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数字乳腺断层合成术在对比增强乳腺摄影检测到的病变的真实病理中对升级 BI-RADS 评分的作用。

Digital Breast Tomosynthesis for Upgraded BIRADS Scoring towards the True Pathology of Lesions Detected by Contrast-Enhanced Mammography.

机构信息

Radiology, Rabin Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo 49100, Israel.

Biostatistics, Rabin Medical Center, Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo 49100, Israel.

出版信息

Tomography. 2024 May 20;10(5):806-815. doi: 10.3390/tomography10050061.

Abstract

OBJECTIVE

To determine the added value of digital breast tomosynthesis (DBT) in the assessment of lesions detected by contrast-enhanced mammography (CEM).

MATERIAL AND METHODS

A retrospective study was conducted in a tertiary university medical center. All CEM studies including DBT performed between January 2016 and December 2020 were included. Lesions were categorized and scored by four dedicated breast radiologists according to the recent CEM and DBT supplements to the Breast Imaging Reporting and Data System (BIRADS) lexicon. Changes in the BIRADS score of CEM-detected lesions with the addition of DBT were evaluated according to the pathology results and 1-year follow-up imaging study.

RESULTS

BIRADS scores of CEM-detected lesions were upgraded toward the lesion's pathology with the addition of DBT ( > 0.0001), overall and for each reader. The difference in BIRADS scores before and after the addition of DBT was more significant for readers who were less experienced. The reason for changes in the BIRADS score was better lesion margin visibility. The main BIRADS descriptors applied in the malignant lesions were spiculations, calcifications, architectural distortion, and sharp or obscured margins.

CONCLUSIONS

The addition of DBT to CEM provides valuable information on the enhancing lesion, leading to a more accurate BIRADS score.

摘要

目的

评估对比增强乳腺摄影(CEM)检出病变中数字乳腺断层合成技术(DBT)的附加价值。

材料与方法

这是一项在三级大学医学中心进行的回顾性研究。纳入 2016 年 1 月至 2020 年 12 月期间进行的所有包含 DBT 的 CEM 研究。根据乳腺影像报告和数据系统(BIRADS)词汇表最近的 CEM 和 DBT 补充,由四位专门的乳腺放射科医生对病变进行分类和评分。根据病理结果和 1 年随访影像学研究,评估 CEM 检出病变的 BIRADS 评分随 DBT 的增加而变化。

结果

与 CEM 检出病变的 BIRADS 评分相比,添加 DBT 后(>0.0001),总体和每位读者的评分均升高。对于经验较少的读者,添加 DBT 前后 BIRADS 评分的差异更显著。BIRADS 评分变化的原因是更好地显示病变边界。在恶性病变中应用的主要 BIRADS 描述符是分叶状、钙化、结构扭曲和锐利或模糊的边界。

结论

将 DBT 添加到 CEM 中可以提供关于增强病变的有价值信息,从而使 BIRADS 评分更准确。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb05/11125662/660c353da1c2/tomography-10-00061-g001.jpg

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