Author:
Zhao Heng,Li Hui,Xie Xia,Tang Hai-yan,Liu Xiao-xin,Wen Yi,Xiao Xin,Ye Lu,Tang You-wei,Dai Gao-yue,He Jia-ni,Chen Li,Wang Qian,Tang De-qiu,Pan Shi-nong
Abstract
Abstract
Objectives
To evaluate the performance of a dual-energy computed tomography (DECT) virtual non-calcium (VNCa) technique in the detection of edema-like marrow signal intensity (ELMSI) in patients with knee joint osteoarthritis (OA) compared to magnetic resonance imaging (MRI).
Methods
The study received local ethics board approval, and written informed consent was obtained. DECT and MRI were used to examine 28 knees in 24 patients with OA. VNCa images were generated by dual-energy subtraction of calcium. The knee joint was divided into 15 regions for ELMSI grading, performed independently by two musculoskeletal radiologists, with MRI as the reference standard. We also analyzed CT numbers through receiver operating characteristics and calculated cut-off values.
Results
For the qualitative analysis, we obtained CT sensitivity (Readers 1, 2 = 83.7%, 89.8%), specificity (Readers 1, 2 = 99.5%, 99.5%), positive predictive value (Readers 1, 2 = 95.3%, 95.7%), and negative predictive value (Readers 1, 2 = 97.9%, 98.7%) for ELMSI. The interobserver agreement was excellent (κ = 0.92). The area under the curve for Reader 1 and Reader 2 was 0.961 (95% CI 0.93, 0.99) and 0.992 (95% CI 0.98, 1.00), respectively. CT numbers obtained from the VNCa images were significantly different between regions with and without ELMSI (p < .001).
Conclusions
VNCa images have good diagnostic performance for the qualitative and quantitative analysis of knee osteoarthritis-related ELMSI.
Funder
the National Natural Science Foundation of China
345 Talent Project and Natural Science Foundation of Liaoning Province
Scientific Research Project of Hunan Provincial Department of Education, Key project
Scientific research project of hunan provincial health department of China
Hunan Provincial Science and Technology Innovation Program of China
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献