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使用双能计算机断层扫描定量评估髂外淋巴结的长短轴:一种用于人工关节周围感染的潜在诊断方法——一项前瞻性研究。

Quantifying the Long and Short Axes of the External Iliac Lymph Nodes Using Dual-Energy Computed Tomography: A Potential Diagnostic Approach for Periprosthetic Joint Infection - A Prospective Study.

作者信息

Yang Yaji, Zhou Haotian, Kang Runxing, Zhao Chen, Li Jia, Li Feilong, Shen Yidong, Chen Yuelong, Huang Wei, Qin Leilei

机构信息

Department of Orthopaedic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China.

Chongqing Municipal Health Commission Key Laboratory of Musculoskeletal Regeneration and Translational Medicine, Chongqing, People's Republic of China.

出版信息

Infect Drug Resist. 2024 Dec 17;17:5605-5617. doi: 10.2147/IDR.S497736. eCollection 2024.

Abstract

PURPOSE

Periprosthetic joint infection (PJI) is a severe complication following joint replacement surgery, and there is a current lack of rapid, accurate, and non-invasive diagnostic methods. This study aims to assess the effectiveness of using dual-energy computed tomography (DECT) to quantify the maximum long and short axes of the external iliac lymph nodes (LNs) as a diagnostic tool for PJI.

PATIENTS AND METHODS

In this prospective controlled study, 112 patients undergoing total hip or total knee revision surgery were enrolled. All patients underwent preoperative DECT scanning to measure the maximum long and short axes of the external iliac LNs on the affected side. The diagnostic value of lymph node size for PJI was assessed using receiver operating characteristic curves.

RESULTS

The AUC (Area Under the Curve) quantifies the diagnostic method's ability to distinguish between positive and negative outcomes in this study. A value closer to 1.0 indicates better discriminatory performance. Compared to erythrocyte sedimentation rate (Area Under the Curve (AUC) = 0.834), percentage of polymorphonuclear leukocytes (AUC = 0.621), and C-reactive protein (AUC = 0.765), the maximum long axis (AUC =0.895) and maximum short axis (AUC = 0.858) of the external iliac LNs better differentiated PJI from aseptic failure. For diagnosing PJI, the threshold for the maximum long axis of the LNs was 20.5 mm, with a sensitivity of 84.21% and a specificity of 87.84%. For the maximum short axis, the threshold was 8.5 mm, with a sensitivity of 89.47% and a specificity of 82.43%. Combining the maximum long and short axes of the external iliac LNs enhanced the diagnostic accuracy for PJI.

CONCLUSION

Measuring the long and short axes of external iliac LNs using DECT is an effective diagnostic approach for PJI, aiding in the differentiation between PJI and aseptic failure following joint replacement surgery.

摘要

目的

人工关节周围感染(PJI)是关节置换术后的一种严重并发症,目前缺乏快速、准确且无创的诊断方法。本研究旨在评估使用双能计算机断层扫描(DECT)量化髂外淋巴结(LN)的最大长轴和短轴作为PJI诊断工具的有效性。

患者与方法

在这项前瞻性对照研究中,纳入了112例行全髋关节或全膝关节翻修手术的患者。所有患者术前行DECT扫描,以测量患侧髂外淋巴结的最大长轴和短轴。使用受试者操作特征曲线评估淋巴结大小对PJI的诊断价值。

结果

曲线下面积(AUC)量化了本研究中诊断方法区分阳性和阴性结果的能力。值越接近1.0表明鉴别性能越好。与红细胞沉降率(曲线下面积(AUC)=0.834)、多形核白细胞百分比(AUC =0.621)和C反应蛋白(AUC =0.765)相比,髂外淋巴结的最大长轴(AUC =0.895)和最大短轴(AUC =0.858)能更好地区分PJI与无菌性失败。对于诊断PJI,淋巴结最大长轴的阈值为20.5 mm,敏感性为84.21%,特异性为87.84%。对于最大短轴,阈值为8.5 mm,敏感性为89.47%,特异性为82.43%。结合髂外淋巴结的最大长轴和短轴可提高PJI的诊断准确性。

结论

使用DECT测量髂外淋巴结的长轴和短轴是PJI的一种有效诊断方法,有助于区分关节置换术后的PJI与无菌性失败。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d537/11663990/1d49dd5fde08/IDR-17-5605-g0001.jpg

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