SummaryCerebral small vessel disease (SVD) is a common accompaniment of ageing. Features seen on neuroimaging include recent small subcortical infarcts, lacunes, white matter hyperintensities, perivascular spaces, microbleeds, and brain atrophy. SVD can present as a stroke or cognitive decline, or can have few or no symptoms. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive deficits, physical disabilities, and other symptoms of neurodegeneration. Terminology and definitions for imaging the features of SVD vary widely, which is also true for protocols for image acquisition and image analysis. This lack of consistency hampers progress in identifying the contribution of SVD to the pathophysiology and clinical features of common neurodegenerative diseases. We are an international working group from the Centres of Excellence in Neurodegeneration. We completed a structured process to develop definitions and imaging standards for markers and consequences of SVD. We aimed to achieve the following: first, to provide a common advisory about terms and definitions for features visible on MRI; second, to suggest minimum standards for image acquisition and analysis; third, to agree on standards for scientific reporting of changes related to SVD on neuroimaging; and fourth, to review emerging imaging methods for detection and quantification of preclinical manifestations of SVD. Our findings and recommendations apply to research studies, and can be used in the clinical setting to standardise image interpretation, acquisition, and reporting. This Position Paper summarises the main outcomes of this international effort to provide the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE).

SummaryBackgroundAlteplase is effective for treatment of acute ischaemic stroke but debate continues about its use after longer times since stroke onset, in older patients, and among patients who have had the least or most severe strokes. We assessed the role of these factors in affecting good stroke outcome in patients given alteplase.MethodsWe did a pre-specified meta-analysis of individual patient data from 6756 patients in nine randomised trials comparing alteplase with placebo or open control. We included all completed randomised phase 3 trials of intravenous alteplase for treatment of acute ischaemic stroke for which data were available. Retrospective checks confirmed that no eligible trials had been omitted. We defined a good stroke outcome as no significant disability at 3–6 months, defined by a modified Rankin Score of 0 or 1. Additional outcomes included symptomatic intracranial haemorrhage (defined by type 2 parenchymal haemorrhage within 7 days and, separately, by the SITS-MOST definition of parenchymal type 2 haemorrhage within 36 h), fatal intracranial haemorrhage within 7 days, and 90-day mortality.FindingsAlteplase increased the odds of a good stroke outcome, with earlier treatment associated with bigger proportional benefit. Treatment within 3·0 h resulted in a good outcome for 259 (32·9%) of 787 patients who received alteplase versus 176 (23·1%) of 762 who received control (OR 1·75, 95% CI 1·35–2·27); delay of greater than 3·0 h, up to 4·5 h, resulted in good outcome for 485 (35·3%) of 1375 versus 432 (30·1%) of 1437 (OR 1·26, 95% CI 1·05–1·51); and delay of more than 4·5 h resulted in good outcome for 401 (32·6%) of 1229 versus 357 (30·6%) of 1166 (OR 1·15, 95% CI 0·95–1·40). Proportional treatment benefits were similar irrespective of age or stroke severity. Alteplase significantly increased the odds of symptomatic intracranial haemorrhage (type 2 parenchymal haemorrhage definition 231 [6·8%] of 3391 vs 44 [1·3%] of 3365, OR 5·55, 95% CI 4·01–7·70, p<0·0001; SITS-MOST definition 124 [3·7%] vs 19 [0·6%], OR 6·67, 95% CI 4·11–10·84, p<0·0001) and of fatal intracranial haemorrhage within 7 days (91 [2·7%] vs 13 [0·4%]; OR 7·14, 95% CI 3·98–12·79, p<0·0001). The relative increase in fatal intracranial haemorrhage from alteplase was similar irrespective of treatment delay, age, or stroke severity, but the absolute excess risk attributable to alteplase was bigger among patients who had more severe strokes. There was no excess in other early causes of death and no significant effect on later causes of death. Consequently, mortality at 90 days was 608 (17·9%) in the alteplase group versus 556 (16·5%) in the control group (hazard ratio 1·11, 95% CI 0·99–1·25, p=0·07). Taken together, therefore, despite an average absolute increased risk of early death from intracranial haemorrhage of about 2%, by 3–6 months this risk was offset by an average absolute increase in disability-free survival of about 10% for patients treated within 3·0 h and about 5% for patients treated after 3·0 h, up to 4·5 h.Interpretat...

The term "cerebral small vessel disease" (SVD) describes a range of neuroimaging, pathological and associated clinical features. The latter range from none, to discrete focal neurological symptoms (stroke), to insidious global neurological dysfunction and dementia. The public health burden is considerable. The pathogenesis is largely unknown. Although associated with vascular risk factors, and generally considered to result from an intrinsic cerebral arteriolar occlusive disease, the pathological processes leading to the arteriolar disease, how these result in brain disease, how SVD lesions contribute to neurological or cognitive symptoms and the relationship to risk factors, have been the subject of much speculation. Pathology often reflects end-stage disease making determination of the earliest stages difficult. Neuroimaging provides considerable insights: the small vessels are not easily seen themselves, but the effects of their malfunction on the brain can be tracked on detailed brain imaging. We review the growing evidence for the most likely mechanisms.

The highly complex structure of the human brain is strongly shaped by genetic influences1. Subcortical brain regions form circuits with cortical areas to coordinate movement2, learning, memory3 and motivation4, and altered circuits can lead to abnormal behaviour and disease2. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume5 and intracranial volume6. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10−33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability inhuman brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

Objectives:In this cross-sectional study, we tested the construct validity of a “total SVD score,” which combines individual MRI features of small-vessel disease (SVD) in one measure, by testing associations with vascular risk factors and stroke subtype.Methods:We analyzed data from patients with lacunar or nondisabling cortical stroke from 2 prospective stroke studies. Brain MRI was rated for the presence of lacunes, white matter hyperintensities, cerebral microbleeds, and perivascular spaces independently. The presence of each SVD feature was summed in an ordinal “SVD score” (range 0–4). We tested associations with vascular risk factors, stroke subtype, and cerebral atrophy using ordinal regression analysis.Results:In 461 patients, multivariable analysis found that age (odds ratio [OR] 1.10, 95% confidence interval [CI] 1.08–1.12), male sex (OR 1.58, 95% CI 1.10–2.29), hypertension (OR 1.50, 95% CI 1.02–2.20), smoking (OR 2.81, 95% CI 1.59–3.63), and lacunar stroke subtype (OR 2.45, 95% CI 1.70–3.54) were significantly and independently associated with the total SVD score. The score was not associated with cerebral atrophy.Conclusions:The total SVD score may provide a more complete estimate of the full impact of SVD on the brain, in a simple and pragmatic way. It could have potential for patient or risk stratification or early efficacy assessment in clinical trials of interventions to prevent SVD progression and may (after further testing) have a useful role in clinical practice.

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA’s first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Quantifying the microstructural properties of the human brain's connections is necessary for understanding normal ageing and disease. Here we examine brain white matter magnetic resonance imaging (MRI) data in 3,513 generally healthy people aged 44.64-77.12 years from the UK Biobank. Using conventional water diffusion measures and newer, rarely studied indices from neurite orientation dispersion and density imaging, we document large age associations with white matter microstructure. Mean diffusivity is the most age-sensitive measure, with negative age associations strongest in the thalamic radiation and association fibres. White matter microstructure across brain tracts becomes increasingly correlated in older age. This may reflect an age-related aggregation of systemic detrimental effects. We report several other novel results, including age associations with hemisphere and sex, and comparative volumetric MRI analyses. Results from this unusually large, single-scanner sample provide one of the most extensive characterizations of age associations with major white matter tracts in the human brain.