Search

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., (© 2022 by American Journal of Neuroradiology.)

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., (© 2019 by American Journal of Neuroradiology.)

Background and Purpose: High resolution 7T MRI is increasingly used to investigate hippocampal subfields in vivo, but most studies rely on manual segmentation which is labor intensive. We aimed to evaluate an automated technique to segment hippocampal subfields and the entorhinal cortex at 7T MRI., Materials and Methods: The cornu ammonis (CA)1, CA2, CA3, dentate gyrus, subiculum, and entorhinal cortex were manually segmented, covering most of the long axis of the hippocampus on 0.70-mm(3) T2-weighted 7T images of 26 participants (59 ± 9 years, 46% men). The automated segmentation of hippocampal subfields approach was applied and evaluated by using leave-one-out cross-validation., Results: Comparison of automated segmentations with corresponding manual segmentations yielded a Dice similarity coefficient of >0.75 for CA1, the dentate gyrus, subiculum, and entorhinal cortex and >0.54 for CA2 and CA3. Intraclass correlation coefficients were >0.74 for CA1, the dentate gyrus, and subiculum; and >0.43 for CA2, CA3, and the entorhinal cortex. Restricting the comparison of the entorhinal cortex segmentation to a smaller range along the anteroposterior axis improved both intraclass correlation coefficients (left: 0.71; right: 0.82) and Dice similarity coefficients (left: 0.78; right: 0.77). The accuracy of the automated segmentation versus a manual rater was lower, though only slightly for most subfields, than the intrarater reliability of an expert manual rater, but it was similar to or slightly higher than the accuracy of an expert-versus-manual rater with ∼170 hours of training for almost all subfields., Conclusions: This work demonstrates the feasibility of using a computational technique to automatically label hippocampal subfields and the entorhinal cortex at 7T MRI, with a high accuracy for most subfields that is competitive with the labor-intensive manual segmentation. The software and atlas are publicly available: http://www.nitrc.org/projects/ashs/., (© 2016 by American Journal of Neuroradiology.)

Summary: MR imaging at 7T has a high sensitivity for cerebral microbleed detection. We identified mIP processing conditions with an optimal balance between the number of visually detected microbleeds and the number of sections on 7T MR imaging. Even with optimal mIP processing, the limited size of some of the microbleeds and the susceptibility effects of other adjacent structures were a challenge for visual detection, which led to a modest inter-rater agreement, mainly due to missed microbleeds. Automated lesion-detection techniques may be required to optimally benefit from the increased spatial resolution offered by 7T MR imaging.

Background and Purpose: The detection of microbleeds differs strongly between studies, due to differences in scan protocol. This study aims to compare the visualization of microbleeds with 3D T2*-weighted imaging at 1.5T with 3D dual-echo T2*-weighted imaging at 7T., Materials and Methods: Thirty-four patients (29 male; mean age, 58 ± 12 years) with atherosclerotic disease from the Second Manifestations of ARTerial Disease study were included. 3D T2*-weighted imaging at 1.5T and dual-echo T2*-weighted imaging at 7T were done in all patients. The presence and number of definite microbleeds were recorded on minimal intensity projections. Inter- and intraobserver reliability was assessed with Cohen κ test and the ICC. The difference in presence and number of microbleeds was tested with the McNemar test and Wilcoxon signed rank test., Results: The interobserver ICC at 7T was 0.61 and the intraobserver ICC was 0.94, whereas at 1.5T the interobserver ICC was 0.50 and the intraobserver ICC was 0.59. Microbleeds were detected in significantly more patients on 7T (50%) than on 1.5T scans (21%) (P = .001). The number of microbleeds was also higher at 7T (median, 0.5; range, 0-5) than on 1.5T (median, 0.0; range, 0-6) (P = .002)., Conclusions: 3D dual-echo T2*-weighted imaging at 7T results in better and more reliable detection of microbleeds compared with 3D T2*-weighted imaging at 1.5T.