Systematic review of signal post-processing methods in blood-brain barrier dysfunction assessments via dynamic-contrast enhanced magnetic resonance imaging

  • Jose Bernal Moyano (Creator)

Dataset

Abstract

DCE-MRI enables quantification of vascular permeability, but current acquisition and processing protocols may be sub-optimal. While the literature has started to recognise this is indeed a problem, decisions concerning the application of post-processing or the lack thereof is still being driven by intuition or experience in high permeability scenarios and not necessarily by facts, potentially compromising the quality of subsequent analyses. In this systematic revision of the literature, we seek to identify MRI issues affecting BBB assessments via DCE-MRI, identify post-processing techniques typically considered to cope with them, and determine whether researchers thoroughly evaluate their effect prior to their application. This dataset contains the results of such a systematic search and data extraction.
## Funders ##
This work was supported by the following:
- the MRC Doctoral Training Programme in Precision Medicine (JB - Award Reference No. 2096671);
- the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK MRC, Alzheimer's Society and Alzheimer's Research UK;
- the Fondation Leducq Network for the Study of Perivascular Spaces in Small Vessel Disease (16 CVD 05);
- the Stroke Association 'Small Vessel Disease-Spotlight on Symptoms (SVD-SOS)' (SAPG 19\100068);
- the Row Fogo Charitable Trust Centre for Research into Aging and the Brain (MVH) (BRO-D.FID3668413);
- a British Heart Foundation Chair award (RMT) (CH/12/4/29762);
- the European Union Horizon 2020, PHC03-15, project No666881, 'SVDs@Target'.

Data Citation

Bernal, Jose. (2021). Systematic review of signal post-processing methods in blood-brain barrier dysfunction assessments via dynamic-contrast enhanced magnetic resonance imaging, [dataset]. University of Edinburgh. Edinburgh Medical School. https://doi.org/10.7488/ds/3039.
Date made available19 May 2021
PublisherEdinburgh DataShare

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