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基于 TOLF CT 骨窗 102 个分段的硬脑膜骨化诊断影像分级系统。

Imaging grading system for the diagnosis of dural ossification based on 102 segments of TOLF CT bone-window data.

机构信息

Department of Orthopaedics, Shanghai Changzheng Hospital, Fengyang Road No. 415, Shanghai, 200003, China.

出版信息

Sci Rep. 2017 Jun 7;7(1):2983. doi: 10.1038/s41598-017-03178-x.

DOI:10.1038/s41598-017-03178-x
PMID:28592849
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5462817/
Abstract

Thoracic ossification of the ligamentum flavum (TOLF) complicated with dural ossification (DO) is a severe clinical disease. The diagnosis of DO preoperatively remains challenging. The current study retrospectively analyzed imaging features of 102 segments with TOLF from 39 patients and proposed a grading system for evaluating DO risk. Logistic regression results showed that unilateral spinal canal occupational rate (UCOR), tram track signs, and C-signs were all risk factors for DO (odds ratios of 5.393, 19.734 and 72.594, respectively). In validation analyses for the TOLF-DO grading system, sensitivity was 76.0% (19/25), specificity was 91.0% (70/77), and Youden's index was 0.66. Thus, implementation of the TOLF-DO grading system has the potential to improve the diagnosis of DO.

摘要

黄韧带骨化(TOLF)合并硬脊膜骨化(DO)是一种严重的临床疾病。术前 DO 的诊断仍然具有挑战性。本研究回顾性分析了 39 例患者 102 个 TOLF 节段的影像学特征,并提出了一种评估 DO 风险的分级系统。Logistic 回归结果表明,单侧椎管占位率(UCOR)、轨道征和 C 征均为 DO 的危险因素(比值比分别为 5.393、19.734 和 72.594)。在 TOLF-DO 分级系统的验证分析中,该系统的灵敏度为 76.0%(19/25),特异性为 91.0%(70/77),约登指数为 0.66。因此,实施 TOLF-DO 分级系统有可能提高 DO 的诊断率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/669f/5462817/3482864f9d7a/41598_2017_3178_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/669f/5462817/563be02e6720/41598_2017_3178_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/669f/5462817/2d73dcf7e3a6/41598_2017_3178_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/669f/5462817/fee41626b7d8/41598_2017_3178_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/669f/5462817/3482864f9d7a/41598_2017_3178_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/669f/5462817/563be02e6720/41598_2017_3178_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/669f/5462817/2d73dcf7e3a6/41598_2017_3178_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/669f/5462817/fee41626b7d8/41598_2017_3178_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/669f/5462817/3482864f9d7a/41598_2017_3178_Fig4_HTML.jpg

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Med Hypotheses. 2016 Nov;96:9-10. doi: 10.1016/j.mehy.2016.09.012. Epub 2016 Sep 21.
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