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扩散峰度磁共振成像在浸润性乳腺癌中的应用:与预后因素和分子亚型的相关性。

Diffusion Kurtosis MR Imaging of Invasive Breast Cancer: Correlations With Prognostic Factors and Molecular Subtypes.

机构信息

Department of Radiology, Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea.

Siemens Healthineers Ltd. Seoul, Korea.

出版信息

J Magn Reson Imaging. 2022 Jul;56(1):110-120. doi: 10.1002/jmri.27999. Epub 2021 Nov 18.

Abstract

BACKGROUND

The associations between diffusion kurtosis imaging (DKI)-derived parameters and clinical prognostic factors of breast cancer have not been fully evaluated; this knowledge may have implications for outcome prediction and treatment strategies.

PURPOSE

To determine associations between quantitative diffusion parameters derived from DKI and diffusion-weighted imaging (DWI) and the prognostic factors and molecular subtypes of breast cancer.

STUDY TYPE

Retrospective.

POPULATION

A total of 383 women (mean age, 53.8 years; range, 31-82 years) with breast cancer who underwent preoperative breast MRI including DKI and DWI.

FIELD STRENGTH/SEQUENCE: A 3.0 T; DKI using a spin-echo echo-planar imaging (EPI) sequence (b values: 200, 500, 1000, 1500, and 2000 sec/mm ), DWI using a readout-segmented EPI sequence (b values: 0 and 1000 sec/mm ) and dynamic contrast-enhanced breast MRI.

ASSESSMENT

Two radiologists (J.Y.K. and H.S.K. with 9 years and 1 year of experience in MRI, respectively) independently measured kurtosis, diffusivity, and apparent diffusion coefficient (ADC) values of breast cancer by manually placing a regions of interest within the lesion. Diffusion measures were compared according to nodal status, grade, and molecular subtypes.

STATISTICAL TESTS

Kruskal-Wallis test, Mann-Whitney U test with Bonferroni correction, receiver operating characteristic (ROC) analysis, and multivariate logistic regression analysis. (Statistical significance level of P < 0.05).

RESULTS

All diffusion measures showed significant differences according to axillary nodal status and histological grade. Kurtosis showed significant differences among molecular subtypes. The luminal subtype (median 1.163) showed a higher kurtosis value compared to the HER2-positive (median 0.962) or triple-negative subtypes (median 1.072). ROC analysis for differentiating HER2-positive from luminal subtypes revealed that kurtosis yielded the highest area under the curve of 0.781. In multivariate analyses, kurtosis remained a significant factor associated with differentiation between HER2-positive and luminal (odds ratio [OR] = 0.993), triple-negative and luminal (OR = 0.995), and HER2-positive and triple-negative subtypes (OR = 0.994).

DATA CONCLUSION

Quantitative diffusion parameters derived from DKI and DWI are associated with prognostic factors for breast cancer. Moreover, DKI-derived kurtosis can help distinguish between the molecular subtypes of breast cancer.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: 3.

摘要

背景

扩散峰度成像(DKI)衍生参数与乳腺癌临床预后因素之间的相关性尚未得到充分评估;这些知识可能对预测结果和治疗策略具有重要意义。

目的

确定 DKI 衍生的定量扩散参数与乳腺癌预后因素和分子亚型之间的相关性。

研究类型

回顾性研究。

人群

383 名接受过术前乳腺 MRI 检查(包括 DKI 和 DWI)的女性乳腺癌患者(平均年龄 53.8 岁;范围 31-82 岁)。

磁场强度/序列:3.0T;DKI 使用自旋回波平面成像(EPI)序列(b 值:200、500、1000、1500 和 2000 sec/mm),DWI 使用读出分段 EPI 序列(b 值:0 和 1000 sec/mm)和动态对比增强乳腺 MRI。

评估

两位放射科医生(J.Y.K.和 H.S.K.,分别具有 9 年和 1 年的 MRI 经验)通过手动在病变内放置感兴趣区域,分别独立测量乳腺癌的峰度、弥散度和表观扩散系数(ADC)值。根据淋巴结状态、分级和分子亚型比较扩散测量值。

统计检验

Kruskal-Wallis 检验、Mann-Whitney U 检验(Bonferroni 校正)、受试者工作特征(ROC)分析和多变量逻辑回归分析。(统计学显著性水平 P < 0.05)。

结果

所有扩散测量值均根据腋窝淋巴结状态和组织学分级存在显著差异。峰度在分子亚型之间存在显著差异。腔型(中位数 1.163)的峰度值高于 HER2 阳性(中位数 0.962)或三阴性(中位数 1.072)。ROC 分析用于区分 HER2 阳性与腔型,结果表明峰度的曲线下面积最高,为 0.781。在多变量分析中,峰度仍然是区分 HER2 阳性与腔型(比值比 [OR] = 0.993)、三阴性与腔型(OR = 0.995)以及 HER2 阳性与三阴性亚型(OR = 0.994)的重要因素。

数据结论

从 DKI 和 DWI 衍生的定量扩散参数与乳腺癌的预后因素相关。此外,DKI 衍生的峰度有助于区分乳腺癌的分子亚型。

证据水平

4 级 技术功效:3 级

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