Yun Su, Ya Qiu, Xingke Huang, Yuqin Peng, Zehong Yang, Miamiao Ding, Lanxin Hu, Yishi Wang, Chen Zhao, Wenshu Qian, Xiang Zhang, Jun Shen
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引用次数: 0
Abstract
Purpose To investigate the diagnostic performance of microstructural metrics from time-dependent diffusion MRI (Td-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 Td-dMRI and conventional diffusion-weighted imaging (DWI). Td-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 Td-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 Td-dMRI were higher and the ADC was lower in malignant lesions compared with benign lesions (P < .001 to P = .001). Among microstructural metrics from Td-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], P = .03). Conclusion A single microstructural metric derived from Td-dMRI, cell density, had higher performance than conventional ADC in distinguishing benign and malignant breast lesions. Keywords: MR-Diffusion Weighted Imaging, Breast Clinical trial registration no. NCT05373628 Supplemental material is available for this article. © RSNA, 2025.
良性和恶性乳腺病变:鉴别使用显微结构指标衍生的时间依赖扩散MRI。
目的探讨时间依赖扩散MRI (Td-dMRI)显微结构指标对乳腺良恶性病变的鉴别诊断价值。材料和方法本前瞻性研究(ClinicalTrials.gov识别码:NCT05373628)于2022年1月至2023年6月招募了通过超声、乳房x光检查或两者同时确诊的乳腺病变的参与者。参与者接受振荡和脉冲梯度编码的Td-dMRI和常规弥散加权成像(DWI)。采用有限光谱编辑扩散模型,利用成像显微结构参数拟合Td-dMRI数据。病变根据病理分为良性和恶性。使用受者工作特征分析评估Td-dMRI指标和DWI的表观扩散系数(adc)在区分良恶性肿瘤方面的诊断性能,并使用DeLong测试进行比较。结果本研究纳入102例女性受试者,平均年龄48岁±12岁[SD],乳腺病变105例(其中3例为2例),其中良性病变31例,恶性病变74例。与良性病变相比,恶性病变的细胞直径、细胞密度和细胞内体积分数更高,ADC更低(P < 0.001 ~ P = 0.001)。在Td-dMRI的显微结构指标中,细胞密度在受者工作特征曲线下的面积最大,高于ADC (0.93 [95% CI: 0.88, 0.98] vs 0.79 [95% CI: 0.70, 0.88], P = 0.03)。结论基于Td-dMRI的单一显微结构指标细胞密度在鉴别乳腺良恶性病变方面优于传统ADC。关键词:磁共振扩散加权成像;乳腺;NCT05373628本文有补充材料。©rsna, 2025。
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