructing a standardized 2D synthetic image was produced.

摘要

在美国,乳腺 X 光摄影已转向数字乳腺断层合成技术(DBT)。评估了一种针对二维(2D)应用设计的自动乳腺密度(PD)百分比技术,该技术使用了几种乳腺癌风险预测指标:归一化体积;致密体积;应用于体积切片并取平均值(切片平均值);以及应用于合成 2D 图像。体积测量是从理论上推导出来的。PD 被建模为压缩乳腺厚度(CBT)的函数。研究了像素值的平均值和标准差。评估了一项匹配病例对照(CC)研究(n=426 对)。估计了 95%置信区间的比值比(OR)。PD 的 OR 具有统计学意义:体积和切片平均值测量的 OR 相同[OR=1.43(1.18,1.72)]和[OR=1.44(1.18,1.75)]对于合成图像。使用二次多项式(凹向下)将 PD 建模为 CBT 的函数:CC 之间最大 PD 值的位置相似,出现在 0.41×CBT 处,PD 有统计学意义[OR=1.47(1.21,1.78)]。体积和合成图像的平均值也具有统计学意义[ORs~1.31(1.09,1.57)]。还构建了替代的标准化 2D 合成图像,其中每个像素值代表其位置以上的乳腺密度百分比。有几个指标具有统计学意义,并生成了构建标准化 2D 合成图像的替代方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/d4c5590503da/41598_2023_45402_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/5e7757fc733d/41598_2023_45402_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/6a0b8348161b/41598_2023_45402_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/79f60208b639/41598_2023_45402_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/3ef8b42d1b90/41598_2023_45402_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/d4c5590503da/41598_2023_45402_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/5e7757fc733d/41598_2023_45402_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/8801b35dd1b0/41598_2023_45402_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/bbf19273c4a4/41598_2023_45402_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/6a0b8348161b/41598_2023_45402_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/79f60208b639/41598_2023_45402_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/3ef8b42d1b90/41598_2023_45402_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17d9/10618274/d4c5590503da/41598_2023_45402_Fig7_HTML.jpg

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2
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Breast. 2022 Dec;66:62-68. doi: 10.1016/j.breast.2022.09.007. Epub 2022 Sep 26.
3
A risk model for digital breast tomosynthesis to predict breast cancer and guide clinical care.一种用于数字乳腺断层合成的风险模型,以预测乳腺癌并指导临床护理。
Medicina (Kaunas). 2024 Mar 30;60(4):570. doi: 10.3390/medicina60040570.
Sci Transl Med. 2022 May 11;14(644):eabn3971. doi: 10.1126/scitranslmed.abn3971.
4
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Phys Med. 2022 Jun;98:88-97. doi: 10.1016/j.ejmp.2022.04.006. Epub 2022 May 5.
5
Artificial intelligence in mammographic phenotyping of breast cancer risk: a narrative review.人工智能在乳腺癌风险的乳腺摄影表型中的应用:叙述性综述。
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6
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J Am Coll Radiol. 2021 Nov;18(11S):S456-S473. doi: 10.1016/j.jacr.2021.09.002.
7
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