BACKGROUND: Perivascular Spaces (PVS) become increasingly visible with advancing age on brain MRI, yet their relationship to morphological changes in the underlying microvessels remains poorly understood. Retinal and cerebral microvessels share morphological and physiological properties. We compared computationally-derived PVS morphologies with retinal vessel morphologies in older people. METHODS: We analysed data from community-dwelling individuals who underwent multimodal brain MRI and retinal fundus camera imaging at mean age 72.55 years (SD=0.71). We assessed centrum semiovale PVS computationally to determine PVS total volume and count, and mean per-subject individual PVS length, width and size. We analysed retinal images using the VAMPIRE software suite, obtaining the Central Retinal Artery and Vein Equivalents (CRVE and CRAE), Arteriole-to-Venule ratio (AVR), and fractal dimension (FD) of both eyes. We investigated associations using general linear models, adjusted for age, gender, and major vascular risk factors. RESULTS: In 381 subjects with all measures, increasing total PVS volume and count were associated with decreased CRAE in the left eye (volume β=-0.170, count β=-0.184, p<0.001). No associations of PVS with CRVE were found. The PVS total volume, individual width and size increased with decreasing FD of the arterioles (a) and venules (v) of the left eye (total volume: FDa β=-0.137, FDv β=-0.139, p<0.01; width: FDa β=-0.144, FDv β=-0.158, p<0.01; size: FDa β=-0.157, FDv β=-0.162, p<0.01). CONCLUSIONS: Increase in PVS number and size visible on MRI reflect arteriolar narrowing and lower retinal arteriole and venule branching complexity, both markers of impaired microvascular health. Computationally-derived PVS metrics may be an early indicator of failing vascular health and should be tested in longitudinal studies.
BACKGROUND: Perivascular Spaces (PVS) become increasingly visible with advancing age on brain MRI, yet their relationship to morphological changes in the underlying microvessels remains poorly understood. Retinal and cerebral microvessels share morphological and physiological properties. We compared computationally-derived PVS morphologies with retinal vessel morphologies in older people. METHODS: We analysed data from community-dwelling individuals who underwent multimodal brain MRI and retinal fundus camera imaging at mean age 72.55 years (SD=0.71). We assessed centrum semiovale PVS computationally to determine PVS total volume and count, and mean per-subject individual PVS length, width and size. We analysed retinal images using the VAMPIRE software suite, obtaining the Central Retinal Artery and Vein Equivalents (CRVE and CRAE), Arteriole-to-Venule ratio (AVR), and fractal dimension (FD) of both eyes. We investigated associations using general linear models, adjusted for age, gender, and major vascular risk factors. RESULTS: In 381 subjects with all measures, increasing total PVS volume and count were associated with decreased CRAE in the left eye (volume β=-0.170, count β=-0.184, p<0.001). No associations of PVS with CRVE were found. The PVS total volume, individual width and size increased with decreasing FD of the arterioles (a) and venules (v) of the left eye (total volume: FDa β=-0.137, FDv β=-0.139, p<0.01; width: FDa β=-0.144, FDv β=-0.158, p<0.01; size: FDa β=-0.157, FDv β=-0.162, p<0.01). CONCLUSIONS: Increase in PVS number and size visible on MRI reflect arteriolar narrowing and lower retinal arteriole and venule branching complexity, both markers of impaired microvascular health. Computationally-derived PVS metrics may be an early indicator of failing vascular health and should be tested in longitudinal studies.
Authors: L D Hubbard; R J Brothers; W N King; L X Clegg; R Klein; L S Cooper; A R Sharrett; M D Davis; J Cai Journal: Ophthalmology Date: 1999-12 Impact factor: 12.079
Authors: James R Cameron; Roly D Megaw; Andrew J Tatham; Sarah McGrory; Thomas J MacGillivray; Fergus N Doubal; Joanna M Wardlaw; Emanuele Trucco; Siddharthan Chandran; Baljean Dhillon Journal: Prog Retin Eye Res Date: 2017-04-28 Impact factor: 21.198
Authors: Unal Mutlu; Hieab H H Adams; Albert Hofman; Aad van der Lugt; Caroline C W Klaver; Meike W Vernooij; M Kamran Ikram; M Arfan Ikram Journal: Stroke Date: 2016-03-15 Impact factor: 7.914
Authors: Tien Yin Wong; Ronald Klein; A Richey Sharrett; Bruce B Duncan; David J Couper; James M Tielsch; Barbara E K Klein; Larry D Hubbard Journal: JAMA Date: 2002-03-06 Impact factor: 56.272
Authors: Maria del C Valdés Hernández; Karen J Ferguson; Francesca M Chappell; Joanna M Wardlaw Journal: Eur Radiol Date: 2010-02-16 Impact factor: 5.315
Authors: Fergus N Doubal; Rosemarie de Haan; Thomas J MacGillivray; Petra E Cohn-Hokke; Bal Dhillon; Martin S Dennis; Joanna M Wardlaw Journal: Int J Stroke Date: 2010-12 Impact factor: 5.266
Authors: Sarah McGrory; James R Cameron; Enrico Pellegrini; Claire Warren; Fergus N Doubal; Ian J Deary; Baljean Dhillon; Joanna M Wardlaw; Emanuele Trucco; Thomas J MacGillivray Journal: Alzheimers Dement (Amst) Date: 2016-12-02