Sartoretti Elisabeth, Sartoretti-Schefer Sabine, van Smoorenburg Luuk, Eichenberger Barbara, Schwenk Árpád, Czell David, Alfieri Alex, Gutzeit Andreas, Mannil Manoj, Binkert Christoph A, Wyss Michael, Sartoretti Thomas
Institute of Radiology, Kantonsspital Winterthur, Brauerstrasse 15, 8401, Winterthur, Switzerland.
Faculty of Medicine, University of Zürich, Zürich, Switzerland.
Eur J Radiol Open. 2021 Sep 22;8:100377. doi: 10.1016/j.ejro.2021.100377. eCollection 2021.
To investigate the diagnostic yield of low to ultra-high b-values for the differentiation of benign from malignant vertebral fractures using a state-of-the-art single-shot zonal-oblique-multislice spin-echo echo-planar diffusion-weighted imaging sequence (SShot ZOOM SE-EPI DWI).
66 patients (34 malignant, 32 benign) were examined on 1.5 T MR scanners. ADC maps were generated from b-values of 0,400; 0,1000 and 0,2000s/mm. ROIs were placed into the fracture of interest on ADC maps and trace images and into adjacent normal vertebral bodies on trace images. The ADC of fractures and the Signal-Intensity-Ratio (SIR) of fractures relative to normal vertebral bodies on trace images were considered quantitative metrics. The appearance of the fracture of interest was graded qualitatively as iso-, hypo-, or hyperintense relative to normal vertebrae.
ADC achieved an area under the curve (AUC) of 0.785/0.698/0.592 for b = 0,400/0,1000/0,2000s/mm ADC maps respectively. SIR achieved an AUC of 0.841/0.919/0.917 for b = 400/1000/2000s/mm trace images respectively. In qualitative analyses, only b = 2000s/mm trace images were diagnostically valuable (sensitivity:1, specificity:0.794). Machine learning models incorporating all qualitative and quantitative metrics achieved an AUC of 0.95/0.98/0.98 for b-values of 400/1000/2000s/mm respectively. The model incorporating only qualitative metrics from b = 2000s/mm achieved an AUC of 0.97.
By using quantitative and qualitative metrics from SShot ZOOM SE-EPI DWI, benign and malignant vertebral fractures can be differentiated with high diagnostic accuracy. Importantly qualitative analysis of ultra-high b-value images may suffice for differentiation as well.
使用先进的单次分区斜位多层自旋回波平面扩散加权成像序列(SShot ZOOM SE-EPI DWI),研究低至超高b值对鉴别良性与恶性椎体骨折的诊断效能。
对66例患者(34例恶性,32例良性)进行1.5T磁共振扫描仪检查。从b值为0、400;0、1000和0、2000s/mm生成表观扩散系数(ADC)图。在ADC图和追踪图像上,将感兴趣区(ROI)置于骨折处,并在追踪图像上置于相邻正常椎体。骨折的ADC以及追踪图像上骨折相对于正常椎体的信号强度比(SIR)被视为定量指标。将感兴趣骨折的表现相对于正常椎体定性分为等信号、低信号或高信号。
对于b = 0、400/0、1000/0、2000s/mm的ADC图,ADC的曲线下面积(AUC)分别为0.785/0.698/0.592。对于b = 400/1000/2000s/mm的追踪图像,SIR的AUC分别为0.841/0.919/0.917。在定性分析中,仅b = 2000s/mm的追踪图像具有诊断价值(敏感性:1,特异性:0.794)。纳入所有定性和定量指标的机器学习模型,对于b值为400/1000/2000s/mm时,AUC分别为0.95/0.98/0.98。仅纳入b = 2000s/mm定性指标的模型,AUC为0.97。
通过使用SShot ZOOM SE-EPI DWI的定量和定性指标,良性和恶性椎体骨折可实现高诊断准确性的鉴别。重要的是,超高b值图像的定性分析可能也足以进行鉴别。