Chen Wei, Liu Limin, Zhao Heng, Li Hui, Luo Jing, Qu Yao-Lin, Zhang Dan, He Ya-Han, Pan Yi-Sha, Gao Fang, Liao Hua-Zhi, Chen Xiao-Long, Lei Hao, Tang De-Qiu, Peng Fei
Department of Radiology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Chuanshan Road No. 69, Hengyang, 421001, Hunan, China.
Department of Ultrasound, The Second Affiliated Hospital, Hengyang Medical School, University of South China, Jiefang Road No. 35, Hengyang, 421001, Hunan, China.
Sci Rep. 2025 Jan 27;15(1):3331. doi: 10.1038/s41598-025-86697-2.
To determine the diagnostic performance of dual-energy CT (DECT) virtual noncalcium (VNCa) technique in the detection of bone marrow lesions (BMLs) in knee osteoarthritis, and further analyze the correlation between the severity of BMLs on VNCa image and the degree of knee pain. 23 consecutive patients with clinically diagnosed knee osteoarthritis were underwent DECT and 3.0T MRI between August 2017 and November 2018. Evaluation of two pain assessment scales (WOMAC and KOOS) were collected. VNCa images and MRI were independently scored by three readers using a four-level scoring system over 15 anatomical subregions in each knee joint. Spearman correlation coefficient was used for total BML scores on DECT and MRI correlation with WOMAC and KOOS. Specificity, Sensitivity, NPV and PPV of reader 1 and reader 2 were 99.4%/99.2%, 89.4%/87.2%, 98.6%/98.3% and 95.5%/93.2%. A cutoff value of - 41.5 HU/- 46.5 HU provided sensitivities of 93.2%/90.9% and specificities of 100.0%/93.9% for diagnosing BMLs with AUC of 0.970/0.996. A stronger correlation was observed between the WOMAC and total BML score compared to the KOOS. DECT possessed excellent diagnostic performance in the detection of BMLs in knee osteoarthritis. And the pain degree increased with the severity of BMLs on VNCa images.
为确定双能CT(DECT)虚拟去钙(VNCa)技术在检测膝关节骨关节炎骨髓病变(BMLs)中的诊断性能,并进一步分析VNCa图像上BMLs的严重程度与膝关节疼痛程度之间的相关性。2017年8月至2018年11月期间,对23例临床诊断为膝关节骨关节炎的连续患者进行了DECT和3.0T MRI检查。收集了两种疼痛评估量表(WOMAC和KOOS)的评估结果。三位阅片者使用四级评分系统对每个膝关节的15个解剖亚区域的VNCa图像和MRI进行独立评分。采用Spearman相关系数分析DECT和MRI上BMLs总评分与WOMAC和KOOS的相关性。阅片者1和阅片者2的特异性、敏感性、阴性预测值和阳性预测值分别为99.4%/99.2%、89.4%/87.2%、98.6%/98.3%和95.5%/93.2%。-41.5 HU/-46.5 HU的截断值诊断BMLs的敏感性为93.2%/90.9%,特异性为100.0%/93.9%,曲线下面积为0.970/0.996。与KOOS相比,WOMAC与BMLs总评分之间的相关性更强。DECT在检测膝关节骨关节炎的BMLs方面具有优异的诊断性能。并且VNCa图像上BMLs的严重程度越高,疼痛程度越高。