Su Yun, Qiu Ya, Huang Xingke, Peng Yuqin, Yang Zehong, Ding Miamiao, Hu Lanxin, Wang Yishi, Zhao Chen, Qian Wenshu, Zhang Xiang, Shen Jun
Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120, People's Republic of China.
Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, People's Republic of China.
Radiol Imaging Cancer. 2025 May;7(3):e240287. doi: 10.1148/rycan.240287.
Purpose To investigate the diagnostic performance of microstructural metrics from time-dependent diffusion MRI (T-dMRI) in distinguishing between benign and malignant breast lesions. Materials and Methods This prospective study (ClinicalTrials.gov identifier: NCT05373628) enrolled participants with breast lesions confirmed with US, mammography, or both from January 2022 to June 2023. Participants underwent oscillating and pulsed gradient encoded T-dMRI and conventional diffusion-weighted imaging (DWI). T-dMRI data were fitted using the imaging microstructural parameters using limited spectrally edited diffusion model. Lesions were classified as benign or malignant based on pathology. Diagnostic performances of T-dMRI metrics and apparent diffusion coefficients (ADCs) from DWI in distinguishing between benign and malignant tumors were assessed using receiver operating characteristic analysis and compared using the DeLong test. Results The study included 102 female participants (mean age: 48 years ± 12 [SD]) with 105 breast lesions (three participants had two lesions), including 31 benign and 74 malignant lesions. The cell diameter, cell density, and intracellular volume fraction from T-dMRI were higher and the ADC was lower in malignant lesions compared with benign lesions ( < .001 to = .001). Among microstructural metrics from T-dMRI, the cell density had the highest area under the receiver operating characteristic curve, which was higher than that of the ADC (0.93 [95% CI: 0.88, 0.98] vs 0.79 [95% CI: 0.70, 0.88], = .03). Conclusion A single microstructural metric derived from T-dMRI, cell density, had higher performance than conventional ADC in distinguishing benign and malignant breast lesions. MR-Diffusion Weighted Imaging, Breast Clinical trial registration no. NCT05373628 © RSNA, 2025.
目的 研究基于时间依赖扩散磁共振成像（T-dMRI）的微观结构指标在鉴别乳腺良恶性病变中的诊断性能。材料与方法 本前瞻性研究（ClinicalTrials.gov标识符：NCT05373628）纳入了2022年1月至2023年6月期间经超声、乳腺X线摄影或两者证实患有乳腺病变的参与者。参与者接受了振荡和脉冲梯度编码T-dMRI以及传统扩散加权成像（DWI）检查。使用有限频谱编辑扩散模型对T-dMRI数据进行成像微观结构参数拟合。根据病理结果将病变分为良性或恶性。使用受试者操作特征分析评估T-dMRI指标和DWI的表观扩散系数（ADC）在鉴别良恶性肿瘤中的诊断性能，并使用德龙检验进行比较。结果 该研究纳入了102名女性参与者（平均年龄：48岁±12[标准差]），共105个乳腺病变（3名参与者有两个病变），其中包括31个良性病变和74个恶性病变。与良性病变相比，恶性病变的T-dMRI细胞直径、细胞密度和细胞内体积分数更高，ADC更低（<.001至 =.001）。在T-dMRI的微观结构指标中，细胞密度在受试者操作特征曲线下的面积最大，高于ADC（0.93[95%CI：0.88，0.98]对0.79[9
