Glymphatic system is newly discovered pseudolymphatic system in brain and it plays an important role in the removal of interstitial metabolic waste products. We discuss and review the role of glymphatic system in neurological diseases, especially focus on the potential of MRI modelling and its associated challenges to obtain useful new information related to understand the glymphatic system dynamics, pathways, and provide quantitative maps for diagnosis, monitoring and prognosis of the disease. The non-invasive nature of MRI might more readily help with translation of glymphatic measurements from the laboratory to the clinic.

BACKGROUND AND PURPOSE:The demonstration of prominent medullary veins in the deep white matter ipsilateral to acute ischemic stroke has been shown to predict poor clinical outcome. We have investigated the prognostic implications of prominent medullary veins in patients with subacute stroke who present outside the therapeutic window for revascularization therapy.

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Diabetes mellitus (DM) is a common metabolic disease in the middle-aged and older population, and is associated with cognitive impairment and an increased risk of developing dementia. The glymphatic system is a recently characterised brain-wide cerebrospinal fluid and interstitial fluid drainage pathway that enables the clearance of interstitial metabolic waste from the brain parenchyma. Emerging data suggest that DM and ageing impair the glymphatic system, leading to accumulation of metabolic wastes including amyloid-β within the brain parenchyma, and consequently provoking cognitive dysfunction. In this review, we concisely discuss recent findings regarding the role of the glymphatic system in DM and ageing associated cognitive impairment.

Imaging brain microvasculature is important in cerebrovascular diseases. However, there is still a lack of non-invasive, non-radiation, and whole-body imaging techniques to investigate them. The aim of this study is to develop an ultra-small superparamagnetic iron oxide (USPIO) enhanced susceptibility weighted imaging (SWI) method for imaging micro-vasculature in both animal (~10 μm in rat) and human brain. We hypothesized that the USPIO-SWI technique could improve the detection sensitivity of the diameter of small subpixel vessels 10-fold compared with conventional MRI methods.Computer simulations were first performed with a double-cylinder digital model to investigate the theoretical basis for this hypothesis. The theoretical results were verified using in vitro phantom studies and in vivo rat MRI studies (n = 6) with corresponding ex vivo histological examinations. Additionally, in vivo human studies (n = 3) were carried out to demonstrate the translational power of the USPIO-SWI method.By directly comparing the small vessel diameters of an in vivo rat using USPIO-SWI with the small vessel diameters of the corresponding histological slide using laser scanning confocal microscopy, 13.3-fold and 19.9-fold increases in SWI apparent diameter were obtained with 5.6 mg Fe/kg and 16.8 mg Fe/kg ferumoxytol, respectively. The USPIO-SWI method exhibited its excellent ability to detect small vessels down to about 10 μm diameter in rat brain. The in vivo human study unveiled hidden arterioles and venules and demonstrated its potential in clinical practice. Theoretical modeling simulations and in vitro phantom studies also confirmed a more than 10-fold increase in the USPIO-SWI apparent diameter compared with the actual small vessel diameter size.It is feasible to use SWI blooming effects induced by USPIO to detect small vessels (down to 10 μm in diameter for rat brain), well beyond the spatial resolution limit of conventional MRI methods. The USPIO-SWI method demonstrates higher potential in cerebrovascular disease investigations.Abbreviations: 3D, three dimensional; CA, contrast agent; CNR, contrast-to-noise ratio; FITC-dextran, fluorescein isothiocyanate-dextran; FOV, field of view; IV, intravenous; LSCM, laser scanning confocal microscopy; MRA, magnetic resonance angiography; PVS, para-vascular space; SNR, signal-to-noise ratio; SWI, susceptibility weighted imaging; T 2 *W, T 2 * weighted; USPIO, ultra-small superparamagnetic iron oxide; Δχ, susceptibility difference of adjacent materials.