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.
J Magn Reson Imaging. 2022 Jul;56(1):110-120. doi: 10.1002/jmri.27999. Epub 2021 Nov 18.
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.
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.
Retrospective.
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.
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.
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).
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).
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.
4 TECHNICAL EFFICACY: 3.
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。
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。
回顾性研究。
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。
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。
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）。
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。
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。
4 级 技术功效：3 级
