Association between high-risk extracranial carotid plaque and covert brain infarctions and cerebral microbleeds.

PURPOSE: Covert brain infarctions (CBIs) and cerebral microbleeds (CMBs) represent subclinical sequelae of ischemic and hemorrhagic cerebral small vessel disease, respectively. In addition to thromboembolic stroke, carotid atherosclerosis has been associated with downstream vascular brain injury, including inflammation and small vessel disease. The specific plaque features responsible for this are unknown. We aimed to determine the association of specific vulnerable carotid plaque features to CBIs and CMBs to better understand the relation of large and small vessel disease in a single-center retrospective observational study. METHODS: Intraplaque hemorrhage (IPH) and plaque ulceration were recorded on carotid MRA and total, cortical, and lacunar CBIs and CMBs were recorded on brain MR in 349 patients (698 carotid arteries). Multivariable Poisson regression was performed to relate plaque features to CBIs and CMBs. Within-subject analysis in those with unilateral IPH and ulceration was performed with Poisson regression. RESULTS: Both IPH and plaque ulceration were associated with total CBI (prevalence ratios (PR) 3.33, 95% CI: 2.16-5.15 and 1.91, 95% CI: 1.21-3.00, respectively), after adjusting for stenosis, demographic, and vascular risk factors. In subjects with unilateral IPH, PR was 2.83, 95% CI: 1.76-4.55, for CBI in the ipsilateral hemisphere after adjusting for stenosis. Among those with unilateral ulceration, PR was 1.82, 95% CI: 1.18-2.81, for total CBI ipsilateral to ulceration after adjusting for stenosis. No statistically significant association was seen with CMBs. CONCLUSION: Both IPH and plaque ulceration are associated with total, cortical, and lacunar type CBIs but not CMBs suggesting that advanced atherosclerosis contributes predominantly to ischemic markers of subclinical vascular injury.

DEEPMIR: a deep neural network for differential detection of cerebral microbleeds and iron deposits in MRI.

Lobar cerebral microbleeds (CMBs) and localized non-hemorrhage iron deposits in the basal ganglia have been associated with brain aging, vascular disease and neurodegenerative disorders. Particularly, CMBs are small lesions and require multiple neuroimaging modalities for accurate detection. Quantitative susceptibility mapping (QSM) derived from in vivo magnetic resonance imaging (MRI) is necessary to differentiate between iron content and mineralization. We set out to develop a deep learning-based segmentation method suitable for segmenting both CMBs and iron deposits. We included a convenience sample of 24 participants from the MESA cohort and used T2-weighted images, susceptibility weighted imaging (SWI), and QSM to segment the two types of lesions. We developed a protocol for simultaneous manual annotation of CMBs and non-hemorrhage iron deposits in the basal ganglia. This manual annotation was then used to train a deep convolution neural network (CNN). Specifically, we adapted the U-Net model with a higher number of resolution layers to be able to detect small lesions such as CMBs from standard resolution MRI. We tested different combinations of the three modalities to determine the most informative data sources for the detection tasks. In the detection of CMBs using single class and multiclass models, we achieved an average sensitivity and precision of between 0.84-0.88 and 0.40-0.59, respectively. The same framework detected non-hemorrhage iron deposits with an average sensitivity and precision of about 0.75-0.81 and 0.62-0.75, respectively. Our results showed that deep learning could automate the detection of small vessel disease lesions and including multimodal MR data (particularly QSM) can improve the detection of CMB and non-hemorrhage iron deposits with sensitivity and precision that is compatible with use in large-scale research studies.

Cerebral Venous Sinus Thromboses in Patients with SARS-CoV-2 Infection: Three Cases and a Review of the Literature.

INTRODUCTION: Early studies suggest that acute cerebrovascular events may be common in patients with coronavirus disease 2019 (COVID-19) and may be associated with a high mortality rate. Most cerebrovascular events described have been ischemic strokes, but both intracerebral hemorrhage and rarely cerebral venous sinus thrombosis (CVST) have also been reported. The diagnosis of CVST can be elusive, with wide-ranging and nonspecific presenting symptoms that can include headache or altered sensorium alone. OBJECTIVE: To describe the presentation, barriers to diagnosis, treatment, and outcome of CVST in patients with COVID-19. METHODS: We abstracted data on all patients diagnosed with CVST and COVID-19 from March 1 to August 9, 2020 at Boston Medical Center. Subsequently, we reviewed the literature and extracted all published cases of CVST in patients with COVID-19 from January 1, 2020 through August 9, 2020 and included all studies with case descriptions. RESULTS: We describe the clinical features and management of CVST in 3 women with COVID-19 who developed CVST days to months after initial COVID-19 symptoms. Two patients presented with encephalopathy and without focal neurologic deficits, while one presented with visual symptoms. All patients were treated with intravenous hydration and anticoagulation. None suffered hemorrhagic complications, and all were discharged home. We identified 12 other patients with CVST in the setting of COVID-19 via literature search. There was a female predominance (54.5%), most patients presented with altered sensorium (54.5%), and there was a high mortality rate (36.4%). CONCLUSIONS: During this pandemic, clinicians should maintain a high index of suspicion for CVST in patients with a recent history of COVID-19 presenting with non-specific neurological symptoms such as headache to provide expedient management and prevent complications. The limited data suggests that CVST in COVID-19 is more prevalent in females and may be associated with high mortality.