医学
乳腺癌
乳房磁振造影
乳腺摄影术
邦费罗尼校正
磁共振成像
有效扩散系数
磁共振弥散成像
活检
乳房成像
放射科
核医学
乳腺活检
癌症
内科学
统计
数学
作者
Stéphane Loubrie,Jingjing Zou,Ana E. Rodríguez‐Soto,Jihe Lim,Maren M. Sjaastad Andreassen,Yuwei Cheng,Summer Batasin,Sheida Ebrahimi,Lauren K. Fang,Christopher C. Conlin,Tyler M. Seibert,Michael E. Hahn,Vandana Dialani,Catherine Wei,Zahra Karimi,Joshua Kuperman,Anders M. Dale,Haydee Ojeda‐Fournier,Etta D. Pisano,Rebecca Rakow‐Penner
摘要
Background Breast cancer screening with dynamic contrast‐enhanced MRI (DCE‐MRI) is recommended for high‐risk women but has limitations, including variable specificity and difficulty in distinguishing cancerous (CL) and high‐risk benign lesions (HRBL) from average‐risk benign lesions (ARBL). Complementary non‐invasive imaging techniques would be useful to improve specificity. Purpose To evaluate the performance of a previously‐developed breast‐specific diffusion‐weighted MRI (DW‐MRI) model (BS‐RSI3C) to improve discrimination between CL, HRBL, and ARBL in an enriched screening population. Study Type Prospective. Subjects Exactly 187 women, either with mammography screening recommending additional imaging (N = 49) or high‐risk individuals undergoing routine breast MRI (N = 138), before the biopsy. Field Strength/Sequence Multishell DW‐MRI echo planar imaging sequence with a reduced field of view at 3.0 T. Assessment A total of 72 women had at least one biopsied lesion, with 89 lesions categorized into ARBL, HRBL, CL, and combined CLs and HRBLs (CHRLs). DW‐MRI data were processed to produce apparent diffusion coefficient (ADC) maps, and estimate signal contributions (C 1 , C 2 , and C 3 —restricted, hindered, and free diffusion, respectively) from the BS‐RSI3C model. Lesion regions of interest (ROIs) were delineated on DW images based on suspicious DCE‐MRI findings by two radiologists; control ROIs were drawn in the contralateral breast. Statistical Tests One‐way ANOVA and two‐sided t ‐tests were used to assess differences in signal contributions and ADC values among groups. P ‐values were adjusted using the Bonferroni method for multiple testing, P = 0.05 was used for the significance level. Receiver operating characteristics (ROC) curves and intra‐class correlations (ICC) were also evaluated. Results C 1 , √C 1 C 2 , and were significantly different in HRBLs compared with ARBLs ( P ‐values < 0.05). The had the highest AUC (0.821) in differentiating CHRLs from ARBLs, performing better than ADC (0.696), especially in non‐mass enhancement (0.776 vs. 0.517). Data Conclusion This study demonstrated the BS‐RSI3C could differentiate HRBLs from ARBLs in a screening population, and separate CHRLs from ARBLs better than ADC. Level of Evidence 1. Technical Efficacy Stage 2.
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