Cerebrospinal and interstitial fluid transport via the glymphatic pathway modeled by optimal mass transport.
The glymphatic pathway is a system which facilitates continuous cerebrospinal fluid (CSF) and interstitial fluid (ISF) exchange and plays a key role in removing waste products from the rodent brain. Dysfunction of the glymphatic pathway may be implicated in the pathophysiology of Alzheimer's disease. Intriguingly, the glymphatic system is most active during deep wave sleep general anesthesia. By using paramagnetic tracers administered into CSF of rodents, we previously showed the utility of MRI in characterizing a macroscopic whole brain view of glymphatic transport but we have yet to define and visualize the specific flow patterns. Here we have applied an alternative mathematical analysis approach to a dynamic time series of MRI images acquired every 4min over ∼3h in anesthetized rats, following administration of a small molecular weight paramagnetic tracer into the CSF reservoir of the cisterna magna. We use Optimal Mass Transport (OMT) to model the glymphatic flow vector field, and then analyze the flow to find the network of CSF-ISF flow channels. We use 3D visualization computational tools to visualize the OMT defined network of CSF-ISF flow channels in relation to anatomical and vascular key landmarks from the live rodent brain. The resulting OMT model of the glymphatic transport network agrees largely with the current understanding of the glymphatic transport patterns defined by dynamic contrast-enhanced MRI revealing key CSF transport pathways along the ventral surface of the brain with a trajectory towards the pineal gland, cerebellum, hypothalamus and olfactory bulb. In addition, the OMT analysis also revealed some interesting previously unnoticed behaviors regarding CSF transport involving parenchymal streamlines moving from ventral reservoirs towards the surface of the brain, olfactory bulb and large central veins.
Department of Computer Science, Stony Brook University, Stony Brook, NY 11790, USA.
Vadim
V
Ratner
Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY 11790, USA.
Yi
Y
Gao
Department of Anesthesiology, Yale School of Medicine, New Haven, CT 06519, USA.
Hedok
H
Lee
Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11790, USA.
Rena
R
Elkin
School of Medicine, Rochester University, NY 14642, USA.
Maiken
M
Nedergaard
Department of Anesthesiology, Yale School of Medicine, New Haven, CT 06519, USA.
Helene
H
Benveniste
Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11790, USA; Department of Computer Science, Stony Brook University, Stony Brook, NY 11790, USA. Electronic address: arobertan@gmail.com.
Allen
A
Tannenbaum
D000818:Animals; D001692:Biological Transport; D001921:Brain / Q000098:blood supply / Q000378:metabolism*; D001931:Brain Mapping / Q000379:methods*; D002555:Cerebrospinal Fluid / Q000378:metabolism*; D005260:Female; D008279:Magnetic Resonance Imaging; D051381:Rats
Cerebrospinal fluid transport; Glymphatic transport; Liquid flow modeling; Optical flow; Optimal mass transport; Rat brain