Suppr超能文献

磁共振成像显示脉络丛炎和室管膜炎是 HIV 阴性隐球菌性脑膜脑炎神经元损伤和炎症的生物标志物。

Choroid Plexitis and Ependymitis by Magnetic Resonance Imaging are Biomarkers of Neuronal Damage and Inflammation in HIV-negative Cryptococcal Meningoencephalitis.

机构信息

Center for Infectious Disease Imaging (CIDI), Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD, USA.

Division of Pediatric Radiology, Diagnostic Imaging and Radiology, Children's National Health System, Washington, DC, USA.

出版信息

Sci Rep. 2017 Aug 23;7(1):9184. doi: 10.1038/s41598-017-09694-0.

Abstract

CNS cryptococcal meningoencephalitis in both HIV positive (HIV+) and HIV negative (HIV-) subjects is associated with high morbidity and mortality despite optimal antifungal therapy. We thus conducted a detailed analysis of the MR imaging findings in 45 HIV- and 11 HIV+ patients to identify imaging findings associated with refractory disease. Ventricular abnormalities, namely ependymitis and choroid plexitis were seen in HIV- but not in HIV+ subjects. We then correlated the imaging findings in a subset of HIV- subjects (n = 17) to CSF levels of neurofilament light chain (NFL), reflective of axonal damage and sCD27, known to best predict the presence of intrathecal T-cell mediated inflammation. We found that ependymitis on brain MRI was the best predictor of higher log(sCD27) levels and choroid plexitis was the best predictor of higher log(NFL) levels. The availability of predictive imaging biomarkers of inflammation and neurological damage in HIV- subjects with CNS cryptococcosis may help gauge disease severity and guide the therapeutic approach in those patients.

摘要

中枢神经系统隐球菌性脑膜脑炎在 HIV 阳性(HIV+)和 HIV 阴性(HIV-)患者中均与高发病率和死亡率相关,尽管进行了最佳的抗真菌治疗。因此,我们对 45 例 HIV-和 11 例 HIV+患者的 MRI 表现进行了详细分析,以确定与难治性疾病相关的影像学表现。脑室异常,即室管膜炎和脉络丛炎,见于 HIV-患者,但不存在于 HIV+患者中。然后,我们将 HIV-患者亚组(n=17)的影像学表现与脑脊液神经丝轻链(NFL)水平相关联,NFL 反映轴突损伤,而 sCD27 已知是预测鞘内 T 细胞介导炎症存在的最佳指标。我们发现,脑 MRI 上的室管膜炎是 log(sCD27)水平较高的最佳预测指标,而脉络丛炎是 log(NFL)水平较高的最佳预测指标。中枢神经系统隐球菌病的 HIV-患者中存在炎症和神经损伤的预测性影像学生物标志物,可能有助于评估疾病严重程度并指导这些患者的治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bad3/5569007/14f336b0495e/41598_2017_9694_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验