Honda Maya, Le Bihan Denis, Kataoka Masako, Iima Mami
Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
BJR Open. 2023 Jan 14;5(1):20220038. doi: 10.1259/bjro.20220038. eCollection 2023.
Diffusion kurtosis imaging (DKI) is a diffusion-weighted imaging method that describes non-Gaussian signal behavior using a relatively simple mathematical model. A parameter, kurtosis K, describes the deviation of the diffusion signal decay from a Gaussian pattern. The deviation reflects the complexity of the tissue microstructure affecting water diffusion. Several studies have investigated the diagnostic performance of DKI in distinguishing malignant from benign breast lesions. DKI has been reported to correlate with subtypes and with several molecular and other factors related to the treatment and prognosis of breast cancer. Some technical considerations remain to be resolved for the clinical application of DKI in the breast.
DKI, which increases the sensitivity to complex tissue microstructure compared to standard DWI, has been applied in the breast, allowing to increase clinical performance in distinguishing malignant from benign lesions and in predicting prognosis or treatment response in breast cancer.
扩散峰度成像（DKI）是一种扩散加权成像方法，它使用相对简单的数学模型来描述非高斯信号行为。一个参数，峰度K，描述了扩散信号衰减与高斯模式的偏差。这种偏差反映了影响水扩散的组织微观结构的复杂性。几项研究调查了DKI在区分乳腺良恶性病变中的诊断性能。据报道，DKI与乳腺癌的亚型以及与治疗和预后相关的几种分子和其他因素相关。DKI在乳腺临床应用中仍有一些技术问题有待解决。
与标准扩散加权成像相比，DKI对复杂组织微观结构的敏感性更高，已应用于乳腺，提高了区分乳腺良恶性病变以及预测乳腺癌预后或治疗反应的临床性能。
