Dijkstra Hildebrand, Dorrius Monique D, Wielema Mirjam, Pijnappel Ruud M, Oudkerk Matthijs, Sijens Paul E
University of Groningen, University Medical Center Groningen, Center for Medical Imaging - North East Netherlands, Groningen, The Netherlands.
University of Groningen, University Medical Center Groningen, Department of Radiology, Groningen, The Netherlands.
J Magn Reson Imaging. 2016 Dec;44(6):1642-1649. doi: 10.1002/jmri.25331. Epub 2016 Jun 7.
To assess if specificity can be increased when semiautomated breast lesion analysis of quantitative diffusion-weighted imaging (DWI) is implemented after dynamic contrast-enhanced (DCE-) magnetic resonance imaging (MRI) in the workup of BI-RADS 3 and 4 breast lesions larger than 1 cm.
In all, 120 consecutive patients (mean-age, 48 years; age range, 23-75 years) with 139 breast lesions (≥1 cm) were examined (2010-2014) with 1.5T DCE-MRI and DWI (b = 0, 50, 200, 500, 800, 1000 s/mm ) and the BI-RADS classification and histopathology were obtained. For each lesion malignancy was excluded using voxelwise semiautomated breast lesion analysis based on previously defined thresholds for the apparent diffusion coefficient (ADC) and the three intravoxel incoherent motion (IVIM) parameters: molecular diffusion (D ), microperfusion (D ), and the fraction of D (f ). The sensitivity (Se), specificity (Sp), and negative predictive value (NPV) based on only IVIM parameters combined in parallel (D , D , and f ), or the ADC or the BI-RADS classification by DCE-MRI were compared. Subsequently, the Se, Sp, and NPV of the combination of the BI-RADS classification by DCE-MRI followed by the IVIM parameters in parallel (or the ADC) were compared.
In all, 23 of 139 breast lesions were benign. Se and Sp of DCE-MRI was 100% and 30.4% (NPV = 100%). Se and Sp of IVIM parameters in parallel were 92.2% and 52.2% (NPV = 57.1%) and for the ADC 95.7% and 17.4%, respectively (NPV = 44.4%). In all, 26 of 139 lesions were classified as BI-RADS 3 (n = 7) or BI-RADS 4 (n = 19). DCE-MRI combined with ADC (Se = 99.1%, Sp = 34.8%) or IVIM (Se = 99.1%, Sp = 56.5%) did significantly improve (P = 0.016) Sp of DCE-MRI alone for workup of BI-RADS 3 and 4 lesions (NPV = 92.9%).
Quantitative DWI has a lower NPV compared to DCE-MRI for evaluation of breast lesions and may therefore not be able to replace DCE-MRI; when implemented after DCE-MRI as problem solver for BI-RADS 3 and 4 lesions, the combined specificity improves significantly. J. Magn. Reson. Imaging 2016;44:1642-1649.
评估在对大于1厘米的BI-RADS 3和4类乳腺病变进行检查时，在动态对比增强（DCE）磁共振成像（MRI）后实施定量扩散加权成像（DWI）的半自动乳腺病变分析，是否能提高特异性。
2010年至2014年期间，对120例连续患者（平均年龄48岁；年龄范围23 - 75岁）的139个乳腺病变（≥1厘米）进行了1.5T DCE-MRI和DWI（b = 0、50、200、500、800、1000 s/mm²）检查，并获得了BI-RADS分类和组织病理学结果。对于每个病变，基于先前定义的表观扩散系数（ADC）和三个体素内不相干运动（IVIM）参数：分子扩散（D）、微灌注（D*）和D的分数（f），使用体素级半自动乳腺病变分析排除恶性肿瘤。比较仅基于IVIM参数并行组合（D、D*和f）、ADC或DCE-MRI的BI-RADS分类的敏感性（Se）、特异性（Sp）和阴性预测值（NPV）。随后，比较DCE-MRI的BI-RADS分类与IVIM参数并行组合（或ADC）的Se、Sp和NPV。
139个乳腺病变中，23个为良性。DCE-MRI的Se和Sp分别为100%和30.4%（NPV = 100%）。IVIM参数并行组合的Se和Sp分别为92.2%和52.2%（NPV = 57.1%），ADC的Se和Sp分别为95.7%和17.4%（NPV = 44.4%）。139个病变中，26个被分类为BI-RADS 3（n = 7）或BI-RADS 4（n = 19）。DCE-MRI与ADC（Se = 99.1%，Sp = 34.8%）或IVIM（Se = 99.1%，Sp = 56.5%）联合使用，对于BI-RADS 3和4类病变的检查，显著提高了（P = 0.016）DCE-MRI单独使用时的Sp（NPV = 92.9%）。
在评估乳腺病变时，定量DWI的NPV低于DCE-MRI，因此可能无法替代DCE-MRI；当在DCE-MRI后作为BI-RADS 3和4类病变的问题解决方法实施时，联合特异性显著提高。《磁共振成像杂志》2016年；44：1642 - 1649。
