The Drainage Dysfunction of Meningeal Lymphatic Vessels Is Correlated with the Recurrence of Chronic Subdural Hematoma: a Prospective Study.
Jiahao ZhangLei YuXiaoyu WangQian YuBingrui ZhuHaocheng ZhangYibo LiuHuaming LiAnke ZhangKaikai WangYezhao HeQun WuYuanjian FangJianzhong SunSheng ChenPublished in: Translational stroke research (2023)
Meningeal lymphatic vessels (mLVs) were recently discovered to be involved in the waste drainage process in the brain, which has also been associated with a variety of neurological diseases. This research paper hypothesizes that the drainage function of mLVs may be affected after chronic subdural hematoma (CSDH) and the alterations of mLVs' drainage may predict CSDH recurrence. In this prospective observational study, unenhanced 3D T2-fluid-attenuated inversion recovery (3D T2-FLAIR) MRI data were collected from CSDH patients and healthy participants for analysis. Patients with CSDH who underwent surgery received MRI scans before and after surgery, whereas healthy controls and patients with CSDH who received pharmaceutical treatment received only one MRI scan at enrollment. The signal unit ratio (SUR) of mLVs were then measured according to the MRI data and calculated to define mLVs' drainage function. Finally, the relationship between mLVs' drainage function and CSDH recurrence was analyzed accordingly. Thirty-four participants were enrolled in this study, including 27 CSDH patients and 7 controls. The SUR of mLVs in all CSDH patients changed significantly before and after surgery. Moreover, the drainage function of the mLVs ipsilateral to hematoma (mLVs-IH) in CSDH patients was significantly lower than that in the controls (p < 0.05). Last, a higher improvement rate of the drainage function of the mLVs-IH is correlated to a lower risk of recurrence (p < 0.05). This study revealed the mLVs' drainage dysfunction after CSDH through non-invasive MRI. Furthermore, the drainage function of mLVs is an independent predictive factor of CSDH recurrence.
Keyphrases
- end stage renal disease
- ultrasound guided
- chronic kidney disease
- ejection fraction
- magnetic resonance imaging
- newly diagnosed
- contrast enhanced
- peritoneal dialysis
- computed tomography
- prognostic factors
- magnetic resonance
- healthcare
- risk assessment
- machine learning
- coronary artery disease
- minimally invasive
- patient reported outcomes
- white matter
- percutaneous coronary intervention
- artificial intelligence
- blood brain barrier
- deep learning
- drug induced
- functional connectivity
- municipal solid waste