Dataset for "Novel approaches to model effects of subconjunctival blebs on flow pressure to improve clinical grading systems after glaucoma drainage surgery"

DOI

Dataset from the manuscript: "Novel approaches to model effects of subconjunctival blebs on flow pressure to improve clinical grading systems after glaucoma drainage surgery" published with the journal PLOS One. The total size of the data is less than 100 kB.

Each set of data is named with the figure number of the article.

They are matrices obtained and formatted with Matlab (R2017b, The MathWorks, Inc., Natick, MA, USA).

The variables within each matrix correspond to the axis of each figure from the article.

The experimental method for collection is described extensively in the PLOS One article (DOI soon available) and summarised below.

The ex vivo experiments were conducted at the UCL Institute of Ophthalmology. Blebs were prepared using an ex vivo approach as performed in conventional GFS/GDD surgery. The PEEK tube connecting the anterior chamber to the bleb was hooked up to a reservoir of a dilute aqueous solution of Coomassie Brilliant Blue G250. The tube and reservoir are connected to a microfluidic pressure pump and flow sensor setup (Fluigent, Villejuif, France). The eye experiments ran for up to 4 hours, and the pressure was recorded at a low frequency of 1 Hz. The bleb dimensions increase with time and the measurements of the bleb height, H, and radius, R, is estimated by photographic assessment through image processing algorithms written in Matlab.

The in vitro model experiments were conducted in the environmental fluid mechanics laboratory located in the UCL Department of Mechanical Engineering. The bleb height was estimated using calibrated bespoke image processing algorithms written in Matlab similarly to the ex vivo approach. A 3-way luer lock connector was used to connect a calibrated pressure transducer to the inlet tube. The pressure signal was converted to volts (P8055-1 Velleman 2003) and recorded at a frequency of 1.875 Hz.

Identifier
DOI https://doi.org/10.5522/04/9876440.v1
Related Identifier https://ndownloader.figshare.com/files/17715800
Metadata Access https://api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:figshare.com:article/9876440
Provenance
Creator Bouremel, Yann; Lee, Richard; Eames, Ian; Brocchini, Steve; Khaw, Peng
Publisher University College London UCL
Contributor Figshare
Publication Year 2019
Rights https://creativecommons.org/licenses/by/4.0/
OpenAccess true
Contact researchdatarepository(at)ucl.ac.uk
Representation
Language English
Resource Type Dataset
Discipline Other