| Literature DB >> 34852829 |
Luke A Stangler1,2, Abbas Kouzani1, Kevin E Bennet1,2, Ludovic Dumee1, Michael Berk3, Gregory A Worrell4, Steven Steele2, Terence C Burns5, Charles L Howe6,7,8.
Abstract
Contemporary biomarker collection techniques in blood and cerebrospinal fluid have to date offered only modest clinical insights into neurologic diseases such as epilepsy and glioma. Conversely, the collection of human electroencephalography (EEG) data has long been the standard of care in these patients, enabling individualized insights for therapy and revealing fundamental principles of human neurophysiology. Increasing interest exists in simultaneously measuring neurochemical biomarkers and electrophysiological data to enhance our understanding of human disease mechanisms. This review compares microdialysis, microperfusion, and implanted EEG probe architectures and performance parameters. Invasive consequences of probe implantation are also investigated along with the functional impact of biofouling. Finally, previously developed microdialysis electrodes and microperfusion electrodes are reviewed in preclinical and clinical settings. Critically, current and precedent microdialysis and microperfusion probes lack the ability to collect neurochemical data that is spatially and temporally coincident with EEG data derived from depth electrodes. This ultimately limits diagnostic and therapeutic progress in epilepsy and glioma research. However, this gap also provides a unique opportunity to create a dual-sensing technology that will provide unprecedented insights into the pathogenic mechanisms of human neurologic disease.Entities:
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Year: 2021 PMID: 34852829 PMCID: PMC8638547 DOI: 10.1186/s12987-021-00292-x
Source DB: PubMed Journal: Fluids Barriers CNS ISSN: 2045-8118
Fig. 1Microdialysis and microperfusion systems. The major features of microdialysis and microperfusion devices include cylindrical probes, reservoirs for metabolites and biomarkers, pumps to drive perfusion fluid flow and control fluid fluctuation into the tissue. Exclusive to microdialysis is a membrane that separates and protects the peri-probe tissue from the flowing perfusate. Microperfusion incorporates a secondary pull pump to draw perfusate from the catheter and perfusion ports, allowing larger molecules and compounds to diffuse into the collection fluid
Fig. 2Microdialysis membrane molecular weight cut-off. Recovery rate across a defined MWCO membrane can be approximated by an exponential function that decreases as the molecular weight of the sampled compound increases [137, 138]. Mechanistically, this is related to the presence of progressively fewer large-diameter pores in the membrane relative to small-diameter pores, resulting in reduced probability of large molecule permeation. The largest pore size sets the absolute cut-off for permeability, but the effective cut-off is considerably smaller. The manufacturer specified MWCO for a membrane is a single point along a spectrum where compounds of a known molecular weight experience a specific transmission rate across the membrane, typically 10-20% (or conversely, 80-90% retention or permeability resistance). Therefore, to achieve high recovery (>80%) of a desired molecule with a specific molecular weight (MW-A), a membrane with a much larger MWCO must be employed (MWCO-B)
Advantages and disadvantages of microdialysis and microperfusion
| Microdialysis | Microperfusion | |
|---|---|---|
| Advantages | Strong literature foundation Able to target specific molecular weights Single pump configuration | Less well characterized Largely avoids biofouling Collects biomarkers of all sizes Simple probe construction Simple sterilization process |
| Disadvantages | Membrane biofouling Complicated probe construction Lack of commercial membrane sizes Membrane expense Membrane sterilization challenges | Tissue damage at high flow rates Secondary pull pump required |
Fig. 3No-net-flux calibration method. Plotting the experimentally determined differences between output (Cout = dialysate) and input (Cin = perfusate) concentrations for a molecule of interest against the known input concentrations yields an estimate of actual tissue concentration at the point where the linear regression crosses the abscissa. In addition, the slope of the regression provides the recovery rate. While time consuming, this method provides an accurate estimate of tissue concentration with minimal a priori assumptions