Li Zi, Guan Ming, Sun Dong, Xu Yong, Li Feng, Xiong Wei
Department of orthopedics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095#, Jiefang Ave, Wuhan, Hubei, China.
Department of orthopedics, Taikang Tongji Hospital, Wuhan, Hubei, China.
BMC Musculoskelet Disord. 2018 Nov 20;19(1):406. doi: 10.1186/s12891-018-2331-0.
Various types of magnetic resonance imaging (MRI) and computed tomography (CT) findings are used to differentiate malignant vertebral fractures (MVFs) from osteoporotic vertebral fractures (OVFs). The distinguishing ability of any single finding is limited. This study developed a novel scoring system that integrates multiple MRI and CT signs for improved accuracy of differential diagnosis between MVFs and OVFs.
A total of 150 MVFs and 150 OVFs in thoracolumbar vertebrae were analyzed. MRI and CT images were obtained within 2 months of the probable time of fracture. The sensitivity and specificity of 15 MRI and CT image findings were evaluated. A stepwise discriminant analysis using these signs as variables was used to create a scoring system to differentiate MVFs from OVFs.
All 15 image findings had strong specificity and moderate sensitivity. Seven MRI and three CT image findings were selected and assigned integral values in the final scoring system. A total score of 4 or greater points indicated MVF, whereas a total score of 3 or fewer points indicated OVF. The classification accuracy was 98.3% in the test set.
This novel scoring system using MRI and CT radiologic findings to differentiate MVFs from OVFs in Chinese patients was efficient with high accuracy and good applicability.
多种类型的磁共振成像(MRI)和计算机断层扫描(CT)结果被用于区分恶性椎体骨折(MVF)和骨质疏松性椎体骨折(OVF)。任何单一结果的鉴别能力都有限。本研究开发了一种新颖的评分系统,该系统整合了多种MRI和CT征象,以提高MVF和OVF鉴别诊断的准确性。
对150例胸腰椎的MVF和150例OVF进行分析。在可能的骨折时间2个月内获取MRI和CT图像。评估15项MRI和CT图像结果的敏感性和特异性。使用这些征象作为变量进行逐步判别分析,以创建一个区分MVF和OVF的评分系统。
所有15项图像结果均具有较高的特异性和中等的敏感性。在最终的评分系统中选择了7项MRI和3项CT图像结果并赋予积分值。总分4分或更高表明为MVF,而总分3分或更低表明为OVF。测试集中的分类准确率为98.3%。
这种利用MRI和CT影像学结果来区分中国患者MVF和OVF的新颖评分系统高效、准确且适用性良好。