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从大型多中心 MRI 数据库中衍生的乳腺表观扩散系数分类系统(ADC-B)的介绍。

Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database.

机构信息

Dpt. of Biomedical Imaging and Image Guided Therapy, Medical University Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.

Diagnosezentrum Meidling, Meidlinger Hauptstr. 7 - 9, 1120, Vienna, Austria.

出版信息

Eur Radiol. 2023 Aug;33(8):5400-5410. doi: 10.1007/s00330-023-09675-0. Epub 2023 May 11.

Abstract

OBJECTIVES

To develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria.

METHODS

This was a multicentric, retrospective analysis of 11 independently conducted institutional review board-approved studies from seven institutions performed between 2007 and 2019. Breast Apparent Diffusion coefficient (ADC-B) categories comprised ADC-B0 (ADC non-diagnostic), ADC-B1 (no enhancing lesion), and ADC-B2-5. The latter was defined by plotting ADC versus cumulative malignancy rates. Statistics comprised ANOVA with post hoc testing and ROC analysis. p values ≤ 0.05 were considered statistically significant.

RESULTS

A total of 1625 patients (age: 55.9 years (± 13.8)) with 1736 pathologically verified breast lesions were included. The mean ADC (× 10 mm/s) differed significantly between benign (1.45, SD .40) and malignant lesions (.95, SD .39), and between invasive (.92, SD .22) and in situ carcinomas (1.18, SD .30) (p < .001). The following ADC-B categories were identified: ADC-B0-ADC cannot be assessed; ADC-B1-no contrast-enhancing lesion; ADC-B2-ADC ≥ 1.9 (cumulative malignancy rate < 0.1%); ADC-B3-ADC 1.5 to < 1.9 (0.1-1.7%); ADC-B4-ADC 1.0 to < 1.5 (10-24.5%); and ADC-B5-ADC < 1.0 (> 24.5%). At the latter threshold, a positive predictive value of 95.8% (95% CI 0.94-0.97) for invasive versus non-invasive breast carcinomas was reached.

CONCLUSIONS

The breast apparent diffusion coefficient system (ADC-B) provides a simple and widely applicable categorization scheme for assessment, documentation, and reporting of apparent diffusion coefficient values in contrast-enhancing breast lesions on MRI.

CLINICAL RELEVANCE STATEMENT

The ADC-B system, based on diverse MRI examinations, is clinically relevant for stratifying breast cancer risk via apparent diffusion coefficient measurements, and complements BI-RADS for improved clinical decision-making and patient outcomes.

KEY POINTS

• The breast apparent diffusion coefficient category system (ADC-B) is a simple tool for the assessment, documentation, and reporting of ADC values in contrast-enhancing breast lesions on MRI. • The categories comprise ADC-B0 for non-diagnostic examinations, ADC-B1 for examinations without an enhancing lesion, and ADC-B2-5 for enhancing lesions with an increasing malignancy rate. • The breast apparent diffusion coefficient category system may be used to complement BI-RADS in clinical decision-making.

摘要

目的

开发一种直观且普遍适用的 ADC 报告、评估和记录系统,以补充标准 BI-RADS 标准。

方法

这是一项多中心、回顾性分析,纳入了 2007 年至 2019 年间在 7 个机构进行的 11 项独立的机构审查委员会批准的研究。乳腺表观扩散系数(ADC-B)类别包括 ADC-B0(ADC 无诊断价值)、ADC-B1(无增强病变)和 ADC-B2-5。后一种情况是通过绘制 ADC 与累积恶性率来定义的。统计分析包括方差分析和事后检验以及 ROC 分析。p 值≤0.05 被认为具有统计学意义。

结果

共纳入 1625 例(年龄:55.9 岁(±13.8))和 1736 例经病理证实的乳腺病变患者。良性病变(1.45,SD.40)和恶性病变(1.45,SD.40)之间、浸润性(1.45,SD.40)和原位癌(1.18,SD.30)之间的平均 ADC(×10 mm/s)差异有统计学意义(p < 0.001)。确定了以下 ADC-B 类别:ADC-B0-无法评估 ADC;ADC-B1-无增强病变;ADC-B2-ADC≥1.9(累积恶性率<0.1%);ADC-B3-ADC 为 1.5 至<1.9(0.1-1.7%);ADC-B4-ADC 为 1.0 至<1.5(10-24.5%);和 ADC-B5-ADC<1.0(>24.5%)。在后一个阈值下,浸润性与非浸润性乳腺癌的阳性预测值达到 95.8%(95%CI 0.94-0.97)。

结论

乳腺表观扩散系数系统(ADC-B)为 MRI 增强乳腺病变的 ADC 值的评估、记录和报告提供了一种简单且广泛适用的分类方案。

临床意义

基于多种 MRI 检查,ADC-B 系统通过表观扩散系数测量对乳腺癌风险进行分层,与 BI-RADS 一起补充,以改善临床决策和患者结局。

要点

•乳腺表观扩散系数分类系统(ADC-B)是一种简单的工具,用于评估、记录和报告 MRI 增强乳腺病变中的 ADC 值。•类别包括 ADC-B0 用于非诊断检查、ADC-B1 用于无增强病变检查和 ADC-B2-5 用于具有增加恶性率的增强病变。•乳腺表观扩散系数分类系统可用于补充 BI-RADS 进行临床决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcf0/10326122/b928106e5464/330_2023_9675_Fig1_HTML.jpg

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