Name
Title | ||
|---|---|---|
Developing an Integrated Image Bank and Metadata for Large-scale Research in Cerebrovascular Disease: Our Experience from the Stroke Image Bank Project. |
Abstract | ||
|---|---|---|
A framework for building an infrastructure that semantically integrates, archives and reuses data for various research purposes in human brain imaging remains critical. In particular, problems of aligning technical, clinical and professional systems in order to facilitate data sharing are a recurring issue in brain imaging. However, large samples of well characterised images with detailed metadata are increasingly needed. This paper outlines the experience of the NeuroGrid Stroke Exemplar and further work in the Brain Research Imaging Centre and Stroke Trials Unit in developing an infrastructure that facilitates the linkage, archiving and reuse of imaging data from stroke patients for large scale clinical and epidemiological studies. We examined data from 12 past stroke projects carried out over the past two decades in our centre and two large trials with 329 centres. We assessed previously published schemas and those developed specifically for large multicentre ischaemic and haemorrhagic stroke treatment trials. We then developed our own harmonised and integrated schema and database with a web-based interface system, aiming to be flexible and adaptable to future trials and observational studies. We then linked image and meta-data from 3079 patients acquired in stroke research in one centre in a 14 year period (1996 – 2010) with prospective central hospital health statistics to obtain long term follow-up. Our integrated database includes 3079 subjects and over 550 federated and searchable data items including imaging details, medical history and examination, stroke and laboratory details, which maps to large multicentre stroke trials with imaging data from over 10,000 patients from 30 countries. The central linkage identified 879 of 3079 patients had died, 525 had recurrent strokes and 291 developed dementia during up to a 19 year period (range=0 -19; median=9.04; IQR=12.17) of follow-up, demonstrating its utility. The core metadata schema, has benefited from extensive development in large clinical trials. Further trials’ data can now be added. It provides an opportunity to crosslink and reuse data for a range of large scale stroke brain imaging clinical and research purposes including developing data analytics models for research into common brain diseases and their consequences. |
Year | Venue | Field |
|---|---|---|
2016 | Front. ICT | Data science,Data integration,Metadata,Observational study,Computer science,Data sharing,Stroke,Clinical trial,Neuroimaging,Schema (psychology) |
DocType | Volume | Citations |
Journal | 2016 | 0 |
PageRank | References | Authors |
0.34 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Samuel Danso | 1 | 5 | 1.44 |
| Dominic Edward Job | 2 | 0 | 0.34 |
| David Rodriguez Gonzalez | 3 | 11 | 2.14 |
| David Alexander Dickie | 4 | 25 | 3.16 |
| Jeb Palmer | 5 | 6 | 2.00 |
| Jenny Ure | 6 | 41 | 5.04 |
| Philip Bath | 7 | 0 | 0.34 |
| Peter Sandercock | 8 | 0 | 0.34 |
| Joanna M. Wardlaw | 9 | 108 | 17.52 |