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Aims The 10-year risk of recurrent atherosclerotic cardiovascular disease (ASCVD) events in patients with established ASCVD can be estimated with the Secondary Manifestations of ARTerial disease (SMART) risk score, and may help refine clinical management. To broaden generalizability across regions, we updated the existing tool (SMART2 risk score) and recalibrated it with regional incidence rates and assessed its performance in external populations. Methods and results Individuals with coronary artery disease, cerebrovascular disease, peripheral artery disease, or abdominal aortic aneurysms were included from the Utrecht Cardiovascular Cohort-SMART cohort [n = 8355; 1706 ASCVD events during a median follow-up of 8.2 years (interquartile range 4.2-12.5)] to derive a 10-year risk prediction model for recurrent ASCVD events (non-fatal myocardial infarction, non-fatal stroke, or cardiovascular mortality) using a Fine and Gray competing risk-adjusted model. The model was recalibrated to four regions across Europe, and to Asia (excluding Japan), Japan, Australia, North America, and Latin America using contemporary cohort data from each target region. External validation used data from seven cohorts [Clinical Practice Research Datalink, SWEDEHEART, the international REduction of Atherothrombosis for Continued Health (REACH) Registry, Estonian Biobank, Spanish Biomarkers in Acute Coronary Syndrome and Biomarkers in Acute Myocardial Infarction (BACS/BAMI), the Norwegian COgnitive Impairment After STroke, and Bialystok PLUS/Polaspire] and included 369 044 individuals with established ASCVD of whom 62 807 experienced an ASCVD event. C-statistics ranged from 0.605 [95% confidence interval (CI) 0.547-0.664] in BACS/BAMI to 0.772 (95% CI 0.659-0.886) in REACH Europe high-risk region. The clinical utility of the model was demonstrated across a range of clinically relevant treatment thresholds for intensified treatment options. Conclusion The SMART2 risk score provides an updated, validated tool for the prediction of recurrent ASCVD events in patients with established ASCVD across European and non-European populations. The use of this tool could allow for a more personalized approach to secondary prevention based upon quantitative rather than qualitative estimates of residual risk. Key objective To improve upon prediction of 10-year residual atherosclerotic cardiovascular disease (ASCVD) event risk in individuals with established ASCVD, by taking into account competing risks and geographical differences in ASCVD incidence. Key findings Derivation in 8355 individuals with established ASCVD from the Utrecht Cardiovascular Cohort-Secondary Manifestations of ARTerial disease (SMART) cohort. C-statistics ranged from 0.605 [95% confidence interval (CI) 0.547-0.664] to 0.772 (95% CI 0.659-0.886). Clinical utility was demonstrated across a range of treatment thresholds relevant to therapy intensification. Take-home messages The SMART2 risk score can be used to estimate 10-year residual risk of fatal and non-fatal ASCVD in individuals with established ASCVD. Adapted to the CVD incidence in several global regions. Facilitates shared decision-making on Step 2 prevention goals as recommended by the 2021 ESC Guidelines on cardiovascular prevention.

BACKGROUND AND PURPOSE: The clinical relevance of cortical microinfarcts has recently been established; however, studies on microinfarcts in the deep gray matter are lacking. We examined the risk factors and MR imaging correlates of microinfarcts in the deep gray matter on 7T MR imaging and their relation to cognitive functioning.\MATERIALS AND METHODS: Within the Second Manifestations of ARTerial disease?Magnetic Resonance (SMART-MR) study, 213 patients (mean age, 68 [SD, 8]?years) had a risk-factor assessment, 7T and 1.5T brain MR imaging, and a cognitive examination. Microinfarcts on 7T MR imaging were defined as lesions of < 5 mm. Regression models were used to examine the age-adjusted associations among risk factors, MR imaging markers, and microinfarcts. Cognitive function was summarized as composite and domain-specific z scores. RESULTS: A total of 47 microinfarcts were found in 28 patients (13%), most commonly in the thalamus. Older age, history of stroke, hypertension, and intima-media thickness were associated with microinfarcts. On 1.5T MR imaging, cerebellar infarcts (relative risk = 2.75; 95% CI, 1.4?5.33) and lacunes in the white (relative risk = 3.28; 95% CI, 3.28?6.04) and deep gray matter (relative risk?= 3.06; 95% CI, 1.75?5.35) were associated with microinfarcts, and on 7T MR imaging cortical microinfarcts (relative risk = 2.33; 95% CI, 1.32?4.13). Microinfarcts were also associated with poorer global cognitive functioning (mean difference in the global z score between patients with multiple microinfarcts versus none = ?0.97; 95% CI, ?1.66 to ?0.28, P = .006) and across all cognitive domains. CONCLUSIONS: Microinfarcts in the deep gray matter on 7T MR imaging were associated with worse cognitive functioning and risk factors and MR imaging markers of small-vessel and large-vessel disease. Our findings suggest that microinfarcts in the deep gray matter may represent a novel imaging marker of vascular brain injury.

In cerebral small vessel disease (cSVD), whole brain MRI markers of cSVD-related brain injury explain limited variance to support individualized prediction. Here, we investigate whether considering abnormalities in brain tracts by integrating multimodal metrics from diffusion MRI (dMRI) and structural MRI (sMRI), can better capture cognitive performance in cSVD patients than established approaches based on whole brain markers. We selected 102 patients (73.7 ± 10.2 years old, 59 males) with MRI-visible SVD lesions and both sMRI and dMRI. Conventional linear models using demographics and established whole brain markers were used as benchmark of predicting individual cognitive scores. Multi-modal metrics of 73 major brain tracts were derived from dMRI and sMRI, and used together with established markers as input of a feed-forward artificial neural network (ANN) to predict individual cognitive scores. A feature selection strategy was implemented to reduce the risk of overfitting. Prediction was performed with leave-one-out cross-validation and evaluated with the R2 of the correlation between measured and predicted cognitive scores. Linear models predicted memory and processing speed with R2 = 0.26 and R2 = 0.38, respectively. With ANN, feature selection resulted in 13 tract-specific metrics and 5 whole brain markers for predicting processing speed, and 28 tract-specific metrics and 4 whole brain markers for predicting memory. Leave-one-out ANN prediction with the selected features achieved R2 = 0.49 and R2 = 0.40 for processing speed and memory, respectively. Our results show proof-of-concept that combining tract-specific multimodal MRI metrics can improve the prediction of cognitive performance in cSVD by leveraging tract-specific multi-modal metrics.

Objectives. DISH has been associated with increased coronary artery calcifications and incident ischaemic stroke. The formation of bone along the spine may share pathways with calcium deposition in the aorta. We hypothesized that patients with DISH have increased vascular calcifications. Therefore we aimed to investigate the presence and extent of DISH in relation to thoracic aortic calcification (TAC) severity. Methods. This cross-sectional study included 4703 patients from the Second Manifestation of ARTerial disease cohort, consisting of patients with cardiovascular events or risk factors for cardiovascular disease. Chest radiographs were scored for DISH using the Resnick criteria. Different severities of TAC were scored arbitrarily from no TAC to mild, moderate or severe TAC. Using multivariate logistic regression, the associations between DISH and TAC were analysed with adjustments for age, sex, BMI, diabetes, smoking status, non-high-density lipoprotein cholesterol, cholesterol lowering drug usage, renal function and blood pressure. Results. A total of 442 patients (9.4%) had evidence of DISH and 1789 (38%) patients had TAC. The prevalence of DISH increased from 6.6% in the no TAC group to 10.8% in the mild, 14.3% in the moderate and 17.1% in the severe TAC group. After adjustments, DISH was significantly associated with the presence of TAC [odds ratio (OR) 1.46 [95% CI 1.17, 1.82)]. In multinomial analyses, DISH was associated with moderate TAC [OR 1.43 (95% CI 1.06, 1.93)] and severe TAC [OR 1.67 (95% CI 1.19, 2.36)]. Conclusions. Subjects with DISH have increased TACs, providing further evidence that patients with DISH have an increased burden of vascular calcifications.

Background: We investigated the association between white matter hyperintensity location and depressive symptoms in a memoryclinic population using lesion–symptom mapping.Methods: We included 680 patients with vascular brain injury from the TRACE-VCI cohort (mean age ± standard deviation: 67 ± 8 years; 52% female): 168 patients with subjective cognitive decline, 164 with mild cognitive impairment and 348 with dementia. We assessed depressive symptoms using the Geriatric Depression Scale. We applied assumptionfree voxel-based lesion–symptom mapping, adjusted for age, sex, total white matter hyperintensity volume and multiple testing. Next, we applied exploratory region-of-interest linear regression analyses of major white matter tracts, with additional adjustment for diagnosis.Results: Voxel-based lesion–symptom mapping identified voxel clusters related to the Geriatric Depression Scale in the left corticospinal tract. Region-of-interest analyses showed no relation between white matter hyperintensity volume and the Geriatric Depression Scale, but revealed an interaction with diagnosis in the forceps minor, where larger regional white matter hyperintensity volume was associated with more depressive symptoms in subjective cognitive decline (β = 0.26, p < 0.05), but not in mild cognitive impairment or dementia.Limitations: We observed a lack of convergence of findings between voxel-based lesion–symptom mapping and region-of-interest analyses, which may have been due to small effect sizes and limited lesion coverage despite the large sample size. This warrants replication of our findings and further investigation in other cohorts.Conclusion: This lesion–symptom mapping study in depressive symptoms indicates the corticospinal tract and forceps minor as strategic tracts in which white matter hyperintensity is associated with depressive symptoms in memory-clinic patients with vascular brain injury. The impact of white matter hyperintensity on depressive symptoms is modest, but it appears to depend on the location of white matter hyperintensity and disease severity.

ObjectiveTo determine the occurrence of acute cerebral microinfarcts (ACMIs) in memory clinic patients and relate their presence to vascular risk and cognitive profile, CSF and neuroimaging markers, and clinical outcome.MethodsThe TRACE-VCI study is a memory clinic cohort of patients with vascular brain injury on MRI (i.e., possible vascular cognitive impairment [VCI]). We included 783 patients (mean age 67.6 ± 8.5, 46% female) with available 3T diffusion-weighted imaging (DWI). ACMIs were defined as supratentorial DWI hyperintensities ResultsA total of 23 ACMIs were found in 16 of the 783 patients (2.0%). Patients with ACMIs did not differ in vascular risk or cognitive profile, but were more often diagnosed with vascular dementia (odds ratio [OR] 5.1; 95% confidence interval [CI] 1.4–18.9, p = 0.014). ACMI presence was associated with lower levels of β-amyloid (p < 0.004) and with vascular imaging markers (lacunar infarcts: OR 3.5, CI 1.3–9.6, p = 0.015; nonlacunar infarcts: OR 4.1, CI 1.4–12.5, p = 0.012; severe white matter hyperintensities: OR 4.8, CI 1.7–13.8, p = 0.004; microbleeds: OR 18.9, CI 2.5–144.0, p = 0.0001). After a median follow-up of 2.1 years, the risk of poor clinical outcome (composite of marked cognitive decline, major vascular event, death, and institutionalization) was increased among patients with ACMIs (hazard ratio 3.0; 1.4–6.0, p = 0.005).ConclusionIn patients with possible VCI, ACMI presence was associated with a high burden of cerebrovascular disease of both small and large vessel etiology and poor clinical outcome. ACMIs may thus be a novel marker of active vascular brain injury in these patients.

Cerebral small vessel disease is a heterogeneous disease in which various underlying etiologies can lead to different types of white matter hyperintensities (WMH). WMH shape features might aid in distinguishing these different types. In this proof of principle study in patients with type 2 diabetes mellitus (T2DM), we present a novel approach to assess WMH using shape features. Our algorithm determines WMH volume and different WMH shape and location features on 3T MRI scans. These features were compared between patients with T2DM (n = 60) and a matched control group (n = 54). Although a more traditional marker (WMH volume) was not significantly different between groups (natural log transformed Beta (95% CI): 0.07 (−0.11↔0.24)), patients with T2DM showed a larger number of non-punctuate WMH (median (10th–90th percentile), patients: 40 lesions per person (16–86); controls: 26 (5–58)) and a different shape (eccentricity) of punctuate deep WMH (Beta (95% CI): 0.40 (0.23↔0.58)) compared to controls. In conclusion, our algorithm identified WMH features that are not part of traditional WMH assessment, but showed to be distinguishing features between patients with T2DM and controls. Future studies could address these features to further unravel the etiology and functional impact of WMH.