Department of Radiology, University of Washington, Seattle, Washington.
Department of Radiology, University of Washington, Seattle, Washington; Breast Imaging, Seattle Cancer Care Alliance, 1144 Eastlake Ave E, LG2-200, Seattle, WA 98109.
Acad Radiol. 2021 Aug;28(8):1108-1117. doi: 10.1016/j.acra.2020.03.011. Epub 2020 Apr 16.
On unenhanced diffusion-weighted imaging (DWI), computing or synthesizing high b-value images from lower b-value acquisitions can enhance breast cancer visibility. This study aimed to evaluate relative lesion conspicuity on computed versus acquired diffusion-weighted images and investigate clinical characteristics influencing optimal b-values.
Women with newly diagnosed breast cancer were prospectively enrolled and underwent 3T breast MRI with DWI. Lesion contrast-to-noise ratio (CNR) was measured across a range of b-values (0-2500 s/mm) for computed and acquired DWI. Three readers independently compared lesion visibility between computed and acquired DWI and selected the optimal b-value. Computed versus acquired DWI was compared quantitatively based on CNR by paired t-test and qualitatively based on reader preference using a sign test. Optimal b-values by qualitative and quantitative assessment were compared by paired t-test, and associations with clinical characteristics were assessed by Wilcoxon rank sum test.
The study included 30 women (median age, 48 years); 28 with invasive carcinoma, 2 DCIS. Lesion CNR was higher on acquired versus computed images (p = 0.018), while lesion visibility by reader assessment was not different (p = 0.36). Optimal b-values selected by readers (mean, b = 1411 ± 383 s/mm) were slightly higher than those based on peak CNR (b = 1233 ± 463 s/mm, p = 0.023), and were higher for younger (≤50 years) versus older women (p = 0.002) and dense versus nondense breasts (p = 0.015).
Lesion CNR on computed high b-value images was slightly reduced versus acquired images, but our study suggests that this did not significantly impact lesion visibility. Computing high b-value images offers extra flexibility to adjust b-value during interpretation.
在未增强弥散加权成像(DWI)中,从较低 b 值采集计算或合成高 b 值图像可以提高乳腺癌的可视性。本研究旨在评估计算与采集 DWI 上相对病变对比噪声比(CNR),并探讨影响最佳 b 值的临床特征。
前瞻性纳入新诊断为乳腺癌的女性患者,进行 3T 乳腺 MRI 检查,包括 DWI。对计算和采集 DWI 上的一系列 b 值(0-2500 s/mm)测量病变 CNR。三位观察者独立比较计算与采集 DWI 上的病变可视性,并选择最佳 b 值。采用配对 t 检验比较计算与采集 DWI 之间的定量差异,采用符号检验根据观察者偏好进行定性比较。采用配对 t 检验比较定性和定量评估的最佳 b 值,采用 Wilcoxon 秩和检验评估与临床特征的相关性。
本研究纳入 30 例女性(中位年龄,48 岁);28 例浸润性癌,2 例 DCIS。与采集图像相比,计算图像上的病变 CNR 更高(p=0.018),但观察者评估的病变可视性无差异(p=0.36)。读者选择的最佳 b 值(平均值,b=1411±383 s/mm)略高于基于峰值 CNR 的最佳 b 值(b=1233±463 s/mm,p=0.023),且在≤50 岁的女性中高于>50 岁的女性(p=0.002),在致密乳腺中高于非致密乳腺(p=0.015)。
与采集图像相比,计算高 b 值图像上的病变 CNR 略有降低,但本研究表明,这并未显著影响病变可视性。计算高 b 值图像在解释过程中提供了调整 b 值的额外灵活性。