The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Convection-enhanced delivery of therapeutics for brain disease, and its optimization
Open accessAbstract
✓ Convection-enhanced delivery (CED) is the continuous injection under positive pressure of a fluid containing a therapeutic agent. This technique was proposed and introduced by researchers from the US National Institutes of Health (NIH) by the early 1990s to deliver drugs that would otherwise not cross the blood–brain barrier into the parenchyma and that would be too large to diffuse effectively over the required distances were they simply deposited into the tissue. Despite the many years that have elapsed, this technique remains experimental because of both the absence of approved drugs for intraparenchymal delivery and the difficulty of guaranteed delivery to delineated regions of the brain. During the first decade after the NIH researchers founded this analytical model of drug distribution, the results of several computer simulations that had been conducted according to more realistic assumptions were also published, revealing encouraging results. In the late 1990s, one of the authors of the present paper proposed the development of a computer model that would predict the distribution specific to a particular patient (brain) based on obtainable data from radiological images. Several key developments in imaging technology and, in particular, the relationships between image-obtained quantities and other parameters that enter models of the CED process have been required to implement this model. Note that delivery devices need further development. In the present paper we review key features of CED as well as modeling of the procedure and indulge in informed speculation on optimizing the direct delivery of therapeutic agents into brain tissue.
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Cites
Extracellular space structure revealed by diffusion analysis
Nicholson, C., & Syková, E. (1998) · Trends in Neurosciences · doi:10.1016/s0166-2236(98)01261-2 · Cited by 914
An analytical model of restricted diffusion in bovine optic nerve
Stanisz, G. J., Wright, G. A., Henkelman, R. M., & Szafer, A. (1997) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910370115 · Cited by 501
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Metadata
- Authors
- Raghavan, R., Brady, M. L., Rodríguez-Ponce, M. I., Hartlep, A., Pedain, C., & Sampson, J. H.
- Venue
- Neurosurgical Focus
- Published
- 2006-04
- Volume
- 20
- Issue
- 4
- Pages
- E12
- ISSN
- 1092-0684 (ISSN-L)
- OpenAlex
- W2105060883
- Cited by
- 251
- References
- 2
- FWCI
- 9.50
- Type
- journal article
- Language
- en
- Open access
- bronze
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