Classification and characterization of periventricular and deep white matter hyperintensities on MRI: A study in older adults.
White matter hyperintensities (WMH) are frequently divided into periventricular (PWMH) and deep (DWMH), and the two classes have been associated with different cognitive, microstructural, and clinical correlates. However, although this distinction is widely used in visual ratings scales, how to best anatomically define the two classes is still disputed. In fact, the methods used to define PWMH and DWMH vary significantly between studies, making results difficult to compare. The purpose of this study was twofold: first, to compare four current criteria used to define PWMH and DWMH in a cohort of healthy older adults (mean age: 69.58 ± 5.33 years) by quantifying possible differences in terms of estimated volumes; second, to explore associations between the two WMH sub-classes with cognition, tissue microstructure and cardiovascular risk factors, analysing the impact of different criteria on the specific associations. Our results suggest that the classification criterion used for the definition of PWMH and DWMH should not be considered a major obstacle for the comparison of different studies. We observed that higher PWMH load is associated with reduced cognitive function, higher mean arterial pressure and age. Higher DWMH load is associated with higher body mass index. PWMH have lower fractional anisotropy than DWMH, which also have more heterogeneous microstructure. These findings support the hypothesis that PWMH and DWMH are different entities and that their distinction can provide useful information about healthy and pathological aging processes.
Centre for the functional MRI of the Brain (FMRIB), University of Oxford, UK. Electronic address: ludovica.griffanti@ndcn.ox.ac.uk.
Ludovica
L
Griffanti
Centre for the functional MRI of the Brain (FMRIB), University of Oxford, UK.
Mark
M
Jenkinson
Department of Psychiatry, University of Oxford, UK.
Sana
S
Suri
Department of Psychiatry, University of Oxford, UK.
Enikő
E
Zsoldos
Department of Psychiatry, University of Oxford, UK.
Abda
A
Mahmood
Department of Psychiatry, University of Oxford, UK.
Nicola
N
Filippini
Centre for the functional MRI of the Brain (FMRIB), University of Oxford, UK.
Claire E
CE
Sexton
Department of Psychiatry, University of Oxford, UK.
Anya
A
Topiwala
Department of Psychiatry, University of Oxford, UK.
Charlotte
C
Allan
Department of Epidemiology and Public Health, University College London, London, UK.
Mika
M
Kivimäki
Department of Epidemiology and Public Health, University College London, London, UK; INSERM, U 1018, Hopital PAUL Brousse, Villejuif, France.
Archana
A
Singh-Manoux
Department of Psychiatry, University of Oxford, UK.
Klaus P
KP
Ebmeier
Centre for the functional MRI of the Brain (FMRIB), University of Oxford, UK; Department of Psychiatry, University of Oxford, UK.
Clare E
CE
Mackay
Centre for the functional MRI of the Brain (FMRIB), University of Oxford, UK; Dipartimento di Scienze Biomediche, Metaboliche e Neuroscienze, Università di Modena e Reggio Emilia, Italy.
Giovanna
G
Zamboni
D000367:Age Factors; D000368:Aged; D000375:Aging / Q000473:pathology; D015992:Body Mass Index; D060825:Cognitive Dysfunction / Q000000981:diagnostic imaging* / Q000473:pathology; D015331:Cohort Studies; D005260:Female; D006801:Humans; D006973:Hypertension / Q000000981:diagnostic imaging* / Q000473:pathology; D049292:Leukoaraiosis / Q000145:classification / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D059906:Neuroimaging / Q000379:methods*