Systematic review and meta-analysis of automated methods for quantifying enlarged perivascular spaces in the brain
Jennifer M.J. Waymont,
Maria del C. Valdés Hernández,
José Bernal,
Roberto Duarte Coello,
Rosalind Brown,
Francesca M. Chappell,
Lucia Ballerini,
Joanna M. Wardlaw
Affiliations
Jennifer M.J. Waymont
Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
Maria del C. Valdés Hernández
Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK; Corresponding author at: Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK.
José Bernal
Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK; German Centre for Neurodegenerative Diseases (DZNE), Germany; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Germany
Roberto Duarte Coello
Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
Rosalind Brown
Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
Francesca M. Chappell
Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
Lucia Ballerini
University for Foreigners of Perugia, Perugia, Italy
Joanna M. Wardlaw
Centre for Clinical Brain Sciences, the University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; UK Dementia Research Institute Centre at the University of Edinburgh, UK
Research into magnetic resonance imaging (MRI)-visible perivascular spaces (PVS) has recently increased, as results from studies in different diseases and populations are cementing their association with sleep, disease phenotypes, and overall health indicators. With the establishment of worldwide consortia and the availability of large databases, computational methods that allow to automatically process all this wealth of information are becoming increasingly relevant. Several computational approaches have been proposed to assess PVS from MRI, and efforts have been made to summarise and appraise the most widely applied ones. We systematically reviewed and meta-analysed all publications available up to September 2023 describing the development, improvement, or application of computational PVS quantification methods from MRI. We analysed 67 approaches and 60 applications of their implementation, from 112 publications. The two most widely applied were the use of a morphological filter to enhance PVS-like structures, with Frangi being the choice preferred by most, and the use of a U-Net configuration with or without residual connections. Older adults or population studies comprising adults from 18 years old onwards were, overall, more frequent than studies using clinical samples. PVS were mainly assessed from T2-weighted MRI acquired in 1.5T and/or 3T scanners, although combinations using it with T1-weighted and FLAIR images were also abundant. Common associations researched included age, sex, hypertension, diabetes, white matter hyperintensities, sleep and cognition, with occupation-related, ethnicity, and genetic/hereditable traits being also explored. Despite promising improvements to overcome barriers such as noise and differentiation from other confounds, a need for joined efforts for a wider testing and increasing availability of the most promising methods is now paramount.
