BACKGROUND AND PURPOSE: We undertook this study to evaluate the frequency and risk factors of white matter hyperintensities seen on T2-weighted MR imaging. We examined cohorts of neurologically nondiseased elderly subjects participating in a general-community study, the Helsinki (Finland) Aging Brain Study. Cohorts of consecutive subjects aged 55, 60, 65, 70, 75, 80, and 85 years (n = 20, 18, 20, 18, 19, 18, and 15, respectively; total, n = 128) were divided into a young-old (age < 75 years, n = 76) group and an old-old (age > or = 75 years, n = 52) group. METHODS: Frequency of hyperintensities seen on T2-weighted axial and coronal MR images (0.02 T) was rated using a four-point scale in periventricular and centrum semiovale areas. RESULTS: The majority of the subjects showed only mild white matter hyperintensities, which were more frequent in the periventricular areas. Age was the most important factor to explain the presence of hyperintensities. A logistic regression analysis related periventricular hyperintensities in the entire group to central atrophy (odds ratio [OR], 4.7; 95% confidence interval [CI], 1.7 to 12.9) and silent infarcts (OR, 5.6; 95% CI, 1.0 to 19.8); among the young-old, hyperintensities related to diabetes (OR, 17.0; 95% CI, 1.9 to 154.2) and central atrophy (OR, 14.7; 95% CI, 3.5 to 61.8). Centrum semiovale hyperintensities related in the entire group to cardiac arrhythmia (OR, 4.0; 95% CI, 1.0 to 15.5), central atrophy (OR, 3.9; 95% CI, 1.2 to 12.4), and silent infarcts (OR, 3.6; 95% CI, 1.0 to 12.5). CONCLUSIONS: These mild white matter hyperintensities in the neurologically nondiseased elderly related especially to age and also to concomitant silent infarcts, atrophy, and some vascular risk factors. The known factors, however, explained only part of the variation. The young-old and old-old groups showed different associations. In contrast to former assumptions, the presence of white matter hyperintensities among the aged is likely to be linked to other as yet unidentified age-related factors.
BACKGROUND AND PURPOSE: We undertook this study to evaluate the frequency and risk factors of white matter hyperintensities seen on T2-weighted MR imaging. We examined cohorts of neurologically nondiseased elderly subjects participating in a general-community study, the Helsinki (Finland) Aging Brain Study. Cohorts of consecutive subjects aged 55, 60, 65, 70, 75, 80, and 85 years (n = 20, 18, 20, 18, 19, 18, and 15, respectively; total, n = 128) were divided into a young-old (age < 75 years, n = 76) group and an old-old (age > or = 75 years, n = 52) group. METHODS: Frequency of hyperintensities seen on T2-weighted axial and coronal MR images (0.02 T) was rated using a four-point scale in periventricular and centrum semiovale areas. RESULTS: The majority of the subjects showed only mild white matter hyperintensities, which were more frequent in the periventricular areas. Age was the most important factor to explain the presence of hyperintensities. A logistic regression analysis related periventricular hyperintensities in the entire group to central atrophy (odds ratio [OR], 4.7; 95% confidence interval [CI], 1.7 to 12.9) and silent infarcts (OR, 5.6; 95% CI, 1.0 to 19.8); among the young-old, hyperintensities related to diabetes (OR, 17.0; 95% CI, 1.9 to 154.2) and central atrophy (OR, 14.7; 95% CI, 3.5 to 61.8). Centrum semiovale hyperintensities related in the entire group to cardiac arrhythmia (OR, 4.0; 95% CI, 1.0 to 15.5), central atrophy (OR, 3.9; 95% CI, 1.2 to 12.4), and silent infarcts (OR, 3.6; 95% CI, 1.0 to 12.5). CONCLUSIONS: These mild white matter hyperintensities in the neurologically nondiseased elderly related especially to age and also to concomitant silent infarcts, atrophy, and some vascular risk factors. The known factors, however, explained only part of the variation. The young-old and old-old groups showed different associations. In contrast to former assumptions, the presence of white matter hyperintensities among the aged is likely to be linked to other as yet unidentified age-related factors.
Authors: Kejia Cai; Rongwen Tain; Sandhitsu Das; Frederick C Damen; Yi Sui; Tibor Valyi-Nagy; Mark A Elliott; Xiaohong J Zhou Journal: J Neurosci Methods Date: 2015-09-08 Impact factor: 2.390
Authors: Omar M Al-Janabi; Pradeep Panuganti; Erin L Abner; Ahmed A Bahrani; Ronan Murphy; Shoshana H Bardach; Allison Caban-Holt; Peter T Nelson; Brian T Gold; Charles D Smith; Donna M Wilcock; Gregory A Jicha Journal: J Neuroimaging Date: 2018-01-05 Impact factor: 2.486
Authors: D M J van den Heuvel; V H ten Dam; A J M de Craen; F Admiraal-Behloul; A C G M van Es; W M Palm; A Spilt; E L E M Bollen; G J Blauw; L Launer; R G J Westendorp; M A van Buchem Journal: AJNR Am J Neuroradiol Date: 2006-04 Impact factor: 3.825
Authors: D M J van den Heuvel; V H ten Dam; A J M de Craen; F Admiraal-Behloul; H Olofsen; E L E M Bollen; J Jolles; H M Murray; G J Blauw; R G J Westendorp; M A van Buchem Journal: J Neurol Neurosurg Psychiatry Date: 2006-02 Impact factor: 10.154
Authors: Rosalind Brown; Helene Benveniste; Sandra E Black; Serge Charpak; Martin Dichgans; Anne Joutel; Maiken Nedergaard; Kenneth J Smith; Berislav V Zlokovic; Joanna M Wardlaw Journal: Cardiovasc Res Date: 2018-09-01 Impact factor: 10.787
Authors: Ana Verdelho; Sofia Madureira; José M Ferro; Anna-Maria Basile; Hugues Chabriat; Timo Erkinjuntti; Franz Fazekas; Michael Hennerici; John O'Brien; Leonardo Pantoni; Emilia Salvadori; Philip Scheltens; Marieke C Visser; Lars-Olof Wahlund; Gunhild Waldemar; Anders Wallin; Domenico Inzitari Journal: J Neurol Neurosurg Psychiatry Date: 2007-04-30 Impact factor: 10.154