Microinfarcts in the Deep Gray Matter on 7T MRI: Risk Factors, MRI Correlates, and Relation to Cognitive Functioning-The SMART-MR Study.

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.

Intracranial Atherosclerotic Burden on 7T MRI Is Associated with Markers of Extracranial Atherosclerosis: The SMART-MR Study.

BACKGROUND AND PURPOSE: Intracranial atherosclerosis, a major risk factor for ischemic stroke, is thought to have different atherogenic mechanisms than extracranial atherosclerosis. Studies investigating their relationship in vivo are sparse and report inconsistent results. We studied the relationship between intracranial atherosclerosis and extracranial atherosclerosis in a cohort of patients with a history of vascular disease. MATERIALS AND METHODS: Within the Second Manifestations of ARTerial disease-Magnetic Resonance (SMART) study, cross-sectional analyses were performed in 130 patients (mean age, 68 ± 9 years) with a history of vascular disease and with assessable 7T intracranial vessel wall MR imaging data. Intracranial atherosclerosis burden was defined as the number of intracranial vessel wall lesions in the circle of Willis and its major branches. Age- and sex-adjusted unstandardized regression coefficients (b-value) were calculated with intracranial atherosclerosis burden as the dependent variable and extracranial atherosclerosis markers as independent variables. RESULTS: Ninety-six percent of patients had ≥1 vessel wall lesion, with a mean intracranial atherosclerosis burden of 8.5 ± 5.7 lesions. Significant associations were observed between higher intracranial atherosclerosis burden and carotid intima-media thickness (b = 0.53 lesions per +0.1 mm; 95% CI, 0.1-1.0 lesions), 50%-100% carotid stenosis versus no stenosis (b = 6.6 lesions; 95% CI, 2.3-10.9 lesions), ankle-brachial index ≤ 0.9 versus >0.9 (b = 4.9 lesions; 95% CI, 1.7-8.0 lesions), and estimated glomerular filtration rate (b = -0.77 lesions per +10 mL/min; 95% CI, -1.50 to -0.03 lesions). No significant differences in intracranial atherosclerosis burden were found among different categories of vascular disease. CONCLUSIONS: Intracranial atherosclerosis was associated with various extracranial markers of atherosclerosis, not supporting a different etiology.

Evaluation of the yield of post-clipping angiography and nationwide current practice.

BACKGROUND: Surgical treatment of intracranial saccular aneurysms aims to prevent (re)hemorrhage by complete occlusion of the aneurysmal lumen. It is unclear whether routine postoperative imaging, to assess aneurysmal occlusion, is necessary since intraoperative assessment by the neurosurgeon may be sufficient. We assessed routine clinical protocols for post-clipping imaging in the Netherlands and determined whether intraoperative assessment of aneurysm clippings sufficiently predicts aneurysm residuals. METHODS: A survey was conducted to assess postoperative imaging protocols in centers performing clipping of intracranial aneurysms in the Netherlands (n = 9). Furthermore, a retrospective single-center cohort study was performed to determine the predictive value of intraoperative assessment of aneurysm occlusion in relation to postoperative digital subtraction angiography (DSA) findings, between 2009 and 2017. RESULTS: No center performed intraoperative DSA in a hybrid OR, routinely. Respectively, four (44.4%), seven (77.8%), and three (33.3%) centers did not routinely perform early postoperative imaging, late follow-up imaging, or any routine imaging at all. Regarding our retrospective study, 106 patients with 132 clipped aneurysms were included. There were 23 residuals ≥ 1 mm (17.4%), of which 10 (43.5%) were unexpected. For the presence of these residuals, intraoperative assessment showed a sensitivity of 56.5%, a specificity of 86.2%, a positive predictive value of 46.4%, and a negative predictive value of 90.4%. CONCLUSIONS: There is lack of consensus regarding the post-clipping imaging strategy in the Netherlands. Since intraoperative assessment is shown to be insufficient to predict postoperative aneurysm residuals, we advocate routine postoperative imaging after aneurysm clipping unless this is not warranted on the basis of patient age, clinical condition, and/or comorbidity.