From the Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa (E.S.M., M.D.S.); Center for Statistical Sciences, Brown University, Providence, RI (J.R.); Department of Radiology, University of Washington, 1144 Eastlake Ave E, LG2-200, Seattle, WA 98109 (H.R., A.E.K., S.C.P.); Departments of Radiology and Radiological Sciences (S.M.H.) and Medicine (J.G.W.), Vanderbilt University Medical Center, Nashville, Tenn; Vanderbilt-Ingram Cancer Center, Nashville, Tenn (J.G.W.); Department of Biomedical Engineering, University of Texas, Austin, Tex (T.E.Y.); Department of Radiology, New York University School of Medicine, New York, NY (L.M.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (W.B.D.); Department of Diagnostic Radiology, University of Texas Southwestern Medical Center, Dallas, Tex (B.E.D.); Department of Breast Imaging, MD Anderson Cancer Center, Houston, Tex (W.T.Y.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (L.C.W.); Department of Radiology and Biomedical Imaging, University of California, San Francisco School of Medicine, San Francisco, Calif (B.N.J., L.J.W., N.M.H.); Department of Radiology, Oregon Health and Science University, Portland, Ore (K.Y.O., L.A.T.); Department of Radiology/MRI, University of Michigan, Ann Arbor, Mich (C.H.N., D.I.M., T.L.C.); and Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY (C.E.C.).
Radiology. 2021 Jan;298(1):60-70. doi: 10.1148/radiol.2020202465. Epub 2020 Nov 17.
Background The Eastern Cooperative Oncology Group and American College of Radiology Imaging Network Cancer Research Group A6702 multicenter trial helped confirm the potential of diffusion-weighted MRI for improving differential diagnosis of suspicious breast abnormalities and reducing unnecessary biopsies. A prespecified secondary objective was to explore the relative value of different approaches for quantitative assessment of lesions at diffusion-weighted MRI. Purpose To determine whether alternate calculations of apparent diffusion coefficient (ADC) can help further improve diagnostic performance versus mean ADC values alone for analysis of suspicious breast lesions at MRI. Materials and Methods This prospective trial (ClinicalTrials.gov identifier: NCT02022579) enrolled consecutive women (from March 2014 to April 2015) with a Breast Imaging Reporting and Data System category of 3, 4, or 5 at breast MRI. All study participants underwent standardized diffusion-weighted MRI ( = 0, 100, 600, and 800 sec/mm). Centralized ADC measures were performed, including manually drawn whole-lesion and hotspot regions of interest, histogram metrics, normalized ADC, and variable -value combinations. Diagnostic performance was estimated by using the area under the receiver operating characteristic curve (AUC). Reduction in biopsy rate (maintaining 100% sensitivity) was estimated according to thresholds for each ADC metric. Results Among 107 enrolled women, 81 lesions with outcomes (28 malignant and 53 benign) in 67 women (median age, 49 years; interquartile range, 41-60 years) were analyzed. Among ADC metrics tested, none improved diagnostic performance versus standard mean ADC (AUC, 0.59-0.79 vs AUC, 0.75; = .02-.84), and maximum ADC had worse performance (AUC, 0.52; < .001). The 25th-percentile ADC metric provided the best performance (AUC, 0.79; 95% CI: 0.70, 0.88), and a threshold using median ADC provided the greatest reduction in biopsy rate of 23.9% (95% CI: 14.8, 32.9; 16 of 67 BI-RADS category 4 and 5 lesions). Nonzero minimum value (100, 600, and 800 sec/mm) did not improve the AUC (0.74; = .28), and several combinations of two values (0 and 600, 100 and 600, 0 and 800, and 100 and 800 sec/mm; AUC, 0.73-0.76) provided results similar to those seen with calculations of four values (AUC, 0.75; = .17-.87). Conclusion Mean apparent diffusion coefficient calculated with a two--value acquisition is a simple and sufficient diffusion-weighted MRI metric to augment diagnostic performance of breast MRI compared with more complex approaches to apparent diffusion coefficient measurement. © RSNA, 2020
背景 东肿瘤协作组和美国放射学院成像网络癌症研究组 A6702 多中心试验有助于证实扩散加权 MRI 有助于提高可疑乳腺病变的鉴别诊断能力，并减少不必要的活检。一个预先设定的次要目标是探索在扩散加权 MRI 中定量评估病变时不同方法的相对价值。目的 确定是否可以通过替代计算表观扩散系数 (ADC) 来帮助进一步提高 MRI 分析可疑乳腺病变的诊断性能，与仅使用平均 ADC 值相比。材料与方法 本前瞻性试验（ClinicalTrials.gov 标识符：NCT02022579）纳入了连续的女性（2014 年 3 月至 2015 年 4 月），在乳腺 MRI 上的乳腺成像报告和数据系统 (BI-RADS) 类别为 3、4 或 5。所有研究参与者均接受了标准化的扩散加权 MRI（b 值分别为 0、100、600 和 800 sec/mm）。进行了中央 ADC 测量，包括手动绘制整个病变和热点感兴趣区、直方图指标、归一化 ADC 和变量 b 值组合。使用接受者操作特征曲线下的面积 (AUC) 来评估诊断性能。根据每个 ADC 指标的阈值估计活检率的降低（保持 100%的灵敏度）。结果 在 107 名入组的女性中，对 67 名女性（中位年龄为 49 岁；四分位距为 41-60 岁）的 81 个具有结局（28 个恶性和 53 个良性）的病变进行了分析。在测试的 ADC 指标中，与标准平均 ADC（AUC，0.59-0.79 比 AUC，0.75； =.02-.84）相比，没有任何指标能提高诊断性能，而最大 ADC 的性能更差（AUC，0.52； <.001）。第 25 百分位数 ADC 指标提供了最佳的性能（AUC，0.79；95%CI：0.70，0.88），使用中位数 ADC 的阈值可使活检率降低 23.9%（95%CI：14.8，32.9；67 个 BI-RADS 类别 4 和 5 病变中的 16 个）。非零最小 b 值（100、600 和 800 sec/mm）不会提高 AUC（0.74； =.28），并且两个 b 值（0 和 600、100 和 600、0 和 800 以及 100 和 800 sec/mm）的几种组合提供的结果与使用四个 b 值（AUC，0.75； =.17-.87）的计算结果相似。结论 与更复杂的 ADC 测量方法相比，使用两个 b 值采集计算的平均表观扩散系数是一种简单而充分的扩散加权 MRI 指标，可提高乳腺 MRI 的诊断性能。
